A mixture model-based approach to the clustering of microarray expression data.

PubMed

McLachlan, G J; Bean, R W; Peel, D

2002-03-01

This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets. EMMIX-GENE is available at http://www.maths.uq.edu.au/~gjm/emmix-gene/

The shape of galaxy dark matter haloes in massive galaxy clusters: insights from strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jauzac, Mathilde; Harvey, David; Massey, Richard

2018-07-01

We assess how much unused strong lensing information is available in the deep Hubble Space Telescope imaging and Very Large Telescope/Multi Unit Spectroscopic Explorer spectroscopy of the Frontier Field clusters. As a pilot study, we analyse galaxy cluster MACS J0416.1-2403 (z = 0.397, M(R < 200 kpc) = 1.6 × 1014 M⊙), which has 141 multiple images with spectroscopic redshifts. We find that many additional parameters in a cluster mass model can be constrained, and that adding even small amounts of extra freedom to a model can dramatically improve its figures of merit. We use this information to constrain the distribution of dark matter around cluster member galaxies, simultaneously with the cluster's large-scale mass distribution. We find tentative evidence that some galaxies' dark matter has surprisingly similar ellipticity to their stars (unlike in the field, where it is more spherical), but that its orientation is often misaligned. When non-coincident dark matter and stellar haloes are allowed, the model improves by 35 per cent. This technique may provide a new way to investigate the processes and time-scales on which dark matter is stripped from galaxies as they fall into a massive cluster. Our preliminary conclusions will be made more robust by analysing the remaining five Frontier Field clusters.

A two-stage model of fracture of rocks

USGS Publications Warehouse

Kuksenko, V.; Tomilin, N.; Damaskinskaya, E.; Lockner, D.

1996-01-01

In this paper we propose a two-stage model of rock fracture. In the first stage, cracks or local regions of failure are uncorrelated occur randomly throughout the rock in response to loading of pre-existing flaws. As damage accumulates in the rock, there is a gradual increase in the probability that large clusters of closely spaced cracks or local failure sites will develop. Based on statistical arguments, a critical density of damage will occur where clusters of flaws become large enough to lead to larger-scale failure of the rock (stage two). While crack interaction and cooperative failure is expected to occur within clusters of closely spaced cracks, the initial development of clusters is predicted based on the random variation in pre-existing Saw populations. Thus the onset of the unstable second stage in the model can be computed from the generation of random, uncorrelated damage. The proposed model incorporates notions of the kinetic (and therefore time-dependent) nature of the strength of solids as well as the discrete hierarchic structure of rocks and the flaw populations that lead to damage accumulation. The advantage offered by this model is that its salient features are valid for fracture processes occurring over a wide range of scales including earthquake processes. A notion of the rank of fracture (fracture size) is introduced, and criteria are presented for both fracture nucleation and the transition of the failure process from one scale to another.

A k-space method for acoustic propagation using coupled first-order equations in three dimensions.

PubMed

Tillett, Jason C; Daoud, Mohammad I; Lacefield, James C; Waag, Robert C

2009-09-01

A previously described two-dimensional k-space method for large-scale calculation of acoustic wave propagation in tissues is extended to three dimensions. The three-dimensional method contains all of the two-dimensional method features that allow accurate and stable calculation of propagation. These features are spectral calculation of spatial derivatives, temporal correction that produces exact propagation in a homogeneous medium, staggered spatial and temporal grids, and a perfectly matched boundary layer. Spectral evaluation of spatial derivatives is accomplished using a fast Fourier transform in three dimensions. This computational bottleneck requires all-to-all communication; execution time in a parallel implementation is therefore sensitive to node interconnect latency and bandwidth. Accuracy of the three-dimensional method is evaluated through comparisons with exact solutions for media having spherical inhomogeneities. Large-scale calculations in three dimensions were performed by distributing the nearly 50 variables per voxel that are used to implement the method over a cluster of computers. Two computer clusters used to evaluate method accuracy are compared. Comparisons of k-space calculations with exact methods including absorption highlight the need to model accurately the medium dispersion relationships, especially in large-scale media. Accurately modeled media allow the k-space method to calculate acoustic propagation in tissues over hundreds of wavelengths.

Inherent Structure versus Geometric Metric for State Space Discretization

PubMed Central

Liu, Hanzhong; Li, Minghai; Fan, Jue; Huo, Shuanghong

2016-01-01

Inherent structure (IS) and geometry-based clustering methods are commonly used for analyzing molecular dynamics trajectories. ISs are obtained by minimizing the sampled conformations into local minima on potential/effective energy surface. The conformations that are minimized into the same energy basin belong to one cluster. We investigate the influence of the applications of these two methods of trajectory decomposition on our understanding of the thermodynamics and kinetics of alanine tetrapeptide. We find that at the micro cluster level, the IS approach and root-mean-square deviation (RMSD) based clustering method give totally different results. Depending on the local features of energy landscape, the conformations with close RMSDs can be minimized into different minima, while the conformations with large RMSDs could be minimized into the same basin. However, the relaxation timescales calculated based on the transition matrices built from the micro clusters are similar. The discrepancy at the micro cluster level leads to different macro clusters. Although the dynamic models established through both clustering methods are validated approximately Markovian, the IS approach seems to give a meaningful state space discretization at the macro cluster level. PMID:26915811

Exploring the Internal Dynamics of Globular Clusters

NASA Astrophysics Data System (ADS)

Watkins, Laura L.; van der Marel, Roeland; Bellini, Andrea; Luetzgendorf, Nora; HSTPROMO Collaboration

2018-01-01

Exploring the Internal Dynamics of Globular ClustersThe formation histories and structural properties of globular clusters are imprinted on their internal dynamics. Energy equipartition results in velocity differences for stars of different mass, and leads to mass segregation, which results in different spatial distributions for stars of different mass. Intermediate-mass black holes significantly increase the velocity dispersions at the centres of clusters. By combining accurate measurements of their internal kinematics with state-of-the-art dynamical models, we can characterise both the velocity dispersion and mass profiles of clusters, tease apart the different effects, and understand how clusters may have formed and evolved.Using proper motions from the Hubble Space Telescope Proper Motion (HSTPROMO) Collaboration for a set of 22 Milky Way globular clusters, and our discrete dynamical modelling techniques designed to work with large, high-quality datasets, we are studying a variety of internal cluster properties. We will present the results of theoretical work on simulated clusters that demonstrates the efficacy of our approach, and preliminary results from application to real clusters.

UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data.

PubMed

Adamczak, Rafal; Meller, Jarek

2016-12-28

Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data. Consequently, the computational cost of structure comparison and clustering for large sets of macromolecular structures has become a bottleneck that necessitates further algorithmic improvements and development of efficient software solutions. uQlust is a versatile and easy-to-use tool for ultrafast ranking and clustering of macromolecular structures. uQlust makes use of structural profiles of proteins and nucleic acids, while combining a linear-time algorithm for implicit comparison of all pairs of models with profile hashing to enable efficient clustering of large data sets with a low memory footprint. In addition to ranking and clustering of large sets of models of the same protein or RNA molecule, uQlust can also be used in conjunction with fragment-based profiles in order to cluster structures of arbitrary length. For example, hierarchical clustering of the entire PDB using profile hashing can be performed on a typical laptop, thus opening an avenue for structural explorations previously limited to dedicated resources. The uQlust package is freely available under the GNU General Public License at https://github.com/uQlust . uQlust represents a drastic reduction in the computational complexity and memory requirements with respect to existing clustering and model quality assessment methods for macromolecular structure analysis, while yielding results on par with traditional approaches for both proteins and RNAs.

The VIMOS Public Extragalactic Redshift Survey (VIPERS) . Galaxy clustering and redshift-space distortions at z ≃ 0.8 in the first data release

NASA Astrophysics Data System (ADS)

de la Torre, S.; Guzzo, L.; Peacock, J. A.; Branchini, E.; Iovino, A.; Granett, B. R.; Abbas, U.; Adami, C.; Arnouts, S.; Bel, J.; Bolzonella, M.; Bottini, D.; Cappi, A.; Coupon, J.; Cucciati, O.; Davidzon, I.; De Lucia, G.; Fritz, A.; Franzetti, P.; Fumana, M.; Garilli, B.; Ilbert, O.; Krywult, J.; Le Brun, V.; Le Fèvre, O.; Maccagni, D.; Małek, K.; Marulli, F.; McCracken, H. J.; Moscardini, L.; Paioro, L.; Percival, W. J.; Polletta, M.; Pollo, A.; Schlagenhaufer, H.; Scodeggio, M.; Tasca, L. A. M.; Tojeiro, R.; Vergani, D.; Zanichelli, A.; Burden, A.; Di Porto, C.; Marchetti, A.; Marinoni, C.; Mellier, Y.; Monaco, P.; Nichol, R. C.; Phleps, S.; Wolk, M.; Zamorani, G.

2013-09-01

We present the general real- and redshift-space clustering properties of galaxies as measured in the first data release of the VIPERS survey. VIPERS is a large redshift survey designed to probe in detail the distant Universe and its large-scale structure at 0.5 < z < 1.2. We describe in this analysis the global properties of the sample and discuss the survey completeness and associated corrections. This sample allows us to measure the galaxy clustering with an unprecedented accuracy at these redshifts. From the redshift-space distortions observed in the galaxy clustering pattern we provide a first measurement of the growth rate of structure at z = 0.8: fσ8 = 0.47 ± 0.08. This is completely consistent with the predictions of standard cosmological models based on Einstein gravity, although this measurement alone does not discriminate between different gravity models. Based on observations collected at the European Southern Observatory, Cerro Paranal, Chile, using the Very Large Telescope under programmes 182.A-0886 and partly 070.A-9007. Also based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT), which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at TERAPIX and the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. The VIPERS web site is http://www.vipers.inaf.it/

Analysis of the Seismicity Preceding Large Earthquakes

NASA Astrophysics Data System (ADS)

Stallone, A.; Marzocchi, W.

2016-12-01

The most common earthquake forecasting models assume that the magnitude of the next earthquake is independent from the past. This feature is probably one of the most severe limitations of the capability to forecast large earthquakes.In this work, we investigate empirically on this specific aspect, exploring whether spatial-temporal variations in seismicity encode some information on the magnitude of the future earthquakes. For this purpose, and to verify the universality of the findings, we consider seismic catalogs covering quite different space-time-magnitude windows, such as the Alto Tiberina Near Fault Observatory (TABOO) catalogue, and the California and Japanese seismic catalog. Our method is inspired by the statistical methodology proposed by Zaliapin (2013) to distinguish triggered and background earthquakes, using the nearest-neighbor clustering analysis in a two-dimension plan defined by rescaled time and space. In particular, we generalize the metric based on the nearest-neighbor to a metric based on the k-nearest-neighbors clustering analysis that allows us to consider the overall space-time-magnitude distribution of k-earthquakes (k-foreshocks) which anticipate one target event (the mainshock); then we analyze the statistical properties of the clusters identified in this rescaled space. In essence, the main goal of this study is to verify if different classes of mainshock magnitudes are characterized by distinctive k-foreshocks distribution. The final step is to show how the findings of this work may (or not) improve the skill of existing earthquake forecasting models.

Towards semantically sensitive text clustering: a feature space modeling technology based on dimension extension.

PubMed

Liu, Yuanchao; Liu, Ming; Wang, Xin

2015-01-01

The objective of text clustering is to divide document collections into clusters based on the similarity between documents. In this paper, an extension-based feature modeling approach towards semantically sensitive text clustering is proposed along with the corresponding feature space construction and similarity computation method. By combining the similarity in traditional feature space and that in extension space, the adverse effects of the complexity and diversity of natural language can be addressed and clustering semantic sensitivity can be improved correspondingly. The generated clusters can be organized using different granularities. The experimental evaluations on well-known clustering algorithms and datasets have verified the effectiveness of our approach.

Towards Semantically Sensitive Text Clustering: A Feature Space Modeling Technology Based on Dimension Extension

PubMed Central

Liu, Yuanchao; Liu, Ming; Wang, Xin

2015-01-01

The objective of text clustering is to divide document collections into clusters based on the similarity between documents. In this paper, an extension-based feature modeling approach towards semantically sensitive text clustering is proposed along with the corresponding feature space construction and similarity computation method. By combining the similarity in traditional feature space and that in extension space, the adverse effects of the complexity and diversity of natural language can be addressed and clustering semantic sensitivity can be improved correspondingly. The generated clusters can be organized using different granularities. The experimental evaluations on well-known clustering algorithms and datasets have verified the effectiveness of our approach. PMID:25794172

Temporal models for the episodic volcanism of Campi Flegrei caldera (Italy) with uncertainty quantification

NASA Astrophysics Data System (ADS)

Bevilacqua, Andrea; Flandoli, Franco; Neri, Augusto; Isaia, Roberto; Vitale, Stefano

2016-11-01

After the large-scale event of Neapolitan Yellow Tuff ( 15 ka B.P.), intense and mostly explosive volcanism has occurred within and along the boundaries of the Campi Flegrei caldera (Italy). Eruptions occurred closely spaced in time, over periods from a few centuries to a few millennia, and were alternated with periods of quiescence lasting up to several millennia. Often events also occurred closely in space, thus generating a cluster of events. This study had two main objectives: (1) to describe the uncertainty in the geologic record by using a quantitative model and (2) to develop, based on the uncertainty assessment, a long-term subdomain specific temporal probability model that describes the temporal and spatial eruptive behavior of the caldera. In particular, the study adopts a space-time doubly stochastic nonhomogeneous Poisson-type model with a local self-excitation feature able to generate clustering of events which are consistent with the reconstructed record of Campi Flegrei. Results allow the evaluation of similarities and differences between the three epochs of activity as well as to derive eruptive base rate of the caldera and its capacity to generate clusters of events. The temporal probability model is also used to investigate the effect of the most recent eruption of Monte Nuovo (A.D. 1538) in a possible reactivation of the caldera and to estimate the time to the next eruption under different volcanological and modeling assumptions.

Frequency-sensitive competitive learning for scalable balanced clustering on high-dimensional hyperspheres.

PubMed

Banerjee, Arindam; Ghosh, Joydeep

2004-05-01

Competitive learning mechanisms for clustering, in general, suffer from poor performance for very high-dimensional (>1000) data because of "curse of dimensionality" effects. In applications such as document clustering, it is customary to normalize the high-dimensional input vectors to unit length, and it is sometimes also desirable to obtain balanced clusters, i.e., clusters of comparable sizes. The spherical kmeans (spkmeans) algorithm, which normalizes the cluster centers as well as the inputs, has been successfully used to cluster normalized text documents in 2000+ dimensional space. Unfortunately, like regular kmeans and its soft expectation-maximization-based version, spkmeans tends to generate extremely imbalanced clusters in high-dimensional spaces when the desired number of clusters is large (tens or more). This paper first shows that the spkmeans algorithm can be derived from a certain maximum likelihood formulation using a mixture of von Mises-Fisher distributions as the generative model, and in fact, it can be considered as a batch-mode version of (normalized) competitive learning. The proposed generative model is then adapted in a principled way to yield three frequency-sensitive competitive learning variants that are applicable to static data and produced high-quality and well-balanced clusters for high-dimensional data. Like kmeans, each iteration is linear in the number of data points and in the number of clusters for all the three algorithms. A frequency-sensitive algorithm to cluster streaming data is also proposed. Experimental results on clustering of high-dimensional text data sets are provided to show the effectiveness and applicability of the proposed techniques. Index Terms-Balanced clustering, expectation maximization (EM), frequency-sensitive competitive learning (FSCL), high-dimensional clustering, kmeans, normalized data, scalable clustering, streaming data, text clustering.

On the analysis of large data sets

NASA Astrophysics Data System (ADS)

Ruch, Gerald T., Jr.

We present a set of tools and techniques for performing detailed comparisons between computational models with high dimensional parameter spaces and large sets of archival data. By combining a principal component analysis of a large grid of samples from the model with an artificial neural network, we create a powerful data visualization tool as well as a way to robustly recover physical parameters from a large set of experimental data. Our techniques are applied in the context of circumstellar disks, the likely sites of planetary formation. An analysis is performed applying the two layer approximation of Chiang et al. (2001) and Dullemond et al. (2001) to the archive created by the Spitzer Space Telescope Cores to Disks Legacy program. We find two populations of disk sources. The first population is characterized by the lack of a puffed up inner rim while the second population appears to contain an inner rim which casts a shadow across the disk. The first population also exhibits a trend of increasing spectral index while the second population exhibits a decreasing trend in the strength of the 20 mm silicate emission feature. We also present images of the giant molecular cloud W3 obtained with the Infrared Array Camera (IRAC) and the Multiband Imaging Photometer (MIPS) on board the Spitzer Space Telescope. The images encompass the star forming regions W3 Main, W3(OH), and a region that we refer to as the Central Cluster which encloses the emission nebula IC 1795. We present a star count analysis of the point sources detected in W3. The star count analysis shows that the stellar population of the Central Cluster, when compared to that in the background, contains an over density of sources. The Central Cluster also contains an excess of sources with colors consistent with Class II Young Stellar Objects (YSOs). A analysis of the color-color diagrams also reveals a large number of Class II YSOs in the Central Cluster. Our results suggest that an earlier epoch of star formation created the Central Cluster, created a cavity, and triggered the active star formation in the W3 Main and W3(OH) regions. We also detect a new outflow and its candidate exciting star.

A latent class distance association model for cross-classified data with a categorical response variable.

PubMed

Vera, José Fernando; de Rooij, Mark; Heiser, Willem J

2014-11-01

In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single outcome variable. In many cases such tables are sparse, with many zero entries, which makes traditional models problematic. By clustering the row profiles into a few specific classes and representing these together with the categories of the response variable in a low-dimensional Euclidean space using a distance association model, a parsimonious prediction model can be obtained. A generalized EM algorithm is proposed to estimate the model parameters and the adjusted Bayesian information criterion statistic is employed to test the number of mixture components and the dimensionality of the representation. An empirical example highlighting the advantages of the new approach and comparing it with traditional approaches is presented. © 2014 The British Psychological Society.

LoCuSS: connecting the dominance and shape of brightest cluster galaxies with the assembly history of massive clusters

NASA Astrophysics Data System (ADS)

Smith, Graham P.; Khosroshahi, Habib G.; Dariush, A.; Sanderson, A. J. R.; Ponman, T. J.; Stott, J. P.; Haines, C. P.; Egami, E.; Stark, D. P.

2010-11-01

We study the luminosity gap, Δm12, between the first- and second-ranked galaxies in a sample of 59 massive (~1015Msolar) galaxy clusters, using data from the Hale Telescope, the Hubble Space Telescope, Chandra and Spitzer. We find that the Δm12 distribution, p(Δm12), is a declining function of Δm12 to which we fitted a straight line: p(Δm12) ~ -(0.13 +/- 0.02)Δm12. The fraction of clusters with `large' luminosity gaps is p(Δm12 >= 1) = 0.37 +/- 0.08, which represents a 3σ excess over that obtained from Monte Carlo simulations of a Schechter function that matches the mean cluster galaxy luminosity function. We also identify four clusters with `extreme' luminosity gaps, Δm12 >= 2, giving a fraction of . More generally, large luminosity gap clusters are relatively homogeneous, with elliptical/discy brightest cluster galaxies (BCGs), cuspy gas density profiles (i.e. strong cool cores), high concentrations and low substructure fractions. In contrast, small luminosity gap clusters are heterogeneous, spanning the full range of boxy/elliptical/discy BCG morphologies, the full range of cool core strengths and dark matter concentrations, and have large substructure fractions. Taken together, these results imply that the amplitude of the luminosity gap is a function of both the formation epoch and the recent infall history of the cluster. `BCG dominance' is therefore a phase that a cluster may evolve through and is not an evolutionary `cul-de-sac'. We also compare our results with semi-analytic model predictions based on the Millennium Simulation. None of the models is able to reproduce all of the observational results on Δm12, underlining the inability of the current generation of models to match the empirical properties of BCGs. We identify the strength of active galactic nucleus feedback and the efficiency with which cluster galaxies are replenished after they merge with the BCG in each model as possible causes of these discrepancies.

Improvements on GPS Location Cluster Analysis for the Prediction of Large Carnivore Feeding Activities: Ground-Truth Detection Probability and Inclusion of Activity Sensor Measures

PubMed Central

Blecha, Kevin A.; Alldredge, Mat W.

2015-01-01

Animal space use studies using GPS collar technology are increasingly incorporating behavior based analysis of spatio-temporal data in order to expand inferences of resource use. GPS location cluster analysis is one such technique applied to large carnivores to identify the timing and location of feeding events. For logistical and financial reasons, researchers often implement predictive models for identifying these events. We present two separate improvements for predictive models that future practitioners can implement. Thus far, feeding prediction models have incorporated a small range of covariates, usually limited to spatio-temporal characteristics of the GPS data. Using GPS collared cougar (Puma concolor) we include activity sensor data as an additional covariate to increase prediction performance of feeding presence/absence. Integral to the predictive modeling of feeding events is a ground-truthing component, in which GPS location clusters are visited by human observers to confirm the presence or absence of feeding remains. Failing to account for sources of ground-truthing false-absences can bias the number of predicted feeding events to be low. Thus we account for some ground-truthing error sources directly in the model with covariates and when applying model predictions. Accounting for these errors resulted in a 10% increase in the number of clusters predicted to be feeding events. Using a double-observer design, we show that the ground-truthing false-absence rate is relatively low (4%) using a search delay of 2–60 days. Overall, we provide two separate improvements to the GPS cluster analysis techniques that can be expanded upon and implemented in future studies interested in identifying feeding behaviors of large carnivores. PMID:26398546

Constraints on dark matter annihilation in clusters of galaxies with the Fermi large area telescope

DOE PAGES

Ackermann, M.; Ajello, M.; Allafort, A.; ...

2010-05-20

Nearby clusters and groups of galaxies are potentially bright sources of high-energy gamma-ray emission resulting from the pair-annihilation of dark matter particles. However, no significant gamma-ray emission has been detected so far from clusters in the first 11 months of observations with the Fermi Large Area Telescope. We interpret this non-detection in terms of constraints on dark matter particle properties. In particular for leptonic annihilation final states and particle masses greater than ~ 200 GeV, gamma-ray emission from inverse Compton scattering of CMB photons is expected to dominate the dark matter annihilation signal from clusters, and our gamma-ray limits excludemore » large regions of the parameter space that would give a good fit to the recent anomalous Pamela and Fermi-LAT electron-positron measurements. We also present constraints on the annihilation of more standard dark matter candidates, such as the lightest neutralino of supersymmetric models. The constraints are particularly strong when including the fact that clusters are known to contain substructure at least on galaxy scales, increasing the expected gamma-ray flux by a factor of ~ 5 over a smooth-halo assumption. Here, we also explore the effect of uncertainties in cluster dark matter density profiles, finding a systematic uncertainty in the constraints of roughly a factor of two, but similar overall conclusions. Finally, in this work, we focus on deriving limits on dark matter models; a more general consideration of the Fermi-LAT data on clusters and clusters as gamma-ray sources is forthcoming.« less

From atoms to layers: in situ gold cluster growth kinetics during sputter deposition

NASA Astrophysics Data System (ADS)

Schwartzkopf, Matthias; Buffet, Adeline; Körstgens, Volker; Metwalli, Ezzeldin; Schlage, Kai; Benecke, Gunthard; Perlich, Jan; Rawolle, Monika; Rothkirch, André; Heidmann, Berit; Herzog, Gerd; Müller-Buschbaum, Peter; Röhlsberger, Ralf; Gehrke, Rainer; Stribeck, Norbert; Roth, Stephan V.

2013-05-01

The adjustment of size-dependent catalytic, electrical and optical properties of gold cluster assemblies is a very significant issue in modern applied nanotechnology. We present a real-time investigation of the growth kinetics of gold nanostructures from small nuclei to a complete gold layer during magnetron sputter deposition with high time resolution by means of in situ microbeam grazing incidence small-angle X-ray scattering (μGISAXS). We specify the four-stage growth including their thresholds with sub-monolayer resolution and identify phase transitions monitored in Yoneda intensity as a material-specific characteristic. An innovative and flexible geometrical model enables the extraction of morphological real space parameters, such as cluster size and shape, correlation distance, layer porosity and surface coverage, directly from reciprocal space scattering data. This approach enables a large variety of future investigations of the influence of different process parameters on the thin metal film morphology. Furthermore, our study allows for deducing the wetting behavior of gold cluster films on solid substrates and provides a better understanding of the growth kinetics in general, which is essential for optimization of manufacturing parameters, saving energy and resources.The adjustment of size-dependent catalytic, electrical and optical properties of gold cluster assemblies is a very significant issue in modern applied nanotechnology. We present a real-time investigation of the growth kinetics of gold nanostructures from small nuclei to a complete gold layer during magnetron sputter deposition with high time resolution by means of in situ microbeam grazing incidence small-angle X-ray scattering (μGISAXS). We specify the four-stage growth including their thresholds with sub-monolayer resolution and identify phase transitions monitored in Yoneda intensity as a material-specific characteristic. An innovative and flexible geometrical model enables the extraction of morphological real space parameters, such as cluster size and shape, correlation distance, layer porosity and surface coverage, directly from reciprocal space scattering data. This approach enables a large variety of future investigations of the influence of different process parameters on the thin metal film morphology. Furthermore, our study allows for deducing the wetting behavior of gold cluster films on solid substrates and provides a better understanding of the growth kinetics in general, which is essential for optimization of manufacturing parameters, saving energy and resources. Electronic supplementary information (ESI) available: The full GISAXS image sequence of the experiment, the model-based IsGISAXS-simulation sequence as movie files for comparison and detailed information about sample cleaning, XRR, FESEM, IsGISAXS, comparison μGIWAXS/μGISAXS, and sampling statistics. See DOI: 10.1039/c3nr34216f

On the streaming model for redshift-space distortions

NASA Astrophysics Data System (ADS)

Kuruvilla, Joseph; Porciani, Cristiano

2018-06-01

The streaming model describes the mapping between real and redshift space for 2-point clustering statistics. Its key element is the probability density function (PDF) of line-of-sight pairwise peculiar velocities. Following a kinetic-theory approach, we derive the fundamental equations of the streaming model for ordered and unordered pairs. In the first case, we recover the classic equation while we demonstrate that modifications are necessary for unordered pairs. We then discuss several statistical properties of the pairwise velocities for DM particles and haloes by using a suite of high-resolution N-body simulations. We test the often used Gaussian ansatz for the PDF of pairwise velocities and discuss its limitations. Finally, we introduce a mixture of Gaussians which is known in statistics as the generalised hyperbolic distribution and show that it provides an accurate fit to the PDF. Once inserted in the streaming equation, the fit yields an excellent description of redshift-space correlations at all scales that vastly outperforms the Gaussian and exponential approximations. Using a principal-component analysis, we reduce the complexity of our model for large redshift-space separations. Our results increase the robustness of studies of anisotropic galaxy clustering and are useful for extending them towards smaller scales in order to test theories of gravity and interacting dark-energy models.

Redshift-space distortions with the halo occupation distribution - II. Analytic model

NASA Astrophysics Data System (ADS)

Tinker, Jeremy L.

2007-01-01

We present an analytic model for the galaxy two-point correlation function in redshift space. The cosmological parameters of the model are the matter density Ωm, power spectrum normalization σ8, and velocity bias of galaxies αv, circumventing the linear theory distortion parameter β and eliminating nuisance parameters for non-linearities. The model is constructed within the framework of the halo occupation distribution (HOD), which quantifies galaxy bias on linear and non-linear scales. We model one-halo pairwise velocities by assuming that satellite galaxy velocities follow a Gaussian distribution with dispersion proportional to the virial dispersion of the host halo. Two-halo velocity statistics are a combination of virial motions and host halo motions. The velocity distribution function (DF) of halo pairs is a complex function with skewness and kurtosis that vary substantially with scale. Using a series of collisionless N-body simulations, we demonstrate that the shape of the velocity DF is determined primarily by the distribution of local densities around a halo pair, and at fixed density the velocity DF is close to Gaussian and nearly independent of halo mass. We calibrate a model for the conditional probability function of densities around halo pairs on these simulations. With this model, the full shape of the halo velocity DF can be accurately calculated as a function of halo mass, radial separation, angle and cosmology. The HOD approach to redshift-space distortions utilizes clustering data from linear to non-linear scales to break the standard degeneracies inherent in previous models of redshift-space clustering. The parameters of the occupation function are well constrained by real-space clustering alone, separating constraints on bias and cosmology. We demonstrate the ability of the model to separately constrain Ωm,σ8 and αv in models that are constructed to have the same value of β at large scales as well as the same finger-of-god distortions at small scales.

Lens models and magnification maps of the six Hubble Frontier Fields clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Traci L.; Sharon, Keren; Bayliss, Matthew B.

2014-12-10

We present strong-lensing models as well as mass and magnification maps for the cores of the six Hubble Space Telescope (HST) Frontier Fields galaxy clusters. Our parametric lens models are constrained by the locations and redshifts of multiple image systems of lensed background galaxies. We use a combination of photometric redshifts and spectroscopic redshifts of the lensed background sources obtained by us (for A2744 and AS1063), collected from the literature, or kindly provided by the lensing community. Using our results, we (1) compare the derived mass distribution of each cluster to its light distribution, (2) quantify the cumulative magnification powermore » of the HST Frontier Fields clusters, (3) describe how our models can be used to estimate the magnification and image multiplicity of lensed background sources at all redshifts and at any position within the cluster cores, and (4) discuss systematic effects and caveats resulting from our modeling methods. We specifically investigate the effect of the use of spectroscopic and photometric redshift constraints on the uncertainties of the resulting models. We find that the photometric redshift estimates of lensed galaxies are generally in excellent agreement with spectroscopic redshifts, where available. However, the flexibility associated with relaxed redshift priors may cause the complexity of large-scale structure that is needed to account for the lensing signal to be underestimated. Our findings thus underline the importance of spectroscopic arc redshifts, or tight photometric redshift constraints, for high precision lens models. All products from our best-fit lens models (magnification, convergence, shear, deflection field) and model simulations for estimating errors are made available via the Mikulski Archive for Space Telescopes.« less

Dispersion Distance and the Matter Distribution of the Universe in Dispersion Space.

PubMed

Masui, Kiyoshi Wesley; Sigurdson, Kris

2015-09-18

We propose that "standard pings," brief broadband radio impulses, can be used to study the three-dimensional clustering of matter in the Universe even in the absence of redshift information. The dispersion of radio waves as they travel through the intervening plasma can, like redshift, be used as a cosmological distance measure. Because of inhomogeneities in the electron density along the line of sight, dispersion is an imperfect proxy for radial distance and we show that this leads to calculable dispersion-space distortions in the apparent clustering of sources. Fast radio bursts (FRBs) are a new class of radio transients that are the prototypical standard ping and, due to their high observed dispersion, have been interpreted as originating at cosmological distances. The rate of fast radio bursts has been estimated to be several thousand over the whole sky per day and, if cosmological, the sources of these events should trace the large-scale structure of the Universe. We calculate the dispersion-space power spectra for a simple model where electrons and FRBs are biased tracers of the large-scale structure of the Universe, and we show that the clustering signal could be measured using as few as 10 000 events. Such a survey is in line with what may be achieved with upcoming wide-field radio telescopes.

Dispersion Distance and the Matter Distribution of the Universe in Dispersion Space

NASA Astrophysics Data System (ADS)

Masui, Kiyoshi Wesley; Sigurdson, Kris

2015-09-01

We propose that "standard pings," brief broadband radio impulses, can be used to study the three-dimensional clustering of matter in the Universe even in the absence of redshift information. The dispersion of radio waves as they travel through the intervening plasma can, like redshift, be used as a cosmological distance measure. Because of inhomogeneities in the electron density along the line of sight, dispersion is an imperfect proxy for radial distance and we show that this leads to calculable dispersion-space distortions in the apparent clustering of sources. Fast radio bursts (FRBs) are a new class of radio transients that are the prototypical standard ping and, due to their high observed dispersion, have been interpreted as originating at cosmological distances. The rate of fast radio bursts has been estimated to be several thousand over the whole sky per day and, if cosmological, the sources of these events should trace the large-scale structure of the Universe. We calculate the dispersion-space power spectra for a simple model where electrons and FRBs are biased tracers of the large-scale structure of the Universe, and we show that the clustering signal could be measured using as few as 10 000 events. Such a survey is in line with what may be achieved with upcoming wide-field radio telescopes.

Space versus Place in Complex Human-Natural Systems: Spatial and Multi-level Models of Tropical Land Use and Cover Change (LUCC) in Guatemala

PubMed Central

López-Carr, David; Davis, Jason; Jankowska, Marta; Grant, Laura; López-Carr, Anna Carla; Clark, Matthew

2013-01-01

The relative role of space and place has long been debated in geography. Yet modeling efforts applied to coupled human-natural systems seemingly favor models assuming continuous spatial relationships. We examine the relative importance of placebased hierarchical versus spatial clustering influences in tropical land use/cover change (LUCC). Guatemala was chosen as our study site given its high rural population growth and deforestation in recent decades. We test predictors of 2009 forest cover and forest cover change from 2001-2009 across Guatemala's 331 municipalities and 22 departments using spatial and multi-level statistical models. Our results indicate the emergence of several socio-economic predictors of LUCC regardless of model choice. Hierarchical model results suggest that significant differences exist at the municipal and departmental levels but largely maintain the magnitude and direction of single-level model coefficient estimates. They are also intervention-relevant since policies tend to be applicable to distinct political units rather than to continuous space. Spatial models complement hierarchical approaches by indicating where and to what magnitude significant negative and positive clustering associations emerge. Appreciating the comparative advantages and limitations of spatial and nested models enhances a holistic approach to geographical analysis of tropical LUCC and human-environment interactions. PMID:24013908

Spatial-temporal clustering of tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2016-12-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Spatial-Temporal Clustering of Tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2017-04-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Underestimated role of the secondary electron emission in the space

NASA Astrophysics Data System (ADS)

Nemecek, Zdenek; Richterova, Ivana; Safrankova, Jana; Pavlu, Jiri; Vaverka, Jakub; Nouzak, Libor

2016-07-01

Secondary electron emission (SEE) is one of many processes that charges surfaces of bodies immersed into a plasma. Until present, a majority of considerations in theories and experiments is based on the sixty year old description of an interaction of planar metallic surfaces with electrons, thus the effects of a surface curvature, roughness, presence of clusters as well as an influence of the material conductance on different aspects of this interaction are neglected. Dust grains or their clusters can be frequently found in many space environments - interstellar clouds, atmospheres of planets, tails of comets or planetary rings are only typical examples. The grains are exposed to electrons of different energies and they can acquire positive or negative charge during this interaction. We review the progress in experimental investigations and computer simulations of the SEE from samples relevant to space that was achieved in course of the last decade. We present a systematic study of well-defined systems that starts from spherical grains of various diameters and materials, and it continues with clusters consisting of different numbers of small spherical grains that can be considered as examples of real irregularly shaped space grains. The charges acquired by investigated objects as well as their secondary emission yields are calculated using the SEE model. We show that (1) the charge and surface potential of clusters exposed to the electron beam are influenced by the number of grains and by their geometry within a particular cluster, (2) the model results are in an excellent agreement with the experiment, and (3) there is a large difference between charging of a cluster levitating in the free space and that attached to a planar surface. The calculation provides a reduction of the secondary electron emission yield of the surface covered by dust clusters by a factor up to 1.5 with respect to the yield of a smooth surface. (4) These results are applied on charging of the lunar surface and the dust grains levitating above it, and it is shown that the SEE is more important for isolated dust grains than for the lunar surface covered by them.

Effect of Clustering Algorithm on Establishing Markov State Model for Molecular Dynamics Simulations.

PubMed

Li, Yan; Dong, Zigang

2016-06-27

Recently, the Markov state model has been applied for kinetic analysis of molecular dynamics simulations. However, discretization of the conformational space remains a primary challenge in model building, and it is not clear how the space decomposition by distinct clustering strategies exerts influence on the model output. In this work, different clustering algorithms are employed to partition the conformational space sampled in opening and closing of fatty acid binding protein 4 as well as inactivation and activation of the epidermal growth factor receptor. Various classifications are achieved, and Markov models are set up accordingly. On the basis of the models, the total net flux and transition rate are calculated between two distinct states. Our results indicate that geometric and kinetic clustering perform equally well. The construction and outcome of Markov models are heavily dependent on the data traits. Compared to other methods, a combination of Bayesian and hierarchical clustering is feasible in identification of metastable states.

Corrected Mean-Field Model for Random Sequential Adsorption on Random Geometric Graphs

NASA Astrophysics Data System (ADS)

Dhara, Souvik; van Leeuwaarden, Johan S. H.; Mukherjee, Debankur

2018-03-01

A notorious problem in mathematics and physics is to create a solvable model for random sequential adsorption of non-overlapping congruent spheres in the d-dimensional Euclidean space with d≥ 2 . Spheres arrive sequentially at uniformly chosen locations in space and are accepted only when there is no overlap with previously deposited spheres. Due to spatial correlations, characterizing the fraction of accepted spheres remains largely intractable. We study this fraction by taking a novel approach that compares random sequential adsorption in Euclidean space to the nearest-neighbor blocking on a sequence of clustered random graphs. This random network model can be thought of as a corrected mean-field model for the interaction graph between the attempted spheres. Using functional limit theorems, we characterize the fraction of accepted spheres and its fluctuations.

Strong-lensing analysis of A2744 with MUSE and Hubble Frontier Fields images

NASA Astrophysics Data System (ADS)

Mahler, G.; Richard, J.; Clément, B.; Lagattuta, D.; Schmidt, K.; Patrício, V.; Soucail, G.; Bacon, R.; Pello, R.; Bouwens, R.; Maseda, M.; Martinez, J.; Carollo, M.; Inami, H.; Leclercq, F.; Wisotzki, L.

2018-01-01

We present an analysis of Multi Unit Spectroscopic Explorer (MUSE) observations obtained on the massive Frontier Fields (FFs) cluster A2744. This new data set covers the entire multiply imaged region around the cluster core. The combined catalogue consists of 514 spectroscopic redshifts (with 414 new identifications). We use this redshift information to perform a strong-lensing analysis revising multiple images previously found in the deep FF images, and add three new MUSE-detected multiply imaged systems with no obvious Hubble Space Telescope counterpart. The combined strong-lensing constraints include a total of 60 systems producing 188 images altogether, out of which 29 systems and 83 images are spectroscopically confirmed, making A2744 one of the most well-constrained clusters to date. Thanks to the large amount of spectroscopic redshifts, we model the influence of substructures at larger radii, using a parametrization including two cluster-scale components in the cluster core and several group scale in the outskirts. The resulting model accurately reproduces all the spectroscopic multiple systems, reaching an rms of 0.67 arcsec in the image plane. The large number of MUSE spectroscopic redshifts gives us a robust model, which we estimate reduces the systematic uncertainty on the 2D mass distribution by up to ∼2.5 times the statistical uncertainty in the cluster core. In addition, from a combination of the parametrization and the set of constraints, we estimate the relative systematic uncertainty to be up to 9 per cent at 200 kpc.

Unconventional nozzle tradeoff study. [space tug propulsion

NASA Technical Reports Server (NTRS)

Obrien, C. J.

1979-01-01

Plug cluster engine design, performance, weight, envelope, operational characteristics, development cost, and payload capability, were evaluated and comparisons were made with other space tug engine candidates using oxygen/hydrogen propellants. Parametric performance data were generated for existing developed or high technology thrust chambers clustered around a plug nozzle of very large diameter. The uncertainties in the performance prediction of plug cluster engines with large gaps between the modules (thrust chambers) were evaluated. The major uncertainty involves, the aerodynamics of the flow from discrete nozzles, and the lack of this flow to achieve the pressure ratio corresponding to the defined area ratio for a plug cluster. This uncertainty was reduced through a cluster design that consists of a plug contour that is formed from the cluster of high area ratio bell nozzles that have been scarfed. Light-weight, high area ratio, bell nozzles were achieved through the use of AGCarb (carbon-carbon cloth) nozzle extensions.

The shape of galaxy dark matter halos in massive galaxy clusters: Insights from strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jauzac, Mathilde; Harvey, David; Massey, Richard

2018-04-01

We assess how much unused strong lensing information is available in the deep Hubble Space Telescope imaging and VLT/MUSE spectroscopy of the Frontier Field clusters. As a pilot study, we analyse galaxy cluster MACS J0416.1-2403 (z=0.397, M(R < 200 kpc)=1.6×1014M⊙), which has 141 multiple images with spectroscopic redshifts. We find that many additional parameters in a cluster mass model can be constrained, and that adding even small amounts of extra freedom to a model can dramatically improve its figures of merit. We use this information to constrain the distribution of dark matter around cluster member galaxies, simultaneously with the cluster's large-scale mass distribution. We find tentative evidence that some galaxies' dark matter has surprisingly similar ellipticity to their stars (unlike in the field, where it is more spherical), but that its orientation is often misaligned. When non-coincident dark matter and stellar halos are allowed, the model improves by 35%. This technique may provide a new way to investigate the processes and timescales on which dark matter is stripped from galaxies as they fall into a massive cluster. Our preliminary conclusions will be made more robust by analysing the remaining five Frontier Field clusters.

High- and low-level hierarchical classification algorithm based on source separation process

NASA Astrophysics Data System (ADS)

Loghmari, Mohamed Anis; Karray, Emna; Naceur, Mohamed Saber

2016-10-01

High-dimensional data applications have earned great attention in recent years. We focus on remote sensing data analysis on high-dimensional space like hyperspectral data. From a methodological viewpoint, remote sensing data analysis is not a trivial task. Its complexity is caused by many factors, such as large spectral or spatial variability as well as the curse of dimensionality. The latter describes the problem of data sparseness. In this particular ill-posed problem, a reliable classification approach requires appropriate modeling of the classification process. The proposed approach is based on a hierarchical clustering algorithm in order to deal with remote sensing data in high-dimensional space. Indeed, one obvious method to perform dimensionality reduction is to use the independent component analysis process as a preprocessing step. The first particularity of our method is the special structure of its cluster tree. Most of the hierarchical algorithms associate leaves to individual clusters, and start from a large number of individual classes equal to the number of pixels; however, in our approach, leaves are associated with the most relevant sources which are represented according to mutually independent axes to specifically represent some land covers associated with a limited number of clusters. These sources contribute to the refinement of the clustering by providing complementary rather than redundant information. The second particularity of our approach is that at each level of the cluster tree, we combine both a high-level divisive clustering and a low-level agglomerative clustering. This approach reduces the computational cost since the high-level divisive clustering is controlled by a simple Boolean operator, and optimizes the clustering results since the low-level agglomerative clustering is guided by the most relevant independent sources. Then at each new step we obtain a new finer partition that will participate in the clustering process to enhance semantic capabilities and give good identification rates.

Unsupervised classification of multivariate geostatistical data: Two algorithms

NASA Astrophysics Data System (ADS)

Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques

2015-12-01

With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.

Universal dynamical properties preclude standard clustering in a large class of biochemical data.

PubMed

Gomez, Florian; Stoop, Ralph L; Stoop, Ruedi

2014-09-01

Clustering of chemical and biochemical data based on observed features is a central cognitive step in the analysis of chemical substances, in particular in combinatorial chemistry, or of complex biochemical reaction networks. Often, for reasons unknown to the researcher, this step produces disappointing results. Once the sources of the problem are known, improved clustering methods might revitalize the statistical approach of compound and reaction search and analysis. Here, we present a generic mechanism that may be at the origin of many clustering difficulties. The variety of dynamical behaviors that can be exhibited by complex biochemical reactions on variation of the system parameters are fundamental system fingerprints. In parameter space, shrimp-like or swallow-tail structures separate parameter sets that lead to stable periodic dynamical behavior from those leading to irregular behavior. We work out the genericity of this phenomenon and demonstrate novel examples for their occurrence in realistic models of biophysics. Although we elucidate the phenomenon by considering the emergence of periodicity in dependence on system parameters in a low-dimensional parameter space, the conclusions from our simple setting are shown to continue to be valid for features in a higher-dimensional feature space, as long as the feature-generating mechanism is not too extreme and the dimension of this space is not too high compared with the amount of available data. For online versions of super-paramagnetic clustering see http://stoop.ini.uzh.ch/research/clustering. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Presentation on systems cluster research

NASA Technical Reports Server (NTRS)

Morgenthaler, George W.

1989-01-01

This viewgraph presentation presents an overview of systems cluster research performed by the Center for Space Construction. The goals of the research are to develop concepts, insights, and models for space construction and to develop systems engineering/analysis curricula for training future aerospace engineers. The following topics are covered: CSC systems analysis/systems engineering (SIMCON) model, CSC systems cluster schedule, system life-cycle, model optimization techniques, publications, cooperative efforts, and sponsored research.

A Commodity Computing Cluster

NASA Astrophysics Data System (ADS)

Teuben, P. J.; Wolfire, M. G.; Pound, M. W.; Mundy, L. G.

We have assembled a cluster of Intel-Pentium based PCs running Linux to compute a large set of Photodissociation Region (PDR) and Dust Continuum models. For various reasons the cluster is heterogeneous, currently ranging from a single Pentium-II 333 MHz to dual Pentium-III 450 MHz CPU machines. Although this will be sufficient for our ``embarrassingly parallelizable problem'' it may present some challenges for as yet unplanned future use. In addition the cluster was used to construct a MIRIAD benchmark, and compared to equivalent Ultra-Sparc based workstations. Currently the cluster consists of 8 machines, 14 CPUs, 50GB of disk-space, and a total peak speed of 5.83 GHz, or about 1.5 Gflops. The total cost of this cluster has been about $12,000, including all cabling, networking equipment, rack, and a CD-R backup system. The URL for this project is http://dustem.astro.umd.edu.

STAR CLUSTER FORMATION WITH STELLAR FEEDBACK AND LARGE-SCALE INFLOW

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matzner, Christopher D.; Jumper, Peter H., E-mail: matzner@astro.utoronto.ca

2015-12-10

During star cluster formation, ongoing mass accretion is resisted by stellar feedback in the form of protostellar outflows from the low-mass stars and photo-ionization and radiation pressure feedback from the massive stars. We model the evolution of cluster-forming regions during a phase in which both accretion and feedback are present and use these models to investigate how star cluster formation might terminate. Protostellar outflows are the strongest form of feedback in low-mass regions, but these cannot stop cluster formation if matter continues to flow in. In more massive clusters, radiation pressure and photo-ionization rapidly clear the cluster-forming gas when itsmore » column density is too small. We assess the rates of dynamical mass ejection and of evaporation, while accounting for the important effect of dust opacity on photo-ionization. Our models are consistent with the census of protostellar outflows in NGC 1333 and Serpens South and with the dust temperatures observed in regions of massive star formation. Comparing observations of massive cluster-forming regions against our model parameter space, and against our expectations for accretion-driven evolution, we infer that massive-star feedback is a likely cause of gas disruption in regions with velocity dispersions less than a few kilometers per second, but that more massive and more turbulent regions are too strongly bound for stellar feedback to be disruptive.« less

The correlation function for density perturbations in an expanding universe. III The three-point and predictions of the four-point and higher order correlation functions

NASA Technical Reports Server (NTRS)

Mcclelland, J.; Silk, J.

1978-01-01

Higher-order correlation functions for the large-scale distribution of galaxies in space are investigated. It is demonstrated that the three-point correlation function observed by Peebles and Groth (1975) is not consistent with a distribution of perturbations that at present are randomly distributed in space. The two-point correlation function is shown to be independent of how the perturbations are distributed spatially, and a model of clustered perturbations is developed which incorporates a nonuniform perturbation distribution and which explains the three-point correlation function. A model with hierarchical perturbations incorporating the same nonuniform distribution is also constructed; it is found that this model also explains the three-point correlation function, but predicts different results for the four-point and higher-order correlation functions than does the model with clustered perturbations. It is suggested that the model of hierarchical perturbations might be explained by the single assumption of having density fluctuations or discrete objects all of the same mass randomly placed at some initial epoch.

Clustering in the SDSS Redshift Survey

NASA Astrophysics Data System (ADS)

Zehavi, I.; Blanton, M. R.; Frieman, J. A.; Weinberg, D. H.; SDSS Collaboration

2002-05-01

We present measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our current sample consists of roughly 80,000 galaxies with redshifts in the range 0.02 < z < 0.2, covering about 1200 square degrees. We measure the clustering in redshift space and in real space. The two-dimensional correlation function ξ (rp,π ) shows clear signatures of redshift distortions, both the small-scale ``fingers-of-God'' effect and the large-scale compression. The inferred real-space correlation function is well described by a power law. The SDSS is especially suitable for investigating the dependence of clustering on galaxy properties, due to the wealth of information in the photometric survey. We focus on the dependence of clustering on color and on luminosity.

An Open-Source Galaxy Redshift Survey Simulator for next-generation Large Scale Structure Surveys

NASA Astrophysics Data System (ADS)

Seijak, Uros

Galaxy redshift surveys produce three-dimensional maps of the galaxy distribution. On large scales these maps trace the underlying matter fluctuations in a relatively simple manner, so that the properties of the primordial fluctuations along with the overall expansion history and growth of perturbations can be extracted. The BAO standard ruler method to measure the expansion history of the universe using galaxy redshift surveys is thought to be robust to observational artifacts and understood theoretically with high precision. These same surveys can offer a host of additional information, including a measurement of the growth rate of large scale structure through redshift space distortions, the possibility of measuring the sum of neutrino masses, tighter constraints on the expansion history through the Alcock-Paczynski effect, and constraints on the scale-dependence and non-Gaussianity of the primordial fluctuations. Extracting this broadband clustering information hinges on both our ability to minimize and subtract observational systematics to the observed galaxy power spectrum, and our ability to model the broadband behavior of the observed galaxy power spectrum with exquisite precision. Rapid development on both fronts is required to capitalize on WFIRST's data set. We propose to develop an open-source computational toolbox that will propel development in both areas by connecting large scale structure modeling and instrument and survey modeling with the statistical inference process. We will use the proposed simulator to both tailor perturbation theory and fully non-linear models of the broadband clustering of WFIRST galaxies and discover novel observables in the non-linear regime that are robust to observational systematics and able to distinguish between a wide range of spatial and dynamic biasing models for the WFIRST galaxy redshift survey sources. We have demonstrated the utility of this approach in a pilot study of the SDSS-III BOSS galaxies, in which we improved the redshift space distortion growth rate measurement precision by a factor of 2.5 using customized clustering statistics in the non-linear regime that were immunized against observational systematics. We look forward to addressing the unique challenges of modeling and empirically characterizing the WFIRST galaxies and observational systematics.

Predictability of Circulation Transitions (Observed and Modeled): Non-diffusive Dynamics, Markov Chains and Error Growth.

NASA Astrophysics Data System (ADS)

Straus, D. M.

2006-12-01

The transitions between portions of the state space of the large-scale flow is studied from daily wintertime data over the Pacific North America region using the NCEP reanalysis data set (54 winters) and very large suites of hindcasts made with the COLA atmospheric GCM with observed SST (55 members for each of 18 winters). The partition of the large-scale state space is guided by cluster analysis, whose statistical significance and relationship to SST is reviewed (Straus and Molteni, 2004; Straus, Corti and Molteni, 2006). The determination of the global nature of the flow through state space is studied using Markov Chains (Crommelin, 2004). In particular the non-diffusive part of the flow is contrasted in nature (small data sample) and the AGCM (large data sample). The intrinsic error growth associated with different portions of the state space is studied through sets of identical twin AGCM simulations. The goal is to obtain realistic estimates of predictability times for large-scale transitions that should be useful in long-range forecasting.

Redshift space clustering of galaxies and cold dark matter model

NASA Technical Reports Server (NTRS)

Bahcall, Neta A.; Cen, Renyue; Gramann, Mirt

1993-01-01

The distorting effect of peculiar velocities on the power speturm and correlation function of IRAS and optical galaxies is studied. The observed redshift space power spectra and correlation functions of IRAS and optical the galaxies over the entire range of scales are directly compared with the corresponding redshift space distributions using large-scale computer simulations of cold dark matter (CDM) models in order to study the distortion effect of peculiar velocities on the power spectrum and correlation function of the galaxies. It is found that the observed power spectrum of IRAS and optical galaxies is consistent with the spectrum of an Omega = 1 CDM model. The problems that such a model currently faces may be related more to the high value of Omega in the model than to the shape of the spectrum. A low-density CDM model is also investigated and found to be consistent with the data.

The evolution of the Sun's birth cluster and the search for the solar siblings with Gaia

NASA Astrophysics Data System (ADS)

Martínez-Barbosa, C. A.; Brown, A. G. A.; Boekholt, T.; Portegies Zwart, S.; Antiche, E.; Antoja, T.

2016-03-01

We use self-consistent numerical simulations of the evolution and disruption of the Sun's birth cluster in the Milky Way potential to investigate the present-day phase-space distribution of the Sun's siblings. The simulations include the gravitational N-body forces within the cluster and the effects of stellar evolution on the cluster population. In addition, the gravitational forces due to the Milky Way potential are accounted for in a self-consistent manner. Our aim is to understand how the astrometric and radial velocity data from the Gaia mission can be used to pre-select solar sibling candidates. We vary the initial conditions of the Sun's birth cluster, as well as the parameters of the Galactic potential. In particular, we use different configurations and strengths of the bar and spiral arms. We show that the disruption time-scales of the cluster are insensitive to the details of the non-axisymmetric components of the Milky Way model and we make predictions, averaged over the different simulated possibilities, about the number of solar siblings that should appear in surveys such as Gaia or GALAH. We find a large variety of present-day phase-space distributions of solar siblings, which depend on the cluster initial conditions and the Milky Way model parameters. We show that nevertheless robust predictions can be made about the location of the solar siblings in the space of parallaxes (ϖ), proper motions (μ) and radial velocities (Vr). By calculating the ratio of the number of simulated solar siblings to that of the number of stars in a model Galactic disc, we find that this ratio is above 0.5 in the region given by: ϖ ≥ 5 mas, 4 ≤ μ ≤ 6 mas yr-1, and -2 ≤ Vr ≤ 0 km s-1. Selecting stars from this region should increase the probability of success in identifying solar siblings through follow-up observations. However the proposed pre-selection criterion is sensitive to our assumptions, in particular about the Galactic potential. Using a more realistic potential (e.g. including transient spiral structure and molecular clouds) would make the pre-selection of solar sibling candidates based on astrometric and radial velocity data very inefficient. This reinforces the need for large-scale surveys to determine precise astrophysical properties of stars, in particular their ages and chemical abundances, if we want to identify the solar family.

The GALAH survey: chemical tagging of star clusters and new members in the Pleiades

NASA Astrophysics Data System (ADS)

Kos, Janez; Bland-Hawthorn, Joss; Freeman, Ken; Buder, Sven; Traven, Gregor; De Silva, Gayandhi M.; Sharma, Sanjib; Asplund, Martin; Duong, Ly; Lin, Jane; Lind, Karin; Martell, Sarah; Simpson, Jeffrey D.; Stello, Dennis; Zucker, Daniel B.; Zwitter, Tomaž; Anguiano, Borja; Da Costa, Gary; D'Orazi, Valentina; Horner, Jonathan; Kafle, Prajwal R.; Lewis, Geraint; Munari, Ulisse; Nataf, David M.; Ness, Melissa; Reid, Warren; Schlesinger, Katie; Ting, Yuan-Sen; Wyse, Rosemary

2018-02-01

The technique of chemical tagging uses the elemental abundances of stellar atmospheres to 'reconstruct' chemically homogeneous star clusters that have long since dispersed. The GALAH spectroscopic survey - which aims to observe one million stars using the Anglo-Australian Telescope - allows us to measure up to 30 elements or dimensions in the stellar chemical abundance space, many of which are not independent. How to find clustering reliably in a noisy high-dimensional space is a difficult problem that remains largely unsolved. Here, we explore t-distributed stochastic neighbour embedding (t-SNE) - which identifies an optimal mapping of a high-dimensional space into fewer dimensions - whilst conserving the original clustering information. Typically, the projection is made to a 2D space to aid recognition of clusters by eye. We show that this method is a reliable tool for chemical tagging because it can: (i) resolve clustering in chemical space alone, (ii) recover known open and globular clusters with high efficiency and low contamination, and (iii) relate field stars to known clusters. t-SNE also provides a useful visualization of a high-dimensional space. We demonstrate the method on a data set of 13 abundances measured in the spectra of 187 000 stars by the GALAH survey. We recover seven of the nine observed clusters (six globular and three open clusters) in chemical space with minimal contamination from field stars and low numbers of outliers. With chemical tagging, we also identify two Pleiades supercluster members (which we confirm kinematically), one as far as 6° - one tidal radius away from the cluster centre.

Resolved photometry of extragalactic young massive star clusters

NASA Astrophysics Data System (ADS)

Larsen, S. S.; de Mink, S. E.; Eldridge, J. J.; Langer, N.; Bastian, N.; Seth, A.; Smith, L. J.; Brodie, J.; Efremov, Yu. N.

2011-08-01

Aims: We present colour-magnitude diagrams (CMDs) of young massive star clusters in several galaxies located well beyond the Local Group. The richness of these clusters allows us to obtain large samples of post-main sequence stars and test how well the observed CMDs are reproduced by canonical stellar isochrones. Methods: We use imaging of seven clusters in the galaxies NGC 1313, NGC 1569, NGC 1705, NGC 5236 and NGC 7793 obtained with the Advanced Camera for Surveys on board the Hubble Space Telescope and carry out PSF-fitting photometry of individual stars in the clusters. The clusters have ages in the range ~(5-50) × 106 years and masses of ~105 M⊙-106 M⊙. Although crowding prevents us from obtaining photometry in the inner regions of the clusters, we are still able to measure up to 30-100 supergiant stars in each of the richest clusters. The resulting CMDs and luminosity functions are compared with photometry of artificially generated clusters, designed to reproduce the photometric errors and completeness as realistically as possible. Results: In agreement with previous studies, our CMDs show no clear gap between the H-burning main sequence and the He-burning supergiant stars, contrary to predictions by common stellar isochrones. In general, the isochrones also fail to match the observed number ratios of red-to-blue supergiant stars, although the difficulty of separating blue supergiants from the main sequence complicates this comparison. In several cases we observe a large spread (1-2 mag) in the luminosities of the supergiant stars that cannot be accounted for by observational errors. We find that this spread can be reproduced by including an age spread of ~(10-30) × 106 years in the models. However, age spreads cannot fully account for the observed morphology of the CMDs and other processes, such as the evolution of interacting binary stars, may also play a role. Conclusions: Colour-magnitude diagrams can be successfully obtained for massive star clusters out to distances of at least 4-5 Mpc. Comparing such CMDs with models based on canonical isochrones we find several areas of disagreement. One interesting possibility is that an age spread of up to ~30 Myr may be present in some clusters. The data presented here may provide useful constraints on models for single and/or binary stellar evolution. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained from the data archive at the Space Telescope Science Institute. STScI is operated by the association of Universities for Research in Astronomy, Inc. under the NASA contract NAS 5-26555Tables 4-10 are only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/532/A147

The WAGGS project - I. The WiFeS Atlas of Galactic Globular cluster Spectra

NASA Astrophysics Data System (ADS)

Usher, Christopher; Pastorello, Nicola; Bellstedt, Sabine; Alabi, Adebusola; Cerulo, Pierluigi; Chevalier, Leonie; Fraser-McKelvie, Amelia; Penny, Samantha; Foster, Caroline; McDermid, Richard M.; Schiavon, Ricardo P.; Villaume, Alexa

2017-07-01

We present the WiFeS Atlas of Galactic Globular cluster Spectra, a library of integrated spectra of Milky Way and Local Group globular clusters. We used the WiFeS integral field spectrograph on the Australian National University 2.3 m telescope to observe the central regions of 64 Milky Way globular clusters and 22 globular clusters hosted by the Milky Way's low-mass satellite galaxies. The spectra have wider wavelength coverage (3300-9050 Å) and higher spectral resolution (R = 6800) than existing spectral libraries of Milky Way globular clusters. By including Large and Small Magellanic Cloud star clusters, we extend the coverage of parameter space of existing libraries towards young and intermediate ages. While testing stellar population synthesis models and analysis techniques is the main aim of this library, the observations may also further our understanding of the stellar populations of Local Group globular clusters and make possible the direct comparison of extragalactic globular cluster integrated light observations with well-understood globular clusters in the Milky Way. The integrated spectra are publicly available via the project website.

The impact of galaxy formation on satellite kinematics and redshift-space distortions

NASA Astrophysics Data System (ADS)

Orsi, Álvaro A.; Angulo, Raúl E.

2018-04-01

Galaxy surveys aim to map the large-scale structure of the Universe and use redshift-space distortions to constrain deviations from general relativity and probe the existence of massive neutrinos. However, the amount of information that can be extracted is limited by the accuracy of theoretical models used to analyse the data. Here, by using the L-Galaxies semi-analytical model run over the Millennium-XXL N-body simulation, we assess the impact of galaxy formation on satellite kinematics and the theoretical modelling of redshift-space distortions. We show that different galaxy selection criteria lead to noticeable differences in the radial distributions and velocity structure of satellite galaxies. Specifically, whereas samples of stellar mass selected galaxies feature satellites that roughly follow the dark matter, emission line satellite galaxies are located preferentially in the outskirts of haloes and display net infall velocities. We demonstrate that capturing these differences is crucial for modelling the multipoles of the correlation function in redshift space, even on large scales. In particular, we show how modelling small-scale velocities with a single Gaussian distribution leads to a poor description of the measured clustering. In contrast, we propose a parametrization that is flexible enough to model the satellite kinematics and that leads to an accurate description of the correlation function down to sub-Mpc scales. We anticipate that our model will be a necessary ingredient in improved theoretical descriptions of redshift-space distortions, which together could result in significantly tighter cosmological constraints and a more optimal exploitation of future large data sets.

A two-step patterning process increases the robustness of periodic patterning in the fly eye.

PubMed

Gavish, Avishai; Barkai, Naama

2016-06-01

Complex periodic patterns can self-organize through dynamic interactions between diffusible activators and inhibitors. In the biological context, self-organized patterning is challenged by spatial heterogeneities ('noise') inherent to biological systems. How spatial variability impacts the periodic patterning mechanism and how it can be buffered to ensure precise patterning is not well understood. We examine the effect of spatial heterogeneity on the periodic patterning of the fruit fly eye, an organ composed of ∼800 miniature eye units (ommatidia) whose periodic arrangement along a hexagonal lattice self-organizes during early stages of fly development. The patterning follows a two-step process, with an initial formation of evenly spaced clusters of ∼10 cells followed by a subsequent refinement of each cluster into a single selected cell. Using a probabilistic approach, we calculate the rate of patterning errors resulting from spatial heterogeneities in cell size, position and biosynthetic capacity. Notably, error rates were largely independent of the desired cluster size but followed the distributions of signaling speeds. Pre-formation of large clusters therefore greatly increases the reproducibility of the overall periodic arrangement, suggesting that the two-stage patterning process functions to guard the pattern against errors caused by spatial heterogeneities. Our results emphasize the constraints imposed on self-organized patterning mechanisms by the need to buffer stochastic effects. Author summary Complex periodic patterns are common in nature and are observed in physical, chemical and biological systems. Understanding how these patterns are generated in a precise manner is a key challenge. Biological patterns are especially intriguing, as they are generated in a noisy environment; cell position and cell size, for example, are subject to stochastic variations, as are the strengths of the chemical signals mediating cell-to-cell communication. The need to generate a precise and robust pattern in this 'noisy' environment restricts the space of patterning mechanisms that can function in the biological setting. Mathematical modeling is useful in comparing the sensitivity of different mechanisms to such variations, thereby highlighting key aspects of their design.We use mathematical modeling to study the periodic patterning of the fruit fly eye. In this system, a highly ordered lattice of differentiated cells is generated in a two-dimensional cell epithelium. The pattern is first observed by the appearance of evenly spaced clusters of ∼10 cells that express specific genes. Each cluster is subsequently refined into a single cell, which initiates the formation and differentiation of a miniature eye unit, the ommatidium. We formulate a mathematical model based on the known molecular properties of the patterning mechanism, and use a probabilistic approach to calculate the errors in cluster formation and refinement resulting from stochastic cell-to-cell variations ('noise') in different quantitative parameters. This enables us to define the parameters most influencing noise sensitivity. Notably, we find that this error is roughly independent of the desired cluster size, suggesting that large clusters are beneficial for ensuring the overall reproducibility of the periodic cluster arrangement. For the stage of cluster refinement, we find that rapid communication between cells is critical for reducing error. Our work provides new insights into the constraints imposed on mechanisms generating periodic patterning in a realistic, noisy environment, and in particular, discusses the different considerations in achieving optimal design of the patterning network.

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

NASA Astrophysics Data System (ADS)

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard

2014-09-01

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G., E-mail: yannis@princeton.edu, E-mail: gerhard.hummer@biophys.mpg.de

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlapmore » with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.« less

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

PubMed Central

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard

2014-01-01

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space. PMID:25240340

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Cosmological implications of the Fourier space wedges of the final sample

NASA Astrophysics Data System (ADS)

Grieb, Jan Niklas; Sánchez, Ariel G.; Salazar-Albornoz, Salvador; Scoccimarro, Román; Crocce, Martín; Dalla Vecchia, Claudio; Montesano, Francesco; Gil-Marín, Héctor; Ross, Ashley J.; Beutler, Florian; Rodríguez-Torres, Sergio; Chuang, Chia-Hsun; Prada, Francisco; Kitaura, Francisco-Shu; Cuesta, Antonio J.; Eisenstein, Daniel J.; Percival, Will J.; Vargas-Magaña, Mariana; Tinker, Jeremy L.; Tojeiro, Rita; Brownstein, Joel R.; Maraston, Claudia; Nichol, Robert C.; Olmstead, Matthew D.; Samushia, Lado; Seo, Hee-Jong; Streblyanska, Alina; Zhao, Gong-bo

2017-05-01

We extract cosmological information from the anisotropic power-spectrum measurements from the recently completed Baryon Oscillation Spectroscopic Survey (BOSS), extending the concept of clustering wedges to Fourier space. Making use of new fast-Fourier-transform-based estimators, we measure the power-spectrum clustering wedges of the BOSS sample by filtering out the information of Legendre multipoles ℓ > 4. Our modelling of these measurements is based on novel approaches to describe non-linear evolution, bias and redshift-space distortions, which we test using synthetic catalogues based on large-volume N-body simulations. We are able to include smaller scales than in previous analyses, resulting in tighter cosmological constraints. Using three overlapping redshift bins, we measure the angular-diameter distance, the Hubble parameter and the cosmic growth rate, and explore the cosmological implications of our full-shape clustering measurements in combination with cosmic microwave background and Type Ia supernova data. Assuming a Λ cold dark matter (ΛCDM) cosmology, we constrain the matter density to Ω M= 0.311_{-0.010}^{+0.009} and the Hubble parameter to H_0 = 67.6_{-0.6}^{+0.7} km s^{-1 Mpc^{-1}}, at a confidence level of 68 per cent. We also allow for non-standard dark energy models and modifications of the growth rate, finding good agreement with the ΛCDM paradigm. For example, we constrain the equation-of-state parameter to w = -1.019_{-0.039}^{+0.048}. This paper is part of a set that analyses the final galaxy-clustering data set from BOSS. The measurements and likelihoods presented here are combined with others in Alam et al. to produce the final cosmological constraints from BOSS.

Topic modeling for cluster analysis of large biological and medical datasets

PubMed Central

2014-01-01

Background The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. Results In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Conclusion Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets. PMID:25350106

Topic modeling for cluster analysis of large biological and medical datasets.

PubMed

Zhao, Weizhong; Zou, Wen; Chen, James J

2014-01-01

The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets.

A gravitational puzzle.

PubMed

Caldwell, Robert R

2011-12-28

The challenge to understand the physical origin of the cosmic acceleration is framed as a problem of gravitation. Specifically, does the relationship between stress-energy and space-time curvature differ on large scales from the predictions of general relativity. In this article, we describe efforts to model and test a generalized relationship between the matter and the metric using cosmological observations. Late-time tracers of large-scale structure, including the cosmic microwave background, weak gravitational lensing, and clustering are shown to provide good tests of the proposed solution. Current data are very close to proving a critical test, leaving only a small window in parameter space in the case that the generalized relationship is scale free above galactic scales.

Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition

PubMed Central

Vajda, Szilárd; Rangoni, Yves; Cecotti, Hubert

2015-01-01

For training supervised classifiers to recognize different patterns, large data collections with accurate labels are necessary. In this paper, we propose a generic, semi-automatic labeling technique for large handwritten character collections. In order to speed up the creation of a large scale ground truth, the method combines unsupervised clustering and minimal expert knowledge. To exploit the potential discriminant complementarities across features, each character is projected into five different feature spaces. After clustering the images in each feature space, the human expert labels the cluster centers. Each data point inherits the label of its cluster’s center. A majority (or unanimity) vote decides the label of each character image. The amount of human involvement (labeling) is strictly controlled by the number of clusters – produced by the chosen clustering approach. To test the efficiency of the proposed approach, we have compared, and evaluated three state-of-the art clustering methods (k-means, self-organizing maps, and growing neural gas) on the MNIST digit data set, and a Lampung Indonesian character data set, respectively. Considering a k-nn classifier, we show that labeling manually only 1.3% (MNIST), and 3.2% (Lampung) of the training data, provides the same range of performance than a completely labeled data set would. PMID:25870463

Model-based Clustering of High-Dimensional Data in Astrophysics

NASA Astrophysics Data System (ADS)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

Clustering methods for the optimization of atomic cluster structure

NASA Astrophysics Data System (ADS)

Bagattini, Francesco; Schoen, Fabio; Tigli, Luca

2018-04-01

In this paper, we propose a revised global optimization method and apply it to large scale cluster conformation problems. In the 1990s, the so-called clustering methods were considered among the most efficient general purpose global optimization techniques; however, their usage has quickly declined in recent years, mainly due to the inherent difficulties of clustering approaches in large dimensional spaces. Inspired from the machine learning literature, we redesigned clustering methods in order to deal with molecular structures in a reduced feature space. Our aim is to show that by suitably choosing a good set of geometrical features coupled with a very efficient descent method, an effective optimization tool is obtained which is capable of finding, with a very high success rate, all known putative optima for medium size clusters without any prior information, both for Lennard-Jones and Morse potentials. The main result is that, beyond being a reliable approach, the proposed method, based on the idea of starting a computationally expensive deep local search only when it seems worth doing so, is capable of saving a huge amount of searches with respect to an analogous algorithm which does not employ a clustering phase. In this paper, we are not claiming the superiority of the proposed method compared to specific, refined, state-of-the-art procedures, but rather indicating a quite straightforward way to save local searches by means of a clustering scheme working in a reduced variable space, which might prove useful when included in many modern methods.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Powalka, Mathieu; Lançon, Ariane; Duc, Pierre-Alain

Large samples of globular clusters (GC) with precise multi-wavelength photometry are becoming increasingly available and can be used to constrain the formation history of galaxies. We present the results of an analysis of Milky Way (MW) and Virgo core GCs based on 5 optical-near-infrared colors and 10 synthetic stellar population models. For the MW GCs, the models tend to agree on photometric ages and metallicities, with values similar to those obtained with previous studies. When used with Virgo core GCs, for which photometry is provided by the Next Generation Virgo cluster Survey (NGVS), the same models generically return younger ages.more » This is a consequence of the systematic differences observed between the locus occupied by Virgo core GCs and models in panchromatic color space. Only extreme fine-tuning of the adjustable parameters available to us can make the majority of the best-fit ages old. Although we cannot exclude that the formation history of the Virgo core may lead to more conspicuous populations of relatively young GCs than in other environments, we emphasize that the intrinsic properties of the Virgo GCs are likely to differ systematically from those assumed in the models. Thus, the large wavelength coverage and photometric quality of modern GC samples, such as those used here, is not by itself sufficient to better constrain the GC formation histories. Models matching the environment-dependent characteristics of GCs in multi-dimensional color space are needed to improve the situation.« less

Avulsion Clusters in Alluvial Systems: An Example of Large-Scale Self-Organization in Ancient and Experimental Basins

NASA Astrophysics Data System (ADS)

Hajek, E.; Heller, P.; Huzurbazar, S.; Sheets, B.; Paola, C.

2006-12-01

The stratigraphic record of at least some alluvial basins exhibits a spatial structure that may reflect long time- scale (103-105 yr in natural basins) autogenic organization of river avulsions. Current models of avulsion-dominated alluvial sequences emphasize the spatial and temporal distribution of coarse-grained channel-belt deposits amid fine-grained floodplain materials. These models typically assume that individual avulsions move, either randomly or deterministically, to low spots distributed throughout the model space. However, our observations of ancient deposits and experimental stratigraphy indicate a previously unrecognized pattern of channel-belt organization, where clusters of closely-spaced channel-belt deposits are separated from each other by extensive intervals of overbank deposits. We explore potential causes of and controls on avulsion clustering with outcrop and subsurface data from Late Cretaceous/Early Paleogene fluvial deposits in the Rocky Mountains (including the Ferris, Lance, and Fort Union formations of Wyoming) and results of physical stratigraphy experiments from the St. Anthony Falls Lab, University of Minnesota. We use Ripley's K-function to determine the degree and scales of clustering in these basins with results that show moderate statistical clustering in experimental deposits and strong clustering in the Ferris Formation (Hanna Basin, Wyoming). External controls (base level, subsidence rate, and sediment/water supplies) were not varied during the experiment, and therefore not factors in cluster formation. Likewise, the stratigraphic context of the ancient system (including the absence of incised valleys and lack of faulting) suggests that obvious extrinsic controls, such as base level change and local tectonics, were not major influences on the development of clusters. We propose that avulsion clusters, as seen in this study, reflect a scale of self-organization in alluvial basins that is not usually recognized in stratigraphy. However cursory examination of other ancient systems suggests that such structure may be common in the rock record. Understanding mechanisms driving avulsion clustering will shed light on the dominant processes in alluvial basins over long time scales. Furthermore, characterizing autogenic avulsion clusters will be an important factor to consider when interpreting allogenic signals in ancient basin fills.

Impact of large-scale tides on cosmological distortions via redshift-space power spectrum

NASA Astrophysics Data System (ADS)

Akitsu, Kazuyuki; Takada, Masahiro

2018-03-01

Although large-scale perturbations beyond a finite-volume survey region are not direct observables, these affect measurements of clustering statistics of small-scale (subsurvey) perturbations in large-scale structure, compared with the ensemble average, via the mode-coupling effect. In this paper we show that a large-scale tide induced by scalar perturbations causes apparent anisotropic distortions in the redshift-space power spectrum of galaxies in a way depending on an alignment between the tide, wave vector of small-scale modes and line-of-sight direction. Using the perturbation theory of structure formation, we derive a response function of the redshift-space power spectrum to large-scale tide. We then investigate the impact of large-scale tide on estimation of cosmological distances and the redshift-space distortion parameter via the measured redshift-space power spectrum for a hypothetical large-volume survey, based on the Fisher matrix formalism. To do this, we treat the large-scale tide as a signal, rather than an additional source of the statistical errors, and show that a degradation in the parameter is restored if we can employ the prior on the rms amplitude expected for the standard cold dark matter (CDM) model. We also discuss whether the large-scale tide can be constrained at an accuracy better than the CDM prediction, if the effects up to a larger wave number in the nonlinear regime can be included.

Nano-confinement inside molecular metal oxide clusters: Dynamics and modified encapsulation behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhe; Daemen, Luke L.; Cheng, Yongqiang

Encapsulation behavior, as well as the presence of internal catalytically-active sites, has been spurring the applications of a 3 nm hollow spherical metal oxide cluster {Mo 132} as an encapsulation host and a nano-reactor. Due to its well-defined and tunable cluster structures, and nano-scaled internal void space comparable to the volumes of small molecules, this cluster provides a good model to study the dynamics of materials under ultra-confinement. Neutron scattering studies suggest that bulky internal ligands inside the cluster show slower and limited dynamics compared to their counterparts in the bulk state, revealing the rigid nature of the skeleton ofmore » the internal ligands. Furthermore, NMR studies indicate that the rigid internal ligands that partially cover the interfacial pore on the molybdenum oxide shells are able to block some large guest molecules from going inside the capsule cluster, which provides a convincing protocol for size-selective encapsulation and separation.« less

Nano-confinement inside molecular metal oxide clusters: Dynamics and modified encapsulation behavior

DOE PAGES

Wang, Zhe; Daemen, Luke L.; Cheng, Yongqiang; ...

2016-08-19

Encapsulation behavior, as well as the presence of internal catalytically-active sites, has been spurring the applications of a 3 nm hollow spherical metal oxide cluster {Mo 132} as an encapsulation host and a nano-reactor. Due to its well-defined and tunable cluster structures, and nano-scaled internal void space comparable to the volumes of small molecules, this cluster provides a good model to study the dynamics of materials under ultra-confinement. Neutron scattering studies suggest that bulky internal ligands inside the cluster show slower and limited dynamics compared to their counterparts in the bulk state, revealing the rigid nature of the skeleton ofmore » the internal ligands. Furthermore, NMR studies indicate that the rigid internal ligands that partially cover the interfacial pore on the molybdenum oxide shells are able to block some large guest molecules from going inside the capsule cluster, which provides a convincing protocol for size-selective encapsulation and separation.« less

The MICE grand challenge lightcone simulation - I. Dark matter clustering

NASA Astrophysics Data System (ADS)

Fosalba, P.; Crocce, M.; Gaztañaga, E.; Castander, F. J.

2015-04-01

We present a new N-body simulation from the Marenostrum Institut de Ciències de l'Espai (MICE) collaboration, the MICE Grand Challenge (MICE-GC), containing about 70 billion dark matter particles in a (3 Gpc h-1)3 comoving volume. Given its large volume and fine spatial resolution, spanning over five orders of magnitude in dynamic range, it allows an accurate modelling of the growth of structure in the universe from the linear through the highly non-linear regime of gravitational clustering. We validate the dark matter simulation outputs using 3D and 2D clustering statistics, and discuss mass-resolution effects in the non-linear regime by comparing to previous simulations and the latest numerical fits. We show that the MICE-GC run allows for a measurement of the BAO feature with per cent level accuracy and compare it to state-of-the-art theoretical models. We also use sub-arcmin resolution pixelized 2D maps of the dark matter counts in the lightcone to make tomographic analyses in real and redshift space. Our analysis shows the simulation reproduces the Kaiser effect on large scales, whereas we find a significant suppression of power on non-linear scales relative to the real space clustering. We complete our validation by presenting an analysis of the three-point correlation function in this and previous MICE simulations, finding further evidence for mass-resolution effects. This is the first of a series of three papers in which we present the MICE-GC simulation, along with a wide and deep mock galaxy catalogue built from it. This mock is made publicly available through a dedicated web portal, http://cosmohub.pic.es.

Gravitational redshift and asymmetric redshift-space distortions for stacked clusters

NASA Astrophysics Data System (ADS)

Cai, Yan-Chuan; Kaiser, Nick; Cole, Shaun; Frenk, Carlos

2017-06-01

We derive the expression for the observed redshift in the weak field limit in the observer's past light cone, including all relativistic terms up to second order in velocity. We then apply it to compute the cluster-galaxy cross-correlation functions (CGCF) using N-body simulations. The CGCF is asymmetric along the line of sight owing to the presence of the small second-order terms such as the gravitational redshift (GRedshift). We identify two systematics in the modelling of the GRedshift signal in stacked clusters. First, it is affected by the morphology of dark matter haloes and the large-scale cosmic-web. The non-spherical distribution of galaxies around the central halo and the presence of neighbouring clusters systematically reduce the GRedshift signal. This bias is approximately 20 per cent for Mmin ≃ 1014 M⊙ h-1, and is more than 50 per cent for haloes with Mmin ≃ 2 × 1013 M⊙ h-1 at r > 4 Mpc h-1. Secondly, the best-fitting GRedshift profiles as well as the profiles of all other relativistic terms are found to be significantly different in velocity space compared to their real space versions. We find that the relativistic Doppler redshift effect, like other second-order effects, is subdominant to the GRedshift signal. We discuss some subtleties relating to these effects in velocity space. We also find that the S/N of the GRedshift signal increases with decreasing halo mass.

BLUE STRAGGLER EVOLUTION CAUGHT IN THE ACT IN THE LARGE MAGELLANIC CLOUD GLOBULAR CLUSTER HODGE 11

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Chengyuan; De Grijs, Richard; Liu Xiangkun

High-resolution Hubble Space Telescope imaging observations show that the radial distribution of the field-decontaminated sample of 162 'blue straggler' stars (BSs) in the 11.7{sup +0.2}{sub -0.1} Gyr old Large Magellanic Cloud cluster Hodge 11 exhibits a clear bimodality. In combination with their distinct loci in color-magnitude space, this offers new evidence in support of theoretical expectations that suggest different BS formation channels as a function of stellar density. In the cluster's color-magnitude diagram, the BSs in the inner 15'' (roughly corresponding to the cluster's core radius) are located more closely to the theoretical sequence resulting from stellar collisions, while thosemore » in the periphery (at radii between 85'' and 100'') are preferentially found in the region expected to contain objects formed through binary mass transfer or coalescence. In addition, the objects' distribution in color-magnitude space provides us with the rare opportunity in an extragalactic environment to quantify the evolution of the cluster's collisionally induced BS population and the likely period that has elapsed since their formation epoch, which we estimate to have occurred {approx}4-5 Gyr ago.« less

The Formation and Early Evolution of Embedded Massive Star Clusters

NASA Astrophysics Data System (ADS)

Barnes, Peter

We propose to combine Spitzer, WISE, Herschel, and other archival spacecraft data with an existing ground- and space-based mm-wave to near-IR survey of molecular clouds over a large portion of the Milky Way, in order to systematically study the formation and early evolution of massive stars and star clusters, and provide new observational calibrations for a theoretical paradigm of this key astrophysical problem. Central Objectives: The Galactic Census of High- and Medium-mass Protostars (CHaMP) is a large, unbiased, uniform, and panchromatic survey of massive star and cluster formation and early evolution, covering 20°x6° of the Galactic Plane. Its uniqueness lies in the comprehensive molecular spectroscopy of 303 massive dense clumps, which have also been included in several archival spacecraft surveys. Our objective is a systematic demographic analysis of massive star and cluster formation, one which has not been possible without knowledge of our CHaMP cloud sample, including all clouds with embedded clusters as well as those that have not yet formed massive stars. For proto-clusters deeply embedded within dense molecular clouds, analysis of these space-based data will: 1. Yield a complete census of Young Stellar Objects in each cluster. 2. Allow systematic measurements of embedded cluster properties: spectral energy distributions, luminosity functions, protostellar and disk fractions, and how these vary with cluster mass, age, and density. Combined with other, similarly complete and unbiased infrared and mm data, CHaMP's goals include: 3. A detailed comparison of the embedded stellar populations with their natal dense gas to derive extinction maps, star formation efficiencies and feedback effects, and the kinematics, physics, and chemistry of the gas in and around the clusters. 4. Tying the demographics, age spreads, and timescales of the clusters, based on pre-Main Sequence evolution, to that of the dense gas clumps and Giant Molecular Clouds. 5. A measurement of the local star formation rate per gas mass surface density in the Milky Way, as well as examining arm versus interarm dependencies. Methods and Techniques: We will primarily use archival cryogenic-Spitzer, WISE, and Herschel data, and support this with existing data from ground- and space-based facilities, to conduct a comprehensive assay of critical metrics (as above) and provide observational calibration of theoretical models over the entire massive star formation process. The mm-wave molecular maps of 303 dense gas clumps in multiple species, comprising all the gas above a column density limit of 100 Msun/pc^2, are already inhand. We have also surveyed the embedded stellar content of these clumps, down to subsolar masses, in the near-infrared J, H, and K bands and with deep Warm Spitzer data. Relevance to NASA programs: Analysis to date of the space- and ground-based data has yielded several new insights into evolutionary timescales and the chemical & energy evolution of clumps during the cluster formation process. Investigations as described in this proposal will yield new demographic insights on how the properties and evolution of molecular clouds relate to the properties of massive stars and clusters that form within them, and significantly enhance the science return from these spacecraft missions. The large number of resulting data products are already being made publicly available to the astronomical community, providing crucial information for future NASA science targets. This research will be performed within the framework of a broad international collaboration spanning four continents. This ambitious but practical program will therefore maximise the science payoff from these archival data sets, provide enhanced legacy data for more advanced studies with the next generation of ground- and space-based instruments such as JWST, and open up several new windows into the discovery space of Galactic star formation & interstellar medium studies.

Clustering of gamma-ray burst types in the Fermi GBM catalogue: indications of photosphere and synchrotron emissions during the prompt phase

NASA Astrophysics Data System (ADS)

Acuner, Zeynep; Ryde, Felix

2018-04-01

Many different physical processes have been suggested to explain the prompt gamma-ray emission in gamma-ray bursts (GRBs). Although there are examples of both bursts with photospheric and synchrotron emission origins, these distinct spectral appearances have not been generalized to large samples of GRBs. Here, we search for signatures of the different emission mechanisms in the full Fermi Gamma-ray Space Telescope/GBM (Gamma-ray Burst Monitor) catalogue. We use Gaussian Mixture Models to cluster bursts according to their parameters from the Band function (α, β, and Epk) as well as their fluence and T90. We find five distinct clusters. We further argue that these clusters can be divided into bursts of photospheric origin (2/3 of all bursts, divided into three clusters) and bursts of synchrotron origin (1/3 of all bursts, divided into two clusters). For instance, the cluster that contains predominantly short bursts is consistent of photospheric emission origin. We discuss several reasons that can determine which cluster a burst belongs to: jet dissipation pattern and/or the jet content, or viewing angle.

Reduction of the virtual space for coupled-cluster excitation energies of large molecules and embedded systems

PubMed Central

Send, Robert; Kaila, Ville R. I.; Sundholm, Dage

2011-01-01

We investigate how the reduction of the virtual space affects coupled-cluster excitation energies at the approximate singles and doubles coupled-cluster level (CC2). In this reduced-virtual-space (RVS) approach, all virtual orbitals above a certain energy threshold are omitted in the correlation calculation. The effects of the RVS approach are assessed by calculations on the two lowest excitation energies of 11 biochromophores using different sizes of the virtual space. Our set of biochromophores consists of common model systems for the chromophores of the photoactive yellow protein, the green fluorescent protein, and rhodopsin. The RVS calculations show that most of the high-lying virtual orbitals can be neglected without significantly affecting the accuracy of the obtained excitation energies. Omitting all virtual orbitals above 50 eV in the correlation calculation introduces errors in the excitation energies that are smaller than 0.1 eV . By using a RVS energy threshold of 50 eV , the CC2 calculations using triple-ζ basis sets (TZVP) on protonated Schiff base retinal are accelerated by a factor of 6. We demonstrate the applicability of the RVS approach by performing CC2∕TZVP calculations on the lowest singlet excitation energy of a rhodopsin model consisting of 165 atoms using RVS thresholds between 20 eV and 120 eV. The calculations on the rhodopsin model show that the RVS errors determined in the gas-phase are a very good approximation to the RVS errors in the protein environment. The RVS approach thus renders purely quantum mechanical treatments of chromophores in protein environments feasible and offers an ab initio alternative to quantum mechanics∕molecular mechanics separation schemes. PMID:21663351

Reduction of the virtual space for coupled-cluster excitation energies of large molecules and embedded systems.

PubMed

Send, Robert; Kaila, Ville R I; Sundholm, Dage

2011-06-07

We investigate how the reduction of the virtual space affects coupled-cluster excitation energies at the approximate singles and doubles coupled-cluster level (CC2). In this reduced-virtual-space (RVS) approach, all virtual orbitals above a certain energy threshold are omitted in the correlation calculation. The effects of the RVS approach are assessed by calculations on the two lowest excitation energies of 11 biochromophores using different sizes of the virtual space. Our set of biochromophores consists of common model systems for the chromophores of the photoactive yellow protein, the green fluorescent protein, and rhodopsin. The RVS calculations show that most of the high-lying virtual orbitals can be neglected without significantly affecting the accuracy of the obtained excitation energies. Omitting all virtual orbitals above 50 eV in the correlation calculation introduces errors in the excitation energies that are smaller than 0.1 eV. By using a RVS energy threshold of 50 eV, the CC2 calculations using triple-ζ basis sets (TZVP) on protonated Schiff base retinal are accelerated by a factor of 6. We demonstrate the applicability of the RVS approach by performing CC2/TZVP calculations on the lowest singlet excitation energy of a rhodopsin model consisting of 165 atoms using RVS thresholds between 20 eV and 120 eV. The calculations on the rhodopsin model show that the RVS errors determined in the gas-phase are a very good approximation to the RVS errors in the protein environment. The RVS approach thus renders purely quantum mechanical treatments of chromophores in protein environments feasible and offers an ab initio alternative to quantum mechanics/molecular mechanics separation schemes. © 2011 American Institute of Physics

Large-Scale NASA Science Applications on the Columbia Supercluster

NASA Technical Reports Server (NTRS)

Brooks, Walter

2005-01-01

Columbia, NASA's newest 61 teraflops supercomputer that became operational late last year, is a highly integrated Altix cluster of 10,240 processors, and was named to honor the crew of the Space Shuttle lost in early 2003. Constructed in just four months, Columbia increased NASA's computing capability ten-fold, and revitalized the Agency's high-end computing efforts. Significant cutting-edge science and engineering simulations in the areas of space and Earth sciences, as well as aeronautics and space operations, are already occurring on this largest operational Linux supercomputer, demonstrating its capacity and capability to accelerate NASA's space exploration vision. The presentation will describe how an integrated environment consisting not only of next-generation systems, but also modeling and simulation, high-speed networking, parallel performance optimization, and advanced data analysis and visualization, is being used to reduce design cycle time, accelerate scientific discovery, conduct parametric analysis of multiple scenarios, and enhance safety during the life cycle of NASA missions. The talk will conclude by discussing how NAS partnered with various NASA centers, other government agencies, computer industry, and academia, to create a national resource in large-scale modeling and simulation.

Design of double fuzzy clustering-driven context neural networks.

PubMed

Kim, Eun-Hu; Oh, Sung-Kwun; Pedrycz, Witold

2018-08-01

In this study, we introduce a novel category of double fuzzy clustering-driven context neural networks (DFCCNNs). The study is focused on the development of advanced design methodologies for redesigning the structure of conventional fuzzy clustering-based neural networks. The conventional fuzzy clustering-based neural networks typically focus on dividing the input space into several local spaces (implied by clusters). In contrast, the proposed DFCCNNs take into account two distinct local spaces called context and cluster spaces, respectively. Cluster space refers to the local space positioned in the input space whereas context space concerns a local space formed in the output space. Through partitioning the output space into several local spaces, each context space is used as the desired (target) local output to construct local models. To complete this, the proposed network includes a new context layer for reasoning about context space in the output space. In this sense, Fuzzy C-Means (FCM) clustering is useful to form local spaces in both input and output spaces. The first one is used in order to form clusters and train weights positioned between the input and hidden layer, whereas the other one is applied to the output space to form context spaces. The key features of the proposed DFCCNNs can be enumerated as follows: (i) the parameters between the input layer and hidden layer are built through FCM clustering. The connections (weights) are specified as constant terms being in fact the centers of the clusters. The membership functions (represented through the partition matrix) produced by the FCM are used as activation functions located at the hidden layer of the "conventional" neural networks. (ii) Following the hidden layer, a context layer is formed to approximate the context space of the output variable and each node in context layer means individual local model. The outputs of the context layer are specified as a combination of both weights formed as linear function and the outputs of the hidden layer. The weights are updated using the least square estimation (LSE)-based method. (iii) At the output layer, the outputs of context layer are decoded to produce the corresponding numeric output. At this time, the weighted average is used and the weights are also adjusted with the use of the LSE scheme. From the viewpoint of performance improvement, the proposed design methodologies are discussed and experimented with the aid of benchmark machine learning datasets. Through the experiments, it is shown that the generalization abilities of the proposed DFCCNNs are better than those of the conventional FCNNs reported in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

Exploring the nature and synchronicity of early cluster formation in the Large Magellanic Cloud - III. Horizontal branch morphology

NASA Astrophysics Data System (ADS)

Wagner-Kaiser, R.; Mackey, Dougal; Sarajedini, Ata; Cohen, Roger E.; Geisler, Doug; Yang, Soung-Chul; Grocholski, Aaron J.; Cummings, Jeffrey D.

2018-03-01

We leverage new high-quality data from Hubble Space Telescope program GO-14164 to explore the variation in horizontal branch morphology among globular clusters in the Large Magellanic Cloud (LMC). Our new observations lead to photometry with a precision commensurate with that available for the Galactic globular cluster population. Our analysis indicates that, once metallicity is accounted for, clusters in the LMC largely share similar horizontal branch morphologies regardless of their location within the system. Furthermore, the LMC clusters possess, on average, slightly redder morphologies than most of the inner halo Galactic population; we find, instead, that their characteristics tend to be more similar to those exhibited by clusters in the outer Galactic halo. Our results are consistent with previous studies, showing a correlation between horizontal branch morphology and age.

Parallel Multivariate Spatio-Temporal Clustering of Large Ecological Datasets on Hybrid Supercomputers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sreepathi, Sarat; Kumar, Jitendra; Mills, Richard T.

A proliferation of data from vast networks of remote sensing platforms (satellites, unmanned aircraft systems (UAS), airborne etc.), observational facilities (meteorological, eddy covariance etc.), state-of-the-art sensors, and simulation models offer unprecedented opportunities for scientific discovery. Unsupervised classification is a widely applied data mining approach to derive insights from such data. However, classification of very large data sets is a complex computational problem that requires efficient numerical algorithms and implementations on high performance computing (HPC) platforms. Additionally, increasing power, space, cooling and efficiency requirements has led to the deployment of hybrid supercomputing platforms with complex architectures and memory hierarchies like themore » Titan system at Oak Ridge National Laboratory. The advent of such accelerated computing architectures offers new challenges and opportunities for big data analytics in general and specifically, large scale cluster analysis in our case. Although there is an existing body of work on parallel cluster analysis, those approaches do not fully meet the needs imposed by the nature and size of our large data sets. Moreover, they had scaling limitations and were mostly limited to traditional distributed memory computing platforms. We present a parallel Multivariate Spatio-Temporal Clustering (MSTC) technique based on k-means cluster analysis that can target hybrid supercomputers like Titan. We developed a hybrid MPI, CUDA and OpenACC implementation that can utilize both CPU and GPU resources on computational nodes. We describe performance results on Titan that demonstrate the scalability and efficacy of our approach in processing large ecological data sets.« less

Search For Cosmic-Ray-Induced Gamma-Ray Emission In Galaxy Clusters

DOE PAGES

Ackermann, M.

2014-04-30

Current theories predict relativistic hadronic particle populations in clusters of galaxies in addition to the already observed relativistic leptons. In these scenarios hadronic interactions give rise to neutral pions which decay into rays that are potentially observable with the Large Area Telescope (LAT) on board the Fermi space telescope. We present a joint likelihood analysis searching for spatially extended γ-ray emission at the locations of 50 galaxy clusters in 4 years of Fermi-LAT data under the assumption of the universal cosmic-ray model proposed by Pinzke & Pfrommer (2010). We find an excess at a significance of 2.7 σ which uponmore » closer inspection is however correlated to individual excess emission towards three galaxy clusters: Abell 400, Abell 1367 and Abell 3112. We discuss these cases in detail and conservatively attribute the emission to unmodeled background (for example, radio galaxies within the clusters). Through the combined analysis of 50 clusters we exclude hadronic injection efficiencies in simple hadronic models above 21% and establish limits on the cosmic-ray to thermal pressure ratio within the virial radius, R200, to be below 1.2-1.4% depending on the morphological classification. In addition we derive new limits on the γ-ray flux from individual clusters in our sample.« less

Search for Cosmic-Ray-Induced Gamma-Ray Emission in Galaxy Clusters

NASA Technical Reports Server (NTRS)

Ackermann, M.; Ajello, M.; Albert, A.; Allafort, A.; Atwood, W. B.; Baldini, L.; Ballet, J.; Barbiellini, G.; Bastieri, D.; Bechtol, K.;

Inherent structure versus geometric metric for state space discretization.

PubMed

Liu, Hanzhong; Li, Minghai; Fan, Jue; Huo, Shuanghong

2016-05-30

Inherent structure (IS) and geometry-based clustering methods are commonly used for analyzing molecular dynamics trajectories. ISs are obtained by minimizing the sampled conformations into local minima on potential/effective energy surface. The conformations that are minimized into the same energy basin belong to one cluster. We investigate the influence of the applications of these two methods of trajectory decomposition on our understanding of the thermodynamics and kinetics of alanine tetrapeptide. We find that at the microcluster level, the IS approach and root-mean-square deviation (RMSD)-based clustering method give totally different results. Depending on the local features of energy landscape, the conformations with close RMSDs can be minimized into different minima, while the conformations with large RMSDs could be minimized into the same basin. However, the relaxation timescales calculated based on the transition matrices built from the microclusters are similar. The discrepancy at the microcluster level leads to different macroclusters. Although the dynamic models established through both clustering methods are validated approximately Markovian, the IS approach seems to give a meaningful state space discretization at the macrocluster level in terms of conformational features and kinetics. © 2016 Wiley Periodicals, Inc.

Distributions of Gas and Galaxies from Galaxy Clusters to Larger Scales

NASA Astrophysics Data System (ADS)

Patej, Anna

2017-01-01

We address the distributions of gas and galaxies on three scales: the outskirts of galaxy clusters, the clustering of galaxies on large scales, and the extremes of the galaxy distribution. In the outskirts of galaxy clusters, long-standing analytical models of structure formation and recent simulations predict the existence of density jumps in the gas and dark matter profiles. We use these features to derive models for the gas density profile, obtaining a simple fiducial model that is in agreement with both observations of cluster interiors and simulations of the outskirts. We next consider the galaxy density profiles of clusters; under the assumption that the galaxies in cluster outskirts follow similar collisionless dynamics as the dark matter, their distribution should show a steep jump as well. We examine the profiles of a low-redshift sample of clusters and groups, finding evidence for the jump in some of these clusters. Moving to larger scales where massive galaxies of different types are expected to trace the same large-scale structure, we present a test of this prediction by measuring the clustering of red and blue galaxies at z 0.6, finding low stochasticity between the two populations. These results address a key source of systematic uncertainty - understanding how target populations of galaxies trace large-scale structure - in galaxy redshift surveys. Such surveys use baryon acoustic oscillations (BAO) as a cosmological probe, but are limited by the expense of obtaining sufficiently dense spectroscopy. With the intention of leveraging upcoming deep imaging data, we develop a new method of detecting the BAO in sparse spectroscopic samples via cross-correlation with a dense photometric catalog. This method will permit the extension of BAO measurements to higher redshifts than possible with the existing spectroscopy alone. Lastly, we connect galaxies near and far: the Local Group dwarfs and the high redshift galaxies observed by Hubble and Spitzer. We examine how the local dwarfs may have appeared in the past and compare their properties to the detection limits of the upcoming James Webb Space Telescope (JWST), finding that JWST should be able to detect galaxies similar to the progenitors of a few of the brightest of the local galaxies, revealing a hitherto unobserved population of galaxies at high redshifts.

Utilizing the Structure and Content Information for XML Document Clustering

NASA Astrophysics Data System (ADS)

Tran, Tien; Kutty, Sangeetha; Nayak, Richi

This paper reports on the experiments and results of a clustering approach used in the INEX 2008 document mining challenge. The clustering approach utilizes both the structure and content information of the Wikipedia XML document collection. A latent semantic kernel (LSK) is used to measure the semantic similarity between XML documents based on their content features. The construction of a latent semantic kernel involves the computing of singular vector decomposition (SVD). On a large feature space matrix, the computation of SVD is very expensive in terms of time and memory requirements. Thus in this clustering approach, the dimension of the document space of a term-document matrix is reduced before performing SVD. The document space reduction is based on the common structural information of the Wikipedia XML document collection. The proposed clustering approach has shown to be effective on the Wikipedia collection in the INEX 2008 document mining challenge.

Large-scale motions in the universe: Using clusters of galaxies as tracers

NASA Technical Reports Server (NTRS)

Gramann, Mirt; Bahcall, Neta A.; Cen, Renyue; Gott, J. Richard

1995-01-01

Can clusters of galaxies be used to trace the large-scale peculiar velocity field of the universe? We answer this question by using large-scale cosmological simulations to compare the motions of rich clusters of galaxies with the motion of the underlying matter distribution. Three models are investigated: Omega = 1 and Omega = 0.3 cold dark matter (CDM), and Omega = 0.3 primeval baryonic isocurvature (PBI) models, all normalized to the Cosmic Background Explorer (COBE) background fluctuations. We compare the cluster and mass distribution of peculiar velocities, bulk motions, velocity dispersions, and Mach numbers as a function of scale for R greater than or = 50/h Mpc. We also present the large-scale velocity and potential maps of clusters and of the matter. We find that clusters of galaxies trace well the large-scale velocity field and can serve as an efficient tool to constrain cosmological models. The recently reported bulk motion of clusters 689 +/- 178 km/s on approximately 150/h Mpc scale (Lauer & Postman 1994) is larger than expected in any of the models studied (less than or = 190 +/- 78 km/s).

Multipole analysis of redshift-space distortions around cosmic voids

NASA Astrophysics Data System (ADS)

Hamaus, Nico; Cousinou, Marie-Claude; Pisani, Alice; Aubert, Marie; Escoffier, Stéphanie; Weller, Jochen

2017-07-01

We perform a comprehensive redshift-space distortion analysis based on cosmic voids in the large-scale distribution of galaxies observed with the Sloan Digital Sky Survey. To this end, we measure multipoles of the void-galaxy cross-correlation function and compare them with standard model predictions in cosmology. Merely considering linear-order theory allows us to accurately describe the data on the entire available range of scales and to probe void-centric distances down to about 2 h-1Mpc. Common systematics, such as the Fingers-of-God effect, scale-dependent galaxy bias, and nonlinear clustering do not seem to play a significant role in our analysis. We constrain the growth rate of structure via the redshift-space distortion parameter β at two median redshifts, β(bar z=0.32)=0.599+0.134-0.124 and β(bar z=0.54)=0.457+0.056-0.054, with a precision that is competitive with state-of-the-art galaxy-clustering results. While the high-redshift constraint perfectly agrees with model expectations, we observe a mild 2σ deviation at bar z=0.32, which increases to 3σ when the data is restricted to the lowest available redshift range of 0.15

How Many-Body Correlations and α Clustering Shape He 6

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romero-Redondo, Carolina; Quaglioni, Sofia; Navrátil, Petr

The Borromean 6He nucleus is an exotic system characterized by two halo neutrons orbiting around a compact 4He (or α) core, in which the binary subsystems are unbound. The simultaneous reproduction of its small binding energy and extended matter and point-proton radii has been a challenge for ab initio theoretical calculations based on traditional bound-state methods. Using soft nucleon-nucleon interactions based on chiral effective field theory potentials, we show that supplementing the model space with 4He + n + n cluster degrees of freedom largely solves this issue. Lastly, we analyze the role played by α clustering and many-body correlations,more » and study the dependence of the energy spectrum on the resolution scale of the interaction.« less

LISA Sources in Milky Way Globular Clusters

NASA Astrophysics Data System (ADS)

Kremer, Kyle; Chatterjee, Sourav; Breivik, Katelyn; Rodriguez, Carl L.; Larson, Shane L.; Rasio, Frederic A.

2018-05-01

We explore the formation of double-compact-object binaries in Milky Way (MW) globular clusters (GCs) that may be detectable by the Laser Interferometer Space Antenna (LISA). We use a set of 137 fully evolved GC models that, overall, effectively match the properties of the observed GCs in the MW. We estimate that, in total, the MW GCs contain ˜21 sources that will be detectable by LISA. These detectable sources contain all combinations of black hole (BH), neutron star, and white dwarf components. We predict ˜7 of these sources will be BH-BH binaries. Furthermore, we show that some of these BH-BH binaries can have signal-to-noise ratios large enough to be detectable at the distance of the Andromeda galaxy or even the Virgo cluster.

LISA Sources in Milky Way Globular Clusters.

PubMed

Kremer, Kyle; Chatterjee, Sourav; Breivik, Katelyn; Rodriguez, Carl L; Larson, Shane L; Rasio, Frederic A

2018-05-11

We explore the formation of double-compact-object binaries in Milky Way (MW) globular clusters (GCs) that may be detectable by the Laser Interferometer Space Antenna (LISA). We use a set of 137 fully evolved GC models that, overall, effectively match the properties of the observed GCs in the MW. We estimate that, in total, the MW GCs contain ∼21 sources that will be detectable by LISA. These detectable sources contain all combinations of black hole (BH), neutron star, and white dwarf components. We predict ∼7 of these sources will be BH-BH binaries. Furthermore, we show that some of these BH-BH binaries can have signal-to-noise ratios large enough to be detectable at the distance of the Andromeda galaxy or even the Virgo cluster.

How Many-Body Correlations and α Clustering Shape He 6

DOE PAGES

Romero-Redondo, Carolina; Quaglioni, Sofia; Navrátil, Petr; ...

2016-11-23

The Borromean 6He nucleus is an exotic system characterized by two halo neutrons orbiting around a compact 4He (or α) core, in which the binary subsystems are unbound. The simultaneous reproduction of its small binding energy and extended matter and point-proton radii has been a challenge for ab initio theoretical calculations based on traditional bound-state methods. Using soft nucleon-nucleon interactions based on chiral effective field theory potentials, we show that supplementing the model space with 4He + n + n cluster degrees of freedom largely solves this issue. Lastly, we analyze the role played by α clustering and many-body correlations,more » and study the dependence of the energy spectrum on the resolution scale of the interaction.« less

A clustering-based graph Laplacian framework for value function approximation in reinforcement learning.

PubMed

Xu, Xin; Huang, Zhenhua; Graves, Daniel; Pedrycz, Witold

2014-12-01

In order to deal with the sequential decision problems with large or continuous state spaces, feature representation and function approximation have been a major research topic in reinforcement learning (RL). In this paper, a clustering-based graph Laplacian framework is presented for feature representation and value function approximation (VFA) in RL. By making use of clustering-based techniques, that is, K-means clustering or fuzzy C-means clustering, a graph Laplacian is constructed by subsampling in Markov decision processes (MDPs) with continuous state spaces. The basis functions for VFA can be automatically generated from spectral analysis of the graph Laplacian. The clustering-based graph Laplacian is integrated with a class of approximation policy iteration algorithms called representation policy iteration (RPI) for RL in MDPs with continuous state spaces. Simulation and experimental results show that, compared with previous RPI methods, the proposed approach needs fewer sample points to compute an efficient set of basis functions and the learning control performance can be improved for a variety of parameter settings.

Methods in Computational Cosmology

NASA Astrophysics Data System (ADS)

Vakili, Mohammadjavad

State of the inhomogeneous universe and its geometry throughout cosmic history can be studied by measuring the clustering of galaxies and the gravitational lensing of distant faint galaxies. Lensing and clustering measurements from large datasets provided by modern galaxy surveys will forever shape our understanding of the how the universe expands and how the structures grow. Interpretation of these rich datasets requires careful characterization of uncertainties at different stages of data analysis: estimation of the signal, estimation of the signal uncertainties, model predictions, and connecting the model to the signal through probabilistic means. In this thesis, we attempt to address some aspects of these challenges. The first step in cosmological weak lensing analyses is accurate estimation of the distortion of the light profiles of galaxies by large scale structure. These small distortions, known as the cosmic shear signal, are dominated by extra distortions due to telescope optics and atmosphere (in the case of ground-based imaging). This effect is captured by a kernel known as the Point Spread Function (PSF) that needs to be fully estimated and corrected for. We address two challenges a head of accurate PSF modeling for weak lensing studies. The first challenge is finding the centers of point sources that are used for empirical estimation of the PSF. We show that the approximate methods for centroiding stars in wide surveys are able to optimally saturate the information content that is retrievable from astronomical images in the presence of noise. The fist step in weak lensing studies is estimating the shear signal by accurately measuring the shapes of galaxies. Galaxy shape measurement involves modeling the light profile of galaxies convolved with the light profile of the PSF. Detectors of many space-based telescopes such as the Hubble Space Telescope (HST) sample the PSF with low resolution. Reliable weak lensing analysis of galaxies observed by the HST camera requires knowledge of the PSF at a resolution higher than the pixel resolution of HST. This PSF is called the super-resolution PSF. In particular, we present a forward model of the point sources imaged through filters of the HST WFC3 IR channel. We show that this forward model can accurately estimate the super-resolution PSF. We also introduce a noise model that permits us to robustly analyze the HST WFC3 IR observations of the crowded fields. Then we try to address one of the theoretical uncertainties in modeling of galaxy clustering on small scales. Study of small scale clustering requires assuming a halo model. Clustering of halos has been shown to depend on halo properties beyond mass such as halo concentration, a phenomenon referred to as assembly bias. Standard large-scale structure studies with halo occupation distribution (HOD) assume that halo mass alone is sufficient to characterize the connection between galaxies and halos. However, assembly bias could cause the modeling of galaxy clustering to face systematic effects if the expected number of galaxies in halos is correlated with other halo properties. Using high resolution N-body simulations and the clustering measurements of Sloan Digital Sky Survey (SDSS) DR7 main galaxy sample, we show that modeling of galaxy clustering can slightly improve if we allow the HOD model to depend on halo properties beyond mass. One of the key ingredients in precise parameter inference using galaxy clustering is accurate estimation of the error covariance matrix of clustering measurements. This requires generation of many independent galaxy mock catalogs that accurately describe the statistical distribution of galaxies in a wide range of physical scales. We present a fast and accurate method based on low-resolution N-body simulations and an empirical bias model for generating mock catalogs. We use fast particle mesh gravity solvers for generation of dark matter density field and we use Markov Chain Monti Carlo (MCMC) to estimate the bias model that connects dark matter to galaxies. We show that this approach enables the fast generation of mock catalogs that recover clustering at a percent-level accuracy down to quasi-nonlinear scales. Cosmological datasets are interpreted by specifying likelihood functions that are often assumed to be multivariate Gaussian. Likelihood free approaches such as Approximate Bayesian Computation (ABC) can bypass this assumption by introducing a generative forward model of the data and a distance metric for quantifying the closeness of the data and the model. We present the first application of ABC in large scale structure for constraining the connections between galaxies and dark matter halos. We present an implementation of ABC equipped with Population Monte Carlo and a generative forward model of the data that incorporates sample variance and systematic uncertainties. (Abstract shortened by ProQuest.).

Evaluating Mixture Modeling for Clustering: Recommendations and Cautions

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2011-01-01

This article provides a large-scale investigation into several of the properties of mixture-model clustering techniques (also referred to as latent class cluster analysis, latent profile analysis, model-based clustering, probabilistic clustering, Bayesian classification, unsupervised learning, and finite mixture models; see Vermunt & Magdison,…

Membership determination of open clusters based on a spectral clustering method

NASA Astrophysics Data System (ADS)

Gao, Xin-Hua

2018-06-01

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

Using Unsupervised Learning to Unlock the Potential of Hydrologic Similarity

NASA Astrophysics Data System (ADS)

Chaney, N.; Newman, A. J.

2017-12-01

By clustering environmental data into representative hydrologic response units (HRUs), hydrologic similarity aims to harness the covariance between a system's physical environment and its hydrologic response to create reduced-order models. This is the primary approach through which sub-grid hydrologic processes are represented in large-scale models (e.g., Earth System Models). Although the possibilities of hydrologic similarity are extensive, its practical implementations have been limited to 1-d bins of oversimplistic metrics of hydrologic response (e.g., topographic index)—this is a missed opportunity. In this presentation we will show how unsupervised learning is unlocking the potential of hydrologic similarity; clustering methods enable generalized frameworks to effectively and efficiently harness the petabytes of global environmental data to robustly characterize sub-grid heterogeneity in large-scale models. To illustrate the potential that unsupervised learning has towards advancing hydrologic similarity, we introduce a hierarchical clustering algorithm (HCA) that clusters very high resolution (30-100 meters) elevation, soil, climate, and land cover data to assemble a domain's representative HRUs. These HRUs are then used to parameterize the sub-grid heterogeneity in land surface models; for this study we use the GFDL LM4 model—the land component of the GFDL Earth System Model. To explore HCA and its impacts on the hydrologic system we use a ¼ grid cell in southeastern California as a test site. HCA is used to construct an ensemble of 9 different HRU configurations—each configuration has a different number of HRUs; for each ensemble member LM4 is run between 2002 and 2014 with a 26 year spinup. The analysis of the ensemble of model simulations show that: 1) clustering the high-dimensional environmental data space leads to a robust representation of the role of the physical environment in the coupled water, energy, and carbon cycles at a relatively low number of HRUs; 2) the reduced-order model with around 300 HRUs effectively reproduces the fully distributed model simulation (30 meters) with less than 1/1000 of computational expense; 3) assigning each grid cell of the fully distributed grid to an HRU via HCA enables novel visualization methods for large-scale models—this has significant implications for how these models are applied and evaluated. We will conclude by outlining the potential that this work has within operational prediction systems including numerical weather prediction, Earth System models, and Early Warning systems.

A Bimodal Hybrid Model for Time-Dependent Probabilistic Seismic Hazard Analysis

NASA Astrophysics Data System (ADS)

Yaghmaei-Sabegh, Saman; Shoaeifar, Nasser; Shoaeifar, Parva

2018-03-01

The evaluation of evidence provided by geological studies and historical catalogs indicates that in some seismic regions and faults, multiple large earthquakes occur in cluster. Then, the occurrences of large earthquakes confront with quiescence and only the small-to-moderate earthquakes take place. Clustering of large earthquakes is the most distinguishable departure from the assumption of constant hazard of random occurrence of earthquakes in conventional seismic hazard analysis. In the present study, a time-dependent recurrence model is proposed to consider a series of large earthquakes that occurs in clusters. The model is flexible enough to better reflect the quasi-periodic behavior of large earthquakes with long-term clustering, which can be used in time-dependent probabilistic seismic hazard analysis with engineering purposes. In this model, the time-dependent hazard results are estimated by a hazard function which comprises three parts. A decreasing hazard of last large earthquake cluster and an increasing hazard of the next large earthquake cluster, along with a constant hazard of random occurrence of small-to-moderate earthquakes. In the final part of the paper, the time-dependent seismic hazard of the New Madrid Seismic Zone at different time intervals has been calculated for illustrative purpose.

Prospects for Chemically Tagging Stars in the Galaxy

NASA Astrophysics Data System (ADS)

Ting, Yuan-Sen; Conroy, Charlie; Goodman, Alyssa

2015-07-01

It is now well-established that the elemental abundance patterns of stars hold key clues not only to their formation, but also to the assembly histories of galaxies. One of the most exciting possibilities is the use of stellar abundance patterns as “chemical tags” to identify stars that were born in the same molecular cloud. In this paper, we assess the prospects of chemical tagging as a function of several key underlying parameters. We show that in the fiducial case of 104 distinct cells in chemical space and {10}5-{10}6 stars in the survey, one can expect to detect ∼ {10}2-{10}3 groups that are ≥slant 5σ overdensities in the chemical space. However, we find that even very large overdensities in chemical space do not guarantee that the overdensity is due to a single set of stars from a common birth cloud. In fact, for our fiducial model parameters, the typical 5σ overdensity is comprised of stars from a wide range of clusters with the most dominant cluster contributing only 25% of the stars. The most important factors limiting the identification of disrupted clusters via chemical tagging are the number of chemical cells in the chemical space and the survey sampling rate of the underlying stellar population. Both of these factors can be improved through strategic observational plans. While recovering individual clusters through chemical tagging may prove challenging, we show, in agreement with previous work, that different CMFs imprint different degrees of clumpiness in chemical space. These differences provide the opportunity to statistically reconstruct the slope and high-mass cutoff of CMF and its evolution through cosmic time.

New Target for an Old Method: Hubble Measures Globular Cluster Parallax

NASA Astrophysics Data System (ADS)

Hensley, Kerry

2018-05-01

Measuring precise distances to faraway objects has long been a challenge in astrophysics. Now, one of the earliest techniques used to measure the distance to astrophysical objects has been applied to a metal-poor globular cluster for the first time.A Classic TechniqueAn artists impression of the European Space Agencys Gaia spacecraft. Gaia is on track to map the positions and motions of a billion stars. [ESA]Distances to nearby stars are often measured using the parallax technique tracing the tiny apparent motion of a target star against the background of more distant stars as Earth orbits the Sun. This technique has come a long way since it was first used in the 1800s to measure the distance to stars a few tens of light-years away; with the advent of space observatories like Hipparcos and Gaia, parallax can now be used to map the positions of stars out to thousands of light-years.Precise distance measurements arent only important for setting the scale of the universe, however; they can also help us better understand stellar evolution over the course of cosmic history. Stellar evolution models are often anchored to a reference star cluster, the properties of which must be known precisely. These precise properties can be readily determined for young, nearby open clusters using parallax measurements. But stellar evolution models that anchor on themore-distant, ancient, metal-poor globular clusters have been hampered by theless-precise indirect methods used tomeasure distance to these faraway clusters until now.Top: An image of NGC 6397 overlaid with the area scanned by Hubble (dashed green) and the footprint of the camera (solid green). The blue ellipse represents the parallax motion of a star in the cluster, exaggerated by a factor of ten thousand. Bottom: An example scan from this field. [Adapted from Brown et al. 2018]New Measurement to an Old ClusterThomas Brown (Space Telescope Science Institute) and collaborators used the Hubble Space Telescope todetermine the distance to NGC 6397, one of the nearest metal-poor globular clusters and anchor for one stellar population model. Brown and coauthors used a technique called spatial scanning to greatly broaden the reach of the parallax method.Spatial scanning was initially developed as a way to increase the signal-to-noise of exoplanet transit observations, but it has also greatly improved the prospects of astrometry precisely determining the separations between astronomical objects. In spatial scanning, the telescope moves while the exposure is being taken, spreading the light out across many pixels.Unprecedented PrecisionThis technique allowed the authors to achieve a precision of 20100microarcseconds. From the observed parallax angle of just 0.418 milliarcseconds (for reference, the moons angular size is about 5 million times larger on the sky!), Brown and collaborators refined the distance to NGC 6397 to 7,795 light-years, with a measurement error of only a few percent.Using spatial scanning, Hubble can make parallax measurements of nearby globular clusters, while Gaia has the potential to reach even farther. Looking ahead, the measurement made by Brown and collaborators can be combined with the recently released Gaia data to trim the uncertainty down to just 1%. This highlights the power of space telescopes to make extremely precise measurements of astoundingly large distances informing our models and helping us measure the universe.CitationThomas Brown et al 2018ApJL856 L6. doi:10.3847/2041-8213/aab55a

Line-of-sight structure toward strong lensing galaxy clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bayliss, Matthew B.; Johnson, Traci; Sharon, Keren

2014-03-01

We present an analysis of the line-of-sight structure toward a sample of 10 strong lensing cluster cores. Structure is traced by groups that are identified spectroscopically in the redshift range, 0.1 ≤ z ≤ 0.9, and we measure the projected angular and comoving separations between each group and the primary strong lensing clusters in each corresponding line of sight. From these data we measure the distribution of projected angular separations between the primary strong lensing clusters and uncorrelated large-scale structure as traced by groups. We then compare the observed distribution of angular separations for our strong lensing selected lines ofmore » sight against the distribution of groups that is predicted for clusters lying along random lines of sight. There is clear evidence for an excess of structure along the line of sight at small angular separations (θ ≤ 6') along the strong lensing selected lines of sight, indicating that uncorrelated structure is a significant systematic that contributes to producing galaxy clusters with large cross sections for strong lensing. The prevalence of line-of-sight structure is one of several biases in strong lensing clusters that can potentially be folded into cosmological measurements using galaxy cluster samples. These results also have implications for current and future studies—such as the Hubble Space Telescope Frontier Fields—that make use of massive galaxy cluster lenses as precision cosmological telescopes; it is essential that the contribution of line-of-sight structure be carefully accounted for in the strong lens modeling of the cluster lenses.« less

THE HUBBLE SPACE TELESCOPE UV LEGACY SURVEY OF GALACTIC GLOBULAR CLUSTERS. VII. IMPLICATIONS FROM THE NEARLY UNIVERSAL NATURE OF HORIZONTAL BRANCH DISCONTINUITIES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, T. M.; Bellini, A.; Anderson, J.

2016-05-01

The UV-initiative Hubble Space Telescope Treasury survey of Galactic globular clusters provides a new window into the phenomena that shape the morphological features of the horizontal branch (HB). Using this large and homogeneous catalog of UV and blue photometry, we demonstrate that the HB exhibits discontinuities that are remarkably consistent in color (effective temperature). This consistency is apparent even among some of the most massive clusters hosting multiple distinct sub-populations (such as NGC 2808, ω Cen, and NGC 6715), demonstrating that these phenomena are primarily driven by atmospheric physics that is independent of the underlying population properties. However, inconsistencies arisemore » in the metal-rich clusters NGC 6388 and NGC 6441, where the discontinuity within the blue HB (BHB) distribution shifts ∼1000–2000 K hotter. We demonstrate that this shift is likely due to a large helium enhancement in the BHB stars of these clusters, which in turn affects the surface convection and evolution of such stars. Our survey also increases the number of Galactic globular clusters known to host blue-hook stars (also known as late hot flashers) from 6 to 23 clusters. These clusters are biased toward the bright end of the globular cluster luminosity function, confirming that blue-hook stars tend to form in the most massive clusters with significant self-enrichment.« less

Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

NASA Astrophysics Data System (ADS)

Swinburne, Thomas D.; Perez, Danny

2018-05-01

A massively parallel method to build large transition rate matrices from temperature-accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher-scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature acceleration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15 interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.

Jellyfish: Evidence of Extreme Ram-pressure Stripping in Massive Galaxy Clusters

NASA Astrophysics Data System (ADS)

Ebeling, H.; Stephenson, L. N.; Edge, A. C.

2014-02-01

Ram-pressure stripping by the gaseous intracluster medium has been proposed as the dominant physical mechanism driving the rapid evolution of galaxies in dense environments. Detailed studies of this process have, however, largely been limited to relatively modest examples affecting only the outermost gas layers of galaxies in nearby and/or low-mass galaxy clusters. We here present results from our search for extreme cases of gas-galaxy interactions in much more massive, X-ray selected clusters at z > 0.3. Using Hubble Space Telescope snapshots in the F606W and F814W passbands, we have discovered dramatic evidence of ram-pressure stripping in which copious amounts of gas are first shock compressed and then removed from galaxies falling into the cluster. Vigorous starbursts triggered by this process across the galaxy-gas interface and in the debris trail cause these galaxies to temporarily become some of the brightest cluster members in the F606W passband, capable of outshining even the Brightest Cluster Galaxy. Based on the spatial distribution and orientation of systems viewed nearly edge-on in our survey, we speculate that infall at large impact parameter gives rise to particularly long-lasting stripping events. Our sample of six spectacular examples identified in clusters from the Massive Cluster Survey, all featuring M F606W < -21 mag, doubles the number of such systems presently known at z > 0.2 and facilitates detailed quantitative studies of the most violent galaxy evolution in clusters. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with programs GO-10491, -10875, -12166, and -12884.

Individualization as Driving Force of Clustering Phenomena in Humans

PubMed Central

Mäs, Michael; Flache, Andreas; Helbing, Dirk

2010-01-01

One of the most intriguing dynamics in biological systems is the emergence of clustering, in the sense that individuals self-organize into separate agglomerations in physical or behavioral space. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is the clustering of opinions in human populations, particularly when opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing continuous opinion formation models predict “monoculture” in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness has not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution to the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting. In summary, the new model can explain cultural clustering in human societies. Strikingly, model predictions are not only robust to “noise”—randomness is actually the central mechanism that sustains pluralism and clustering. PMID:20975937

A high-significance measurement of correlation between unresolved IRAS sources and optically-selected galaxy clusters

NASA Astrophysics Data System (ADS)

Hincks, Adam D.; Hajian, Amir; Addison, Graeme E.

2013-05-01

We cross-correlate the 100 μm Improved Reprocessing of the IRAS Survey (IRIS) map and galaxy clusters at 0.1 < z < 0.3 in the maxBCG catalogue taken from the Sloan Digital Sky Survey, measuring an angular cross-power spectrum over multipole moments 150 < l < 3000 at a total significance of over 40σ. The cross-spectrum, which arises from the spatial correlation between unresolved dusty galaxies that make up the cosmic infrared background (CIB) in the IRIS map and the galaxy clusters, is well-fit by a single power law with an index of -1.28±0.12, similar to the clustering of unresolved galaxies from cross-correlating far-infrared and submillimetre maps at longer wavelengths. Using a recent, phenomenological model for the spectral and clustering properties of the IRIS galaxies, we constrain the large-scale bias of the maxBCG clusters to be 2.6±1.4, consistent with existing analyses of the real-space cluster correlation function. The success of our method suggests that future CIB-optical cross-correlations using Planck and Herschel data will significantly improve our understanding of the clustering and redshift distribution of the faint CIB sources.

Coherent Image Layout using an Adaptive Visual Vocabulary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dillard, Scott E.; Henry, Michael J.; Bohn, Shawn J.

When querying a huge image database containing millions of images, the result of the query may still contain many thousands of images that need to be presented to the user. We consider the problem of arranging such a large set of images into a visually coherent layout, one that places similar images next to each other. Image similarity is determined using a bag-of-features model, and the layout is constructed from a hierarchical clustering of the image set by mapping an in-order traversal of the hierarchy tree into a space-filling curve. This layout method provides strong locality guarantees so we aremore » able to quantitatively evaluate performance using standard image retrieval benchmarks. Performance of the bag-of-features method is best when the vocabulary is learned on the image set being clustered. Because learning a large, discriminative vocabulary is a computationally demanding task, we present a novel method for efficiently adapting a generic visual vocabulary to a particular dataset. We evaluate our clustering and vocabulary adaptation methods on a variety of image datasets and show that adapting a generic vocabulary to a particular set of images improves performance on both hierarchical clustering and image retrieval tasks.« less

Robust root clustering for linear uncertain systems using generalized Lyapunov theory

NASA Technical Reports Server (NTRS)

Yedavalli, R. K.

1993-01-01

Consideration is given to the problem of matrix root clustering in subregions of a complex plane for linear state space models with real parameter uncertainty. The nominal matrix root clustering theory of Gutman & Jury (1981) using the generalized Liapunov equation is extended to the perturbed matrix case, and bounds are derived on the perturbation to maintain root clustering inside a given region. The theory makes it possible to obtain an explicit relationship between the parameters of the root clustering region and the uncertainty range of the parameter space.

Grid-Enabled High Energy Physics Research using a Beowulf Cluster

NASA Astrophysics Data System (ADS)

Mahmood, Akhtar

2005-04-01

At Edinboro University of Pennsylvania, we have built a 8-node 25 Gflops Beowulf Cluster with 2.5 TB of disk storage space to carry out grid-enabled, data-intensive high energy physics research for the ATLAS experiment via Grid3. We will describe how we built and configured our Cluster, which we have named the Sphinx Beowulf Cluster. We will describe the results of our cluster benchmark studies and the run-time plots of several parallel application codes. Once fully functional, the Cluster will be part of Grid3[www.ivdgl.org/grid3]. The current ATLAS simulation grid application, models the entire physical processes from the proton anti-proton collisions and detector's response to the collision debri through the complete reconstruction of the event from analyses of these responses. The end result is a detailed set of data that simulates the real physical collision event inside a particle detector. Grid is the new IT infrastructure for the 21^st century science -- a new computing paradigm that is poised to transform the practice of large-scale data-intensive research in science and engineering. The Grid will allow scientist worldwide to view and analyze huge amounts of data flowing from the large-scale experiments in High Energy Physics. The Grid is expected to bring together geographically and organizationally dispersed computational resources, such as CPUs, storage systems, communication systems, and data sources.

Near real-time space-time cluster analysis for detection of enteric disease outbreaks in a community setting.

PubMed

Glatman-Freedman, Aharona; Kaufman, Zalman; Kopel, Eran; Bassal, Ravit; Taran, Diana; Valinsky, Lea; Agmon, Vered; Shpriz, Manor; Cohen, Daniel; Anis, Emilia; Shohat, Tamy

2016-08-01

To enhance timely surveillance of bacterial enteric pathogens, space-time cluster analysis was introduced in Israel in May 2013. Stool isolation data of Salmonella, Shigella, and Campylobacter from patients of a large Health Maintenance Organization were analyzed weekly by ArcGIS and SaTScan, and cluster results were sent promptly to local departments of health (LDOHs). During eighteen months, we identified 52 Shigella sonnei clusters, two Salmonella clusters, and no Campylobacter clusters. S. sonnei clusters lasted from one to 33 days and included three to 30 individuals. Thirty-one (60%) of the S. sonnei clusters were known to LDOHs prior to cluster analysis. Clusters not previously known by the LDOHs prompted epidemiologic investigations. In 31 of the 37 (84%) confirmed clusters, educational institutes (nursery schools, kindergartens, and a primary school) were involved. Cluster analysis demonstrated capability to complement enteric disease surveillance. Scaling up the system can further enhance timely detection and control of outbreaks. Copyright © 2016 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

A pair natural orbital implementation of the coupled cluster model CC2 for excitation energies.

PubMed

Helmich, Benjamin; Hättig, Christof

2013-08-28

We demonstrate how to extend the pair natural orbital (PNO) methodology for excited states, presented in a previous work for the perturbative doubles correction to configuration interaction singles (CIS(D)), to iterative coupled cluster methods such as the approximate singles and doubles model CC2. The original O(N(5)) scaling of the PNO construction is reduced by using orbital-specific virtuals (OSVs) as an intermediate step without spoiling the initial accuracy of the PNO method. Furthermore, a slower error convergence for charge-transfer states is analyzed and resolved by a numerical Laplace transformation during the PNO construction, so that an equally accurate treatment of local and charge-transfer excitations is achieved. With state-specific truncated PNO expansions, the eigenvalue problem is solved by combining the Davidson algorithm with deflation to project out roots that have already been determined and an automated refresh with a generation of new PNOs to achieve self-consistency of the PNO space. For a large test set, we found that truncation errors for PNO-CC2 excitation energies are only slightly larger than for PNO-CIS(D). The computational efficiency of PNO-CC2 is demonstrated for a large organic dye, where a reduction of the doubles space by a factor of more than 1000 is obtained compared to the canonical calculation. A compression of the doubles space by a factor 30 is achieved by a unified OSV space only. Moreover, calculations with the still preliminary PNO-CC2 implementation on a series of glycine oligomers revealed an early break even point with a canonical RI-CC2 implementation between 100 and 300 basis functions.

Convergent chaos

NASA Astrophysics Data System (ADS)

Pradas, Marc; Pumir, Alain; Huber, Greg; Wilkinson, Michael

2017-07-01

Chaos is widely understood as being a consequence of sensitive dependence upon initial conditions. This is the result of an instability in phase space, which separates trajectories exponentially. Here, we demonstrate that this criterion should be refined. Despite their overall intrinsic instability, trajectories may be very strongly convergent in phase space over extremely long periods, as revealed by our investigation of a simple chaotic system (a realistic model for small bodies in a turbulent flow). We establish that this strong convergence is a multi-facetted phenomenon, in which the clustering is intense, widespread and balanced by lacunarity of other regions. Power laws, indicative of scale-free features, characterize the distribution of particles in the system. We use large-deviation and extreme-value statistics to explain the effect. Our results show that the interpretation of the ‘butterfly effect’ needs to be carefully qualified. We argue that the combination of mixing and clustering processes makes our specific model relevant to understanding the evolution of simple organisms. Lastly, this notion of convergent chaos, which implies the existence of conditions for which uncertainties are unexpectedly small, may also be relevant to the valuation of insurance and futures contracts.

Joint spatial-spectral hyperspectral image clustering using block-diagonal amplified affinity matrix

NASA Astrophysics Data System (ADS)

Fan, Lei; Messinger, David W.

2018-03-01

The large number of spectral channels in a hyperspectral image (HSI) produces a fine spectral resolution to differentiate between materials in a scene. However, difficult classes that have similar spectral signatures are often confused while merely exploiting information in the spectral domain. Therefore, in addition to spectral characteristics, the spatial relationships inherent in HSIs should also be considered for incorporation into classifiers. The growing availability of high spectral and spatial resolution of remote sensors provides rich information for image clustering. Besides the discriminating power in the rich spectrum, contextual information can be extracted from the spatial domain, such as the size and the shape of the structure to which one pixel belongs. In recent years, spectral clustering has gained popularity compared to other clustering methods due to the difficulty of accurate statistical modeling of data in high dimensional space. The joint spatial-spectral information could be effectively incorporated into the proximity graph for spectral clustering approach, which provides a better data representation by discovering the inherent lower dimensionality from the input space. We embedded both spectral and spatial information into our proposed local density adaptive affinity matrix, which is able to handle multiscale data by automatically selecting the scale of analysis for every pixel according to its neighborhood of the correlated pixels. Furthermore, we explored the "conductivity method," which aims at amplifying the block diagonal structure of the affinity matrix to further improve the performance of spectral clustering on HSI datasets.

The Hubble Space Telescope Cluster Supernova Survey. II. The Type la Supernova rate in high-redshift galaxy clusters

DOE PAGES

Barbary, K.; Aldering, G.; Amanullah, R.; ...

2011-12-28

Here we report a measurement of the Type Ia supernova (SN Ia) rate in galaxy clusters at 0.9 < z < 1.46 from the Hubble Space Telescope Cluster Supernova Survey. This is the first cluster SN Ia rate measurement with detected z > 0.9 SNe. Finding 8 ± 1 cluster SNe Ia, we determine an SN Ia rate of 0.50 +0.23 -0.19 (stat) +0.10 -0.09 (sys) h 2 70 SNuB (SNuB ≡ 10 -12 SNe L -1 ⊙,B yr -1). In units of stellar mass, this translates to 0.36 + 0.16 -0.13 (stat) +0.07 -0.06 (sys) h 2 70 SNuMmore » (SNuM ≡ 10 -12 SNe M –1 ⊙ yr –1). This represents a factor of ≈ 5 ± 2 increase over measurements of the cluster rate at z < 0.2. We parameterize the late-time SN Ia delay time distribution (DTD) with a power law: Ψ(t)∝t s . Under the approximation of a single-burst cluster formation redshift of zf = 3, our rate measurement in combination with lower-redshift cluster SN Ia rates constrains s = –1.41 +0.47 –0.40, consistent with measurements of the DTD in the field. This measurement is generally consistent with expectations for the "double degenerate" scenario and inconsistent with some models for the "single degenerate" scenario predicting a steeper DTD at large delay times. We check for environmental dependence and the influence of younger stellar populations by calculating the rate specifically in cluster red-sequence galaxies and in morphologically early-type galaxies, finding results similar to the full cluster rate. Finally, the upper limit of one hostless cluster SN Ia detected in the survey implies that the fraction of stars in the intra-cluster medium is less than 0.47 (95% confidence), consistent with measurements at lower redshifts.« less

Robust watermarking scheme for binary images using a slice-based large-cluster algorithm with a Hamming Code

NASA Astrophysics Data System (ADS)

Chen, Wen-Yuan; Liu, Chen-Chung

2006-01-01

The problems with binary watermarking schemes are that they have only a small amount of embeddable space and are not robust enough. We develop a slice-based large-cluster algorithm (SBLCA) to construct a robust watermarking scheme for binary images. In SBLCA, a small-amount cluster selection (SACS) strategy is used to search for a feasible slice in a large-cluster flappable-pixel decision (LCFPD) method, which is used to search for the best location for concealing a secret bit from a selected slice. This method has four major advantages over the others: (a) SBLCA has a simple and effective decision function to select appropriate concealment locations, (b) SBLCA utilizes a blind watermarking scheme without the original image in the watermark extracting process, (c) SBLCA uses slice-based shuffling capability to transfer the regular image into a hash state without remembering the state before shuffling, and finally, (d) SBLCA has enough embeddable space that every 64 pixels could accommodate a secret bit of the binary image. Furthermore, empirical results on test images reveal that our approach is a robust watermarking scheme for binary images.

2-Way k-Means as a Model for Microbiome Samples.

PubMed

Jackson, Weston J; Agarwal, Ipsita; Pe'er, Itsik

2017-01-01

Motivation . Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k -means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project.

2-Way k-Means as a Model for Microbiome Samples

PubMed Central

2017-01-01

Motivation. Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k-means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project. PMID:29177026

Dark matter dynamics in Abell 3827: new data consistent with standard cold dark matter

NASA Astrophysics Data System (ADS)

Massey, Richard; Harvey, David; Liesenborgs, Jori; Richard, Johan; Stach, Stuart; Swinbank, Mark; Taylor, Peter; Williams, Liliya; Clowe, Douglas; Courbin, Frédéric; Edge, Alastair; Israel, Holger; Jauzac, Mathilde; Joseph, Rémy; Jullo, Eric; Kitching, Thomas D.; Leonard, Adrienne; Merten, Julian; Nagai, Daisuke; Nightingale, James; Robertson, Andrew; Romualdez, Luis Javier; Saha, Prasenjit; Smit, Renske; Tam, Sut-Ieng; Tittley, Eric

2018-06-01

We present integral field spectroscopy of galaxy cluster Abell 3827, using Atacama Large Millimetre Array (ALMA) and Very Large Telescope/Multi-Unit Spectroscopic Explorer. It reveals an unusual configuration of strong gravitational lensing in the cluster core, with at least seven lensed images of a single background spiral galaxy. Lens modelling based on Hubble Space Telescope imaging had suggested that the dark matter associated with one of the cluster's central galaxies may be offset. The new spectroscopic data enable better subtraction of foreground light, and better identification of multiple background images. The inferred distribution of dark matter is consistent with being centred on the galaxies, as expected by Λ cold dark matter. Each galaxy's dark matter also appears to be symmetric. Whilst, we do not find an offset between mass and light (suggestive of self-interacting dark matter) as previously reported, the numerical simulations that have been performed to calibrate Abell 3827 indicate that offsets and asymmetry are still worth looking for in collisions with particular geometries. Meanwhile, ALMA proves exceptionally useful for strong lens image identifications.

Evolution of the early-type galaxy fraction in clusters since z = 0.8

NASA Astrophysics Data System (ADS)

Simard, L.; Clowe, D.; Desai, V.; Dalcanton, J. J.; von der Linden, A.; Poggianti, B. M.; White, S. D. M.; Aragón-Salamanca, A.; De Lucia, G.; Halliday, C.; Jablonka, P.; Milvang-Jensen, B.; Saglia, R. P.; Pelló, R.; Rudnick, G. H.; Zaritsky, D.

2009-12-01

We study the morphological content of a large sample of high-redshift clusters to determine its dependence on cluster mass and redshift. Quantitative morphologies are based on PSF-convolved, 2D bulge+disk decompositions of cluster and field galaxies on deep Very Large Telescope FORS2 images of eighteen, optically-selected galaxy clusters at 0.45 < z < 0.80 observed as part of the ESO Distant Cluster Survey (“EDisCS”). Morphological content is characterized by the early-type galaxy fraction f_et, and early-type galaxies are objectively selected based on their bulge fraction and image smoothness. This quantitative selection is equivalent to selecting galaxies visually classified as E or S0. Changes in early-type fractions as a function of cluster velocity dispersion, redshift and star-formation activity are studied. A set of 158 clusters extracted from the Sloan Digital Sky Survey is analyzed exactly as the distant EDisCS sample to provide a robust local comparison. We also compare our results to a set of clusters from the Millennium Simulation. Our main results are: (1) the early-type fractions of the SDSS and EDisCS clusters exhibit no clear trend as a function of cluster velocity dispersion. (2) Mid-z EDisCS clusters around σ = 500 km s-1 have f_et ≃ 0.5 whereas high-z EDisCS clusters have f_et ≃ 0.4. This represents a ~25% increase over a time interval of 2 Gyr. (3) There is a marked difference in the morphological content of EDisCS and SDSS clusters. None of the EDisCS clusters have early-type galaxy fractions greater than 0.6 whereas half of the SDSS clusters lie above this value. This difference is seen in clusters of all velocity dispersions. (4) There is a strong and clear correlation between morphology and star formation activity in SDSS and EDisCS clusters in the sense that decreasing fractions of [OII] emitters are tracked by increasing early-type fractions. This correlation holds independent of cluster velocity dispersion and redshift even though the fraction of [OII] emitters decreases from z ˜0.8 to z ˜ 0.06 in all environments. Our results pose an interesting challenge to structural transformation and star formation quenching processes that strongly depend on the global cluster environment (e.g., a dense ICM) and suggest that cluster membership may be of lesser importance than other variables in determining galaxy properties. Based on observations obtained in visitor and service modes at the ESO Very Large Telescope (VLT) as part of the Large Programme 166.A-0162 (the ESO Distant Cluster Survey). Also based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with proposal 9476. Support for this proposal was provided by NASA through a grant from the Space Telescope Science Institute. Table [see full textsee full textsee full textsee full textsee full text] is only available in electronic form at http://www.aanda.org

Multipole analysis of redshift-space distortions around cosmic voids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamaus, Nico; Weller, Jochen; Cousinou, Marie-Claude

We perform a comprehensive redshift-space distortion analysis based on cosmic voids in the large-scale distribution of galaxies observed with the Sloan Digital Sky Survey. To this end, we measure multipoles of the void-galaxy cross-correlation function and compare them with standard model predictions in cosmology. Merely considering linear-order theory allows us to accurately describe the data on the entire available range of scales and to probe void-centric distances down to about 2 h {sup −1}Mpc. Common systematics, such as the Fingers-of-God effect, scale-dependent galaxy bias, and nonlinear clustering do not seem to play a significant role in our analysis. We constrainmore » the growth rate of structure via the redshift-space distortion parameter β at two median redshifts, β( z-bar =0.32)=0.599{sup +0.134}{sub −0.124} and β( z-bar =0.54)=0.457{sup +0.056}{sub −0.054}, with a precision that is competitive with state-of-the-art galaxy-clustering results. While the high-redshift constraint perfectly agrees with model expectations, we observe a mild 2σ deviation at z-bar =0.32, which increases to 3σ when the data is restricted to the lowest available redshift range of 0.15< z <0.33.« less

Intermediate-Mass Black Holes in Globular Cluster Systems

NASA Astrophysics Data System (ADS)

Wrobel, J. M.; Miller-Jones, J. C. A.; Nyland, K. E.; Maccarone, T. J.

2018-01-01

Theory suggests that globular clusters (GCs) of stars can host intermediate-mass black holes (IMBHs) with masses of about 100 to 100,000 solar masses. We invoke a semi-empirical model to predict the mass of an IMBH that, if undergoing accretion in the long-lived hard X-ray state, is consistent with the synchrotron radio luminosity of a GC. We apply this model to extant images from the Karl G. Jansky Very Large Array (VLA) and to simulated images from the Next Generation Very Large Array (ngVLA). Guided by our VLA results for M81's system of 206 probable GCs at a distance of 3.6 Mpc, we consider using the ngVLA to study the hundreds of globular cluster systems out to a distance of 25 Mpc. With its sensitivity, spatial resolution, and field of view, we conclude that the ngVLA at 2cm will efficiently probe IMBH masses for tens of thousands of GCs. Finding IMBHs in GCs could validate a formation channel for seed BHs in the early universe, underpin gravitational wave predictions for space missions, and test scaling relations between stellar systems and the central BHs they host. The NRAO is a facility of the NSF, operated under cooperative agreement by AUI, Inc.

Angular correlation function of 1.5 million luminous red galaxies: clustering evolution and a search for baryon acoustic oscillations

NASA Astrophysics Data System (ADS)

Sawangwit, U.; Shanks, T.; Abdalla, F. B.; Cannon, R. D.; Croom, S. M.; Edge, A. C.; Ross, Nicholas P.; Wake, D. A.

2011-10-01

We present the angular correlation function measured from photometric samples comprising 1562 800 luminous red galaxies (LRGs). Three LRG samples were extracted from the Sloan Digital Sky Survey (SDSS) imaging data, based on colour-cut selections at redshifts, z≈ 0.35, 0.55 and 0.7 as calibrated by the spectroscopic surveys, SDSS-LRG, 2dF-SDSS LRG and QSO (quasi-stellar object) (2SLAQ) and the AAΩ-LRG survey. The galaxy samples cover ≈7600 deg2 of sky, probing a total cosmic volume of ≈5.5 h-3 Gpc3. The small- and intermediate-scale correlation functions generally show significant deviations from a single power-law fit with a well-detected break at ≈1 h-1 Mpc, consistent with the transition scale between the one- and two-halo terms in halo occupation models. For galaxy separations 1-20 h-1 Mpc and at fixed luminosity, we see virtually no evolution of the clustering with redshift and the data are consistent with a simple high peaks biasing model where the comoving LRG space density is constant with z. At fixed z, the LRG clustering amplitude increases with luminosity in accordance with the simple high peaks model, with a typical LRG dark matter halo mass 1013-1014 h-1 M⊙. For r < 1 h-1 Mpc, the evolution is slightly faster and the clustering decreases towards high redshift consistent with a virialized clustering model. However, assuming the halo occupation distribution (HOD) and Λ cold dark matter (ΛCDM) halo merger frameworks, ˜2-3 per cent/Gyr of the LRGs are required to merge in order to explain the small scales clustering evolution, consistent with previous results. At large scales, our result shows good agreement with the SDSS-LRG result of Eisenstein et al. but we find an apparent excess clustering signal beyond the baryon acoustic oscillations (BAO) scale. Angular power spectrum analyses of similar LRG samples also detect a similar apparent large-scale clustering excess but more data are required to check for this feature in independent galaxy data sets. Certainly, if the ΛCDM model were correct then we would have to conclude that this excess was caused by systematics at the level of Δw≈ 0.001-0.0015 in the photometric AAΩ-LRG sample.

Density-based clustering: A 'landscape view' of multi-channel neural data for inference and dynamic complexity analysis.

PubMed

Baglietto, Gabriel; Gigante, Guido; Del Giudice, Paolo

2017-01-01

Two, partially interwoven, hot topics in the analysis and statistical modeling of neural data, are the development of efficient and informative representations of the time series derived from multiple neural recordings, and the extraction of information about the connectivity structure of the underlying neural network from the recorded neural activities. In the present paper we show that state-space clustering can provide an easy and effective option for reducing the dimensionality of multiple neural time series, that it can improve inference of synaptic couplings from neural activities, and that it can also allow the construction of a compact representation of the multi-dimensional dynamics, that easily lends itself to complexity measures. We apply a variant of the 'mean-shift' algorithm to perform state-space clustering, and validate it on an Hopfield network in the glassy phase, in which metastable states are largely uncorrelated from memories embedded in the synaptic matrix. In this context, we show that the neural states identified as clusters' centroids offer a parsimonious parametrization of the synaptic matrix, which allows a significant improvement in inferring the synaptic couplings from the neural activities. Moving to the more realistic case of a multi-modular spiking network, with spike-frequency adaptation inducing history-dependent effects, we propose a procedure inspired by Boltzmann learning, but extending its domain of application, to learn inter-module synaptic couplings so that the spiking network reproduces a prescribed pattern of spatial correlations; we then illustrate, in the spiking network, how clustering is effective in extracting relevant features of the network's state-space landscape. Finally, we show that the knowledge of the cluster structure allows casting the multi-dimensional neural dynamics in the form of a symbolic dynamics of transitions between clusters; as an illustration of the potential of such reduction, we define and analyze a measure of complexity of the neural time series.

Cluster-cluster clustering

NASA Technical Reports Server (NTRS)

Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C. S.

1985-01-01

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales.

Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression.

PubMed

Song, Chao; Kwan, Mei-Po; Zhu, Jiping

2017-04-08

An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale.

Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression

PubMed Central

Song, Chao; Kwan, Mei-Po; Zhu, Jiping

2017-01-01

An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale. PMID:28397745

Using Star Clusters as Tracers of Star Formation and Chemical Evolution: The Chemical Enrichment History of the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Chilingarian, Igor V.; Asa’d, Randa

2018-05-01

The star formation (SFH) and chemical enrichment (CEH) histories of Local Group galaxies are traditionally studied by analyzing their resolved stellar populations in a form of color–magnitude diagrams obtained with the Hubble Space Telescope. Star clusters can be studied in integrated light using ground-based telescopes to much larger distances. They represent snapshots of the chemical evolution of their host galaxy at different ages. Here we present a simple theoretical framework for the chemical evolution based on the instantaneous recycling approximation (IRA) model. We infer a CEH from an SFH and vice versa using observational data. We also present a more advanced model for the evolution of individual chemical elements that takes into account the contribution of supernovae type Ia. We demonstrate that ages, iron, and α-element abundances of 15 star clusters derived from the fitting of their integrated optical spectra reliably trace the CEH of the Large Magellanic Cloud obtained from resolved stellar populations in the age range 40 Myr < t < 3.5 Gyr. The CEH predicted by our model from the global SFH of the LMC agrees remarkably well with the observed cluster age–metallicity relation. Moreover, the present-day total gas mass of the LMC estimated by the IRA model (6.2× {10}8 {M}ȯ ) matches within uncertainties the observed H I mass corrected for the presence of molecular gas (5.8+/- 0.5× {10}8 {M}ȯ ). We briefly discuss how our approach can be used to study SFHs of galaxies as distant as 10 Mpc at the level of detail that is currently available only in a handful of nearby Milky Way satellites. .

THE VERY MASSIVE STAR CONTENT OF THE NUCLEAR STAR CLUSTERS IN NGC 5253

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, L. J.; Crowther, P. A.; Calzetti, D.

2016-05-20

The blue compact dwarf galaxy NGC 5253 hosts a very young starburst containing twin nuclear star clusters, separated by a projected distance of 5 pc. One cluster (#5) coincides with the peak of the H α emission and the other (#11) with a massive ultracompact H ii region. A recent analysis of these clusters shows that they have a photometric age of 1 ± 1 Myr, in apparent contradiction with the age of 3–5 Myr inferred from the presence of Wolf-Rayet features in the cluster #5 spectrum. We examine Hubble Space Telescope ultraviolet and Very Large Telescope optical spectroscopy ofmore » #5 and show that the stellar features arise from very massive stars (VMSs), with masses greater than 100 M {sub ⊙}, at an age of 1–2 Myr. We further show that the very high ionizing flux from the nuclear clusters can only be explained if VMSs are present. We investigate the origin of the observed nitrogen enrichment in the circumcluster ionized gas and find that the excess N can be produced by massive rotating stars within the first 1 Myr. We find similarities between the NGC 5253 cluster spectrum and those of metal-poor, high-redshift galaxies. We discuss the presence of VMSs in young, star-forming galaxies at high redshift; these should be detected in rest-frame UV spectra to be obtained with the James Webb Space Telescope . We emphasize that population synthesis models with upper mass cutoffs greater than 100 M {sub ⊙} are crucial for future studies of young massive star clusters at all redshifts.« less

Galaxy clusters and cold dark matter - A low-density unbiased universe?

NASA Technical Reports Server (NTRS)

Bahcall, Neta A.; Cen, Renyue

1992-01-01

Large-scale simulations of a universe dominated by cold dark matter (CDM) are tested against two fundamental properties of clusters of galaxies: the cluster mass function and the cluster correlation function. We find that standard biased CDM models are inconsistent with these observations for any bias parameter b. A low-density, low-bias CDM-type model, with or without a cosmological constant, appears to be consistent with both the cluster mass function and the cluster correlations. The low-density model agrees well with the observed correlation function of the Abell, Automatic Plate Measuring Facility (APM), and Edinburgh-Durham cluster catalogs. The model is in excellent agreement with the observed dependence of the correlation strength on cluster mean separation, reproducing the measured universal dimensionless cluster correlation. The low-density model is also consistent with other large-scale structure observations, including the APM angular galaxy-correlations, and for lambda = 1-Omega with the COBE results of the microwave background radiation fluctuations.

Spatial cluster detection using dynamic programming.

PubMed

Sverchkov, Yuriy; Jiang, Xia; Cooper, Gregory F

2012-03-25

The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP) estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. We conclude that the dynamic programming algorithm performs on-par with other available methods for spatial cluster detection and point to its low computational cost and extendability as advantages in favor of further research and use of the algorithm.

Spatial cluster detection using dynamic programming

PubMed Central

2012-01-01

Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP) estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic programming algorithm performs on-par with other available methods for spatial cluster detection and point to its low computational cost and extendability as advantages in favor of further research and use of the algorithm. PMID:22443103

An analysis of the massless planet approximation in transit light curve models

NASA Astrophysics Data System (ADS)

Millholland, Sarah; Ruch, Gerry

2015-08-01

Many extrasolar planet transit light curve models use the approximation of a massless planet. They approximate the planet as orbiting elliptically with the host star at the orbit’s focus instead of depicting the planet and star as both orbiting around a common center of mass. This approximation should generally be very good because the transit is a small fraction of the full-phase curve and the planet to stellar mass ratio is typically very small. However, to fully examine the legitimacy of this approximation, it is useful to perform a robust, all-parameter space-encompassing statistical comparison between the massless planet model and the more accurate model.Towards this goal, we establish two questions: (1) In what parameter domain is the approximation invalid? (2) If characterizing an exoplanetary system in this domain, what is the error of the parameter estimates when using the simplified model? We first address question (1). Given each parameter vector in a finite space, we can generate the simplified and more complete model curves. Associated with these model curves is a measure of the deviation between them, such as the root mean square (RMS). We use Gibbs sampling to generate a sample that is distributed according to the RMS surface. The high-density regions in the sample correspond to a large deviation between the models. To determine the domains of these high-density areas, we first employ the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm. We then characterize the subclusters by performing the Patient Rule Induction Method (PRIM) on the transformed Principal Component spaces of each cluster. This process yields descriptors of the parameter domains with large discrepancies between the models.To consider question (2), we start by generating synthetic transit curve observations in the domains specified by the above analysis. We then derive the best-fit parameters of these synthetic light curves according to each model and examine the quality of agreement between the estimated parameters. Taken as a whole, these steps allow for a thorough analysis of the validity of the massless planet approximation.

Access and visualization using clusters and other parallel computers

NASA Technical Reports Server (NTRS)

Katz, Daniel S.; Bergou, Attila; Berriman, Bruce; Block, Gary; Collier, Jim; Curkendall, Dave; Good, John; Husman, Laura; Jacob, Joe; Laity, Anastasia;

Studies of Copper, Silver, and Gold Cluster Anions: Evidence of Electronic Shell Structure.

NASA Astrophysics Data System (ADS)

Pettiette, Claire Lynn

A new Ultraviolet Magnetic Time-of-Flight Photoelectron Spectrometer (MTOFPES) has been developed for the study of the electronic structure of clusters produced in a pulsed supersonic molecular beam. This is the first technique which has been successful in probing the valence electronic states of metal clusters. The ultraviolet photoelectron spectra of negative cluster ions of the noble metals have been taken at several different photon energies. These are presented along with the electron affinity and HOMO-LUMO gap measurements for Cu_6^- to Cu_ {41}^-, using 4.66 eV and 6.42 eV detachment energies; Ag_3^- to Ag_{21}^-, using 6.42 eV detachment energy; and Au_3^ - to Au_{21}^-, using 6.42 eV and 7.89 eV detachment energies. The spectra provide the first detailed probes of the s valence electrons of the noble metal clusters. In addition, the 6.42 eV and 7.89 eV spectra probe the first one to two electron volts of the molecular orbitals of the d valence electrons of copper and gold clusters. The electron affinity and HOMO-LUMO gap measurements of the noble metal clusters agree with the predictions of the ellipsoidal shell model for mono-valent metal clusters. In particular, cluster numbers 8, 20, and 40--which correspond to the spherical shell closings of this model--have low electron affinities and large HOMO-LUMO gaps. The spectra of the gold cluster ions indicate that the molecular orbital energies of the cluster valence electrons are more widely spaced for gold than for copper or silver. This is to be expected for the heavy atom clusters when relativistic effects are taken into account.

Detection of high-energy gamma-ray emission from the globular cluster 47 Tucanae with Fermi.

PubMed

Abdo, A A; Ackermann, M; Ajello, M; Atwood, W B; Axelsson, M; Baldini, L; Ballet, J; Barbiellini, G; Bastieri, D; Baughman, B M; Bechtol, K; Bellazzini, R; Berenji, B; Blandford, R D; Bloom, E D; Bonamente, E; Borgland, A W; Bregeon, J; Brez, A; Brigida, M; Bruel, P; Burnett, T H; Caliandro, G A; Cameron, R A; Caraveo, P A; Casandjian, J M; Cecchi, C; Celik, O; Charles, E; Chaty, S; Chekhtman, A; Cheung, C C; Chiang, J; Ciprini, S; Claus, R; Cohen-Tanugi, J; Conrad, J; Cutini, S; Dermer, C D; de Palma, F; Digel, S W; Dormody, M; do Couto e Silva, E; Drell, P S; Dubois, R; Dumora, D; Farnier, C; Favuzzi, C; Fegan, S J; Focke, W B; Frailis, M; Fukazawa, Y; Fusco, P; Gargano, F; Gasparrini, D; Gehrels, N; Germani, S; Giebels, B; Giglietto, N; Giordano, F; Glanzman, T; Godfrey, G; Grenier, I A; Grove, J E; Guillemot, L; Guiriec, S; Hanabata, Y; Harding, A K; Hayashida, M; Hays, E; Horan, D; Hughes, R E; Jóhannesson, G; Johnson, A S; Johnson, R P; Johnson, T J; Johnson, W N; Kamae, T; Katagiri, H; Kawai, N; Kerr, M; Knödlseder, J; Kuehn, F; Kuss, M; Lande, J; Latronico, L; Lemoine-Goumard, M; Longo, F; Loparco, F; Lott, B; Lovellette, M N; Lubrano, P; Makeev, A; Mazziotta, M N; McConville, W; McEnery, J E; Meurer, C; Michelson, P F; Mitthumsiri, W; Mizuno, T; Moiseev, A A; Monte, C; Monzani, M E; Morselli, A; Moskalenko, I V; Murgia, S; Nolan, P L; Norris, J P; Nuss, E; Ohsugi, T; Omodei, N; Orlando, E; Ormes, J F; Paneque, D; Panetta, J H; Parent, D; Pelassa, V; Pepe, M; Pierbattista, M; Piron, F; Porter, T A; Rainò, S; Rando, R; Razzano, M; Rea, N; Reimer, A; Reimer, O; Reposeur, T; Ritz, S; Rochester, L S; Rodriguez, A Y; Romani, R W; Roth, M; Ryde, F; Sadrozinski, H F-W; Sanchez, D; Sander, A; Saz Parkinson, P M; Sgrò, C; Smith, D A; Smith, P D; Spandre, G; Spinelli, P; Starck, J-L; Strickman, M S; Suson, D J; Tajima, H; Takahashi, H; Tanaka, T; Thayer, J B; Thayer, J G; Thompson, D J; Tibaldo, L; Torres, D F; Tosti, G; Tramacere, A; Uchiyama, Y; Usher, T L; Vasileiou, V; Vilchez, N; Vitale, V; Wang, P; Webb, N; Winer, B L; Wood, K S; Ylinen, T; Ziegler, M

2009-08-14

We report the detection of gamma-ray emissions above 200 megaelectron volts at a significance level of 17sigma from the globular cluster 47 Tucanae, using data obtained with the Large Area Telescope onboard the Fermi Gamma-ray Space Telescope. Globular clusters are expected to emit gamma rays because of the large populations of millisecond pulsars that they contain. The spectral shape of 47 Tucanae is consistent with gamma-ray emission from a population of millisecond pulsars. The observed gamma-ray luminosity implies an upper limit of 60 millisecond pulsars present in 47 Tucanae.

Weak Lensing : Ground vs. Space in the Cosmos Field

NASA Astrophysics Data System (ADS)

Kasliwal, Mansi M.; Massey, R. J.; Ellis, R. S.; Rhodes, J.

2006-12-01

Weak lensing statistics are best for large numbers wide surveys with greater number of galaxies and deep surveys with a higher number density of galaxies. Although space-based surveys are unparalleled in their depth, ground-based surveys are the more cost-effective way to survey wide regions of the sky. We assess the relative merits of the two observing platforms, by using premier, multi-band, ground-based Subaru SuprimeCam data and space-based Hubble ACS data, in the 2 sq. degree COSMOS field in three ways. First, we compare shear measurements of individual galaxies and identify the relative calibration of the two datasets in terms of the largest subset in magnitude and size that is consistent. Second, we compare spaceand ground-based mass maps to quantify the relative completeness and contamination of the resulting cluster catalogs. We find that more clusters with XMM catalog counterparts are detected from space than ground and some ground-based clusters are possibly spurious detections. Third, we perform a detailed comparison of the precision with which it is possible to reconstruct the mass and size of four clusters at various redshifts identified from both ground and space. We find that the noise is much lower from space in all three investigations, but find no evidence for systematic overestimation or underestimation of the individual cluster properties by either survey.

Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space.

PubMed

Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

2008-07-01

UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request.

Evolution of clustering length, large-scale bias, and host halo mass at 2 < z < 5 in the VIMOS Ultra Deep Survey (VUDS)⋆

NASA Astrophysics Data System (ADS)

Durkalec, A.; Le Fèvre, O.; Pollo, A.; de la Torre, S.; Cassata, P.; Garilli, B.; Le Brun, V.; Lemaux, B. C.; Maccagni, D.; Pentericci, L.; Tasca, L. A. M.; Thomas, R.; Vanzella, E.; Zamorani, G.; Zucca, E.; Amorín, R.; Bardelli, S.; Cassarà, L. P.; Castellano, M.; Cimatti, A.; Cucciati, O.; Fontana, A.; Giavalisco, M.; Grazian, A.; Hathi, N. P.; Ilbert, O.; Paltani, S.; Ribeiro, B.; Schaerer, D.; Scodeggio, M.; Sommariva, V.; Talia, M.; Tresse, L.; Vergani, D.; Capak, P.; Charlot, S.; Contini, T.; Cuby, J. G.; Dunlop, J.; Fotopoulou, S.; Koekemoer, A.; López-Sanjuan, C.; Mellier, Y.; Pforr, J.; Salvato, M.; Scoville, N.; Taniguchi, Y.; Wang, P. W.

2015-11-01

We investigate the evolution of galaxy clustering for galaxies in the redshift range 2.0

STRUCTURAL PARAMETERS FOR 10 HALO GLOBULAR CLUSTERS IN M33

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Jun, E-mail: majun@nao.cas.cn

2015-05-15

In this paper, we present the properties of 10 halo globular clusters (GCs) with luminosities L ≃ 5–7 × 10{sup 5} L{sub ⊙} in the Local Group galaxy M33 using images from the Hubble Space Telescope WFPC2 in the F555W and F814W bands. We obtained the ellipticities, position angles, and surface brightness profiles for each GC. In general, the ellipticities of the M33 sample clusters are similar to those of the M31 clusters. The structural and dynamical parameters are derived by fitting the profiles to three different models combined with mass-to-light ratios (M/L values) from population-synthesis models. The structural parametersmore » include core radii, concentration, half-light radii, and central surface brightness. The dynamical parameters include the integrated cluster mass, integrated binding energy, central surface mass density, and predicted line of sight velocity dispersion at the cluster center. The velocity dispersions of the four clusters predicted here agree well with the observed dispersions by Larsen et al. The results here showed that the majority of the sample halo GCs are better fitted by both the King model and the Wilson model than the Sérsic model. In general, the properties of the clusters in M33, M31, and the Milky Way fall in the same regions of parameter spaces. The tight correlations of cluster properties indicate a “fundamental plane” for clusters, which reflects some universal physical conditions and processes operating at the epoch of cluster formation.« less

Percolation Analysis as a Tool to Describe the Topology of the Large Scale Structure of the Universe

NASA Astrophysics Data System (ADS)

Yess, Capp D.

1997-09-01

Percolation analysis is the study of the properties of clusters. In cosmology, it is the statistics of the size and number of clusters. This thesis presents a refinement of percolation analysis and its application to astronomical data. An overview of the standard model of the universe and the development of large scale structure is presented in order to place the study in historical and scientific context. Then using percolation statistics we, for the first time, demonstrate the universal character of a network pattern in the real space, mass distributions resulting from nonlinear gravitational instability of initial Gaussian fluctuations. We also find that the maximum of the number of clusters statistic in the evolved, nonlinear distributions is determined by the effective slope of the power spectrum. Next, we present percolation analyses of Wiener Reconstructions of the IRAS 1.2 Jy Redshift Survey. There are ten reconstructions of galaxy density fields in real space spanning the range β = 0.1 to 1.0, where β=Ω0.6/b,/ Ω is the present dimensionless density and b is the linear bias factor. Our method uses the growth of the largest cluster statistic to characterize the topology of a density field, where Gaussian randomized versions of the reconstructions are used as standards for analysis. For the reconstruction volume of radius, R≈100h-1 Mpc, percolation analysis reveals a slight 'meatball' topology for the real space, galaxy distribution of the IRAS survey. Finally, we employ a percolation technique developed for pointwise distributions to analyze two-dimensional projections of the three northern and three southern slices in the Las Campanas Redshift Survey and then give consideration to further study of the methodology, errors and application of percolation. We track the growth of the largest cluster as a topological indicator to a depth of 400 h-1 Mpc, and report an unambiguous signal, with high signal-to-noise ratio, indicating a network topology which in two dimensions is indicative of a filamentary distribution. It is hoped that one day percolation analysis can characterize the structure of the universe to a degree that will aid theorists in confidently describing the nature of our world.

Theoretical accuracy in cosmological growth estimation

NASA Astrophysics Data System (ADS)

Bose, Benjamin; Koyama, Kazuya; Hellwing, Wojciech A.; Zhao, Gong-Bo; Winther, Hans A.

2017-07-01

We elucidate the importance of the consistent treatment of gravity-model specific nonlinearities when estimating the growth of cosmological structures from redshift space distortions (RSD). Within the context of standard perturbation theory (SPT), we compare the predictions of two theoretical templates with redshift space data from COLA (comoving Lagrangian acceleration) simulations in the normal branch of DGP gravity (nDGP) and general relativity (GR). Using COLA for these comparisons is validated using a suite of full N-body simulations for the same theories. The two theoretical templates correspond to the standard general relativistic perturbation equations and those same equations modeled within nDGP. Gravitational clustering nonlinear effects are accounted for by modeling the power spectrum up to one-loop order and redshift space clustering anisotropy is modeled using the Taruya, Nishimichi and Saito (TNS) RSD model. Using this approach, we attempt to recover the simulation's fiducial logarithmic growth parameter f . By assigning the simulation data with errors representing an idealized survey with a volume of 10 Gpc3/h3 , we find the GR template is unable to recover fiducial f to within 1 σ at z =1 when we match the data up to kmax=0.195 h /Mpc . On the other hand, the DGP template recovers the fiducial value within 1 σ . Further, we conduct the same analysis for sets of mock data generated for generalized models of modified gravity using SPT, where again we analyze the GR template's ability to recover the fiducial value. We find that for models with enhanced gravitational nonlinearity, the theoretical bias of the GR template becomes significant for stage IV surveys. Thus, we show that for the future large data volume galaxy surveys, the self-consistent modeling of non-GR gravity scenarios will be crucial in constraining theory parameters.

CLASH: A census of magnified star-forming galaxies at z ∼ 6-8

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, L. D.; Coe, D.; Postman, M.

2014-09-01

We utilize 16 band Hubble Space Telescope (HST) observations of 18 lensing clusters obtained as part of the Cluster Lensing And Supernova survey with Hubble (CLASH) Multi-Cycle Treasury program to search for z ∼ 6-8 galaxies. We report the discovery of 204, 45, and 13 Lyman-break galaxy candidates at z ∼ 6, z ∼ 7, and z ∼ 8, respectively, identified from purely photometric redshift selections. This large sample, representing nearly an order of magnitude increase in the number of magnified star-forming galaxies at z ∼ 6-8 presented to date, is unique in that we have observations in four WFC3/UVISmore » UV, seven ACS/WFC optical, and all five WFC3/IR broadband filters, which enable very accurate photometric redshift selections. We construct detailed lensing models for 17 of the 18 clusters to estimate object magnifications and to identify two new multiply lensed z ≳ 6 candidates. The median magnifications over the 17 clusters are 4, 4, and 5 for the z ∼ 6, z ∼ 7, and z ∼ 8 samples, respectively, over an average area of 4.5 arcmin{sup 2} per cluster. We compare our observed number counts with expectations based on convolving 'blank' field UV luminosity functions through our cluster lens models and find rough agreement down to ∼27 mag, where we begin to suffer significant incompleteness. In all three redshift bins, we find a higher number density at brighter observed magnitudes than the field predictions, empirically demonstrating for the first time the enhanced efficiency of lensing clusters over field surveys. Our number counts also are in general agreement with the lensed expectations from the cluster models, especially at z ∼ 6, where we have the best statistics.« less

Electric-field-induced association of colloidal particles

NASA Astrophysics Data System (ADS)

Fraden, Seth; Hurd, Alan J.; Meyer, Robert B.

1989-11-01

Dilute suspensions of micron diameter dielectric spheres confined to two dimensions are induced to aggregate linearly by application of an electric field. The growth of the average cluster size agrees well with the Smoluchowski equation, but the evolution of the measured cluster size distribution exhibits significant departures from theory at large times due to the formation of long linear clusters which effectively partition space into isolated one-dimensional strips.

Comparison of temporal and spectral scattering methods using acoustically large breast models derived from magnetic resonance images.

PubMed

Hesford, Andrew J; Tillett, Jason C; Astheimer, Jeffrey P; Waag, Robert C

2014-08-01

Accurate and efficient modeling of ultrasound propagation through realistic tissue models is important to many aspects of clinical ultrasound imaging. Simplified problems with known solutions are often used to study and validate numerical methods. Greater confidence in a time-domain k-space method and a frequency-domain fast multipole method is established in this paper by analyzing results for realistic models of the human breast. Models of breast tissue were produced by segmenting magnetic resonance images of ex vivo specimens into seven distinct tissue types. After confirming with histologic analysis by pathologists that the model structures mimicked in vivo breast, the tissue types were mapped to variations in sound speed and acoustic absorption. Calculations of acoustic scattering by the resulting model were performed on massively parallel supercomputer clusters using parallel implementations of the k-space method and the fast multipole method. The efficient use of these resources was confirmed by parallel efficiency and scalability studies using large-scale, realistic tissue models. Comparisons between the temporal and spectral results were performed in representative planes by Fourier transforming the temporal results. An RMS field error less than 3% throughout the model volume confirms the accuracy of the methods for modeling ultrasound propagation through human breast.

Nonrotating Convective Self-Aggregation in a Limited Area AGCM

NASA Astrophysics Data System (ADS)

Arnold, Nathan P.; Putman, William M.

2018-04-01

We present nonrotating simulations with the Goddard Earth Observing System (GEOS) atmospheric general circulation model (AGCM) in a square limited area domain over uniform sea surface temperature. As in previous studies, convection spontaneously aggregates into humid clusters, driven by a combination of radiative and moisture-convective feedbacks. The aggregation is qualitatively independent of resolution, with horizontal grid spacing from 3 to 110 km, with both explicit and parameterized deep convection. A budget for the spatial variance of column moist static energy suggests that longwave radiative and surface flux feedbacks help establish aggregation, while the shortwave feedback contributes to its maintenance. Mechanism-denial experiments confirm that aggregation does not occur without interactive longwave radiation. Ice cloud radiative effects help support the humid convecting regions but are not essential for aggregation, while liquid clouds have a negligible effect. Removing the dependence of parameterized convection on tropospheric humidity reduces the intensity of aggregation but does not prevent the formation of dry regions. In domain sizes less than (5,000 km)2, the aggregation forms a single cluster, while larger domains develop multiple clusters. Larger domains initialized with a single large cluster are unable to maintain them, suggesting an upper size limit. Surface wind speed increases with domain size, implying that maintenance of the boundary layer winds may limit cluster size. As cluster size increases, large boundary layer temperature anomalies develop to maintain the surface pressure gradient, leading to an increase in the depth of parameterized convective heating and an increase in gross moist stability.

Small-Scale Drop-Size Variability: Empirical Models for Drop-Size-Dependent Clustering in Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Knyazikhin, Yuri; Larsen, Michael L.; Wiscombe, Warren J.

2005-01-01

By analyzing aircraft measurements of individual drop sizes in clouds, it has been shown in a companion paper that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)), where 0 less than or equals D(r) less than or equals 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and a Poisson distribution of cloud drops, these models illustrate strong drop clustering, especially with larger drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics, including how fast rain can form. For radiative transfer theory, clustering of large drops enhances their impact on the cloud optical path. The clustering phenomenon also helps explain why remotely sensed cloud drop size is generally larger than that measured in situ.

The devil is in the tails: the role of globular cluster mass evolution on stream properties

NASA Astrophysics Data System (ADS)

Balbinot, Eduardo; Gieles, Mark

2018-02-01

We present a study of the effects of collisional dynamics on the formation and detectability of cold tidal streams. A semi-analytical model for the evolution of the stellar mass function was implemented and coupled to a fast stellar stream simulation code, as well as the synthetic cluster evolution code EMACSS for the mass evolution as a function of a globular cluster orbit. We find that the increase in the average mass of the escaping stars for clusters close to dissolution has a major effect on the observable stream surface density. As an example, we show that Palomar 5 would have undetectable streams (in an SDSS-like survey) if it was currently three times more massive, despite the fact that a more massive cluster loses stars at a higher rate. This bias due to the preferential escape of low-mass stars is an alternative explanation for the absence of tails near massive clusters, than a dark matter halo associated with the cluster. We explore the orbits of a large sample of Milky Way globular clusters and derive their initial masses and remaining mass fraction. Using properties of known tidal tails, we explore regions of parameter space that favour the detectability of a stream. A list of high-probability candidates is discussed.

What drives the evolution of Luminous Compact Blue Galaxies in Clusters vs. the Field?

NASA Astrophysics Data System (ADS)

Wirth, Gregory

2017-08-01

Present-day galaxy clusters consist chiefly of low-mass dwarf elliptical galaxies, but the progenitors of this dominant population remain unclear. A prime candidate is the class of objects known as Luminous Compact Blue Galaxies, common in intermediate-reshift clusters but virtually extinct today. Recent cosmological simulations suggest that the present-day dwarfs galaxies begin as irregular field galaxies, undergo an environmentally-driven starburst phase as they enter the cluster, and stop forming stars earlier than their counterparts in the field. This model predicts that cluster dwarfs should have lower stellar mass per unit dynamical mass than their counterparts in the field. We propose a two-pronged archival research program to test this key prediction using the combination of precision photometry from space and high-quality spectroscopy. First, we will combine optical HST/ACS imaging of five z=0.55 clusters (including two HST Frontier Fields) with Spitzer IR imaging and publicly-released Keck/DEIMOS spectroscopy to measure stellar-to-dynamical-mass ratios for a large sample of cluster LCBGs. Second, we will exploit a new catalog of LCBGs in the COSMOS field to gather corresponding data for a significant sample of field LCBGs. By comparing mass ratios from these datasets, we will test theoretical predictions and determine the primary physical driver of cluster dwarf-galaxy evolution.

BUDHIES II: a phase-space view of H I gas stripping and star formation quenching in cluster galaxies

NASA Astrophysics Data System (ADS)

Jaffé, Yara L.; Smith, Rory; Candlish, Graeme N.; Poggianti, Bianca M.; Sheen, Yun-Kyeong; Verheijen, Marc A. W.

2015-04-01

We investigate the effect of ram-pressure from the intracluster medium on the stripping of H I gas in galaxies in a massive, relaxed, X-ray bright, galaxy cluster at z = 0.2 from the Blind Ultra Deep H I Environmental Survey (BUDHIES). We use cosmological simulations, and velocity versus position phase-space diagrams to infer the orbital histories of the cluster galaxies. In particular, we embed a simple analytical description of ram-pressure stripping in the simulations to identify the regions in phase-space where galaxies are more likely to have been sufficiently stripped of their H I gas to fall below the detection limit of our survey. We find a striking agreement between the model predictions and the observed location of H I-detected and non-detected blue (late-type) galaxies in phase-space, strongly implying that ram-pressure plays a key role in the gas removal from galaxies, and that this can happen during their first infall into the cluster. However, we also find a significant number of gas-poor, red (early-type) galaxies in the infall region of the cluster that cannot easily be explained with our model of ram-pressure stripping alone. We discuss different possible additional mechanisms that could be at play, including the pre-processing of galaxies in their previous environment. Our results are strengthened by the distribution of galaxy colours (optical and UV) in phase-space, that suggests that after a (gas-rich) field galaxy falls into the cluster, it will lose its gas via ram-pressure stripping, and as it settles into the cluster, its star formation will decay until it is completely quenched. Finally, this work demonstrates the utility of phase-space diagrams to analyse the physical processes driving the evolution of cluster galaxies, in particular H I gas stripping.

Exploring Connectivity in Sequence Space of Functional RNA

NASA Technical Reports Server (NTRS)

Wei, Chenyu; Pohorille, Andrzej; Popovic, Milena; Ditzler, Mark

2017-01-01

Emergence of replicable genetic molecules was one of the marking points in the origin of life, evolution of which can be conceptualized as a walk through the space of all possible sequences. A theoretical concept of fitness landscape helps to understand evolutionary processes through assigning a value of fitness to each genotype. Then, evolution of a phenotype is viewed as a series of consecutive, single-point mutations. Natural selection biases evolution toward peaks of high fitness and away from valleys of low fitness. whereas neutral drift occurs in the sequence space without direction as mutations are introduced at random. Large networks of neutral or near-neutral mutations on a fitness landscape, especially for sufficiently long genomes, are possible or even inevitable. Their detection in experiments, however, has been elusive. Although a few near-neutral evolutionary pathways have been found, recent experimental evidence indicates landscapes consist of largely isolated islands. The generality of these results, however, is not clear, as the genome length or the fraction of functional molecules in the genotypic space might have been insufficient for the emergence of large, neutral networks. Thorough investigation on the structure of the fitness landscape is essential to understand the mechanisms of evolution of early genomes. RNA molecules are commonly assumed to play the pivotal role in the origin of genetic systems. They are widely believed to be early, if not the earliest, genetic and catalytic molecules, with abundant biochemical activities as aptamers and ribozymes, i.e. RNA molecules capable, respectively, to bind small molecules or catalyze chemical reactions. Here, we present results of our recent studies on the structure of the sequence space of RNA ligase ribozymes selected through in vitro evolution. Several hundred thousands of sequences active to a different degree were obtained by way of deep sequencing. Analysis of these sequences revealed several large clusters defined such that every sequence in a cluster can be reached from any other sequence in the same cluster through a series of single point mutations. Sequences in a single cluster appear to adopt more than one secondary structure. The mechanism of refolding within a single cluster was examined. To shed light on possible evolutionary paths in the space of ribozymes, the connectivity between clusters was investigated. The effect of length of RNA molecules on the structure of the fitness landscape and possible evolutionary paths was examined by way of comparing functional sequences of 20 and 80 nucleobases in length. It was found that sequences of different lengths shared secondary structure motifs that were presumed responsible for catalytic activity, with increasing complexity and global structural rearrangements emerging in longer molecules.

Mapping the spatial distribution of star formation in cluster galaxies at z ~ 0.5 with the Grism Lens-Amplified Survey from Space (GLASS)

NASA Astrophysics Data System (ADS)

Vulcani, Benedetta; Vulcani

We present the first study of the spatial distribution of star formation in z ~ 0.5 cluster galaxies. The analysis is based on data taken with the Wide Field Camera 3 as part of the Grism Lens-Amplified Survey from Space (GLASS). We illustrate the methodology by focusing on two clusters (MACS0717.5+3745 and MACS1423.8+2404) with different morphologies (one relaxed and one merging) and use foreground and background galaxies as field control sample. The cluster+field sample consists of 42 galaxies with stellar masses in the range 108-1011 M ⊙, and star formation rates in the range 1-20 M⊙ yr -1. In both environments, Hα is more extended than the rest-frame UV continuum in 60% of the cases, consistent with diffuse star formation and inside out growth. The Hα emission appears more extended in cluster galaxies than in the field, pointing perhaps to ionized gas being stripped and/or star formation being enhanced at large radii. The peak of the Hα emission and that of the continuum are offset by less than 1 kpc. We investigate trends with the hot gas density as traced by the X-ray emission, and with the surface mass density as inferred from gravitational lens models and find no conclusive results. The diversity of morphologies and sizes observed in Hα illustrates the complexity of the environmental process that regulate star formation.

Feasibility study using large ribbon parachutes, retrorockets, and hydrodynamic attenuation to recover liquid rocket boosters for the Space Shuttle

NASA Technical Reports Server (NTRS)

Pepper, William B.; Wailes, William K.

1989-01-01

A new three-phase approach to recovery of the large liquid rocket boosters being studied for the Space Shuttle is proposed. The concept consists of a cluster of larger ribbon parachutes, retrorockets, and spar mode flotation. The two inert liquid rocket boosters weighing 115,000 lb to 183,000 lb descend from high altitude in a side-on coning attitude to 16,000 ft altitude where a cluster of large ribbon parachutes are deployed. The terminal velocity near water landing is 80 ft/sec. Retrorockets are used to decrease the velocity to about 40 ft/sec. The third phase is opening of the front end of the cylindrical rocket case to allow flooding to cushion impact and allow vertical flotation in the spar mode keeping the four expensive liquid rocket engines dry.

Through the Looking GLASS: HST Spectroscopy of Faint Galaxies Lensed by the Frontier Fields Cluster MACSJ0717.5+3745

NASA Astrophysics Data System (ADS)

Schmidt, K. B.; Treu, T.; Brammer, G. B.; Bradač, M.; Wang, X.; Dijkstra, M.; Dressler, A.; Fontana, A.; Gavazzi, R.; Henry, A. L.; Hoag, A.; Jones, T. A.; Kelly, P. L.; Malkan, M. A.; Mason, C.; Pentericci, L.; Poggianti, B.; Stiavelli, M.; Trenti, M.; von der Linden, A.; Vulcani, B.

2014-02-01

The Grism Lens-Amplified Survey from Space (GLASS) is a Hubble Space Telescope (HST) Large Program, which will obtain 140 orbits of grism spectroscopy of the core and infall regions of 10 galaxy clusters, selected to be among the very best cosmic telescopes. Extensive HST imaging is available from many sources including the CLASH and Frontier Fields programs. We introduce the survey by analyzing spectra of faint multiply-imaged galaxies and z >~ 6 galaxy candidates obtained from the first 7 orbits out of 14 targeting the core of the Frontier Fields cluster MACSJ0717.5+3745. Using the G102 and G141 grisms to cover the wavelength range 0.8-1.7 μm, we confirm four strongly lensed systems by detecting emission lines in each of the images. For the 9 z >~ 6 galaxy candidates clear from contamination, we do not detect any emission lines down to a 7 orbit 1σ noise level of ~5 × 10-18 erg s-1 cm-2. Taking lensing magnification into account, our flux sensitivity reaches ~0.2-5 × 10-18 erg s-1cm-2. These limits over an uninterrupted wavelength range rule out the possibility that the high-z galaxy candidates are instead strong line emitters at lower redshift. These results show that by means of careful modeling of the background—and with the assistance of lensing magnification—interesting flux limits can be reached for large numbers of objects, avoiding pre-selection and the wavelength restrictions inherent to ground-based multi-slit spectroscopy. These observations confirm the power of slitless HST spectroscopy even in fields as crowded as a cluster core.

Parallel Density-Based Clustering for Discovery of Ionospheric Phenomena

NASA Astrophysics Data System (ADS)

Pankratius, V.; Gowanlock, M.; Blair, D. M.

2015-12-01

Ionospheric total electron content maps derived from global networks of dual-frequency GPS receivers can reveal a plethora of ionospheric features in real-time and are key to space weather studies and natural hazard monitoring. However, growing data volumes from expanding sensor networks are making manual exploratory studies challenging. As the community is heading towards Big Data ionospheric science, automation and Computer-Aided Discovery become indispensable tools for scientists. One problem of machine learning methods is that they require domain-specific adaptations in order to be effective and useful for scientists. Addressing this problem, our Computer-Aided Discovery approach allows scientists to express various physical models as well as perturbation ranges for parameters. The search space is explored through an automated system and parallel processing of batched workloads, which finds corresponding matches and similarities in empirical data. We discuss density-based clustering as a particular method we employ in this process. Specifically, we adapt Density-Based Spatial Clustering of Applications with Noise (DBSCAN). This algorithm groups geospatial data points based on density. Clusters of points can be of arbitrary shape, and the number of clusters is not predetermined by the algorithm; only two input parameters need to be specified: (1) a distance threshold, (2) a minimum number of points within that threshold. We discuss an implementation of DBSCAN for batched workloads that is amenable to parallelization on manycore architectures such as Intel's Xeon Phi accelerator with 60+ general-purpose cores. This manycore parallelization can cluster large volumes of ionospheric total electronic content data quickly. Potential applications for cluster detection include the visualization, tracing, and examination of traveling ionospheric disturbances or other propagating phenomena. Acknowledgments. We acknowledge support from NSF ACI-1442997 (PI V. Pankratius).

Chemical models for simulating single-walled nanotube production in arc vaporization and laser ablation processes

NASA Technical Reports Server (NTRS)

Scott, Carl D.

2004-01-01

Chemical kinetic models for the nucleation and growth of clusters and single-walled carbon nanotube (SWNT) growth are developed for numerical simulations of the production of SWNTs. Two models that involve evaporation and condensation of carbon and metal catalysts, a full model involving all carbon clusters up to C80, and a reduced model are discussed. The full model is based on a fullerene model, but nickel and carbon/nickel cluster reactions are added to form SWNTs from soot and fullerenes. The full model has a large number of species--so large that to incorporate them into a flow field computation for simulating laser ablation and arc processes requires that they be simplified. The model is reduced by defining large clusters that represent many various sized clusters. Comparisons are given between these models for cases that may be applicable to arc and laser ablation production. Solutions to the system of chemical rate equations of these models for a ramped temperature profile show that production of various species, including SWNTs, agree to within about 50% for a fast ramp, and within 10% for a slower temperature decay time.

The Richness Dependence of Galaxy Cluster Correlations: Results From A Redshift Survey Of Rich APM Clusters

NASA Technical Reports Server (NTRS)

Croft, R. A. C.; Dalton, G. B.; Efstathiou, G.; Sutherland, W. J.; Maddox, S. J.

1997-01-01

We analyze the spatial clustering properties of a new catalog of very rich galaxy clusters selected from the APM Galaxy Survey. These clusters are of comparable richness and space density to Abell Richness Class greater than or equal to 1 clusters, but selected using an objective algorithm from a catalog demonstrably free of artificial inhomogeneities. Evaluation of the two-point correlation function xi(sub cc)(r) for the full sample and for richer subsamples reveals that the correlation amplitude is consistent with that measured for lower richness APM clusters and X-ray selected clusters. We apply a maximum likelihood estimator to find the best fitting slope and amplitude of a power law fit to x(sub cc)(r), and to estimate the correlation length r(sub 0) (the value of r at which xi(sub cc)(r) is equal to unity). For clusters with a mean space density of 1.6 x 10(exp -6) h(exp 3) MpC(exp -3) (equivalent to the space density of Abell Richness greater than or equal to 2 clusters), we find r(sub 0) = 21.3(+11.1/-9.3) h(exp -1) Mpc (95% confidence limits). This is consistent with the weak richness dependence of xi(sub cc)(r) expected in Gaussian models of structure formation. In particular, the amplitude of xi(sub cc)(r) at all richnesses matches that of xi(sub cc)(r) for clusters selected in N-Body simulations of a low density Cold Dark Matter model.

The development rainfall forecasting using kalman filter

NASA Astrophysics Data System (ADS)

Zulfi, Mohammad; Hasan, Moh.; Dwidja Purnomo, Kosala

2018-04-01

Rainfall forecasting is very interesting for agricultural planing. Rainfall information is useful to make decisions about the plan planting certain commodities. In this studies, the rainfall forecasting by ARIMA and Kalman Filter method. Kalman Filter method is used to declare a time series model of which is shown in the form of linear state space to determine the future forecast. This method used a recursive solution to minimize error. The rainfall data in this research clustered by K-means clustering. Implementation of Kalman Filter method is for modelling and forecasting rainfall in each cluster. We used ARIMA (p,d,q) to construct a state space for KalmanFilter model. So, we have four group of the data and one model in each group. In conclusions, Kalman Filter method is better than ARIMA model for rainfall forecasting in each group. It can be showed from error of Kalman Filter method that smaller than error of ARIMA model.

Stellar Collisions and Blue Straggler Stars in Dense Globular Clusters

NASA Astrophysics Data System (ADS)

Chatterjee, Sourav; Rasio, Frederic A.; Sills, Alison; Glebbeek, Evert

2013-11-01

Blue straggler stars (BSSs) are abundantly observed in all Galactic globular clusters (GGCs) where data exist. However, observations alone cannot reveal the relative importance of various formation channels or the typical formation times for this well-studied population of anomalous stars. Using a state-of-the-art Hénon-type Monte Carlo code that includes all relevant physical processes, we create 128 models with properties typical of the observed GGCs. These models include realistic numbers of single and binary stars, use observationally motivated initial conditions, and span large ranges in central density, concentration, binary fraction, and mass. Their properties can be directly compared with those of observed GGCs. We can easily identify the BSSs in our models and determine their formation channels and birth times. We find that for central densities above ~103 M ⊙ pc-3, the dominant formation channel is stellar collisions, while for lower density clusters, mass transfer in binaries provides a significant contribution (up to 60% in our models). The majority of these collisions are binary-mediated, occurring during three-body and four-body interactions. As a result, a strong correlation between the specific frequency of BSSs and the binary fraction in a cluster can be seen in our models. We find that the number of BSSs in the core shows only a weak correlation with the collision rate estimator Γ traditionally used by observers, in agreement with the latest Hubble Space Telescope Advanced Camera for Surveys data. Using an idealized "full mixing" prescription for collision products, our models indicate that the BSSs observed today may have formed several Gyr ago. However, denser clusters tend to have younger (~1 Gyr) BSSs.

Voronoi distance based prospective space-time scans for point data sets: a dengue fever cluster analysis in a southeast Brazilian town

PubMed Central

2011-01-01

Background The Prospective Space-Time scan statistic (PST) is widely used for the evaluation of space-time clusters of point event data. Usually a window of cylindrical shape is employed, with a circular or elliptical base in the space domain. Recently, the concept of Minimum Spanning Tree (MST) was applied to specify the set of potential clusters, through the Density-Equalizing Euclidean MST (DEEMST) method, for the detection of arbitrarily shaped clusters. The original map is cartogram transformed, such that the control points are spread uniformly. That method is quite effective, but the cartogram construction is computationally expensive and complicated. Results A fast method for the detection and inference of point data set space-time disease clusters is presented, the Voronoi Based Scan (VBScan). A Voronoi diagram is built for points representing population individuals (cases and controls). The number of Voronoi cells boundaries intercepted by the line segment joining two cases points defines the Voronoi distance between those points. That distance is used to approximate the density of the heterogeneous population and build the Voronoi distance MST linking the cases. The successive removal of edges from the Voronoi distance MST generates sub-trees which are the potential space-time clusters. Finally, those clusters are evaluated through the scan statistic. Monte Carlo replications of the original data are used to evaluate the significance of the clusters. An application for dengue fever in a small Brazilian city is presented. Conclusions The ability to promptly detect space-time clusters of disease outbreaks, when the number of individuals is large, was shown to be feasible, due to the reduced computational load of VBScan. Instead of changing the map, VBScan modifies the metric used to define the distance between cases, without requiring the cartogram construction. Numerical simulations showed that VBScan has higher power of detection, sensitivity and positive predicted value than the Elliptic PST. Furthermore, as VBScan also incorporates topological information from the point neighborhood structure, in addition to the usual geometric information, it is more robust than purely geometric methods such as the elliptic scan. Those advantages were illustrated in a real setting for dengue fever space-time clusters. PMID:21513556

Vent modification of large ribbon parachutes to enhance cluster performance

NASA Technical Reports Server (NTRS)

Kolega, D. J.; Woodis, W. R.; Reuter, J. D.

1986-01-01

Due to uneven load sharing and lagging inflation rates, the design of the Large Main Parachute (LMP) cluster, used to recover the Space Shuttle steel case Solid Rocket Boosters, had to be modified. The cause of the problem was excessive variation in effective porosity in the crown area of the LMP during first stage inflation. The design modification consisted of adding horizontal ribbons above the existing vent band to reduce the vent porosity and better control the position and attitude of the vent lines. Performance of modified LMP's since introduction indicates that the load sharing between the clustered chutes has been significantly improved.

Quantiprot - a Python package for quantitative analysis of protein sequences.

PubMed

Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold

2017-07-17

The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.

Hybrid clustering based fuzzy structure for vibration control - Part 1: A novel algorithm for building neuro-fuzzy system

NASA Astrophysics Data System (ADS)

Nguyen, Sy Dzung; Nguyen, Quoc Hung; Choi, Seung-Bok

2015-01-01

This paper presents a new algorithm for building an adaptive neuro-fuzzy inference system (ANFIS) from a training data set called B-ANFIS. In order to increase accuracy of the model, the following issues are executed. Firstly, a data merging rule is proposed to build and perform a data-clustering strategy. Subsequently, a combination of clustering processes in the input data space and in the joint input-output data space is presented. Crucial reason of this task is to overcome problems related to initialization and contradictory fuzzy rules, which usually happen when building ANFIS. The clustering process in the input data space is accomplished based on a proposed merging-possibilistic clustering (MPC) algorithm. The effectiveness of this process is evaluated to resume a clustering process in the joint input-output data space. The optimal parameters obtained after completion of the clustering process are used to build ANFIS. Simulations based on a numerical data, 'Daily Data of Stock A', and measured data sets of a smart damper are performed to analyze and estimate accuracy. In addition, convergence and robustness of the proposed algorithm are investigated based on both theoretical and testing approaches.

Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space

PubMed Central

Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

2008-01-01

Motivation: UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. Application: We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. Results: We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. Availability: A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request. Contact: lonshy@cs.huji.ac.il PMID:18586742

Detonation of Meta-stable Clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuhl, Allen; Kuhl, Allen L.; Fried, Laurence E.

2008-05-31

We consider the energy accumulation in meta-stable clusters. This energy can be much larger than the typical chemical bond energy (~;;1 ev/atom). For example, polymeric nitrogen can accumulate 4 ev/atom in the N8 (fcc) structure, while helium can accumulate 9 ev/atom in the excited triplet state He2* . They release their energy by cluster fission: N8 -> 4N2 and He2* -> 2He. We study the locus of states in thermodynamic state space for the detonation of such meta-stable clusters. In particular, the equilibrium isentrope, starting at the Chapman-Jouguet state, and expanding down to 1 atmosphere was calculated with the Cheetahmore » code. Large detonation pressures (3 and 16 Mbar), temperatures (12 and 34 kilo-K) and velocities (20 and 43 km/s) are a consequence of the large heats of detonation (6.6 and 50 kilo-cal/g) for nitrogen and helium clusters respectively. If such meta-stable clusters could be synthesized, they offer the potential for large increases in the energy density of materials.« less

Enhanced conformational sampling to visualize a free-energy landscape of protein complex formation

PubMed Central

Iida, Shinji; Nakamura, Haruki; Higo, Junichi

2016-01-01

We introduce various, recently developed, generalized ensemble methods, which are useful to sample various molecular configurations emerging in the process of protein–protein or protein–ligand binding. The methods introduced here are those that have been or will be applied to biomolecular binding, where the biomolecules are treated as flexible molecules expressed by an all-atom model in an explicit solvent. Sampling produces an ensemble of conformations (snapshots) that are thermodynamically probable at room temperature. Then, projection of those conformations to an abstract low-dimensional space generates a free-energy landscape. As an example, we show a landscape of homo-dimer formation of an endothelin-1-like molecule computed using a generalized ensemble method. The lowest free-energy cluster at room temperature coincided precisely with the experimentally determined complex structure. Two minor clusters were also found in the landscape, which were largely different from the native complex form. Although those clusters were isolated at room temperature, with rising temperature a pathway emerged linking the lowest and second-lowest free-energy clusters, and a further temperature increment connected all the clusters. This exemplifies that the generalized ensemble method is a powerful tool for computing the free-energy landscape, by which one can discuss the thermodynamic stability of clusters and the temperature dependence of the cluster networks. PMID:27288028

Data Mining Technologies Inspired from Visual Principle

NASA Astrophysics Data System (ADS)

Xu, Zongben

In this talk we review the recent work done by our group on data mining (DM) technologies deduced from simulating visual principle. Through viewing a DM problem as a cognition problems and treading a data set as an image with each light point located at a datum position, we developed a series of high efficient algorithms for clustering, classification and regression via mimicking visual principles. In pattern recognition, human eyes seem to possess a singular aptitude to group objects and find important structure in an efficient way. Thus, a DM algorithm simulating visual system may solve some basic problems in DM research. From this point of view, we proposed a new approach for data clustering by modeling the blurring effect of lateral retinal interconnections based on scale space theory. In this approach, as the data image blurs, smaller light blobs merge into large ones until the whole image becomes one light blob at a low enough level of resolution. By identifying each blob with a cluster, the blurring process then generates a family of clustering along the hierarchy. The proposed approach provides unique solutions to many long standing problems, such as the cluster validity and the sensitivity to initialization problems, in clustering. We extended such an approach to classification and regression problems, through combatively employing the Weber's law in physiology and the cell response classification facts. The resultant classification and regression algorithms are proven to be very efficient and solve the problems of model selection and applicability to huge size of data set in DM technologies. We finally applied the similar idea to the difficult parameter setting problem in support vector machine (SVM). Viewing the parameter setting problem as a recognition problem of choosing a visual scale at which the global and local structures of a data set can be preserved, and the difference between the two structures be maximized in the feature space, we derived a direct parameter setting formula for the Gaussian SVM. The simulations and applications show that the suggested formula significantly outperforms the known model selection methods in terms of efficiency and precision.

Interaction of intense ultrashort pulse lasers with clusters.

NASA Astrophysics Data System (ADS)

Petrov, George

2007-11-01

The last ten years have witnessed an explosion of activity involving the interaction of clusters with intense ultrashort pulse lasers. Atomic or molecular clusters are targets with unique properties, as they are halfway between solid and gases. The intense laser radiation creates hot dense plasma, which can provide a compact source of x-rays and energetic particles. The focus of this investigation is to understand the salient features of energy absorption and Coulomb explosion by clusters. The evolution of clusters is modeled with a relativistic time-dependent 3D Molecular Dynamics (MD) model [1]. The Coulomb interaction between particles is handled by a fast tree algorithm, which allows large number of particles to be used in simulations [2]. The time histories of all particles in a cluster are followed in time and space. The model accounts for ionization-ignition effects (enhancement of the laser field in the vicinity of ions) and a variety of elementary processes for free electrons and charged ions, such as optical field and collisional ionization, outer ionization and electron recapture. The MD model was applied to study small clusters (1-20 nm) irradiated by a high-intensity (10^16-10^20 W/cm^2) sub-picosecond laser pulse. We studied fundamental cluster features such as energy absorption, x-ray emission, particle distribution, average charge per atom, and cluster explosion as a function of initial cluster radius, laser peak intensity and wavelength. Simulations of novel applications, such as table-top nuclear fusion from exploding deuterium clusters [3] and high power synchrotron radiation for biological applications and imaging [4] have been performed. The application for nuclear fusion was motivated by the efficient absorption of laser energy (˜100%) and its high conversion efficiency into ion kinetic energy (˜50%), resulting in neutron yield of 10^6 neutrons/Joule laser energy. Contributors: J. Davis and A. L. Velikovich. [1] G. M. Petrov, et al Phys. Plasmas 12 063103 (2005); 13 033106 (2006) [2] G. M. Petrov, J. Davis, European Phys. J. D 41 629 (2007) [3] G. M. Petrov, J. Davis, A. L. Velikovich, Plasma Phys. Contr. Fusion 48 1721 (2006) [4] G. M. Petrov, J. Davis, A. L. Velikovich, J. Phys. B 39 4617 (2006)

Parallel Clustering Algorithm for Large-Scale Biological Data Sets

PubMed Central

Wang, Minchao; Zhang, Wu; Ding, Wang; Dai, Dongbo; Zhang, Huiran; Xie, Hao; Chen, Luonan; Guo, Yike; Xie, Jiang

2014-01-01

Backgrounds Recent explosion of biological data brings a great challenge for the traditional clustering algorithms. With increasing scale of data sets, much larger memory and longer runtime are required for the cluster identification problems. The affinity propagation algorithm outperforms many other classical clustering algorithms and is widely applied into the biological researches. However, the time and space complexity become a great bottleneck when handling the large-scale data sets. Moreover, the similarity matrix, whose constructing procedure takes long runtime, is required before running the affinity propagation algorithm, since the algorithm clusters data sets based on the similarities between data pairs. Methods Two types of parallel architectures are proposed in this paper to accelerate the similarity matrix constructing procedure and the affinity propagation algorithm. The memory-shared architecture is used to construct the similarity matrix, and the distributed system is taken for the affinity propagation algorithm, because of its large memory size and great computing capacity. An appropriate way of data partition and reduction is designed in our method, in order to minimize the global communication cost among processes. Result A speedup of 100 is gained with 128 cores. The runtime is reduced from serval hours to a few seconds, which indicates that parallel algorithm is capable of handling large-scale data sets effectively. The parallel affinity propagation also achieves a good performance when clustering large-scale gene data (microarray) and detecting families in large protein superfamilies. PMID:24705246

Robust continuous clustering

PubMed Central

Shah, Sohil Atul

2017-01-01

Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank. PMID:28851838

Quantum gravity as an information network self-organization of a 4D universe

NASA Astrophysics Data System (ADS)

Trugenberger, Carlo A.

2015-10-01

I propose a quantum gravity model in which the fundamental degrees of freedom are information bits for both discrete space-time points and links connecting them. The Hamiltonian is a very simple network model consisting of a ferromagnetic Ising model for space-time vertices and an antiferromagnetic Ising model for the links. As a result of the frustration between these two terms, the ground state self-organizes as a new type of low-clustering graph with finite Hausdorff dimension 4. The spectral dimension is lower than the Hausdorff dimension: it coincides with the Hausdorff dimension 4 at a first quantum phase transition corresponding to an IR fixed point, while at a second quantum phase transition describing small scales space-time dissolves into disordered information bits. The large-scale dimension 4 of the universe is related to the upper critical dimension 4 of the Ising model. At finite temperatures the universe graph emerges without a big bang and without singularities from a ferromagnetic phase transition in which space-time itself forms out of a hot soup of information bits. When the temperature is lowered the universe graph unfolds and expands by lowering its connectivity, a mechanism I have called topological expansion. The model admits topological black hole excitations corresponding to graphs containing holes with no space-time inside and with "Schwarzschild-like" horizons with a lower spectral dimension.

Strategy Generalization across Orientation Tasks: Testing a Computational Cognitive Model

DTIC Science & Technology

2008-07-01

arranged in groups ( clusters ). The space, itself, was divided into four quadrants, which had 1, 2, 3, and 4 objects, respectively. The arrangement of... clusters , of objects play an important role in the model’s performance, by providing some context for narrowing the search for the target to a portion of the...model uses a hierarchical approach to accomplish this. First, the model identifies a group or cluster of objects that contains the target. The number of

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

Universal clustering of dark matter in phase space

NASA Astrophysics Data System (ADS)

Zavala, Jesús; Afshordi, Niayesh

2016-03-01

We have recently introduced a novel statistical measure of dark matter clustering in phase space, the particle phase-space average density (P2SAD). In a two-paper series, we studied the structure of P2SAD in the Milky Way-size Aquarius haloes, constructed a physically motivated model to describe it, and illustrated its potential as a powerful tool to predict signals sensitive to the nanostructure of dark matter haloes. In this work, we report a remarkable universality of the clustering of dark matter in phase space as measured by P2SAD within the subhaloes of host haloes across different environments covering a range from dwarf-size to cluster-size haloes (1010-1015 M⊙). Simulations show that the universality of P2SAD holds for more than seven orders of magnitude, over a 2D phase space, covering over three orders of magnitude in distance/velocity, with a simple functional form that can be described by our model. Invoking the universality of P2SAD, we can accurately predict the non-linear power spectrum of dark matter at small scales all the way down to the decoupling mass limit of cold dark matter particles. As an application, we compute the subhalo boost to the annihilation of dark matter in a wide range of host halo masses.

Characterization of the temporal and spatial distribution and reproductive ratio of vesicular stomatitis outbreaks in Mexico in 2008.

PubMed

Arroyo, Montserrat; Perez, Andres M; Rodriguez, Luis L

2011-02-01

To characterize the temporal and spatial distribution and reproductive ratio of vesicular stomatitis (VS) outbreaks reported in Mexico in 2008. Bovine herds in Mexico in which VS outbreaks were officially reported and confirmed from January 1 through December 31, 2008. The Poisson model of the space-time scan statistic was used to identify periods and geographical locations at highest risk for VS in Mexico in 2008. The herd reproductive ratio (R(h)) of the epidemic was computed by use of the doubling-time method. 1 significant space-time cluster of VS was detected in the state of Michoacan from September 4 through December 10, 2008. The temporal extent of the VS outbreaks and the value and pattern of decrease of the R(h) were different in the endemic zone of Tabasco and Chiapas, compared with findings in the region included in the space-time cluster. The large number of VS outbreaks reported in Mexico in 2008 was associated with the spread of the disease from the endemic zone in southern Mexico to areas sporadically affected by the disease. Results suggested that implementation of a surveillance system in the endemic zone of Mexico aimed at early detection of changes in the value of R(h) and space-time clustering of the disease could help predict occurrence of future VS outbreaks originating from this endemic zone. This information will help prevent VS spread into regions of Mexico and neighboring countries that are only sporadically affected by the disease.

Soliton matter in the two-dimensional linear sigma model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dodd, L.R.; Lohe, M.A.; Rossi, M.

1987-10-01

We consider a one-dimensional model of nuclear matter where the quark clusters are described by solutions of the sigma model on a linear lattice in the self-consistent mean field approximation. Exact expressions are given for the baglike solutions confined to a finite interval, corresponding in the infinite interval limit to the free solitons previously found by Campbell and Liao. Periodic, self-consistent solutions which satisfy Bloch's theorem are constructed. Their energies and associated quark sigma field distributions are calculated numerically as functions of the baryon spacing, and compared with those of the uniform quark plasma. The predicted configuration of the groundmore » state depends critically on the assumed manner of filling the lowest band of quark single-particle levels, and on the density. In the absence of additional repulsive forces in the model, we find that the high density massless quark plasma is energetically favored and that there is a smooth transition from the baglike state to a uniform plasma with nonvanishing sigma field at comparatively large lattice constants 2dapprox. =10m/sub q//sup -1/ (m/sub q/ is the quark mass). If dilute filling of the entire band is employed, the clustered state is stable and a first order phase transition can occur for a range of much smaller lattice spacings 2dapprox. =4m/sub q//sup -1/. .AE« less

The Globular Cluster NGC 2419: A Crucible for Theories of Gravity

NASA Astrophysics Data System (ADS)

Ibata, R.; Sollima, A.; Nipoti, C.; Bellazzini, M.; Chapman, S. C.; Dalessandro, E.

2011-09-01

We present the analysis of a kinematic data set of stars in the globular cluster NGC 2419, taken with the DEep Imaging Multi-Object Spectrograph at the Keck II telescope. Combined with a reanalysis of deep Hubble Space Telescope and Subaru Telescope imaging data, which provide an accurate luminosity profile of the cluster, we investigate the validity of a large set of dynamical models of the system, which are checked for stability via N-body simulations. We find that isotropic models in either Newtonian or Modified Newtonian Dynamics (MOND) are ruled out with extremely high confidence. However, a simple Michie model in Newtonian gravity with anisotropic velocity dispersion provides an excellent representation of the luminosity profile and kinematics of the cluster. The anisotropy profiles of these models ensure an isotropic center to the cluster, which progresses to extreme radial anisotropy toward the outskirts. In contrast, with MOND we find that Michie models that reproduce the luminosity profile either overpredict the velocity dispersion on the outskirts of the cluster if the mass-to-light ratio (M/L) is kept at astrophysically motivated values or else they underpredict the central velocity dispersion if the M/L is taken to be very small. We find that the best Michie model in MOND is a factor of ~104 less likely than the Newtonian model that best fits the system. A likelihood ratio of 350 is found when we investigate more general models by solving the Jeans equation with a Markov Chain Monte Carlo scheme. We verified with N-body simulations that these results are not significantly different when the MOND external field effect is accounted for. If the assumptions that the cluster is in dynamical equilibrium, spherical, not on a peculiar orbit, and possesses a single dynamical tracer population of constant M/L are correct, we conclude that the present observations provide a very severe challenge for MOND. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation. This paper was also based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institute National des Sciences de l'Univers of the Centre National de la Recherche Scientifique of France, and the University of Hawaii.

Users matter : multi-agent systems model of high performance computing cluster users.

DOE Office of Scientific and Technical Information (OSTI.GOV)

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less

Active Optical Devices and Applications. Volume 228

DTIC Science & Technology

1980-04-01

Research Center, Minneapolis, Minnesota 55413 Abstract In this paper a control engineer’s point of view of the Large Space Structure (LSS) problem is...CASSIOPEIA SUPERNOVA REMNANT GALAXIES IN VIRGO CLUSTER QUASAR 3C273 CRAB PULSAR Figure 2. A collage of images of X-ray sources obtained with the HEAO...Telescope. Yet ST will not be able to study vari- able stars (primary distance indicators) to the Virgo cluster of galaxies and beyond. This cluster is

A Latent Class Multidimensional Scaling Model for Two-Way One-Mode Continuous Rating Dissimilarity Data

ERIC Educational Resources Information Center

Vera, J. Fernando; Macias, Rodrigo; Heiser, Willem J.

2009-01-01

In this paper, we propose a cluster-MDS model for two-way one-mode continuous rating dissimilarity data. The model aims at partitioning the objects into classes and simultaneously representing the cluster centers in a low-dimensional space. Under the normal distribution assumption, a latent class model is developed in terms of the set of…

"Non-cold" dark matter at small scales: a general approach

NASA Astrophysics Data System (ADS)

Murgia, R.; Merle, A.; Viel, M.; Totzauer, M.; Schneider, A.

2017-11-01

Structure formation at small cosmological scales provides an important frontier for dark matter (DM) research. Scenarios with small DM particle masses, large momenta or hidden interactions tend to suppress the gravitational clustering at small scales. The details of this suppression depend on the DM particle nature, allowing for a direct link between DM models and astrophysical observations. However, most of the astrophysical constraints obtained so far refer to a very specific shape of the power suppression, corresponding to thermal warm dark matter (WDM), i.e., candidates with a Fermi-Dirac or Bose-Einstein momentum distribution. In this work we introduce a new analytical fitting formula for the power spectrum, which is simple yet flexible enough to reproduce the clustering signal of large classes of non-thermal DM models, which are not at all adequately described by the oversimplified notion of WDM . We show that the formula is able to fully cover the parameter space of sterile neutrinos (whether resonantly produced or from particle decay), mixed cold and warm models, fuzzy dark matter, as well as other models suggested by effective theory of structure formation (ETHOS). Based on this fitting formula, we perform a large suite of N-body simulations and we extract important nonlinear statistics, such as the matter power spectrum and the halo mass function. Finally, we present first preliminary astrophysical constraints, based on linear theory, from both the number of Milky Way satellites and the Lyman-α forest. This paper is a first step towards a general and comprehensive modeling of small-scale departures from the standard cold DM model.

Testing gravity using large-scale redshift-space distortions

NASA Astrophysics Data System (ADS)

Raccanelli, Alvise; Bertacca, Daniele; Pietrobon, Davide; Schmidt, Fabian; Samushia, Lado; Bartolo, Nicola; Doré, Olivier; Matarrese, Sabino; Percival, Will J.

2013-11-01

We use luminous red galaxies from the Sloan Digital Sky Survey (SDSS) II to test the cosmological structure growth in two alternatives to the standard Λ cold dark matter (ΛCDM)+general relativity (GR) cosmological model. We compare observed three-dimensional clustering in SDSS Data Release 7 (DR7) with theoretical predictions for the standard vanilla ΛCDM+GR model, unified dark matter (UDM) cosmologies and the normal branch Dvali-Gabadadze-Porrati (nDGP). In computing the expected correlations in UDM cosmologies, we derive a parametrized formula for the growth factor in these models. For our analysis we apply the methodology tested in Raccanelli et al. and use the measurements of Samushia et al. that account for survey geometry, non-linear and wide-angle effects and the distribution of pair orientation. We show that the estimate of the growth rate is potentially degenerate with wide-angle effects, meaning that extremely accurate measurements of the growth rate on large scales will need to take such effects into account. We use measurements of the zeroth and second-order moments of the correlation function from SDSS DR7 data and the Large Suite of Dark Matter Simulations (LasDamas), and perform a likelihood analysis to constrain the parameters of the models. Using information on the clustering up to rmax = 120 h-1 Mpc, and after marginalizing over the bias, we find, for UDM models, a speed of sound c∞ ≤ 6.1e-4, and, for the nDGP model, a cross-over scale rc ≥ 340 Mpc, at 95 per cent confidence level.

Clustered Multi-Task Learning for Automatic Radar Target Recognition

PubMed Central

Li, Cong; Bao, Weimin; Xu, Luping; Zhang, Hua

2017-01-01

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms. PMID:28953267

Latent structure modeling underlying theophylline tablet formulations using a Bayesian network based on a self-organizing map clustering.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2015-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and design space. In this article, we integrate thin-plate spline (TPS) interpolation, Kohonen's self-organizing map (SOM) and a Bayesian network (BN) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared using a standard formulation. We measured the tensile strength and disintegration time as response variables and the compressibility, cohesion and dispersibility of the pretableting blend as latent variables. We predicted these variables quantitatively using nonlinear TPS, generated a large amount of data on pretableting blends and tablets and clustered these data into several clusters using a SOM. Our results show that we are able to predict the experimental values of the latent and response variables with a high degree of accuracy and are able to classify the tablet data into several distinct clusters. In addition, to visualize the latent structure between the causal and latent factors and the response variables, we applied a BN method to the SOM clustering results. We found that despite having inserted latent variables between the causal factors and response variables, their relation is equivalent to the results for the SOM clustering, and thus we are able to explain the underlying latent structure. Consequently, this technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulation.

Hierarchical trie packet classification algorithm based on expectation-maximization clustering.

PubMed

Bi, Xia-An; Zhao, Junxia

2017-01-01

With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm.

The Ongoing Assembly of a Central Cluster Galaxy: Phase-space Substructures in the Halo of M87

NASA Astrophysics Data System (ADS)

Romanowsky, Aaron J.; Strader, Jay; Brodie, Jean P.; Mihos, J. Christopher; Spitler, Lee R.; Forbes, Duncan A.; Foster, Caroline; Arnold, Jacob A.

2012-03-01

The halos of galaxies preserve unique records of their formation histories. We carry out the first combined observational and theoretical study of phase-space halo substructure in an early-type galaxy: M87, the central galaxy in the Virgo cluster. We analyze an unprecedented wide-field, high-precision photometric and spectroscopic data set for 488 globular clusters (GCs), which includes new, large-radius Subaru/Suprime-Cam and Keck/DEIMOS observations. We find signatures of two substructures in position-velocity phase space. One is a small, cold stream associated with a known stellar filament in the outer halo; the other is a large shell-like pattern in the inner halo that implies a massive, hitherto unrecognized accretion event. We perform extensive statistical tests and independent metallicity analyses to verify the presence and characterize the properties of these features, and to provide more general methodologies for future extragalactic studies of phase-space substructure. The cold outer stream is consistent with a dwarf galaxy accretion event, while for the inner shell there is tension between a low progenitor mass implied by the cold velocity dispersion, and a high mass from the large number of GCs, which might be resolved by a ~0.5 L* E/S0 progenitor. We also carry out proof-of-principle numerical simulations of the accretion of smaller galaxies in an M87-like gravitational potential. These produce analogous features to the observed substructures, which should have observable lifetimes of ~1 Gyr. The shell and stream GCs together support a scenario where the extended stellar envelope of M87 has been built up by a steady rain of material that continues until the present day. This phase-space method demonstrates unique potential for detailed tests of galaxy formation beyond the Local Group.

Fragmentation scaling of percolation clusters in two and three dimensions: Large-cell Monte Carlo RG approach

NASA Astrophysics Data System (ADS)

Cheon, M.; Chang, I.

1999-04-01

The scaling behavior for a binary fragmentation of critical percolation clusters is investigated by a large-cell Monte Carlo real-space renormalization group method in two and three dimensions. We obtain accurate values of critical exponents λ and phi describing the scaling of fragmentation rate and the distribution of fragments' masses produced by a binary fragmentation. Our results for λ and phi show that the fragmentation rate is proportional to the size of mother cluster, and the scaling relation σ = 1 + λ - phi conjectured by Edwards et al. to be valid for all dimensions is satisfied in two and three dimensions, where σ is the crossover exponent of the average cluster number in percolation theory, which excludes the other scaling relations.

Configurational coupled cluster approach with applications to magnetic model systems

NASA Astrophysics Data System (ADS)

Wu, Siyuan; Nooijen, Marcel

2018-05-01

A general exponential, coupled cluster like, approach is discussed to extract an effective Hamiltonian in configurational space, as a sum of 1-body, 2-body up to n-body operators. The simplest two-body approach is illustrated by calculations on simple magnetic model systems. A key feature of the approach is that equations up to a certain rank do not depend on higher body cluster operators.

Atmospheric considerations regarding the impact of heat dissipation from a nuclear energy center

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rotty, R.M.; Bauman, H.; Bennett, L.L.

1976-05-01

Potential changes in climate resulting from a large nuclear energy center are discussed. On a global scale, no noticeable changes are likely, but on both a regional and a local scale, changes can be expected. Depending on the cooling system employed, the amount of fog may increase, the amount and distribution of precipitation will change, and the frequency or location of severe storms may change. Very large heat releases over small surface areas can result in greater atmospheric instability; a large number of closely spaced natural-draft cooling towers have this disadvantage. On the other hand, employment of natural-draft towers makesmore » an increase in the occurrence of ground fog unlikely. The analysis suggests that the cooling towers for a large nuclear energy center should be located in clusters of four with at least 2.5-mile spacing between the clusters. This is equivalent to the requirement of one acre of land surface per each two megawatts of heat being rejected.« less

Assessment and Requirements of Nuclear Reaction Databases for GCR Transport in the Atmosphere and Structures

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Wilson, J. W.; Shinn, J. L.; Tripathi, R. K.

1998-01-01

The transport properties of galactic cosmic rays (GCR) in the atmosphere, material structures, and human body (self-shielding) am of interest in risk assessment for supersonic and subsonic aircraft and for space travel in low-Earth orbit and on interplanetary missions. Nuclear reactions, such as knockout and fragmentation, present large modifications of particle type and energies of the galactic cosmic rays in penetrating materials. We make an assessment of the current nuclear reaction models and improvements in these model for developing required transport code data bases. A new fragmentation data base (QMSFRG) based on microscopic models is compared to the NUCFRG2 model and implications for shield assessment made using the HZETRN radiation transport code. For deep penetration problems, the build-up of light particles, such as nucleons, light clusters and mesons from nuclear reactions in conjunction with the absorption of the heavy ions, leads to the dominance of the charge Z = 0, 1, and 2 hadrons in the exposures at large penetration depths. Light particles are produced through nuclear or cluster knockout and in evaporation events with characteristically distinct spectra which play unique roles in the build-up of secondary radiation's in shielding. We describe models of light particle production in nucleon and heavy ion induced reactions and make an assessment of the importance of light particle multiplicity and spectral parameters in these exposures.

Data Management as a Cluster Middleware Centerpiece

NASA Technical Reports Server (NTRS)

Zero, Jose; McNab, David; Sawyer, William; Cheung, Samson; Duffy, Daniel; Rood, Richard; Webster, Phil; Palm, Nancy; Salmon, Ellen; Schardt, Tom

2004-01-01

Through earth and space modeling and the ongoing launches of satellites to gather data, NASA has become one of the largest producers of data in the world. These large data sets necessitated the creation of a Data Management System (DMS) to assist both the users and the administrators of the data. Halcyon Systems Inc. was contracted by the NASA Center for Computational Sciences (NCCS) to produce a Data Management System. The prototype of the DMS was produced by Halcyon Systems Inc. (Halcyon) for the Global Modeling and Assimilation Office (GMAO). The system, which was implemented and deployed within a relatively short period of time, has proven to be highly reliable and deployable. Following the prototype deployment, Halcyon was contacted by the NCCS to produce a production DMS version for their user community. The system is composed of several existing open source or government-sponsored components such as the San Diego Supercomputer Center s (SDSC) Storage Resource Broker (SRB), the Distributed Oceanographic Data System (DODS), and other components. Since Data Management is one of the foremost problems in cluster computing, the final package not only extends its capabilities as a Data Management System, but also to a cluster management system. This Cluster/Data Management System (CDMS) can be envisioned as the integration of existing packages.

Quantitative properties of clustering within modern microscopic nuclear models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Volya, A.; Tchuvil’sky, Yu. M., E-mail: tchuvl@nucl-th.sinp.msu.ru

2016-09-15

A method for studying cluster spectroscopic properties of nuclear fragmentation, such as spectroscopic amplitudes, cluster form factors, and spectroscopic factors, is developed on the basis of modern precision nuclear models that take into account the mixing of large-scale shell-model configurations. Alpha-cluster channels are considered as an example. A mathematical proof of the need for taking into account the channel-wave-function renormalization generated by exchange terms of the antisymmetrization operator (Fliessbach effect) is given. Examples where this effect is confirmed by a high quality of the description of experimental data are presented. By and large, the method in question extends substantially themore » possibilities for studying clustering phenomena in nuclei and for improving the quality of their description.« less

What drives the evolution of Luminous Compact Blue Galaxies in Clusters vs. the Field?

NASA Astrophysics Data System (ADS)

Wirth, Gregory D.; Bershady, Matthew A.; Crawford, Steven M.; Hunt, Lucas; Pisano, Daniel J.; Randriamampandry, Solohery M.

2018-06-01

Low-mass dwarf ellipticals are the most numerous members of present-day galaxy clusters, but the progenitors of this dominant population remain unclear. A prime candidate is the class of objects known as Luminous Compact Blue Galaxies (LCBGs), common in intermediate-redshift clusters but virtually extinct today. Recent cosmological simulations suggest that present-day dwarf galaxies begin as irregular field galaxies, undergo an environmentally-driven starburst phase as they enter the cluster, and stop forming stars earlier than their counterparts in the field. This model predicts that cluster dwarfs should have lower stellar mass per unit dynamical mass than their counterparts in the field. We are undertaking a two-pronged archival research program to test this key prediction using the combination of precision photometry from space and high-quality spectroscopy. First, we are combining optical HST/ACS imaging of five z=0.55 clusters (including two HST Frontier Fields) with Spitzer IR imaging and publicly-released Keck/DEIMOS spectroscopy to measure stellar-to-dynamical-mass ratios for a large sample of cluster LCBGs. Second, we are exploiting a new catalog of LCBGs in the COSMOS field to gather corresponding data for a significant sample of field LCBGs. By comparing mass ratios from these datasets, we aim to test theoretical predictions and determine the primary physical driver of cluster dwarf-galaxy evolution.

Gamma-ray Emission from Globular Clusters

NASA Astrophysics Data System (ADS)

Tam, Pak-Hin T.; Hui, Chung Y.; Kong, Albert K. H.

2016-03-01

Over the last few years, the data obtained using the Large Area Telescope (LAT) aboard the Fermi Gamma-ray Space Telescope has provided new insights on high-energy processes in globular clusters, particularly those involving compact objects such as MilliSecond Pulsars (MSPs). Gamma-ray emission in the 100 MeV to 10 GeV range has been detected from more than a dozen globular clusters in our galaxy, including 47 Tucanae and Terzan 5. Based on a sample of known gammaray globular clusters, the empirical relations between gamma-ray luminosity and properties of globular clusters such as their stellar encounter rate, metallicity, and possible optical and infrared photon energy densities, have been derived. The measured gamma-ray spectra are generally described by a power law with a cut-off at a few gigaelectronvolts. Together with the detection of pulsed γ-rays from two MSPs in two different globular clusters, such spectral signature lends support to the hypothesis that γ-rays from globular clusters represent collective curvature emission from magnetospheres of MSPs in the clusters. Alternative models, involving Inverse-Compton (IC) emission of relativistic electrons that are accelerated close to MSPs or pulsar wind nebula shocks, have also been suggested. Observations at >100 GeV by using Fermi/LAT and atmospheric Cherenkov telescopes such as H.E.S.S.-II, MAGIC-II, VERITAS, and CTA will help to settle some questions unanswered by current data.

THE DYNAMICS OF MERGING CLUSTERS: A MONTE CARLO SOLUTION APPLIED TO THE BULLET AND MUSKET BALL CLUSTERS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dawson, William A., E-mail: wadawson@ucdavis.edu

2013-08-01

Merging galaxy clusters have become one of the most important probes of dark matter, providing evidence for dark matter over modified gravity and even constraints on the dark matter self-interaction cross-section. To properly constrain the dark matter cross-section it is necessary to understand the dynamics of the merger, as the inferred cross-section is a function of both the velocity of the collision and the observed time since collision. While the best understanding of merging system dynamics comes from N-body simulations, these are computationally intensive and often explore only a limited volume of the merger phase space allowed by observed parametermore » uncertainty. Simple analytic models exist but the assumptions of these methods invalidate their results near the collision time, plus error propagation of the highly correlated merger parameters is unfeasible. To address these weaknesses I develop a Monte Carlo method to discern the properties of dissociative mergers and propagate the uncertainty of the measured cluster parameters in an accurate and Bayesian manner. I introduce this method, verify it against an existing hydrodynamic N-body simulation, and apply it to two known dissociative mergers: 1ES 0657-558 (Bullet Cluster) and DLSCL J0916.2+2951 (Musket Ball Cluster). I find that this method surpasses existing analytic models-providing accurate (10% level) dynamic parameter and uncertainty estimates throughout the merger history. This, coupled with minimal required a priori information (subcluster mass, redshift, and projected separation) and relatively fast computation ({approx}6 CPU hours), makes this method ideal for large samples of dissociative merging clusters.« less

The Grism Lens-Amplified Survey from Space (GLASS). V. Extent and Spatial Distribution of Star Formation in z ~ 0.5 Cluster Galaxies

NASA Astrophysics Data System (ADS)

Vulcani, Benedetta; Treu, Tommaso; Schmidt, Kasper B.; Poggianti, Bianca M.; Dressler, Alan; Fontana, Adriano; Bradač, Marusa; Brammer, Gabriel B.; Hoag, Austin; Huang, Kuan-Han; Malkan, Matthew; Pentericci, Laura; Trenti, Michele; von der Linden, Anja; Abramson, Louis; He, Julie; Morris, Glenn

2015-12-01

We present the first study of the spatial distribution of star formation in z ˜ 0.5 cluster galaxies. The analysis is based on data taken with the Wide Field Camera 3 as part of the Grism Lens-Amplified Survey from Space (GLASS). We illustrate the methodology by focusing on two clusters (MACS 0717.5+3745 and MACS 1423.8+2404) with different morphologies (one relaxed and one merging) and use foreground and background galaxies as a field control sample. The cluster+field sample consists of 42 galaxies with stellar masses in the range 108-1011 M⊙ and star formation rates in the range 1-20 M⊙ yr-1. Both in clusters and in the field, Hα is more extended than the rest-frame UV continuum in 60% of the cases, consistent with diffuse star formation and inside-out growth. In ˜20% of the cases, the Hα emission appears more extended in cluster galaxies than in the field, pointing perhaps to ionized gas being stripped and/or star formation being enhanced at large radii. The peak of the Hα emission and that of the continuum are offset by less than 1 kpc. We investigate trends with the hot gas density as traced by the X-ray emission, and with the surface mass density as inferred from gravitational lens models, and find no conclusive results. The diversity of morphologies and sizes observed in Hα illustrates the complexity of the environmental processes that regulate star formation. Upcoming analysis of the full GLASS data set will increase our sample size by almost an order of magnitude, verifying and strengthening the inference from this initial data set.

Discovery of a Large-Scale Filament Connected to the Massive Galaxy Cluster MACS J0717.5+3745 at z=0.551,

NASA Astrophysics Data System (ADS)

Ebeling, H.; Barrett, E.; Donovan, D.

2004-07-01

We report the detection of a 4 h-170 Mpc long large-scale filament leading into the massive galaxy cluster MACS J0717.5+3745. The extent of this object well beyond the cluster's nominal virial radius (~2.3 Mpc) rules out prior interaction between its constituent galaxies and the cluster and makes it a prime candidate for a genuine filament as opposed to a merger remnant or a double cluster. The structure was discovered as a pronounced overdensity of galaxies selected to have V-R colors close to the cluster red sequence. Extensive spectroscopic follow-up of over 300 of these galaxies in a region covering the filament and the cluster confirms that the entire structure is located at the cluster redshift of z=0.545. Featuring galaxy surface densities of typically 15 Mpc-2 down to luminosities of 0.13L*V, the most diffuse parts of the filament are comparable in density to the clumps of red galaxies found around A851 in the only similar study carried out to date (Kodama et al.). Our direct detection of an extended large-scale filament funneling matter onto a massive distant cluster provides a superb target for in-depth studies of the evolution of galaxies in environments of greatly varying density and supports the predictions from theoretical models and numerical simulations of structure formation in a hierarchical picture. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The observatory was made possible by the generous financial support of the W. M. Keck Foundation. Based partly on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (US), the Particle Physics and Astronomy Research Council (UK), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), CNP (Brazil), and CONICET (Argentina).

The Gaussian streaming model and convolution Lagrangian effective field theory

DOE PAGES

Vlah, Zvonimir; Castorina, Emanuele; White, Martin

2016-12-05

We update the ingredients of the Gaussian streaming model (GSM) for the redshift-space clustering of biased tracers using the techniques of Lagrangian perturbation theory, effective field theory (EFT) and a generalized Lagrangian bias expansion. After relating the GSM to the cumulant expansion, we present new results for the real-space correlation function, mean pairwise velocity and pairwise velocity dispersion including counter terms from EFT and bias terms through third order in the linear density, its leading derivatives and its shear up to second order. We discuss the connection to the Gaussian peaks formalism. We compare the ingredients of the GSM tomore » a suite of large N-body simulations, and show the performance of the theory on the low order multipoles of the redshift-space correlation function and power spectrum. We highlight the importance of a general biasing scheme, which we find to be as important as higher-order corrections due to non-linear evolution for the halos we consider on the scales of interest to us.« less

The Gaussian streaming model and convolution Lagrangian effective field theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vlah, Zvonimir; Castorina, Emanuele; White, Martin, E-mail: zvlah@stanford.edu, E-mail: ecastorina@berkeley.edu, E-mail: mwhite@berkeley.edu

We update the ingredients of the Gaussian streaming model (GSM) for the redshift-space clustering of biased tracers using the techniques of Lagrangian perturbation theory, effective field theory (EFT) and a generalized Lagrangian bias expansion. After relating the GSM to the cumulant expansion, we present new results for the real-space correlation function, mean pairwise velocity and pairwise velocity dispersion including counter terms from EFT and bias terms through third order in the linear density, its leading derivatives and its shear up to second order. We discuss the connection to the Gaussian peaks formalism. We compare the ingredients of the GSM tomore » a suite of large N-body simulations, and show the performance of the theory on the low order multipoles of the redshift-space correlation function and power spectrum. We highlight the importance of a general biasing scheme, which we find to be as important as higher-order corrections due to non-linear evolution for the halos we consider on the scales of interest to us.« less

The Hubble Space Telescope Frontier Fields Program

NASA Astrophysics Data System (ADS)

Koekemoer, Anton M.; Mack, Jennifer; Lotz, Jennifer M.; Borncamp, David; Khandrika, Harish G.; Lucas, Ray A.; Martlin, Catherine; Porterfield, Blair; Sunnquist, Ben; Anderson, Jay; Avila, Roberto J.; Barker, Elizabeth A.; Grogin, Norman A.; Gunning, Heather C.; Hilbert, Bryan; Ogaz, Sara; Robberto, Massimo; Sembach, Kenneth; Flanagan, Kathryn; Mountain, Matt

2017-08-01

The Hubble Space Telescope Frontier Fields program is a large Director's Discretionary program of 840 orbits, to obtain ultra-deep observations of six strong lensing clusters of galaxies, together with parallel deep blank fields, making use of the strong lensing amplification by these clusters of distant background galaxies to detect the faintest galaxies currently observable in the high-redshift universe. The entire program has now completed successfully for all 6 clusters, namely Abell 2744, Abell S1063, Abell 370, MACS J0416.1-2403, MACS J0717.5+3745 and MACS J1149.5+2223,. Each of these was observed over two epochs, to a total depth of 140 orbits on the main cluster and an associated parallel field, obtaining images in ACS (F435W, F606W, F814W) and WFC3/IR (F105W, F125W, F140W, F160W) on both the main cluster and the parallel field in all cases. Full sets of high-level science products have been generated for all these clusters by the team at STScI, including cumulative-depth data releases during each epoch, as well as full-depth releases after the completion of each epoch. These products include all the full-depth distortion-corrected drizzled mosaics and associated products for each cluster, which are science-ready to facilitate the construction of lensing models as well as enabling a wide range of other science projects. Many improvements beyond default calibration for ACS and WFC3/IR are implemented in these data products, including corrections for persistence, time-variable sky, and low-level dark current residuals, as well as improvements in astrometric alignment to achieve milliarcsecond-level accuracy. The full set of resulting high-level science products and mosaics are publicly delivered to the community via the Mikulski Archive for Space Telescopes (MAST) to enable the widest scientific use of these data, as well as ensuring a public legacy dataset of the highest possible quality that is of lasting value to the entire community.

Precise strong lensing mass profile of the CLASH galaxy cluster MACS 2129

NASA Astrophysics Data System (ADS)

Monna, A.; Seitz, S.; Balestra, I.; Rosati, P.; Grillo, C.; Halkola, A.; Suyu, S. H.; Coe, D.; Caminha, G. B.; Frye, B.; Koekemoer, A.; Mercurio, A.; Nonino, M.; Postman, M.; Zitrin, A.

2017-04-01

We present a detailed strong lensing (SL) mass reconstruction of the core of the galaxy cluster MACS J2129.4-0741 (zcl = 0.589) obtained by combining high-resolution Hubble Space Telescope photometry from the CLASH (Cluster Lensing And Supernovae survey with Hubble) survey with new spectroscopic observations from the CLASH-VLT (Very Large Telescope) survey. A background bright red passive galaxy at zsp = 1.36, sextuply lensed in the cluster core, has four radial lensed images located over the three central cluster members. Further 19 background lensed galaxies are spectroscopically confirmed by our VLT survey, including 3 additional multiple systems. A total of 31 multiple images are used in the lensing analysis. This allows us to trace with high precision the total mass profile of the cluster in its very inner region (R < 100 kpc). Our final lensing mass model reproduces the multiple images systems identified in the cluster core with high accuracy of 0.4 arcsec. This translates to a high-precision mass reconstruction of MACS 2129, which is constrained at a level of 2 per cent. The cluster has Einstein parameter ΘE = (29 ± 4) arcsec and a projected total mass of Mtot(<ΘE) = (1.35 ± 0.03) × 1014 M⊙ within such radius. Together with the cluster mass profile, we provide here also the complete spectroscopic data set for the cluster members and lensed images measured with VLT/Visible Multi-Object Spectrograph within the CLASH-VLT survey.

Flow currents and ventilation in Langstroth beehives due to brood thermoregulation efforts of honeybees.

PubMed

Sudarsan, Rangarajan; Thompson, Cody; Kevan, Peter G; Eberl, Hermann J

2012-02-21

Beekeepers universally agree that ensuring sufficient ventilation is vital for sustaining a thriving, healthy honeybee colony. Despite this fact, surprisingly little is known about the ventilation and flow patterns in bee hives. We take a first step towards developing a model-based approach that uses computational fluid dynamics to simulate natural ventilation flow inside a standard Langstroth beehive. A 3-D model of a Langstroth beehive with one brood chamber and one honey super was constructed and inside it the honeybee colony was distributed among different clusters each occupying the different bee-spaces between frames in the brood chamber. For the purpose of modeling, each honeybee cluster was treated as an air-saturated porous medium with constant porosity. Heat and mass transfer interactions of the honeybees with the air, the outcome of metabolism, were captured in the porous medium model as source and sink terms appearing in the governing equations of fluid dynamics. The temperature of the brood that results from the thermoregulation efforts of the colony is applied as a boundary condition for the governing equations. The governing equations for heat, mass transport and fluid flow were solved using Fluent(©), a commercially available CFD program. The results from the simulations indicate that (a) both heat and mass transfer resulting from honeybee metabolism play a vital role in determining the structure of the flow inside the beehive and mass transfer cannot be neglected, (b) at low ambient temperatures, the nonuniform temperature profile on comb surfaces that results from brood incubation enhances flow through the honeybee cluster which removes much of the carbon-dioxide produced by the cluster resulting in lower carbon-dioxide concentration next to the brood, (c) increasing ambient (outside) air temperature causes ventilation flow rate to drop resulting in weaker flow inside the beehive. Flow visualization indicates that at low ambient air temperatures the flow inside the beehive has an interesting 3-D structure with the presence of large recirculating vortices occupying the space between honey super frames above the honeybee clusters in the brood chamber and the structure and strength of the flow inside and around the honeybee clusters changes as we increase the ambient air temperature outside the beehive. Copyright © 2011 Elsevier Ltd. All rights reserved.

Cloud-enabled large-scale land surface model simulations with the NASA Land Information System

NASA Astrophysics Data System (ADS)

Duffy, D.; Vaughan, G.; Clark, M. P.; Peters-Lidard, C. D.; Nijssen, B.; Nearing, G. S.; Rheingrover, S.; Kumar, S.; Geiger, J. V.

2017-12-01

Developed by the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center (GSFC), the Land Information System (LIS) is a high-performance software framework for terrestrial hydrology modeling and data assimilation. LIS provides the ability to integrate satellite and ground-based observational products and advanced modeling algorithms to extract land surface states and fluxes. Through a partnership with the National Center for Atmospheric Research (NCAR) and the University of Washington, the LIS model is currently being extended to include the Structure for Unifying Multiple Modeling Alternatives (SUMMA). With the addition of SUMMA in LIS, meaningful simulations containing a large multi-model ensemble will be enabled and can provide advanced probabilistic continental-domain modeling capabilities at spatial scales relevant for water managers. The resulting LIS/SUMMA application framework is difficult for non-experts to install due to the large amount of dependencies on specific versions of operating systems, libraries, and compilers. This has created a significant barrier to entry for domain scientists that are interested in using the software on their own systems or in the cloud. In addition, the requirement to support multiple run time environments across the LIS community has created a significant burden on the NASA team. To overcome these challenges, LIS/SUMMA has been deployed using Linux containers, which allows for an entire software package along with all dependences to be installed within a working runtime environment, and Kubernetes, which orchestrates the deployment of a cluster of containers. Within a cloud environment, users can now easily create a cluster of virtual machines and run large-scale LIS/SUMMA simulations. Installations that have taken weeks and months can now be performed in minutes of time. This presentation will discuss the steps required to create a cloud-enabled large-scale simulation, present examples of its use, and describe the potential deployment of this information technology with other NASA applications.

A History of H I Stripping in Virgo: A Phase-space View of VIVA Galaxies

NASA Astrophysics Data System (ADS)

Yoon, Hyein; Chung, Aeree; Smith, Rory; Jaffé, Yara L.

2017-04-01

We investigate the orbital histories of Virgo galaxies at various stages of H I gas stripping. In particular, we compare the location of galaxies with different H I morphology in phase space. This method is a great tool for tracing the gas stripping histories of galaxies as they fall into the cluster. Most galaxies at the early stage of H I stripping are found in the first infall region of Virgo, while galaxies undergoing active H I stripping mostly appear to be falling in or moving out near the cluster core for the first time. Galaxies with severely stripped, yet symmetric, H I disks are found in one of two locations. Some are deep inside the cluster, but others are found in the cluster outskirts with low orbital velocities. We suggest that the latter group of galaxies belong to a “backsplash” population. These present the clearest candidates for backsplashed galaxies observationally identified to date. We further investigate the distribution of a large sample of H I-detected galaxies toward Virgo in phase space, confirming that most galaxies are stripped of their gas as they settle into the gravitational potential of the cluster. In addition, we discuss the impact of tidal interactions between galaxies and group preprocessing on the H I properties of the cluster galaxies, and link the associated star formation evolution to the stripping sequence of cluster galaxies.

ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution

PubMed Central

Kurkcuoglu, Zeynep; Bahar, Ivet; Doruker, Pemra

2016-01-01

Accurate sampling of conformational space and, in particular, the transitions between functional substates has been a challenge in molecular dynamic (MD) simulations of large biomolecular systems. We developed an Elastic Network Model (ENM)-based computational method, ClustENM, for sampling large conformational changes of biomolecules with various sizes and oligomerization states. ClustENM is an iterative method that combines ENM with energy minimization and clustering steps. It is an unbiased technique, which requires only an initial structure as input, and no information about the target conformation. To test the performance of ClustENM, we applied it to six biomolecular systems: adenylate kinase (AK), calmodulin, p38 MAP kinase, HIV-1 reverse transcriptase (RT), triosephosphate isomerase (TIM), and the 70S ribosomal complex. The generated ensembles of conformers determined at atomic resolution show good agreement with experimental data (979 structures resolved by X-ray and/or NMR) and encompass the subspaces covered in independent MD simulations for TIM, p38, and RT. ClustENM emerges as a computationally efficient tool for characterizing the conformational space of large systems at atomic detail, in addition to generating a representative ensemble of conformers that can be advantageously used in simulating substrate/ligand-binding events. PMID:27494296

Parallelized traveling cluster approximation to study numerically spin-fermion models on large lattices

NASA Astrophysics Data System (ADS)

Mukherjee, Anamitra; Patel, Niravkumar D.; Bishop, Chris; Dagotto, Elbio

2015-06-01

Lattice spin-fermion models are important to study correlated systems where quantum dynamics allows for a separation between slow and fast degrees of freedom. The fast degrees of freedom are treated quantum mechanically while the slow variables, generically referred to as the "spins," are treated classically. At present, exact diagonalization coupled with classical Monte Carlo (ED + MC) is extensively used to solve numerically a general class of lattice spin-fermion problems. In this common setup, the classical variables (spins) are treated via the standard MC method while the fermion problem is solved by exact diagonalization. The "traveling cluster approximation" (TCA) is a real space variant of the ED + MC method that allows to solve spin-fermion problems on lattice sizes with up to 103 sites. In this publication, we present a novel reorganization of the TCA algorithm in a manner that can be efficiently parallelized. This allows us to solve generic spin-fermion models easily on 104 lattice sites and with some effort on 105 lattice sites, representing the record lattice sizes studied for this family of models.

Cost-effective description of strong correlation: Efficient implementations of the perfect quadruples and perfect hextuples models

DOE PAGES

Lehtola, Susi; Parkhill, John; Head-Gordon, Martin

2016-10-07

Novel implementations based on dense tensor storage are presented here for the singlet-reference perfect quadruples (PQ) [J. A. Parkhill et al., J. Chem. Phys. 130, 084101 (2009)] and perfect hextuples (PH) [J. A. Parkhill and M. Head-Gordon, J. Chem. Phys. 133, 024103 (2010)] models. The methods are obtained as block decompositions of conventional coupled-cluster theory that are exact for four electrons in four orbitals (PQ) and six electrons in six orbitals (PH), but that can also be applied to much larger systems. PQ and PH have storage requirements that scale as the square, and as the cube of the numbermore » of active electrons, respectively, and exhibit quartic scaling of the computational effort for large systems. Applications of the new implementations are presented for full-valence calculations on linear polyenes (C nH n+2), which highlight the excellent computational scaling of the present implementations that can routinely handle active spaces of hundreds of electrons. The accuracy of the models is studied in the π space of the polyenes, in hydrogen chains (H 50), and in the π space of polyacene molecules. In all cases, the results compare favorably to density matrix renormalization group values. With the novel implementation of PQ, active spaces of 140 electrons in 140 orbitals can be solved in a matter of minutes on a single core workstation, and the relatively low polynomial scaling means that very large systems are also accessible using parallel computing.« less

Cost-effective description of strong correlation: Efficient implementations of the perfect quadruples and perfect hextuples models

NASA Astrophysics Data System (ADS)

Lehtola, Susi; Parkhill, John; Head-Gordon, Martin

2016-10-01

Novel implementations based on dense tensor storage are presented for the singlet-reference perfect quadruples (PQ) [J. A. Parkhill et al., J. Chem. Phys. 130, 084101 (2009)] and perfect hextuples (PH) [J. A. Parkhill and M. Head-Gordon, J. Chem. Phys. 133, 024103 (2010)] models. The methods are obtained as block decompositions of conventional coupled-cluster theory that are exact for four electrons in four orbitals (PQ) and six electrons in six orbitals (PH), but that can also be applied to much larger systems. PQ and PH have storage requirements that scale as the square, and as the cube of the number of active electrons, respectively, and exhibit quartic scaling of the computational effort for large systems. Applications of the new implementations are presented for full-valence calculations on linear polyenes (CnHn+2), which highlight the excellent computational scaling of the present implementations that can routinely handle active spaces of hundreds of electrons. The accuracy of the models is studied in the π space of the polyenes, in hydrogen chains (H50), and in the π space of polyacene molecules. In all cases, the results compare favorably to density matrix renormalization group values. With the novel implementation of PQ, active spaces of 140 electrons in 140 orbitals can be solved in a matter of minutes on a single core workstation, and the relatively low polynomial scaling means that very large systems are also accessible using parallel computing.

Quantifying opening-mode fracture spatial organization in horizontal wellbore image logs, core and outcrop: Application to Upper Cretaceous Frontier Formation tight gas sandstones, USA

NASA Astrophysics Data System (ADS)

Li, J. Z.; Laubach, S. E.; Gale, J. F. W.; Marrett, R. A.

2018-03-01

The Upper Cretaceous Frontier Formation is a naturally fractured gas-producing sandstone in Wyoming. Regionally, random and statistically more clustered than random patterns exist in the same upper to lower shoreface depositional facies. East-west- and north-south-striking regional fractures sampled using image logs and cores from three horizontal wells exhibit clustered patterns, whereas data collected from east-west-striking fractures in outcrop have patterns that are indistinguishable from random. Image log data analyzed with the correlation count method shows clusters ∼35 m wide and spaced ∼50 to 90 m apart as well as clusters up to 12 m wide with periodic inter-cluster spacings. A hierarchy of cluster sizes exists; organization within clusters is likely fractal. These rocks have markedly different structural and burial histories, so regional differences in degree of clustering are unsurprising. Clustered patterns correspond to fractures having core quartz deposition contemporaneous with fracture opening, circumstances that some models suggest might affect spacing patterns by interfering with fracture growth. Our results show that quantifying and identifying patterns as statistically more or less clustered than random delineates differences in fracture patterns that are not otherwise apparent but that may influence gas and water production, and therefore may be economically important.

Cellular packing, mechanical stress and the evolution of multicellularity

NASA Astrophysics Data System (ADS)

Jacobeen, Shane; Pentz, Jennifer T.; Graba, Elyes C.; Brandys, Colin G.; Ratcliff, William C.; Yunker, Peter J.

2018-03-01

The evolution of multicellularity set the stage for sustained increases in organismal complexity1-5. However, a fundamental aspect of this transition remains largely unknown: how do simple clusters of cells evolve increased size when confronted by forces capable of breaking intracellular bonds? Here we show that multicellular snowflake yeast clusters6-8 fracture due to crowding-induced mechanical stress. Over seven weeks ( 291 generations) of daily selection for large size, snowflake clusters evolve to increase their radius 1.7-fold by reducing the accumulation of internal stress. During this period, cells within the clusters evolve to be more elongated, concomitant with a decrease in the cellular volume fraction of the clusters. The associated increase in free space reduces the internal stress caused by cellular growth, thus delaying fracture and increasing cluster size. This work demonstrates how readily natural selection finds simple, physical solutions to spatial constraints that limit the evolution of group size—a fundamental step in the evolution of multicellularity.

Space-Time Analysis of Testicular Cancer Clusters Using Residential Histories: A Case-Control Study in Denmark

PubMed Central

Sloan, Chantel D.; Nordsborg, Rikke B.; Jacquez, Geoffrey M.; Raaschou-Nielsen, Ole; Meliker, Jaymie R.

2015-01-01

Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population. PMID:25756204

Space-time analysis of testicular cancer clusters using residential histories: a case-control study in Denmark.

PubMed

Sloan, Chantel D; Nordsborg, Rikke B; Jacquez, Geoffrey M; Raaschou-Nielsen, Ole; Meliker, Jaymie R

2015-01-01

Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population.

Structural and electronic properties for atomic clusters

NASA Astrophysics Data System (ADS)

Sun, Yan

We have studied the structural and electronic properties for different groups of atomic clusters by doing a global search on the potential energy surface using the Taboo Search in Descriptors Space (TSDS) method and calculating the energies with Kohn-Sham Density Functional Theory (KS-DFT). Our goal was to find the structural and electronic principles for predicting the structure and stability of clusters. For Ben (n = 3--20), we have found that the evolution of geometric and electronic properties with size reflects a change in the nature of the bonding from van der Waals to metallic and then bulk-like. The cluster sizes with extra stability agree well with the predictions of the jellium model. In the 4d series of transition metal (TM) clusters, as the d-type bonding becomes more important, the preferred geometric structure changes from icosahedral (Y, Zr), to distorted compact structures (Nb, Mo), and FCC or simple cubic crystal fragments (Tc, Ru, Rh) due to the localized nature of the d-type orbital. Analysis of relative isomer energies and their electronic density of states suggest that these clusters tend to follow a maximum hardness principle (MHP). For A4B12 clusters (A is divalent, B is monovalent), we found unusually large (on average 1.95 eV) HOMO-LUMO gap values. This shows the extra stability at an electronic closed shell (20 electrons) predicted by the jellium model. The importance of symmetry, closed electronic and ionic shells in stability is shown by the relative stability of homotops of Mg4Ag12 which also provides support for the hypothesis that clusters that satisfy more than one stability criterion ("double magic") should be particularly stable.

CASP10-BCL::Fold efficiently samples topologies of large proteins.

PubMed

Heinze, Sten; Putnam, Daniel K; Fischer, Axel W; Kohlmann, Tim; Weiner, Brian E; Meiler, Jens

2015-03-01

During CASP10 in summer 2012, we tested BCL::Fold for prediction of free modeling (FM) and template-based modeling (TBM) targets. BCL::Fold assembles the tertiary structure of a protein from predicted secondary structure elements (SSEs) omitting more flexible loop regions early on. This approach enables the sampling of conformational space for larger proteins with more complex topologies. In preparation of CASP11, we analyzed the quality of CASP10 models throughout the prediction pipeline to understand BCL::Fold's ability to sample the native topology, identify native-like models by scoring and/or clustering approaches, and our ability to add loop regions and side chains to initial SSE-only models. The standout observation is that BCL::Fold sampled topologies with a GDT_TS score > 33% for 12 of 18 and with a topology score > 0.8 for 11 of 18 test cases de novo. Despite the sampling success of BCL::Fold, significant challenges still exist in clustering and loop generation stages of the pipeline. The clustering approach employed for model selection often failed to identify the most native-like assembly of SSEs for further refinement and submission. It was also observed that for some β-strand proteins model refinement failed as β-strands were not properly aligned to form hydrogen bonds removing otherwise accurate models from the pool. Further, BCL::Fold samples frequently non-natural topologies that require loop regions to pass through the center of the protein. © 2015 Wiley Periodicals, Inc.

Behavioral self-organization underlies the resilience of a coastal ecosystem.

PubMed

de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R; Herman, Peter M J; van de Koppel, Johan

2017-07-25

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds ( Mytilus edulis ) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance.

Behavioral self-organization underlies the resilience of a coastal ecosystem

PubMed Central

de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R.; Herman, Peter M. J.

2017-01-01

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds (Mytilus edulis) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance. PMID:28696313

The VIMOS Public Extragalactic Redshift Survey (VIPERS) . Luminosity and stellar mass dependence of galaxy clustering at 0.5 < z < 1.1

NASA Astrophysics Data System (ADS)

Marulli, F.; Bolzonella, M.; Branchini, E.; Davidzon, I.; de la Torre, S.; Granett, B. R.; Guzzo, L.; Iovino, A.; Moscardini, L.; Pollo, A.; Abbas, U.; Adami, C.; Arnouts, S.; Bel, J.; Bottini, D.; Cappi, A.; Coupon, J.; Cucciati, O.; De Lucia, G.; Fritz, A.; Franzetti, P.; Fumana, M.; Garilli, B.; Ilbert, O.; Krywult, J.; Le Brun, V.; Le Fèvre, O.; Maccagni, D.; Małek, K.; McCracken, H. J.; Paioro, L.; Polletta, M.; Schlagenhaufer, H.; Scodeggio, M.; Tasca, L. A. M.; Tojeiro, R.; Vergani, D.; Zanichelli, A.; Burden, A.; Di Porto, C.; Marchetti, A.; Marinoni, C.; Mellier, Y.; Nichol, R. C.; Peacock, J. A.; Percival, W. J.; Phleps, S.; Wolk, M.; Zamorani, G.

2013-09-01

Aims: We investigate the dependence of galaxy clustering on luminosity and stellar mass in the redshift range 0.5 < z < 1.1, using the first ~ 55 000 redshifts from the VIMOS Public Extragalactic Redshift Survey (VIPERS). Methods: We measured the redshift-space two-point correlation functions (2PCF), ξ(s) and ξ(rp,π) , and the projected correlation function, wp(rp), in samples covering different ranges of B-band absolute magnitudes and stellar masses. We considered both threshold and binned galaxy samples, with median B-band absolute magnitudes - 21.6 ≲ MB - 5log (h) ≲ - 19.5 and median stellar masses 9.8 ≲ log (M⋆ [h-2 M⊙]) ≲ 10.7. We assessed the real-space clustering in the data from the projected correlation function, which we model as a power law in the range 0.2 < rp [h-1 Mpc ] < 20. Finally, we estimated the galaxy bias as a function of luminosity, stellar mass, and redshift, assuming a flat Λ cold dark matter model to derive the dark matter 2PCF. Results: We provide the best-fit parameters of the power-law model assumed for the real-space 2PCF - the correlation length, r0, and the slope, γ - as well as the linear bias parameter, as a function of the B-band absolute magnitude, stellar mass, and redshift. We confirm and provide the tightest constraints on the dependence of clustering on luminosity at 0.5 < z < 1.1. We prove the complexity of comparing the clustering dependence on stellar mass from samples that are originally flux-limited and discuss the possible origin of the observed discrepancies. Overall, our measurements provide stronger constraints on galaxy formation models, which are now required to match, in addition to local observations, the clustering evolution measured by VIPERS galaxies between z = 0.5 and z = 1.1 for a broad range of luminosities and stellar masses. Based on observations collected at the European Southern Observatory, Paranal, Chile, under programmes 182.A-0886 (LP) at the Very Large Telescope, and also based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT), which is operated by the National Research Council (NRC) of Canada, the Institut National des Science de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at TERAPIX and the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. The VIPERS web site is http://vipers.inaf.it/

Stable clustering and the resolution of dissipationless cosmological N-body simulations

NASA Astrophysics Data System (ADS)

Benhaiem, David; Joyce, Michael; Sylos Labini, Francesco

2017-10-01

The determination of the resolution of cosmological N-body simulations, I.e. the range of scales in which quantities measured in them represent accurately the continuum limit, is an important open question. We address it here using scale-free models, for which self-similarity provides a powerful tool to control resolution. Such models also provide a robust testing ground for the so-called stable clustering approximation, which gives simple predictions for them. Studying large N-body simulations of such models with different force smoothing, we find that these two issues are in fact very closely related: our conclusion is that the accuracy of two-point statistics in the non-linear regime starts to degrade strongly around the scale at which their behaviour deviates from that predicted by the stable clustering hypothesis. Physically the association of the two scales is in fact simple to understand: stable clustering fails to be a good approximation when there are strong interactions of structures (in particular merging) and it is precisely such non-linear processes which are sensitive to fluctuations at the smaller scales affected by discretization. Resolution may be further degraded if the short distance gravitational smoothing scale is larger than the scale to which stable clustering can propagate. We examine in detail the very different conclusions of studies by Smith et al. and Widrow et al. and find that the strong deviations from stable clustering reported by these works are the results of over-optimistic assumptions about scales resolved accurately by the measured power spectra, and the reliance on Fourier space analysis. We emphasize the much poorer resolution obtained with the power spectrum compared to the two-point correlation function.

Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003-2012.

PubMed

Khan, Diba; Rossen, Lauren M; Hamilton, Brady E; He, Yulei; Wei, Rong; Dienes, Erin

2017-06-01

Teen birth rates have evidenced a significant decline in the United States over the past few decades. Most of the states in the US have mirrored this national decline, though some reports have illustrated substantial variation in the magnitude of these decreases across the U.S. Importantly, geographic variation at the county level has largely not been explored. We used National Vital Statistics Births data and Hierarchical Bayesian space-time interaction models to produce smoothed estimates of teen birth rates at the county level from 2003-2012. Results indicate that teen birth rates show evidence of clustering, where hot and cold spots occur, and identify spatial outliers. Findings from this analysis may help inform efforts targeting the prevention efforts by illustrating how geographic patterns of teen birth rates have changed over the past decade and where clusters of high or low teen birth rates are evident. Published by Elsevier Ltd.

Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003–2012

PubMed Central

Khan, Diba; Rossen, Lauren M.; Hamilton, Brady E.; He, Yulei; Wei, Rong; Dienes, Erin

2017-01-01

Teen birth rates have evidenced a significant decline in the United States over the past few decades. Most of the states in the US have mirrored this national decline, though some reports have illustrated substantial variation in the magnitude of these decreases across the U.S. Importantly, geographic variation at the county level has largely not been explored. We used National Vital Statistics Births data and Hierarchical Bayesian space-time interaction models to produce smoothed estimates of teen birth rates at the county level from 2003–2012. Results indicate that teen birth rates show evidence of clustering, where hot and cold spots occur, and identify spatial outliers. Findings from this analysis may help inform efforts targeting the prevention efforts by illustrating how geographic patterns of teen birth rates have changed over the past decade and where clusters of high or low teen birth rates are evident. PMID:28552189

Blocked inverted indices for exact clustering of large chemical spaces.

PubMed

Thiel, Philipp; Sach-Peltason, Lisa; Ottmann, Christian; Kohlbacher, Oliver

2014-09-22

The calculation of pairwise compound similarities based on fingerprints is one of the fundamental tasks in chemoinformatics. Methods for efficient calculation of compound similarities are of the utmost importance for various applications like similarity searching or library clustering. With the increasing size of public compound databases, exact clustering of these databases is desirable, but often computationally prohibitively expensive. We present an optimized inverted index algorithm for the calculation of all pairwise similarities on 2D fingerprints of a given data set. In contrast to other algorithms, it neither requires GPU computing nor yields a stochastic approximation of the clustering. The algorithm has been designed to work well with multicore architectures and shows excellent parallel speedup. As an application example of this algorithm, we implemented a deterministic clustering application, which has been designed to decompose virtual libraries comprising tens of millions of compounds in a short time on current hardware. Our results show that our implementation achieves more than 400 million Tanimoto similarity calculations per second on a common desktop CPU. Deterministic clustering of the available chemical space thus can be done on modern multicore machines within a few days.

The stable clustering ansatz, consistency relations and gravity dual of large-scale structure

NASA Astrophysics Data System (ADS)

Munshi, Dipak

2018-02-01

Gravitational clustering in the nonlinear regime remains poorly understood. Gravity dual of gravitational clustering has recently been proposed as a means to study the nonlinear regime. The stable clustering ansatz remains a key ingredient to our understanding of gravitational clustering in the highly nonlinear regime. We study certain aspects of violation of the stable clustering ansatz in the gravity dual of Large Scale Structure (LSS). We extend the recent studies of gravitational clustering using AdS gravity dual to take into account possible departure from the stable clustering ansatz and to arbitrary dimensions. Next, we extend the recently introduced consistency relations to arbitrary dimensions. We use the consistency relations to test the commonly used models of gravitational clustering including the halo models and hierarchical ansätze. In particular we establish a tower of consistency relations for the hierarchical amplitudes: Q, Ra, Rb, Sa,Sb,Sc etc. as a functions of the scaled peculiar velocity h. We also study the variants of popular halo models in this context. In contrast to recent claims, none of these models, in their simplest incarnation, seem to satisfy the consistency relations in the soft limit.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lehtola, Susi; Parkhill, John; Head-Gordon, Martin

Novel implementations based on dense tensor storage are presented here for the singlet-reference perfect quadruples (PQ) [J. A. Parkhill et al., J. Chem. Phys. 130, 084101 (2009)] and perfect hextuples (PH) [J. A. Parkhill and M. Head-Gordon, J. Chem. Phys. 133, 024103 (2010)] models. The methods are obtained as block decompositions of conventional coupled-cluster theory that are exact for four electrons in four orbitals (PQ) and six electrons in six orbitals (PH), but that can also be applied to much larger systems. PQ and PH have storage requirements that scale as the square, and as the cube of the numbermore » of active electrons, respectively, and exhibit quartic scaling of the computational effort for large systems. Applications of the new implementations are presented for full-valence calculations on linear polyenes (C nH n+2), which highlight the excellent computational scaling of the present implementations that can routinely handle active spaces of hundreds of electrons. The accuracy of the models is studied in the π space of the polyenes, in hydrogen chains (H 50), and in the π space of polyacene molecules. In all cases, the results compare favorably to density matrix renormalization group values. With the novel implementation of PQ, active spaces of 140 electrons in 140 orbitals can be solved in a matter of minutes on a single core workstation, and the relatively low polynomial scaling means that very large systems are also accessible using parallel computing.« less

Surface brightness profiles and structural parameters for 53 rich stellar clusters in the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Mackey, A. D.; Gilmore, G. F.

2003-01-01

We have compiled a pseudo-snapshot data set of two-colour observations from the Hubble Space Telescope archive for a sample of 53 rich LMC clusters with ages of 106-1010 yr. We present surface brightness profiles for the entire sample, and derive structural parameters for each cluster, including core radii, and luminosity and mass estimates. Because we expect the results presented here to form the basis for several further projects, we describe in detail the data reduction and surface brightness profile construction processes, and compare our results with those of previous ground-based studies. The surface brightness profiles show a large amount of detail, including irregularities in the profiles of young clusters (such as bumps, dips and sharp shoulders), and evidence for both double clusters and post-core-collapse (PCC) clusters. In particular, we find power-law profiles in the inner regions of several candidate PCC clusters, with slopes of approximately -0.7, but showing considerable variation. We estimate that 20 +/- 7 per cent of the old cluster population of the Large Magellanic Cloud (LMC) has entered PCC evolution, a similar fraction to that for the Galactic globular cluster system. In addition, we examine the profile of R136 in detail and show that it is probably not a PCC cluster. We also observe a trend in core radius with age that has been discovered and discussed in several previous publications by different authors. Our diagram has better resolution, however, and appears to show a bifurcation at several hundred Myr. We argue that this observed relationship reflects true physical evolution in LMC clusters, with some experiencing small-scale core expansion owing to mass loss, and others large-scale expansion owing to some unidentified characteristic or physical process.

The phase-space structure of nearby dark matter as constrained by the SDSS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leclercq, Florent; Percival, Will; Jasche, Jens

Previous studies using numerical simulations have demonstrated that the shape of the cosmic web can be described by studying the Lagrangian displacement field. We extend these analyses, showing that it is now possible to perform a Lagrangian description of cosmic structure in the nearby Universe based on large-scale structure observations. Building upon recent Bayesian large-scale inference of initial conditions, we present a cosmographic analysis of the dark matter distribution and its evolution, referred to as the dark matter phase-space sheet, in the nearby universe as probed by the Sloan Digital Sky Survey main galaxy sample. We consider its stretchings andmore » foldings using a tetrahedral tessellation of the Lagrangian lattice. The method provides extremely accurate estimates of nearby density and velocity fields, even in regions of low galaxy density. It also measures the number of matter streams, and the deformation and parity reversals of fluid elements, which were previously thought inaccessible using observations. We illustrate the approach by showing the phase-space structure of known objects of the nearby Universe such as the Sloan Great Wall, the Coma cluster and the Boötes void. We dissect cosmic structures into four distinct components (voids, sheets, filaments, and clusters), using the Lagrangian classifiers DIVA, ORIGAMI, and a new scheme which we introduce and call LICH. Because these classifiers use information other than the sheer local density, identified structures explicitly carry physical information about their formation history. Accessing the phase-space structure of dark matter in galaxy surveys opens the way for new confrontations of observational data and theoretical models. We have made our data products publicly available.« less

The phase-space structure of nearby dark matter as constrained by the SDSS

NASA Astrophysics Data System (ADS)

Leclercq, Florent; Jasche, Jens; Lavaux, Guilhem; Wandelt, Benjamin; Percival, Will

2017-06-01

Previous studies using numerical simulations have demonstrated that the shape of the cosmic web can be described by studying the Lagrangian displacement field. We extend these analyses, showing that it is now possible to perform a Lagrangian description of cosmic structure in the nearby Universe based on large-scale structure observations. Building upon recent Bayesian large-scale inference of initial conditions, we present a cosmographic analysis of the dark matter distribution and its evolution, referred to as the dark matter phase-space sheet, in the nearby universe as probed by the Sloan Digital Sky Survey main galaxy sample. We consider its stretchings and foldings using a tetrahedral tessellation of the Lagrangian lattice. The method provides extremely accurate estimates of nearby density and velocity fields, even in regions of low galaxy density. It also measures the number of matter streams, and the deformation and parity reversals of fluid elements, which were previously thought inaccessible using observations. We illustrate the approach by showing the phase-space structure of known objects of the nearby Universe such as the Sloan Great Wall, the Coma cluster and the Boötes void. We dissect cosmic structures into four distinct components (voids, sheets, filaments, and clusters), using the Lagrangian classifiers DIVA, ORIGAMI, and a new scheme which we introduce and call LICH. Because these classifiers use information other than the sheer local density, identified structures explicitly carry physical information about their formation history. Accessing the phase-space structure of dark matter in galaxy surveys opens the way for new confrontations of observational data and theoretical models. We have made our data products publicly available.

The impact of clustering of extreme European windstorm events on (re)insurance market portfolios

NASA Astrophysics Data System (ADS)

Mitchell-Wallace, Kirsten; Alvarez-Diaz, Teresa

2010-05-01

Traditionally the occurrence of windstorm loss events in Europe has been considered as independent. However, a number of significant losses close in space and time indicates that this assumption may need to be revised. Under particular atmospheric conditions multiple loss-causing cyclones can occur in succession, affecting similar geographic regions and, therefore, insurance markets. A notable example is of Lothar and Martin in France in December 1999. Although the existence of cyclone families is well-known by meteorologists, there has been limited research into occurrence of serial windstorms. However, climate modelling research is now providing the ability to explore the physical drivers of clustering, and to improve understanding of the hazard aspect of catastrophe modelling. While analytics tools, including catastrophe models, may incorporate assumptions regarding the influence of dependency through statistical means, the most recent research outputs provide a new strand of information with the potential to re-assess the probabilistic loss potential in light of clustering and to provide an additional view on probable maximum losses to windstorm-exposed portfolios across regions such as Northwest Europe. There is however, a need for the testing of these new techniques within operational (re)insurance applications, and this paper provide an overview of the most current clustering research, including the 2009 paper by Vitolo et. al., in relation to reinsurance risk modelling, and to assess the potential impact of such additional information on the overall risk assessment process. We examine the consequences of the serial clustering of extra-tropical cyclones demonstrated by Vitolo et al. (2009) from the perspective of a large European reinsurer, examining potential implications for: • Pricing • Accumulation And • Capital adequacy

Hubble Sees an Ancient Globular Cluster

NASA Image and Video Library

2017-12-08

This image captures the stunning NGC 6535, a globular cluster 22,000 light-years away in the constellation of Serpens (The Serpent) that measures one light-year across. Globular clusters are tightly bound groups of stars which orbit galaxies. The large mass in the rich stellar centre of the globular cluster pulls the stars inward to form a ball of stars. The word globulus, from which these clusters take their name, is Latin for small sphere. Globular clusters are generally very ancient objects formed around the same time as their host galaxy. To date, no new star formation has been observed within a globular cluster, which explains the abundance of aging yellow stars in this image, most of them containing very few heavy elements. NGC 6535 was first discovered in 1852 by English astronomer John Russell Hind. The cluster would have appeared to Hind as a small, faint smudge through his telescope. Now, over 160 years later, instruments like the Advanced Camera for Surveys (ACS) and Wide Field Camera 3 (WFC3) on the NASA/ European Space Agency (ESA) Hubble Space Telescope allow us to marvel at the cluster and its contents in greater detail. Credit: ESA/Hubble & NASA, Acknowledgement: Gilles Chapdelaine NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

NASA Technical Reports Server (NTRS)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Enhanced conformational sampling to visualize a free-energy landscape of protein complex formation.

PubMed

Iida, Shinji; Nakamura, Haruki; Higo, Junichi

2016-06-15

We introduce various, recently developed, generalized ensemble methods, which are useful to sample various molecular configurations emerging in the process of protein-protein or protein-ligand binding. The methods introduced here are those that have been or will be applied to biomolecular binding, where the biomolecules are treated as flexible molecules expressed by an all-atom model in an explicit solvent. Sampling produces an ensemble of conformations (snapshots) that are thermodynamically probable at room temperature. Then, projection of those conformations to an abstract low-dimensional space generates a free-energy landscape. As an example, we show a landscape of homo-dimer formation of an endothelin-1-like molecule computed using a generalized ensemble method. The lowest free-energy cluster at room temperature coincided precisely with the experimentally determined complex structure. Two minor clusters were also found in the landscape, which were largely different from the native complex form. Although those clusters were isolated at room temperature, with rising temperature a pathway emerged linking the lowest and second-lowest free-energy clusters, and a further temperature increment connected all the clusters. This exemplifies that the generalized ensemble method is a powerful tool for computing the free-energy landscape, by which one can discuss the thermodynamic stability of clusters and the temperature dependence of the cluster networks. © 2016 The Author(s).

Experimental Measurement of the Nonlinear Interaction between Counterpropagating Alfv'en Waves in the LaPD

NASA Astrophysics Data System (ADS)

Schroeder, J. W. R.; Drake, D. J.; Howes, G. G.; Skiff, F.; Kletzing, C. A.; Carter, T. A.; Dorfman, S.; Auerbach, D.

2012-10-01

Turbulence plays an important role in the transport of mass and energy in many space and astrophysical plasmas ranging from galaxy clusters to Earth's magnetosphere. One active topic of research is the application of idealized Alfv'enic turbulence models to plasma conditions relevant to space and astrophysical plasmas. Alfv'enic turbulence models based on incompressible magnetohydrodynamics (MHD) contain a nonlinear interaction that drives the cascade of energy to smaller scales. We describe experiments at the Large Plasma Device (LaPD) that focus on the interaction of an Alfv'en wave traveling parallel to the mean magnetic field with a counterpropagating Alfv'en wave. Theory predicts the nonlinear interaction of the two primary waves will produce a secondary daughter Alfv'en wave. In this study, we present the first experimental identification of the daughter wave generated by nonlinear interactions between the primary Alfv'en waves.

Constraints on deviations from ΛCDM within Horndeski gravity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bellini, Emilio; Cuesta, Antonio J.; Jimenez, Raul

2016-02-01

Recent anomalies found in cosmological datasets such as the low multipoles of the Cosmic Microwave Background or the low redshift amplitude and growth of clustering measured by e.g., abundance of galaxy clusters and redshift space distortions in galaxy surveys, have motivated explorations of models beyond standard ΛCDM. Of particular interest are models where general relativity (GR) is modified on large cosmological scales. Here we consider deviations from ΛCDM+GR within the context of Horndeski gravity, which is the most general theory of gravity with second derivatives in the equations of motion. We adopt a parametrization in which the four additional Horndeskimore » functions of time α{sub i}(t) are proportional to the cosmological density of dark energy Ω{sub DE}(t). Constraints on this extended parameter space using a suite of state-of-the art cosmological observations are presented for the first time. Although the theory is able to accommodate the low multipoles of the Cosmic Microwave Background and the low amplitude of fluctuations from redshift space distortions, we find no significant tension with ΛCDM+GR when performing a global fit to recent cosmological data and thus there is no evidence against ΛCDM+GR from an analysis of the value of the Bayesian evidence ratio of the modified gravity models with respect to ΛCDM, despite introducing extra parameters. The posterior distribution of these extra parameters that we derive return strong constraints on any possible deviations from ΛCDM+GR in the context of Horndeski gravity. We illustrate how our results can be applied to a more general frameworks of modified gravity models.« less

Modelling galaxy clustering on small scales to tighten constraints on dark energy and modified gravity

NASA Astrophysics Data System (ADS)

Wang, Yun

2017-01-01

We present a new approach to measuring cosmic expansion history and growth rate of large-scale structure using the anisotropic two-dimensional galaxy correlation function (2DCF) measured from data; it makes use of the empirical modelling of small-scale galaxy clustering derived from numerical simulations by Zheng et al. We validate this method using mock catalogues, before applying it to the analysis of the CMASS sample from the Sloan Digital Sky Survey Data Release 10 of the Baryon Oscillation Spectroscopic Survey. We find that this method enables accurate and precise measurements of cosmic expansion history and growth rate of large-scale structure. Modelling the 2DCF fully including non-linear effects and redshift space distortions in the scale range of 16-144 h-1 Mpc, we find H(0.57)rs(zd)/c = 0.0459 ± 0.0006, DA(0.57)/rs(zd) = 9.011 ± 0.073, and fg(0.57)σ8(0.57) = 0.476 ± 0.050, which correspond to precisions of 1.3 per cent, 0.8 per cent, and 10.5 per cent, respectively. We have defined rs(zd) to be the sound horizon at the drag epoch computed using a simple integral, fg(z) as the growth rate at redshift z, and σ8(z) as the matter power spectrum normalization on 8 h-1 Mpc scale at z. We find that neglecting the small-scale information significantly weakens the constraints on H(z) and DA(z), and leads to a biased estimate of fg(z). Our results indicate that we can significantly tighten constraints on dark energy and modified gravity by reliably modelling small-scale galaxy clustering.

Rigid-Cluster Models of Conformational Transitions in Macromolecular Machines and Assemblies

PubMed Central

Kim, Moon K.; Jernigan, Robert L.; Chirikjian, Gregory S.

2005-01-01

We present a rigid-body-based technique (called rigid-cluster elastic network interpolation) to generate feasible transition pathways between two distinct conformations of a macromolecular assembly. Many biological molecules and assemblies consist of domains which act more or less as rigid bodies during large conformational changes. These collective motions are thought to be strongly related with the functions of a system. This fact encourages us to simply model a macromolecule or assembly as a set of rigid bodies which are interconnected with distance constraints. In previous articles, we developed coarse-grained elastic network interpolation (ENI) in which, for example, only Cα atoms are selected as representatives in each residue of a protein. We interpolate distance differences of two conformations in ENI by using a simple quadratic cost function, and the feasible conformations are generated without steric conflicts. Rigid-cluster interpolation is an extension of the ENI method with rigid-clusters replacing point masses. Now the intermediate conformations in an anharmonic pathway can be determined by the translational and rotational displacements of large clusters in such a way that distance constraints are observed. We present the derivation of the rigid-cluster model and apply it to a variety of macromolecular assemblies. Rigid-cluster ENI is then modified for a hybrid model represented by a mixture of rigid clusters and point masses. Simulation results show that both rigid-cluster and hybrid ENI methods generate sterically feasible pathways of large systems in a very short time. For example, the HK97 virus capsid is an icosahedral symmetric assembly composed of 60 identical asymmetric units. Its original Hessian matrix size for a Cα coarse-grained model is >(300,000)2. However, it reduces to (84)2 when we apply the rigid-cluster model with icosahedral symmetry constraints. The computational cost of the interpolation no longer scales heavily with the size of structures; instead, it depends strongly on the minimal number of rigid clusters into which the system can be decomposed. PMID:15833998

From Globular Clusters to Tidal Dwarfs: Structure Formation in the Tidal Tails of Merging Galaxies

NASA Astrophysics Data System (ADS)

Knierman, Karen A.; Gallagher, Sarah C.; Charlton, Jane C.; Hunsberger, Sally D.; Whitmore, Bradley; Kundu, Arunav; Hibbard, J. E.; Zaritsky, Dennis

2003-09-01

Using V and I images obtained with the Wide Field Planetary Camera 2 (WFPC2) of the Hubble Space Telescope, we investigate compact stellar structures within tidal tails. Six regions of tidal debris in the four classic ``Toomre sequence'' mergers: NGC 4038/39 (``Antennae''), NGC 3256, NGC 3921, and NGC 7252 (``Atoms for Peace'') have been studied in order to explore how the star formation depends on the local and global physical conditions. These mergers sample a range of stages in the evolutionary sequence and tails with and without embedded tidal dwarf galaxies. The six tails are found to contain a variety of stellar structures, with sizes ranging from those of globular clusters up to those of dwarf galaxies. From V and I WFPC2 images, we measure the luminosities and colors of the star clusters. NGC 3256 is found to have a large population of blue clusters (0.2<~V-I<~0.9), particularly in its western tail, similar to those found in the inner region of the merger. In contrast, NGC 4038/39 has no clusters in the observed region of the tail, only less luminous point sources likely to be individual stars. NGC 3921 and NGC 7252 have small populations of clusters along their tails. A significant cluster population is clearly associated with the prominent tidal dwarf candidates in the eastern and western tails of NGC 7252. The cluster-rich western tail of NGC 3256 is not distinguished from the others by its dynamical age or by its total H I mass. However, the mergers that have few clusters in the tail all have tidal dwarf galaxies, while NGC 3256 does not have prominent tidal dwarfs. We speculate that star formation in tidal tails may manifest itself either in small structures like clusters along the tail or in large structures such as dwarf galaxies, but not in both. Also, NGC 3256 has the highest star formation rate of the four mergers studied, which may contribute to the high number of star clusters in its tidal tails. Based in part on observations obtained with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy (AURA), Inc., under NASA contract NAS 5-26555.

Cluster Physics with Merging Galaxy Clusters

NASA Astrophysics Data System (ADS)

Molnar, Sandor

Collisions between galaxy clusters provide a unique opportunity to study matter in a parameter space which cannot be explored in our laboratories on Earth. In the standard ΛCDM model, where the total density is dominated by the cosmological constant (Λ) and the matter density by cold dark matter (CDM), structure formation is hierarchical, and clusters grow mostly by merging. Mergers of two massive clusters are the most energetic events in the universe after the Big Bang, hence they provide a unique laboratory to study cluster physics. The two main mass components in clusters behave differently during collisions: the dark matter is nearly collisionless, responding only to gravity, while the gas is subject to pressure forces and dissipation, and shocks and turbulence are developed during collisions. In the present contribution we review the different methods used to derive the physical properties of merging clusters. Different physical processes leave their signatures on different wavelengths, thus our review is based on a multifrequency analysis. In principle, the best way to analyze multifrequency observations of merging clusters is to model them using N-body/HYDRO numerical simulations. We discuss the results of such detailed analyses. New high spatial and spectral resolution ground and space based telescopes will come online in the near future. Motivated by these new opportunities, we briefly discuss methods which will be feasible in the near future in studying merging clusters.

Dark matter phenomenology of high-speed galaxy cluster collisions

DOE PAGES

Mishchenko, Yuriy; Ji, Chueng-Ryong

2017-07-29

Here, we perform a general computational analysis of possible post-collision mass distributions in high-speed galaxy cluster collisions in the presence of self-interacting dark matter. Using this analysis, we show that astrophysically weakly self-interacting dark matter can impart subtle yet measurable features in the mass distributions of colliding galaxy clusters even without significant disruptions to the dark matter halos of the colliding galaxy clusters themselves. Most profound such evidence is found to reside in the tails of dark matter halos’ distributions, in the space between the colliding galaxy clusters. Such features appear in our simulations as shells of scattered dark mattermore » expanding in alignment with the outgoing original galaxy clusters, contributing significant densities to projected mass distributions at large distances from collision centers and large scattering angles of up to 90°. Our simulations indicate that as much as 20% of the total collision’s mass may be deposited into such structures without noticeable disruptions to the main galaxy clusters. Such structures at large scattering angles are forbidden in purely gravitational high-speed galaxy cluster collisions.Convincing identification of such structures in real colliding galaxy clusters would be a clear indication of the self-interacting nature of dark matter. Our findings may offer an explanation for the ring-like dark matter feature recently identified in the long-range reconstructions of the mass distribution of the colliding galaxy cluster CL0024+017.« less

Dark matter phenomenology of high-speed galaxy cluster collisions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishchenko, Yuriy; Ji, Chueng-Ryong

Here, we perform a general computational analysis of possible post-collision mass distributions in high-speed galaxy cluster collisions in the presence of self-interacting dark matter. Using this analysis, we show that astrophysically weakly self-interacting dark matter can impart subtle yet measurable features in the mass distributions of colliding galaxy clusters even without significant disruptions to the dark matter halos of the colliding galaxy clusters themselves. Most profound such evidence is found to reside in the tails of dark matter halos’ distributions, in the space between the colliding galaxy clusters. Such features appear in our simulations as shells of scattered dark mattermore » expanding in alignment with the outgoing original galaxy clusters, contributing significant densities to projected mass distributions at large distances from collision centers and large scattering angles of up to 90°. Our simulations indicate that as much as 20% of the total collision’s mass may be deposited into such structures without noticeable disruptions to the main galaxy clusters. Such structures at large scattering angles are forbidden in purely gravitational high-speed galaxy cluster collisions.Convincing identification of such structures in real colliding galaxy clusters would be a clear indication of the self-interacting nature of dark matter. Our findings may offer an explanation for the ring-like dark matter feature recently identified in the long-range reconstructions of the mass distribution of the colliding galaxy cluster CL0024+017.« less

Dark matter component decaying after recombination: Sensitivity to baryon acoustic oscillation and redshift space distortion probes

NASA Astrophysics Data System (ADS)

Chudaykin, A.; Gorbunov, D.; Tkachev, I.

2018-04-01

It has been recently suggested [1] that a subdominant fraction of dark matter decaying after recombination may alleviate tension between high-redshift (CMB anisotropy) and low-redshift (Hubble constant, cluster counts) measurements. In this report, we continue our previous study [2] of the decaying dark matter (DDM) model adding all available recent baryon acoustic oscillation (BAO) and redshift space distortions (RSD) measurements. We find that the BAO/RSD measurements generically prefer the standard Λ CDM and combined with other cosmological measurements impose an upper limit on the DDM fraction at the level of ˜5 %, strengthening by a factor of 1.5 limits obtained in [2] mostly from CMB data. However, the numbers vary from one analysis to other based on the same Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12 (DR12) galaxy sample. Overall, the model with a few percent DDM fraction provides a better fit to the combined cosmological data as compared to the Λ CDM : the cluster counting and direct measurements of the Hubble parameter are responsible for that. The improvement can be as large as 1.5 σ and grows to 3.3 σ when the CMB lensing power amplitude AL is introduced as a free fitting parameter.

Can standard cosmological models explain the observed Abell cluster bulk flow?

NASA Technical Reports Server (NTRS)

Strauss, Michael A.; Cen, Renyue; Ostriker, Jeremiah P.; Laure, Tod R.; Postman, Marc

1995-01-01

Lauer and Postman (LP) observed that all Abell clusters with redshifts less than 15,000 km/s appear to be participating in a bulk flow of 689 km/s with respect to the cosmic microwave background. We find this result difficult to reconcile with all popular models for large-scale structure formation that assume Gaussian initial conditions. This conclusion is based on Monte Carlo realizations of the LP data, drawn from large particle-mesh N-body simulations for six different models of the initial power spectrum (standard, tilted, and Omega(sub 0) = 0.3 cold dark matter, and two variants of the primordial baryon isocurvature model). We have taken special care to treat properly the longest-wavelength components of the power spectra. The simulations are sampled, 'observed,' and analyzed as identically as possible to the LP cluster sample. Large-scale bulk flows as measured from clusters in the simulations are in excellent agreement with those measured from the grid: the clusters do not exhibit any strong velocity bias on large scales. Bulk flows with amplitude as large as that reported by LP are not uncommon in the Monte Carlo data stes; the distribution of measured bulk flows before error bias subtraction is rougly Maxwellian, with a peak around 400 km/s. However the chi squared of the observed bulk flow, taking into account the anisotropy of the error ellipsoid, is much more difficult to match in the simulations. The models examined are ruled out at confidence levels between 94% and 98%.

Exploring the nature and synchronicity of early cluster formation in the Large Magellanic Cloud - II. Relative ages and distances for six ancient globular clusters

NASA Astrophysics Data System (ADS)

Wagner-Kaiser, R.; Mackey, Dougal; Sarajedini, Ata; Chaboyer, Brian; Cohen, Roger E.; Yang, Soung-Chul; Cummings, Jeffrey D.; Geisler, Doug; Grocholski, Aaron J.

2017-11-01

We analyse Hubble Space Telescope observations of six globular clusters in the Large Magellanic Cloud (LMC) from programme GO-14164 in Cycle 23. These are the deepest available observations of the LMC globular cluster population; their uniformity facilitates a precise comparison with globular clusters in the Milky Way. Measuring the magnitude of the main-sequence turn-off point relative to template Galactic globular clusters allows the relative ages of the clusters to be determined with a mean precision of 8.4 per cent, and down to 6 per cent for individual objects. We find that the mean age of our LMC cluster ensemble is identical to the mean age of the oldest metal-poor clusters in the Milky Way halo to 0.2 ± 0.4 Gyr. This provides the most sensitive test to date of the synchronicity of the earliest epoch of globular cluster formation in two independent galaxies. Horizontal branch magnitudes and subdwarf fitting to the main sequence allow us to determine distance estimates for each cluster and examine their geometric distribution in the LMC. Using two different methods, we find an average distance to the LMC of 18.52 ± 0.05.

Cluster analysis of multiple planetary flow regimes

NASA Technical Reports Server (NTRS)

Mo, Kingtse; Ghil, Michael

1987-01-01

A modified cluster analysis method was developed to identify spatial patterns of planetary flow regimes, and to study transitions between them. This method was applied first to a simple deterministic model and second to Northern Hemisphere (NH) 500 mb data. The dynamical model is governed by the fully-nonlinear, equivalent-barotropic vorticity equation on the sphere. Clusters of point in the model's phase space are associated with either a few persistent or with many transient events. Two stationary clusters have patterns similar to unstable stationary model solutions, zonal, or blocked. Transient clusters of wave trains serve as way stations between the stationary ones. For the NH data, cluster analysis was performed in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters are found in the low-frequency band of more than 10 days, and transient clusters in the bandpass frequency window between 2.5 and 6 days. In the low-frequency band three pairs of clusters determine, respectively, EOFs 1, 2, and 3. They exhibit well-known regional features, such as blocking, the Pacific/North American (PNA) pattern and wave trains. Both model and low-pass data show strong bimodality. Clusters in the bandpass window show wave-train patterns in the two jet exit regions. They are related, as in the model, to transitions between stationary clusters.

Evolution of the real-space correlation function from next generation cluster surveys. Recovering the real-space correlation function from photometric redshifts

NASA Astrophysics Data System (ADS)

Sridhar, Srivatsan; Maurogordato, Sophie; Benoist, Christophe; Cappi, Alberto; Marulli, Federico

2017-04-01

Context. The next generation of galaxy surveys will provide cluster catalogues probing an unprecedented range of scales, redshifts, and masses with large statistics. Their analysis should therefore enable us to probe the spatial distribution of clusters with high accuracy and derive tighter constraints on the cosmological parameters and the dark energy equation of state. However, for the majority of these surveys, redshifts of individual galaxies will be mostly estimated by multiband photometry which implies non-negligible errors in redshift resulting in potential difficulties in recovering the real-space clustering. Aims: We investigate to which accuracy it is possible to recover the real-space two-point correlation function of galaxy clusters from cluster catalogues based on photometric redshifts, and test our ability to detect and measure the redshift and mass evolution of the correlation length r0 and of the bias parameter b(M,z) as a function of the uncertainty on the cluster redshift estimate. Methods: We calculate the correlation function for cluster sub-samples covering various mass and redshift bins selected from a 500 deg2 light-cone limited to H < 24. In order to simulate the distribution of clusters in photometric redshift space, we assign to each cluster a redshift randomly extracted from a Gaussian distribution having a mean equal to the cluster cosmological redshift and a dispersion equal to σz. The dispersion is varied in the range σ(z=0)=\\frac{σz{1+z_c} = 0.005,0.010,0.030} and 0.050, in order to cover the typical values expected in forthcoming surveys. The correlation function in real-space is then computed through estimation and deprojection of wp(rp). Four mass ranges (from Mhalo > 2 × 1013h-1M⊙ to Mhalo > 2 × 1014h-1M⊙) and six redshift slices covering the redshift range [0, 2] are investigated, first using cosmological redshifts and then for the four photometric redshift configurations. Results: From the analysis of the light-cone in cosmological redshifts we find a clear increase of the correlation amplitude as a function of redshift and mass. The evolution of the derived bias parameter b(M,z) is in fair agreement with theoretical expectations. We calculate the r0-d relation up to our highest mass, highest redshift sample tested (z = 2,Mhalo > 2 × 1014h-1M⊙). From our pilot sample limited to Mhalo > 5 × 1013h-1M⊙(0.4 < z < 0.7), we find that the real-space correlation function can be recovered by deprojection of wp(rp) within an accuracy of 5% for σz = 0.001 × (1 + zc) and within 10% for σz = 0.03 × (1 + zc). For higher dispersions (besides σz > 0.05 × (1 + zc)), the recovery becomes noisy and difficult. The evolution of the correlation in redshift and mass is clearly detected for all σz tested, but requires a large binning in redshift to be detected significantly between individual redshift slices when increasing σz. The best-fit parameters (r0 and γ) as well as the bias obtained from the deprojection method for all σz are within the 1σ uncertainty of the zc sample.

A Multiphase Model for the Intracluster Medium

NASA Technical Reports Server (NTRS)

Nagai, Daisuke; Sulkanen, Martin E.; Evrard, August E.

1999-01-01

Constraints on the clustered mass density of the universe derived from the observed population mean intracluster gas fraction of x-ray clusters may be biased by reliance on a single-phase assumption for the thermodynamic structure of the intracluster medium (ICM). We propose a descriptive model for multiphase structure in which a spherically symmetric ICM contains isobaric density perturbations with a radially dependent variance. Fixing the x-ray emission and emission weighted temperature, we explore two independently observable signatures of the model in the parameter space. For bremsstrahlung dominated emission, the central Sunyaev-Zel'dovich (SZ) decrement in the multiphase case is increased over the single-phase case and multiphase x-ray spectra in the range 0.1-20 keV are flatter in the continuum and exhibit stronger low energy emission lines than their single-phase counterpart. We quantify these effects for a fiducial 10e8 K cluster and demonstrate how the combination of SZ and x-ray spectroscopy can be used to identify a preferred location in the plane of the model parameter space. From these parameters the correct value of mean intracluster gas fraction in the multiphase model results, allowing an unbiased estimate of clustered mass density to he recovered.

Hierarchical trie packet classification algorithm based on expectation-maximization clustering

PubMed Central

Bi, Xia-an; Zhao, Junxia

2017-01-01

With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm. PMID:28704476

Depth data research of GIS based on clustering analysis algorithm

NASA Astrophysics Data System (ADS)

Xiong, Yan; Xu, Wenli

2018-03-01

The data of GIS have spatial distribution. Geographic data has both spatial characteristics and attribute characteristics, and also changes with time. Therefore, the amount of data is very large. Nowadays, many industries and departments in the society are using GIS. However, without proper data analysis and mining scheme, GIS will not exert its maximum effectiveness and will waste a lot of data. In this paper, we use the geographic information demand of a national security department as the experimental object, combining the characteristics of GIS data, taking into account the characteristics of time, space, attributes and so on, and using cluster analysis algorithm. We further study the mining scheme for depth data, and get the algorithm model. This algorithm can automatically classify sample data, and then carry out exploratory analysis. The research shows that the algorithm model and the information mining scheme can quickly find hidden depth information from the surface data of GIS, thus improving the efficiency of the security department. This algorithm can also be extended to other fields.

On the problem of earthquake correlation in space and time over large distances

NASA Astrophysics Data System (ADS)

Georgoulas, G.; Konstantaras, A.; Maravelakis, E.; Katsifarakis, E.; Stylios, C. D.

2012-04-01

A quick examination of geographical maps with the epicenters of earthquakes marked on them reveals a strong tendency of these points to form compact clusters of irregular shapes and various sizes often traversing with other clusters. According to [Saleur et al. 1996] "earthquakes are correlated in space and time over large distances". This implies that seismic sequences are not formatted randomly but they follow a spatial pattern with consequent triggering of events. Seismic cluster formation is believed to be due to underlying geological natural hazards, which: a) act as the energy storage elements of the phenomenon, and b) tend to form a complex network of numerous interacting faults [Vallianatos and Tzanis, 1998]. Therefore it is imperative to "isolate" meaningful structures (clusters) in order to mine information regarding the underlying mechanism and at a second stage to test the causality effect implied by what is known as the Domino theory [Burgman, 2009]. Ongoing work by Konstantaras et al. 2011 and Katsifarakis et al. 2011 on clustering seismic sequences in the area of the Southern Hellenic Arc and progressively throughout the Greek vicinity and the entire Mediterranean region based on an explicit segmentation of the data based both on their temporal and spatial stamp, following modelling assumptions proposed by Dobrovolsky et al. 1989 and Drakatos et al. 2001, managed to identify geologically validated seismic clusters. These results suggest that that the time component should be included as a dimension during the clustering process as seismic cluster formation is dynamic and the emerging clusters propagate in time. Another issue that has not been investigated yet explicitly is the role of the magnitude of each seismic event. In other words the major seismic event should be treated differently compared to pre or post seismic sequences. Moreover the sometimes irregular and elongated shapes that appear on geophysical maps means that clustering algorithms such as the well known k-means that tend to form "well-shaped" clusters may not suffice for the problem at hand and other families of unsupervised pattern recognition methods might be a better choice. One such algorithm is the DBSCAN algorithm which is based on the notion of density. In this proposed version the density is not estimated solely on the number of seismic events occurring at a specific spatio-temporal area, but also takes into account the size of the seismic event. A second method proposes the use of a modified measure of proximity that will also account for the size of the earthquake along with traditional clustering schemes such as k-means and agglomerative clustering (k-means is seeded with a quite large number for k and the results are fed to the hierarchical algorithm in order to alleviate the memory requirements on one hand and also allow for irregular shapes on the other hand). Preliminary results of seismic cluster formation using these algorithms appear promising as they are in agreement with geophysical observations on distinct seismic regions, such as those of the neighbouring regions in the Ionian sea and that of the southern Hellenic seismic arc; as well as by the location and orientation of the mapped network of underlying natural hazards beneath each clusters vicinity.

Observations and Modeling of Merging Galaxy Clusters

NASA Astrophysics Data System (ADS)

Golovich, Nathan Ryan

Context: Galaxy clusters grow hierarchically with continuous accretion bookended by major merging events that release immense gravitational potential energy (as much as ˜1065 erg). This energy creates an environment for rich astrophysics. Precise measurements of the dark matter halo, intracluster medium, and galaxy population have resulted in a number of important results including dark matter constraints and explanations of the generation of cosmic rays. However, since the timescale of major mergers (˜several Gyr) relegates observations of individual systems to mere snapshots, these results are difficult to understand under a consistent dynamical framework. While computationally expensive simulations are vital in this regard, the vastness of parameter space has necessitated simulations of idealized mergers that are unlikely to capture the full richness. Merger speeds, geometries, and timescales each have a profound consequential effect, but even these simple dynamical properties of the mergers are often poorly understood. A method to identify and constrain the best systems for probing the rich astrophysics of merging clusters is needed. Such a method could then be utilized to prioritize observational follow up and best inform proper exploration of dynamical phase space. Task: In order to identify and model a large number of systems, in this dissertation, we compile an ensemble of major mergers each containing radio relics. We then complete a pan-chromatic study of these 29 systems including wide field optical photometry, targeted optical spectroscopy of member galaxies, radio, and X-ray observations. We use the optical observations to model the galaxy substructure and estimate line of sight motion. In conjunction with the radio and X-ray data, these substructure models helped elucidate the most likely merger scenario for each system and further constrain the dynamical properties of each system. We demonstrate the power of this technique through detailed analyses of two individual merging clusters. Each are largely bimodal mergers occurring in the plane of the sky. We build on the dynamical analyses of Dawson (2013b) and Ng et al. (2015) in order to constrain the merger speeds, timescales, and geometry for these two systems, which are among a gold sample earmarked for further follow up. Findings: MACS J1149.5+2223 has a previously unidentified southern subcluster involved in a major merger with the well-studied northern subcluster. We confirm the system to be among the most massive clusters known, and we study the dynamics of the merger. MACS J1149.5+2223 appears to be a more evolved system than the Bullet Cluster observed near apocenter. ZwCl 0008.8+5215 is a less massive but a bimodal system with two radio relics and a cool-core "bullet" analogous to the namesake of the Bullet Cluster. These two systems occupy different regions of merger phase space with the pericentric relative velocities of ˜2800 km s-1 and ˜1800 km s-1 for MACS J1149.5+2223 and ZwCl 0008.8+5215, respectively. The time since pericenter for the observed states are ˜1.2 Gyr and ˜0.8 Gyr, respectivel. In the ensemble analysis, we confirm that radio relic selection is an efficient trigger for the identification of major mergers. In particular, 28 of the 29 systems exhibit galaxy substructure aligned with the radio relics and the disturbed intra-cluster medium. Radio relics are typically aligned within 20° of the axis connecting the two galaxy subclusters. Furthermore, when radio relics are aligned with substructure, the line of sight velocity difference between the two subclusters is small compared with the infall velocity. This strongly implies radio relic selection is an efficient selector of systems merging in the plane of the sky. While many of the systems are complex with several simultaneous merging subclusters, these systems generally only contain one radio relic. Systems with double radio relics uniformly suggest major mergers with two dominant substructures well aligned between the radio relics. Conclusions: Radio relics are efficient triggers for identifying major mergers occurring within the plane of the sky. This is ideal for observing offsets between galaxies and dark matter distributions as well as cluster shocks. Double radio relic systems, in particular, have the simplest geometries, which allow for accurate dynamical models and inferred astrophysics. Comparing and contrasting the dynamical models of MACS J1149.5+2223 and ZwCl 0008.8+5215 with similar studies in the literature (Dawson, 2013b; Ng et al., 2015; van Weeren et al., 2017), a wide range of dynamical phase space (˜ 1500 - 3000 km -1 at pericenter and ˜ 500 - 1500 Myr after pericenter) may be sampled with radio relic mergers. With sufficient samples of bimodal systems, velocity dependence of underlying astrophysics may be uncovered. (Abstract shortened by ProQuest.).

Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction

ERIC Educational Resources Information Center

Trivedi, Shubhendu; Pardos, Zachary A.; Sarkozy, Gabor N.; Heffernan, Neil T.

2012-01-01

Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data into homogeneous groups by clustering so that separate models could be trained on each cluster. Intuitively each such predictor is a better representative of…

THE CLUSTERING CHARACTERISTICS OF H I-SELECTED GALAXIES FROM THE 40% ALFALFA SURVEY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, Ann M.; Giovanelli, Riccardo; Haynes, Martha P.

The 40% Arecibo Legacy Fast ALFA survey catalog ({alpha}.40) of {approx}10,150 H I-selected galaxies is used to analyze the clustering properties of gas-rich galaxies. By employing the Landy-Szalay estimator and a full covariance analysis for the two-point galaxy-galaxy correlation function, we obtain the real-space correlation function and model it as a power law, {xi}(r) = (r/r{sub 0}){sup -{gamma}}, on scales <10 h{sup -1} Mpc. As the largest sample of blindly H I-selected galaxies to date, {alpha}.40 provides detailed understanding of the clustering of this population. We find {gamma} = 1.51 {+-} 0.09 and r{sub 0} = 3.3 + 0.3, -0.2more » h{sup -1} Mpc, reinforcing the understanding that gas-rich galaxies represent the most weakly clustered galaxy population known; we also observe a departure from a pure power-law shape at intermediate scales, as predicted in {Lambda}CDM halo occupation distribution models. Furthermore, we measure the bias parameter for the {alpha}.40 galaxy sample and find that H I galaxies are severely antibiased on small scales, but only weakly antibiased on large scales. The robust measurement of the correlation function for gas-rich galaxies obtained via the {alpha}.40 sample constrains models of the distribution of H I in simulated galaxies, and will be employed to better understand the role of gas in environmentally dependent galaxy evolution.« less

Models of red giants in the CoRoT asteroseismology fields combining asteroseismic and spectroscopic constraints - The open cluster NGC 6633 and field stars-

NASA Astrophysics Data System (ADS)

Lagarde, Nadège; Miglio, Andrea; Eggenberger, Patrick; Morel, Thierry; Montalbàn, Josefina; Mosser, Benoit

2015-08-01

The availability of asteroseismic constraints for a large sample of red giant stars from the CoRoT and Kepler missions paves the way for various statistical studies of the seismic properties of stellar populations.We use the first detailed spectroscopic study of CoRoT red-giant stars (Morel et al 2014) to compare theoretical stellar evolution models to observations of the open cluster NGC 6633 and field stars.In order to explore the effects of rotation-induced mixing and thermohaline instability, we compare surface abundances of carbon isotopic ratio and lithium with stellar evolution predictions. These chemicals are sensitive to extra-mixing on the red-giant branch.We estimate mass, radius, and distance for each star using the seismic constraints. We note that the Hipparcos and seismic distances are different. However, the uncertainties are such that this may not be significant. Although the seismic distances for the cluster members are self consistent they are somewhat larger than the Hipparcos distance. This is an issue that should be considered elsewhere. Models including thermohaline instability and rotation-induced mixing, together with the seismically determined masses can explain the chemical properties of red-giants targets. Tighter constraints on the physics of the models would be possible if there were detailed knowledge of the core rotation rate and the asymptotic period spacing.

Bayesian Analysis and Characterization of Multiple Populations in Galactic Globular Clusters

NASA Astrophysics Data System (ADS)

Wagner-Kaiser, Rachel A.; Stenning, David; Sarajedini, Ata; von Hippel, Ted; van Dyk, David A.; Robinson, Elliot; Stein, Nathan; Jefferys, William H.; BASE-9, HST UVIS Globular Cluster Treasury Program

2017-01-01

Globular clusters have long been important tools to unlock the early history of galaxies. Thus, it is crucial we understand the formation and characteristics of the globular clusters (GCs) themselves. Historically, GCs were thought to be simple and largely homogeneous populations, formed via collapse of a single molecular cloud. However, this classical view has been overwhelmingly invalidated by recent work. It is now clear that the vast majority of globular clusters in our Galaxy host two or more chemically distinct populations of stars, with variations in helium and light elements at discrete abundance levels. No coherent story has arisen that is able to fully explain the formation of multiple populations in globular clusters nor the mechanisms that drive stochastic variations from cluster to cluster.We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival ACS Treasury observations of 30 Galactic Globular Clusters to characterize two distinct stellar populations. A sophisticated Bayesian technique is employed to simultaneously sample the joint posterior distribution of age, distance, and extinction for each cluster, as well as unique helium values for two populations within each cluster and the relative proportion of those populations. We find the helium differences among the two populations in the clusters fall in the range of 0.04 to 0.11. Because adequate models varying in CNO are not presently available, we view these spreads as upper limits and present them with statistical rather than observational uncertainties. Evidence supports previous studies suggesting an increase in helium content concurrent with increasing mass of the cluster. We also find that the proportion of the first population of stars increases with mass. Our results are examined in the context of proposed globular cluster formation scenarios.

Resident perspectives of the open space conservation subdivision in Hamburg Township, Michigan

Treesearch

Maureen E. Austin

2004-01-01

The open space conservation subdivision (R.G. Arendt, 1996) has been presented as an alternative to conventional large lot residential development. A form of clustering, this planning approach emphasizes the quality as well as the quantity of land preserved. The format offers a means for local planning officials to accommodate residential growth while preserving...

The Large Local Hole in the Galaxy Distribution: The 2MASS Galaxy Angular Power Spectrum

NASA Astrophysics Data System (ADS)

Frith, W. J.; Outram, P. J.; Shanks, T.

2005-06-01

We present new evidence for a large deficiency in the local galaxy distribution situated in the ˜4000 deg2 APM survey area. We use models guided by the 2dF Galaxy Redshift Survey (2dFGRS) n(z) as a probe of the underlying large-scale structure. We first check the usefulness of this technique by comparing the 2dFGRS n(z) model prediction with the K-band and B-band number counts extracted from the 2MASS and 2dFGRS parent catalogues over the 2dFGRS Northern and Southern declination strips, before turning to a comparison with the APM counts. We find that the APM counts in both the B and K-bands indicate a deficiency in the local galaxy distribution of ˜30% to z ≈ 0.1 over the entire APM survey area. We examine the implied significance of such a large local hole, considering several possible forms for the real-space correlation function. We find that such a deficiency in the APM survey area indicates an excess of power at large scales over what is expected from the correlation function observed in 2dFGRS correlation function or predicted from ΛCDM Hubble Volume mock catalogues. In order to check further the clustering at large scales in the 2MASS data, we have calculated the angular power spectrum for 2MASS galaxies. Although in the linear regime (l<30), ΛCDM models can give a good fit to the 2MASS angular power spectrum, over a wider range (l<100) the power spectrum from Hubble Volume mock catalogues suggests that scale-dependent bias may be needed for ΛCDM to fit. However, the modest increase in large-scale power observed in the 2MASS angular power spectrum is still not enough to explain the local hole. If the APM survey area really is 25% deficient in galaxies out to z≈0.1, explanations for the disagreement with observed galaxy clustering statistics include the possibilities that the galaxy clustering is non-Gaussian on large scales or that the 2MASS volume is still too small to represent a `fair sample' of the Universe. Extending the 2dFGRS redshift survey over the whole APM area would resolve many of the remaining questions about the existence and interpretation of this local hole.

Spatial Distribution of Large Cloud Drops

NASA Technical Reports Server (NTRS)

Marshak, A.; Knyazikhin, Y.; Larsen, M.; Wiscombe, W.

2004-01-01

By analyzing aircraft measurements of individual drop sizes in clouds, we have shown in a companion paper (Knyazikhin et al., 2004) that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)) where 0 less than or equal to D(r) less than or equal to 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, these models show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics explaining how rain can form so fast. It also helps explain why remotely sensed cloud drop size is generally biased and why clouds absorb more sunlight than conventional radiative transfer models predict.

Improving 3d Spatial Queries Search: Newfangled Technique of Space Filling Curves in 3d City Modeling

NASA Astrophysics Data System (ADS)

Uznir, U.; Anton, F.; Suhaibah, A.; Rahman, A. A.; Mioc, D.

2013-09-01

The advantages of three dimensional (3D) city models can be seen in various applications including photogrammetry, urban and regional planning, computer games, etc.. They expand the visualization and analysis capabilities of Geographic Information Systems on cities, and they can be developed using web standards. However, these 3D city models consume much more storage compared to two dimensional (2D) spatial data. They involve extra geometrical and topological information together with semantic data. Without a proper spatial data clustering method and its corresponding spatial data access method, retrieving portions of and especially searching these 3D city models, will not be done optimally. Even though current developments are based on an open data model allotted by the Open Geospatial Consortium (OGC) called CityGML, its XML-based structure makes it challenging to cluster the 3D urban objects. In this research, we propose an opponent data constellation technique of space-filling curves (3D Hilbert curves) for 3D city model data representation. Unlike previous methods, that try to project 3D or n-dimensional data down to 2D or 3D using Principal Component Analysis (PCA) or Hilbert mappings, in this research, we extend the Hilbert space-filling curve to one higher dimension for 3D city model data implementations. The query performance was tested using a CityGML dataset of 1,000 building blocks and the results are presented in this paper. The advantages of implementing space-filling curves in 3D city modeling will improve data retrieval time by means of optimized 3D adjacency, nearest neighbor information and 3D indexing. The Hilbert mapping, which maps a subinterval of the [0, 1] interval to the corresponding portion of the d-dimensional Hilbert's curve, preserves the Lebesgue measure and is Lipschitz continuous. Depending on the applications, several alternatives are possible in order to cluster spatial data together in the third dimension compared to its clustering in 2D.

A History of H i Stripping in Virgo: A Phase-space View of VIVA Galaxies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoon, Hyein; Chung, Aeree; Smith, Rory

We investigate the orbital histories of Virgo galaxies at various stages of H i gas stripping. In particular, we compare the location of galaxies with different H i morphology in phase space. This method is a great tool for tracing the gas stripping histories of galaxies as they fall into the cluster. Most galaxies at the early stage of H i stripping are found in the first infall region of Virgo, while galaxies undergoing active H i stripping mostly appear to be falling in or moving out near the cluster core for the first time. Galaxies with severely stripped, yetmore » symmetric, H i disks are found in one of two locations. Some are deep inside the cluster, but others are found in the cluster outskirts with low orbital velocities. We suggest that the latter group of galaxies belong to a “backsplash” population. These present the clearest candidates for backsplashed galaxies observationally identified to date. We further investigate the distribution of a large sample of H i-detected galaxies toward Virgo in phase space, confirming that most galaxies are stripped of their gas as they settle into the gravitational potential of the cluster. In addition, we discuss the impact of tidal interactions between galaxies and group preprocessing on the H i properties of the cluster galaxies, and link the associated star formation evolution to the stripping sequence of cluster galaxies.« less

Astrobiological complexity with probabilistic cellular automata.

PubMed

Vukotić, Branislav; Ćirković, Milan M

2012-08-01

The search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling the astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous space of the input parameters. We perform a simple clustering analysis of typical astrobiological histories with "Copernican" choice of input parameters and discuss the relevant boundary conditions of practical importance for planning and guiding empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.

An Iterative Local Updating Ensemble Smoother for Estimation and Uncertainty Assessment of Hydrologic Model Parameters With Multimodal Distributions

NASA Astrophysics Data System (ADS)

Zhang, Jiangjiang; Lin, Guang; Li, Weixuan; Wu, Laosheng; Zeng, Lingzao

2018-03-01

Ensemble smoother (ES) has been widely used in inverse modeling of hydrologic systems. However, for problems where the distribution of model parameters is multimodal, using ES directly would be problematic. One popular solution is to use a clustering algorithm to identify each mode and update the clusters with ES separately. However, this strategy may not be very efficient when the dimension of parameter space is high or the number of modes is large. Alternatively, we propose in this paper a very simple and efficient algorithm, i.e., the iterative local updating ensemble smoother (ILUES), to explore multimodal distributions of model parameters in nonlinear hydrologic systems. The ILUES algorithm works by updating local ensembles of each sample with ES to explore possible multimodal distributions. To achieve satisfactory data matches in nonlinear problems, we adopt an iterative form of ES to assimilate the measurements multiple times. Numerical cases involving nonlinearity and multimodality are tested to illustrate the performance of the proposed method. It is shown that overall the ILUES algorithm can well quantify the parametric uncertainties of complex hydrologic models, no matter whether the multimodal distribution exists.

Understanding spatial connectivity of individuals with non-uniform population density.

PubMed

Wang, Pu; González, Marta C

2009-08-28

We construct a two-dimensional geometric graph connecting individuals placed in space within a given contact distance. The individuals are distributed using a measured country's density of population. We observe that while large clusters (group of individuals connected) emerge within some regions, they are trapped in detached urban areas owing to the low population density of the regions bordering them. To understand the emergence of a giant cluster that connects the entire population, we compare the empirical geometric graph with the one generated by placing the same number of individuals randomly in space. We find that, for small contact distances, the empirical distribution of population dominates the growth of connected components, but no critical percolation transition is observed in contrast to the graph generated by a random distribution of population. Our results show that contact distances from real-world situations as for WIFI and Bluetooth connections drop in a zone where a fully connected cluster is not observed, hinting that human mobility must play a crucial role in contact-based diseases and wireless viruses' large-scale spreading.

Transformation to equivalent dimensions—a new methodology to study earthquake clustering

NASA Astrophysics Data System (ADS)

Lasocki, Stanislaw

2014-05-01

A seismic event is represented by a point in a parameter space, quantified by the vector of parameter values. Studies of earthquake clustering involve considering distances between such points in multidimensional spaces. However, the metrics of earthquake parameters are different, hence the metric in a multidimensional parameter space cannot be readily defined. The present paper proposes a solution of this metric problem based on a concept of probabilistic equivalence of earthquake parameters. Under this concept the lengths of parameter intervals are equivalent if the probability for earthquakes to take values from either interval is the same. Earthquake clustering is studied in an equivalent rather than the original dimensions space, where the equivalent dimension (ED) of a parameter is its cumulative distribution function. All transformed parameters are of linear scale in [0, 1] interval and the distance between earthquakes represented by vectors in any ED space is Euclidean. The unknown, in general, cumulative distributions of earthquake parameters are estimated from earthquake catalogues by means of the model-free non-parametric kernel estimation method. Potential of the transformation to EDs is illustrated by two examples of use: to find hierarchically closest neighbours in time-space and to assess temporal variations of earthquake clustering in a specific 4-D phase space.

Discovery of a loose star cluster in the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Piatti, Andrés E.

2016-06-01

We present results for an up-to-date uncatalogued star cluster projected towards the Eastern side of the Large Magellanic Cloud (LMC) outer disc. The new object was discovered from a search of loose star cluster in the Magellanic Clouds' (MCs) outskirts using kernel density estimators on Washington CT1 deep images. Contrarily to what would be commonly expected, the star cluster resulted to be a young object (log(t yr-1) = 8.45) with a slightly subsolar metal content (Z = 0.013) and a total mass of 650 M⊙. Its core, half-mass and tidal radii also are within the frequent values of LMC star clusters. However, the new star cluster is placed at the Small Magellanic Cloud distance and at 11.3 kpc from the LMC centre. We speculate with the possibility that it was born in the inner body of the LMC and soon after expelled into the intergalactic space during the recent Milky Way/MCs interaction. Nevertheless, radial velocity and chemical abundance measurements are needed to further understand its origin, as well as extensive search for loose star clusters in order to constrain the effectiveness of star cluster scattering during galaxy interactions.

THROUGH THE LOOKING GLASS: HST SPECTROSCOPY OF FAINT GALAXIES LENSED BY THE FRONTIER FIELDS CLUSTER MACSJ0717.5+3745

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmidt, K. B.; Treu, T.; Wang, X.

The Grism Lens-Amplified Survey from Space (GLASS) is a Hubble Space Telescope (HST) Large Program, which will obtain 140 orbits of grism spectroscopy of the core and infall regions of 10 galaxy clusters, selected to be among the very best cosmic telescopes. Extensive HST imaging is available from many sources including the CLASH and Frontier Fields programs. We introduce the survey by analyzing spectra of faint multiply-imaged galaxies and z ≳ 6 galaxy candidates obtained from the first 7 orbits out of 14 targeting the core of the Frontier Fields cluster MACSJ0717.5+3745. Using the G102 and G141 grisms to covermore » the wavelength range 0.8-1.7 μm, we confirm four strongly lensed systems by detecting emission lines in each of the images. For the 9 z ≳ 6 galaxy candidates clear from contamination, we do not detect any emission lines down to a 7 orbit 1σ noise level of ∼5 × 10{sup –18} erg s{sup –1} cm{sup –2}. Taking lensing magnification into account, our flux sensitivity reaches ∼0.2-5 × 10{sup –18} erg s{sup –1}cm{sup –2}. These limits over an uninterrupted wavelength range rule out the possibility that the high-z galaxy candidates are instead strong line emitters at lower redshift. These results show that by means of careful modeling of the background—and with the assistance of lensing magnification—interesting flux limits can be reached for large numbers of objects, avoiding pre-selection and the wavelength restrictions inherent to ground-based multi-slit spectroscopy. These observations confirm the power of slitless HST spectroscopy even in fields as crowded as a cluster core.« less

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

PubMed

Hensman, James; Lawrence, Neil D; Rattray, Magnus

2013-08-20

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

Studies of the Virgo cluster. VI - Morphological and kinematical structure of the Virgo cluster

NASA Technical Reports Server (NTRS)

Binggeli, Bruno; Tammann, G. A.; Sandage, Allan

1987-01-01

The structure of the Virgo cluster is analyzed on the basis of the positions, Hubble types, and radial velocities of 1277 Virgo cluster galaxies. The surface distribution of galaxies is considered according to type, and is discussed using maps, isopleths, strip counts, and radial-density distributions. It is found that the Virgo cluster shows pronounced double structure. The main concentration has a large velocity dispersion and is made up predominantly of early-type galaxies, while the secondary concentration has a much smaller velocity dispersion and contains late types. There is a strong spatial segregation of the Hubble types, the early-type galaxies being more concentrated toward the cluster center. There is significant substructure in the cluster core. The irregularity of the Virgo cluster in both configuration and velocity space shows that the core and the envelope are still forming, and hence that the cluster is young.

The cosmological analysis of X-ray cluster surveys. III. 4D X-ray observable diagrams

NASA Astrophysics Data System (ADS)

Pierre, M.; Valotti, A.; Faccioli, L.; Clerc, N.; Gastaud, R.; Koulouridis, E.; Pacaud, F.

2017-11-01

Context. Despite compelling theoretical arguments, the use of clusters as cosmological probes is, in practice, frequently questioned because of the many uncertainties surrounding cluster-mass estimates. Aims: Our aim is to develop a fully self-consistent cosmological approach of X-ray cluster surveys, exclusively based on observable quantities rather than masses. This procedure is justified given the possibility to directly derive the cluster properties via ab initio modelling, either analytically or by using hydrodynamical simulations. In this third paper, we evaluate the method on cluster toy-catalogues. Methods: We model the population of detected clusters in the count-rate - hardness-ratio - angular size - redshift space and compare the corresponding four-dimensional diagram with theoretical predictions. The best cosmology+physics parameter configuration is determined using a simple minimisation procedure; errors on the parameters are estimated by averaging the results from ten independent survey realisations. The method allows a simultaneous fit of the cosmological parameters of the cluster evolutionary physics and of the selection effects. Results: When using information from the X-ray survey alone plus redshifts, this approach is shown to be as accurate as the modelling of the mass function for the cosmological parameters and to perform better for the cluster physics, for a similar level of assumptions on the scaling relations. It enables the identification of degenerate combinations of parameter values. Conclusions: Given the considerably shorter computer times involved for running the minimisation procedure in the observed parameter space, this method appears to clearly outperform traditional mass-based approaches when X-ray survey data alone are available.

Function Clustering Self-Organization Maps (FCSOMs) for mining differentially expressed genes in Drosophila and its correlation with the growth medium.

PubMed

Liu, L L; Liu, M J; Ma, M

2015-09-28

The central task of this study was to mine the gene-to-medium relationship. Adequate knowledge of this relationship could potentially improve the accuracy of differentially expressed gene mining. One of the approaches to differentially expressed gene mining uses conventional clustering algorithms to identify the gene-to-medium relationship. Compared to conventional clustering algorithms, self-organization maps (SOMs) identify the nonlinear aspects of the gene-to-medium relationships by mapping the input space into another higher dimensional feature space. However, SOMs are not suitable for huge datasets consisting of millions of samples. Therefore, a new computational model, the Function Clustering Self-Organization Maps (FCSOMs), was developed. FCSOMs take advantage of the theory of granular computing as well as advanced statistical learning methodologies, and are built specifically for each information granule (a function cluster of genes), which are intelligently partitioned by the clustering algorithm provided by the DAVID_6.7 software platform. However, only the gene functions, and not their expression values, are considered in the fuzzy clustering algorithm of DAVID. Compared to the clustering algorithm of DAVID, these experimental results show a marked improvement in the accuracy of classification with the application of FCSOMs. FCSOMs can handle huge datasets and their complex classification problems, as each FCSOM (modeled for each function cluster) can be easily parallelized.

Exponents of non-linear clustering in scale-free one-dimensional cosmological simulations

NASA Astrophysics Data System (ADS)

Benhaiem, David; Joyce, Michael; Sicard, François

2013-03-01

One-dimensional versions of dissipationless cosmological N-body simulations have been shown to share many qualitative behaviours of the three-dimensional problem. Their interest lies in the fact that they can resolve a much greater range of time and length scales, and admit exact numerical integration. We use such models here to study how non-linear clustering depends on initial conditions and cosmology. More specifically, we consider a family of models which, like the three-dimensional Einstein-de Sitter (EdS) model, lead for power-law initial conditions to self-similar clustering characterized in the strongly non-linear regime by power-law behaviour of the two-point correlation function. We study how the corresponding exponent γ depends on the initial conditions, characterized by the exponent n of the power spectrum of initial fluctuations, and on a single parameter κ controlling the rate of expansion. The space of initial conditions/cosmology divides very clearly into two parts: (1) a region in which γ depends strongly on both n and κ and where it agrees very well with a simple generalization of the so-called stable clustering hypothesis in three dimensions; and (2) a region in which γ is more or less independent of both the spectrum and the expansion of the universe. The boundary in (n, κ) space dividing the `stable clustering' region from the `universal' region is very well approximated by a `critical' value of the predicted stable clustering exponent itself. We explain how this division of the (n, κ) space can be understood as a simple physical criterion which might indeed be expected to control the validity of the stable clustering hypothesis. We compare and contrast our findings to results in three dimensions, and discuss in particular the light they may throw on the question of `universality' of non-linear clustering in this context.

Chromatin organization and global regulation of Hox gene clusters

PubMed Central

Montavon, Thomas; Duboule, Denis

2013-01-01

During development, a properly coordinated expression of Hox genes, within their different genomic clusters is critical for patterning the body plans of many animals with a bilateral symmetry. The fascinating correspondence between the topological organization of Hox clusters and their transcriptional activation in space and time has served as a paradigm for understanding the relationships between genome structure and function. Here, we review some recent observations, which revealed highly dynamic changes in the structure of chromatin at Hox clusters, in parallel with their activation during embryonic development. We discuss the relevance of these findings for our understanding of large-scale gene regulation. PMID:23650639

Dwarfs in Coma Cluster

NASA Technical Reports Server (NTRS)

2007-01-01

[figure removed for brevity, see original site] Click on image for larger poster version

This false-color mosaic of the central region of the Coma cluster combines infrared and visible-light images to reveal thousands of faint objects (green). Follow-up observations showed that many of these objects, which appear here as faint green smudges, are dwarf galaxies belonging to the cluster. Two large elliptical galaxies, NGC 4889 and NGC 4874, dominate the cluster's center. The mosaic combines visible-light data from the Sloan Digital Sky Survey (color coded blue) with long- and short-wavelength infrared views (red and green, respectively) from NASA's Spitzer Space Telescope.

Mediator and RNA polymerase II clusters associate in transcription-dependent condensates.

PubMed

Cho, Won-Ki; Spille, Jan-Hendrik; Hecht, Micca; Lee, Choongman; Li, Charles; Grube, Valentin; Cisse, Ibrahim I

2018-06-21

Models of gene control have emerged from genetic and biochemical studies, with limited consideration of the spatial organization and dynamics of key components in living cells. Here we used live cell super-resolution and light sheet imaging to study the organization and dynamics of the Mediator coactivator and RNA polymerase II (Pol II) directly. Mediator and Pol II each form small transient and large stable clusters in living embryonic stem cells. Mediator and Pol II are colocalized in the stable clusters, which associate with chromatin, have properties of phase-separated condensates, and are sensitive to transcriptional inhibitors. We suggest that large clusters of Mediator, recruited by transcription factors at large or clustered enhancer elements, interact with large Pol II clusters in transcriptional condensates in vivo. Copyright © 2018, American Association for the Advancement of Science.

A Starburst in the Core of a Galaxy Cluster: the Dwarf Irregular NGC 1427A in Fornax

NASA Astrophysics Data System (ADS)

Mora, Marcelo D.; Chanamé, Julio; Puzia, Thomas H.

2015-09-01

Gas-rich galaxies in dense environments such as galaxy clusters and massive groups are affected by a number of possible types of interactions with the cluster environment, which make their evolution radically different than that of field galaxies. The dwarf irregular galaxy NGC 1427A, presently infalling toward the core of the Fornax galaxy cluster for the first time, offers a unique opportunity to study those processes at a level of detail not possible to achieve for galaxies at higher redshifts, when galaxy-scale interactions were more common. Using the spatial resolution of the Hubble Space Telescope/Advanced Camera for Surveys and auxiliary Very Large Telescope/FORS1 ground-based observations, we study the properties of the most recent episodes of star formation in this gas-rich galaxy, the only one of its type near the core of the Fornax cluster. We study the structural and photometric properties of young star cluster complexes in NGC 1427A, identifying 12 bright such complexes with exceptionally blue colors. The comparison of our broadband near-UV/optical photometry with simple stellar population models yields ages below ˜ 4× {10}6 years and stellar masses from a few 1000 up to ˜ 3× {10}4{M}⊙ , slightly dependent on the assumption of cluster metallicity and initial mass function. Their grouping is consistent with hierarchical and fractal star cluster formation. We use deep Hα imaging data to determine the current star formation rate in NGC 1427A and estimate the ratio, Γ, of star formation occurring in these star cluster complexes to that in the entire galaxy. We find Γ to be among the largest such values available in the literature, consistent with starburst galaxies. Thus a large fraction of the current star formation in NGC 1427A is occurring in star clusters, with the peculiar spatial arrangement of such complexes strongly hinting at the possibility that the starburst is being triggered by the passage of the galaxy through the cluster environment. Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 70.B-0695.

SACS: Spitzer Archival Cluster Survey

NASA Astrophysics Data System (ADS)

Stern, Daniel

Emerging from the cosmic web, galaxy clusters are the most massive gravitationally bound structures in the universe. Thought to have begun their assembly at z > 2, clusters provide insights into the growth of large-scale structure as well as the physics that drives galaxy evolution. Understanding how and when the most massive galaxies assemble their stellar mass, stop forming stars, and acquire their observed morphologies in these environments remain outstanding questions. The redshift range 1.3 < z < 2 is a key epoch in this respect: elliptical galaxies start to become the dominant population in cluster cores, and star formation in spiral galaxies is being quenched. Until recently, however, this redshift range was essentially unreachable with available instrumentation, with clusters at these redshifts exceedingly challenging to identify from either ground-based optical/nearinfrared imaging or from X-ray surveys. Mid-infrared (MIR) imaging with the IRAC camera on board of the Spitzer Space Telescope has changed the landscape. High-redshift clusters are easily identified in the MIR due to a combination of the unique colors of distant galaxies and a negative k-correction in the 3-5 μm range which makes such galaxies bright. Even 90-sec observations with Spitzer/IRAC, a depth which essentially all extragalactic observations in the archive achieve, is sufficient to robustly detect overdensities of L* galaxies out to z~2. Here we request funding to embark on a ambitious scientific program, the “SACS: Spitzer Archival Cluster Survey”, a comprehensive search for the most distant galaxy clusters in all Spitzer/IRAC extragalactic pointings available in the archive. With the SACS we aim to discover ~2000 of 1.3 < z < 2.5 clusters, thus provide the ultimate catalog for high-redshift MIR selected clusters: a lasting legacy for Spitzer. The study we propose will increase by more than a factor of 10 the number of high-redshift clusters discovered by all previous surveys combined, providing a high-purity, uniform sample. Matching the Spitzer/IRAC-selected clusters with data at similar and longer wavelengths available in the archive (WISE 3- 5μm, Spitzer/MIPS 24μm or Herschel/SPIRE 250μm data) we will be also able to study the dependence on the environment of star formation and AGN activity out to z~2, and to study the effect of star-forming galaxies and AGNs on cosmological results from ongoing Sunyaev-Zel'dovich (SZ) and X-ray cluster surveys. The identified clusters will be valuable for both astrophysics and cosmology. In terms of astrophysics, the redshift probed by the MIR color selection targets a key epoch in cluster development, when star formation is shutting down and the galaxies are becoming passive. Massive clusters also distort space-time around them, creating powerful gravitational telescopes that lens the distant universe. This both allows detailed studies of the lensed objects with otherwise unachievable sensitivity, as well as provides a unique probe of the mass distribution in the lensing cluster. In terms of cosmology, clusters are the most massive structures in the universe, and their space density is sensitive to basic cosmological parameters. Clusters identified by this program will become a lasting legacy of Spitzer, providing exciting targets for Chandra, Hubble, James Webb Space Telescope (JWST), Astro-H, Athena, as well as future 30-m class ground-based telescopes (e.g., GMT, ELT, TMT). The upcoming large-scale, space-based surveys of eROSITA, Euclid, and WFIRST all have distant cluster studies as key scientific goals. Our proposed survey will provide new high redshift targets for those satellites, enabling unique, exciting multi-wavelength studies of the Spitzer-selected sample, as well as a training set to identify additional high-redshift clusters outside of the Spitzer footprint.

Parameters of oscillation generation regions in open star cluster models

NASA Astrophysics Data System (ADS)

Danilov, V. M.; Putkov, S. I.

2017-07-01

We determine the masses and radii of central regions of open star cluster (OCL) models with small or zero entropy production and estimate the masses of oscillation generation regions in clustermodels based on the data of the phase-space coordinates of stars. The radii of such regions are close to the core radii of the OCL models. We develop a new method for estimating the total OCL masses based on the cluster core mass, the cluster and cluster core radii, and radial distribution of stars. This method yields estimates of dynamical masses of Pleiades, Praesepe, and M67, which agree well with the estimates of the total masses of the corresponding clusters based on proper motions and spectroscopic data for cluster stars.We construct the spectra and dispersion curves of the oscillations of the field of azimuthal velocities v φ in OCL models. Weak, low-amplitude unstable oscillations of v φ develop in cluster models near the cluster core boundary, and weak damped oscillations of v φ often develop at frequencies close to the frequencies of more powerful oscillations, which may reduce the non-stationarity degree in OCL models. We determine the number and parameters of such oscillations near the cores boundaries of cluster models. Such oscillations points to the possible role that gradient instability near the core of cluster models plays in the decrease of the mass of the oscillation generation regions and production of entropy in the cores of OCL models with massive extended cores.

The HST Frontier Fields: High-Level Science Data Products for the First 4 Completed Clusters, and Latest Data on the Remaining Clusters

NASA Astrophysics Data System (ADS)

Koekemoer, Anton M.; Mack, Jennifer; Lotz, Jennifer; Anderson, Jay; Avila, Roberto J.; Barker, Elizabeth A.; Borncamp, David; Gunning, Heather C.; Hilbert, Bryan; Khandrika, Harish G.; Lucas, Ray A.; Ogaz, Sara; Porterfield, Blair; Grogin, Norman A.; Robberto, Massimo; Flanagan, Kathryn; Mountain, Matt; HST Frontier Fields Team

2016-01-01

The Hubble Space Telescope Frontier Fields program is a large Director's Discretionary program of 840 orbits, to obtain ultra-deep observations of six strong lensing clusters of galaxies, together with parallel deep blank fields, making use of the strong lensing amplification by these clusters of distant background galaxies to detect the faintest galaxies currently observable in the high-redshift universe. The first four of these clusters are now complete, namely Abell 2744, MACS J0416.1-2403, MACS J0717.5+3745 and MACS J1149.5+2223, with each of these having been observed over two epochs, to a total depth of 140 orbits on the main cluster and an associated parallel field, using ACS (F435W, F606W, F814W) and WFC3/IR (F105W, F125W, F140W, F160W). The remaining two clusters, Abell 370 and Abell S1063, are currently in progress. Full sets of high-level science products have been generated for all these clusters by the team at STScI, including a total of 24 separate cumulative-depth data releases during each epoch, as well as full-depth version 1.0 releases at the end of each completed epoch. These products include all the full-depth distortion-corrected mosaics and associated products for each cluster, which are science-ready to facilitate the construction of lensing models as well as enabling a wide range of other science projects. Many improvements beyond default calibration for ACS and WFC3/IR are implemented in these data products, including corrections for persistence, time-variable sky, and low-level dark current residuals, as well as improvements in astrometric alignment to achieve milliarcsecond-level accuracy. The resulting high-level science products are delivered via the Mikulski Archive for Space Telescopes (MAST) to the community on a rapid timescale to enable the widest scientific use of these data, as well as ensuring a public legacy dataset of the highest possible quality that is of lasting value to the entire community.

The HST Frontier Fields: High-Level Science Data Products for the First 4 Completed Clusters, and for the Last 2 Clusters Currently in Progress

NASA Astrophysics Data System (ADS)

Koekemoer, Anton M.; Mack, Jennifer; Lotz, Jennifer M.; Anderson, Jay; Avila, Roberto J.; Barker, Elizabeth A.; Borncamp, David; Gunning, Heather C.; Hilbert, Bryan; Khandrika, Harish G.; Lucas, Ray A.; Ogaz, Sara; Porterfield, Blair; Sunnquist, Ben; Grogin, Norman A.; Robberto, Massimo; Sembach, Kenneth; Flanagan, Kathryn; Mountain, Matt; HST Frontier Fields Team

2016-06-01

The Hubble Space Telescope Frontier Fields program (PI: J. Lotz) is a large Director's Discretionary program of 840 orbits, to obtain ultra-deep observations of six strong lensing clusters of galaxies, together with parallel deep blank fields, making use of the strong lensing amplification by these clusters of distant background galaxies to detect the faintest galaxies currently observable in the high-redshift universe. The first four of these clusters are now complete, namely Abell 2744, MACS J0416.1-2403, MACS J0717.5+3745 and MACS J1149.5+2223, with each of these having been observed over two epochs, to a total depth of 140 orbits on the main cluster and an associated parallel field, using ACS (F435W, F606W, F814W) and WFC3/IR (F105W, F125W, F140W, F160W). The remaining two clusters, Abell 370 and Abell S1063, are currently in progress, with the first epoch for each having been completed. Full sets of high-level science products have been generated for all these clusters by the team at STScI, including cumulative-depth v0.5 data releases during each epoch, as well as full-depth version 1.0 releases after the completion of each epoch. These products include all the full-depth distortion-corrected mosaics and associated products for each cluster, which are science-ready to facilitate the construction of lensing models as well as enabling a wide range of other science projects. Many improvements beyond default calibration for ACS and WFC3/IR are implemented in these data products, including corrections for persistence, time-variable sky, and low-level dark current residuals, as well as improvements in astrometric alignment to achieve milliarcsecond-level accuracy. The full set of resulting high-level science products are publicly delivered to the community via the Mikulski Archive for Space Telescopes (MAST) to enable the widest scientific use of these data, as well as ensuring a public legacy dataset of the highest possible quality that is of lasting value to the entire community.

Predicting lower mantle heterogeneity from 4-D Earth models

NASA Astrophysics Data System (ADS)

Flament, Nicolas; Williams, Simon; Müller, Dietmar; Gurnis, Michael; Bower, Dan J.

2016-04-01

The Earth's lower mantle is characterized by two large-low-shear velocity provinces (LLSVPs), approximately ˜15000 km in diameter and 500-1000 km high, located under Africa and the Pacific Ocean. The spatial stability and chemical nature of these LLSVPs are debated. Here, we compare the lower mantle structure predicted by forward global mantle flow models constrained by tectonic reconstructions (Bower et al., 2015) to an analysis of five global tomography models. In the dynamic models, spanning 230 million years, slabs subducting deep into the mantle deform an initially uniform basal layer containing 2% of the volume of the mantle. Basal density, convective vigour (Rayleigh number Ra), mantle viscosity, absolute plate motions, and relative plate motions are varied in a series of model cases. We use cluster analysis to classify a set of equally-spaced points (average separation ˜0.45°) on the Earth's surface into two groups of points with similar variations in present-day temperature between 1000-2800 km depth, for each model case. Below ˜2400 km depth, this procedure reveals a high-temperature cluster in which mantle temperature is significantly larger than ambient and a low-temperature cluster in which mantle temperature is lower than ambient. The spatial extent of the high-temperature cluster is in first-order agreement with the outlines of the African and Pacific LLSVPs revealed by a similar cluster analysis of five tomography models (Lekic et al., 2012). Model success is quantified by computing the accuracy and sensitivity of the predicted temperature clusters in predicting the low-velocity cluster obtained from tomography (Lekic et al., 2012). In these cases, the accuracy varies between 0.61-0.80, where a value of 0.5 represents the random case, and the sensitivity ranges between 0.18-0.83. The largest accuracies and sensitivities are obtained for models with Ra ≈ 5 x 107, no asthenosphere (or an asthenosphere restricted to the oceanic domain), and a basal layer ˜ 4% denser than ambient mantle. Increasing convective vigour (Ra ≈ 5 x 108) or decreasing the density of the basal layer decreases both the accuracy and sensitivity of the predicted lower mantle structure. References: D. J. Bower, M. Gurnis, N. Flament, Assimilating lithosphere and slab history in 4-D Earth models. Phys. Earth Planet. Inter. 238, 8-22 (2015). V. Lekic, S. Cottaar, A. Dziewonski, B. Romanowicz, Cluster analysis of global lower mantle tomography: A new class of structure and implications for chemical heterogeneity. Earth Planet. Sci. Lett. 357, 68-77 (2012).

Cluster Dynamical Mass from Magellan Multi-Object Spectroscopy for SGAS Clusters

NASA Astrophysics Data System (ADS)

Murray, Katherine; Sharon, Keren; Johnson, Traci; Gifford, Daniel; Gladders, Michael; Bayliss, Matthew; Florian, Michael; Rigby, Jane R.; Miller, Christopher J.

2016-01-01

Galaxy clusters are giant structures in space consisting of hundreds or thousands of galaxies, interstellar matter, and dark matter, all bound together by gravity. We analyze the spectra of the cluster members of several strong lensing clusters from a large program, the Sloan Giant Arcs Survey, to determine the total mass of the lensing clusters. From spectra obtained with the LDSS3 and IMACS cameras on the Magellan 6.5m telescopes, we measure the spectroscopic redshifts of about 50 galaxies in each cluster, and calculate the velocity distributions within the galaxy clusters, as well as their projected cluster-centric radii. From these two pieces of information, we measure the size and total dynamical mass of each cluster. We can combine this calculation with other measurements of mass of the same galaxy clusters (like measurements from strong lensing or X-ray) to determine the spatial distribution of luminous and dark matter out to the virial radius of the cluster.

Fault Tolerant Frequent Pattern Mining

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shohdy, Sameh; Vishnu, Abhinav; Agrawal, Gagan

FP-Growth algorithm is a Frequent Pattern Mining (FPM) algorithm that has been extensively used to study correlations and patterns in large scale datasets. While several researchers have designed distributed memory FP-Growth algorithms, it is pivotal to consider fault tolerant FP-Growth, which can address the increasing fault rates in large scale systems. In this work, we propose a novel parallel, algorithm-level fault-tolerant FP-Growth algorithm. We leverage algorithmic properties and MPI advanced features to guarantee an O(1) space complexity, achieved by using the dataset memory space itself for checkpointing. We also propose a recovery algorithm that can use in-memory and disk-based checkpointing,more » though in many cases the recovery can be completed without any disk access, and incurring no memory overhead for checkpointing. We evaluate our FT algorithm on a large scale InfiniBand cluster with several large datasets using up to 2K cores. Our evaluation demonstrates excellent efficiency for checkpointing and recovery in comparison to the disk-based approach. We have also observed 20x average speed-up in comparison to Spark, establishing that a well designed algorithm can easily outperform a solution based on a general fault-tolerant programming model.« less

State estimation and prediction using clustered particle filters.

PubMed

Lee, Yoonsang; Majda, Andrew J

2016-12-20

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors.

State estimation and prediction using clustered particle filters

PubMed Central

Lee, Yoonsang; Majda, Andrew J.

2016-01-01

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors. PMID:27930332

Deriving photometric redshifts using fuzzy archetypes and self-organizing maps - I. Methodology

NASA Astrophysics Data System (ADS)

Speagle, Joshua S.; Eisenstein, Daniel J.

2017-07-01

We propose a method to substantially increase the flexibility and power of template fitting-based photometric redshifts by transforming a large number of galaxy spectral templates into a corresponding collection of 'fuzzy archetypes' using a suitable set of perturbative priors designed to account for empirical variation in dust attenuation and emission-line strengths. To bypass widely separated degeneracies in parameter space (e.g. the redshift-reddening degeneracy), we train self-organizing maps (SOMs) on large 'model catalogues' generated from Monte Carlo sampling of our fuzzy archetypes to cluster the predicted observables in a topologically smooth fashion. Subsequent sampling over the SOM then allows full reconstruction of the relevant probability distribution functions (PDFs). This combined approach enables the multimodal exploration of known variation among galaxy spectral energy distributions with minimal modelling assumptions. We demonstrate the power of this approach to recover full redshift PDFs using discrete Markov chain Monte Carlo sampling methods combined with SOMs constructed from Large Synoptic Survey Telescope ugrizY and Euclid YJH mock photometry.

GeV gamma-ray flux upper limits from clusters of galaxies

DOE PAGES

Ackermann, M.; Ajello, M.; Allafort, A.; ...

2010-06-16

The detection of diffuse radio emission associated with clusters of galaxies indicates populations of relativistic leptons infusing the intracluster medium (ICM). Those electrons and positrons are either injected into and accelerated directly in the ICM, or produced as secondary pairs by cosmic-ray ions scattering on ambient protons. Radiation mechanisms involving the energetic leptons together with the decay of neutral pions produced by hadronic interactions have the potential to produce abundant GeV photons. Here in this paper, we report on the search for GeV emission from clusters of galaxies using data collected by the Large Area Telescope on the Fermi Gamma-raymore » Space Telescope from 2008 August to 2010 February. Thirty-three galaxy clusters have been selected according to their proximity and high mass, X-ray flux and temperature, and indications of non-thermal activity for this study. We report upper limits on the photon flux in the range 0.2-100 GeV toward a sample of observed clusters (typical values (1-5) ×10 –9 photon cm –2 s –1) considering both point-like and spatially resolved models for the high-energy emission and discuss how these results constrain the characteristics of energetic leptons and hadrons, and magnetic fields in the ICM. The volume-averaged relativistic-hadron-to-thermal energy density ratio is found to be <5%-10% in several clusters.« less

A deeper look at the X-ray point source population of NGC 4472

NASA Astrophysics Data System (ADS)

Joseph, T. D.; Maccarone, T. J.; Kraft, R. P.; Sivakoff, G. R.

2017-10-01

In this paper we discuss the X-ray point source population of NGC 4472, an elliptical galaxy in the Virgo cluster. We used recent deep Chandra data combined with archival Chandra data to obtain a 380 ks exposure time. We find 238 X-ray point sources within 3.7 arcmin of the galaxy centre, with a completeness flux, FX, 0.5-2 keV = 6.3 × 10-16 erg s-1 cm-2. Most of these sources are expected to be low-mass X-ray binaries. We finding that, using data from a single galaxy which is both complete and has a large number of objects (˜100) below 1038 erg s-1, the X-ray luminosity function is well fitted with a single power-law model. By cross matching our X-ray data with both space based and ground based optical data for NGC 4472, we find that 80 of the 238 sources are in globular clusters. We compare the red and blue globular cluster subpopulations and find red clusters are nearly six times more likely to host an X-ray source than blue clusters. We show that there is evidence that these two subpopulations have significantly different X-ray luminosity distributions. Source catalogues for all X-ray point sources, as well as any corresponding optical data for globular cluster sources, are also presented here.

Neurolinguistic approach to natural language processing with applications to medical text analysis.

PubMed

Duch, Włodzisław; Matykiewicz, Paweł; Pestian, John

2008-12-01

Understanding written or spoken language presumably involves spreading neural activation in the brain. This process may be approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts not found directly in the text. The approximation of this process is of great practical and theoretical interest. Although activations of neural circuits involved in representation of words rapidly change in time snapshots of these activations spreading through associative networks may be captured in a vector model. Concepts of similar type activate larger clusters of neurons, priming areas in the left and right hemisphere. Analysis of recent brain imaging experiments shows the importance of the right hemisphere non-verbal clusterization. Medical ontologies enable development of a large-scale practical algorithm to re-create pathways of spreading neural activations. First concepts of specific semantic type are identified in the text, and then all related concepts of the same type are added to the text, providing expanded representations. To avoid rapid growth of the extended feature space after each step only the most useful features that increase document clusterization are retained. Short hospital discharge summaries are used to illustrate how this process works on a real, very noisy data. Expanded texts show significantly improved clustering and may be classified with much higher accuracy. Although better approximations to the spreading of neural activations may be devised a practical approach presented in this paper helps to discover pathways used by the brain to process specific concepts, and may be used in large-scale applications.

Using Fuzzy Clustering for Real-time Space Flight Safety

NASA Technical Reports Server (NTRS)

Lee, Charles; Haskell, Richard E.; Hanna, Darrin; Alena, Richard L.

2004-01-01

To ensure space flight safety, it is necessary to monitor myriad sensor readings on the ground and in flight. Since a space shuttle has many sensors, monitoring data and drawing conclusions from information contained within the data in real time is challenging. The nature of the information can be critical to the success of the mission and safety of the crew and therefore, must be processed with minimal data-processing time. Data analysis algorithms could be used to synthesize sensor readings and compare data associated with normal operation with the data obtained that contain fault patterns to draw conclusions. Detecting abnormal operation during early stages in the transition from safe to unsafe operation requires a large amount of historical data that can be categorized into different classes (non-risk, risk). Even though the 40 years of shuttle flight program has accumulated volumes of historical data, these data don t comprehensively represent all possible fault patterns since fault patterns are usually unknown before the fault occurs. This paper presents a method that uses a similarity measure between fuzzy clusters to detect possible faults in real time. A clustering technique based on a fuzzy equivalence relation is used to characterize temporal data. Data collected during an initial time period are separated into clusters. These clusters are characterized by their centroids. Clusters formed during subsequent time periods are either merged with an existing cluster or added to the cluster list. The resulting list of cluster centroids, called a cluster group, characterizes the behavior of a particular set of temporal data. The degree to which new clusters formed in a subsequent time period are similar to the cluster group is characterized by a similarity measure, q. This method is applied to downlink data from Columbia flights. The results show that this technique can detect an unexpected fault that has not been present in the training data set.

Cross-correlating Planck tSZ with RCSLenS weak lensing: implications for cosmology and AGN feedback

NASA Astrophysics Data System (ADS)

Hojjati, Alireza; Tröster, Tilman; Harnois-Déraps, Joachim; McCarthy, Ian G.; van Waerbeke, Ludovic; Choi, Ami; Erben, Thomas; Heymans, Catherine; Hildebrandt, Hendrik; Hinshaw, Gary; Ma, Yin-Zhe; Miller, Lance; Viola, Massimo; Tanimura, Hideki

2017-10-01

We present measurements of the spatial mapping between (hot) baryons and the total matter in the Universe, via the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) map from Planck and the weak gravitational lensing maps from the Red Cluster Sequence Lensing Survey (RCSLenS). The cross-correlations are performed on the map level where all the sources (including diffuse intergalactic gas) contribute to the signal. We consider two configuration-space correlation function estimators, ξy-κ and ξ ^ {y-γ t}, and a Fourier-space estimator, C_{ℓ}^{y-κ}, in our analysis. We detect a significant correlation out to 3° of angular separation on the sky. Based on statistical noise only, we can report 13σ and 17σ detections of the cross-correlation using the configuration-space y-κ and y-γt estimators, respectively. Including a heuristic estimate of the sampling variance yields a detection significance of 7σ and 8σ, respectively. A similar level of detection is obtained from the Fourier-space estimator, C_{ℓ}^{y-κ}. As each estimator probes different dynamical ranges, their combination improves the significance of the detection. We compare our measurements with predictions from the cosmo-OverWhelmingly Large Simulations suite of cosmological hydrodynamical simulations, where different galactic feedback models are implemented. We find that a model with considerable active galactic nuclei (AGN) feedback that removes large quantities of hot gas from galaxy groups and Wilkinson Microwave Anisotropy Probe 7-yr best-fitting cosmological parameters provides the best match to the measurements. All baryonic models in the context of a Planck cosmology overpredict the observed signal. Similar cosmological conclusions are drawn when we employ a halo model with the observed 'universal' pressure profile.

Hierarchical modeling of cluster size in wildlife surveys

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

Effects of stomata clustering on leaf gas exchange.

PubMed

Lehmann, Peter; Or, Dani

2015-09-01

A general theoretical framework for quantifying the stomatal clustering effects on leaf gaseous diffusive conductance was developed and tested. The theory accounts for stomatal spacing and interactions among 'gaseous concentration shells'. The theory was tested using the unique measurements of Dow et al. (2014) that have shown lower leaf diffusive conductance for a genotype of Arabidopsis thaliana with clustered stomata relative to uniformly distributed stomata of similar size and density. The model accounts for gaseous diffusion: through stomatal pores; via concentration shells forming at pore apertures that vary with stomata spacing and are thus altered by clustering; and across the adjacent air boundary layer. Analytical approximations were derived and validated using a numerical model for 3D diffusion equation. Stomata clustering increases the interactions among concentration shells resulting in larger diffusive resistance that may reduce fluxes by 5-15%. A similar reduction in conductance was found for clusters formed by networks of veins. The study resolves ambiguities found in the literature concerning stomata end-corrections and stomatal shape, and provides a new stomata density threshold for diffusive interactions of overlapping vapor shells. The predicted reduction in gaseous exchange due to clustering, suggests that guard cell function is impaired, limiting stomatal aperture opening. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Space-time analysis of pneumonia hospitalisations in the Netherlands.

PubMed

Benincà, Elisa; van Boven, Michiel; Hagenaars, Thomas; van der Hoek, Wim

2017-01-01

Community acquired pneumonia is a major global public health problem. In the Netherlands there are 40,000-50,000 hospital admissions for pneumonia per year. In the large majority of these hospital admissions the etiologic agent is not determined and a real-time surveillance system is lacking. Localised and temporal increases in hospital admissions for pneumonia are therefore only detected retrospectively and the etiologic agents remain unknown. Here, we perform spatio-temporal analyses of pneumonia hospital admission data in the Netherlands. To this end, we scanned for spatial clusters on yearly and seasonal basis, and applied wavelet cluster analysis on the time series of five main regions. The pneumonia hospital admissions show strong clustering in space and time superimposed on a regular yearly cycle with high incidence in winter and low incidence in summer. Cluster analysis reveals a heterogeneous pattern, with most significant clusters occurring in the western, highly urbanised, and in the eastern, intensively farmed, part of the Netherlands. Quantitatively, the relative risk (RR) of the significant clusters for the age-standardised incidence varies from a minimum of 1.2 to a maximum of 2.2. We discuss possible underlying causes for the patterns observed, such as variations in air pollution.

The formation and evolution of M33 as revealed by its star clusters

NASA Astrophysics Data System (ADS)

San Roman, Izaskun

2012-03-01

Numerical simulations based on the Lambda-Cold Dark Matter (Λ-CDM) model predict a scenario consistent with observational evidence in terms of the build-up of Milky Way-like halos. Under this scenario, large disk galaxies derive from the merger and accretion of many smaller subsystems. However, it is less clear how low-mass spiral galaxies fit into this picture. The best way to answer this question is to study the nearest example of a dwarf spiral galaxy, M33. We will use star clusters to understand the structure, kinematics and stellar populations of this galaxy. Star clusters provide a unique and powerful tool for studying the star formation histories of galaxies. In particular, the ages and metallicities of star clusters bear the imprint of the galaxy formation process. We have made use of the star clusters to uncover the formation and evolution of M33. In this dissertation, we have carried out a comprehensive study of the M33 star cluster system, including deep photometry as well as high signal-to-noise spectroscopy. In order to mitigate the significant incompleteness presents in previous catalogs, we have conducted ground-based and space-based photometric surveys of M33 star clusters. Using archival images, we have analyzed 12 fields using the Advanced Camera for Surveys Wide Field Channel onboard the Hubble Space Telescope (ACS/HST) along the major axis of the galaxy. We present integrated photometry and color-magnitude diagrams for 161 star clusters in M33, of which 115 were previously uncataloged. This survey extends the depth of the existing M33 cluster catalogs by ˜ 1 mag. We have expanded our search through a photometric survey in a 1° x 1° area centered on M33 using the MegaCam camera on the 3.6m Canada-France-Hawaii Telescope (CFHT). In this work we discuss the photometric properties of the sample, including color-color diagrams of 599 new candidate stellar clusters, and 204 confirmed clusters. Comparisons with models of simple stellar populations suggest a large range of ages some as old as ˜ 10 Gyr. In addition, we find in the color-color diagrams a significant population of very young clusters (< 10 Myr) possessing nebular emission. Analysis of the radial density distribution suggests that the cluster system of M33 has suffered from significant depletion, possibly due to interactions with M31. To further understand the properties of M33 star clusters, we have carried out a morphological study 161 star clusters in M33 using ACS/HST images. We have obtained, for the first time, ellipticities, position angles, and surface brightness profiles of a statistically significant number of clusters. Ellipticities show that, on average, M33 clusters are more flattened than those of the Milky Way and M31, and more similar to clusters in the Small Magellanic Cloud. The ellipticities do not show any correlation with age or mass, suggesting that rotation is not the main cause of elongation in the M33 clusters. The position angles of the clusters show a bimodality with a strong peak perpendicular to the position angle of the galaxy. These results support the notion that tidal forces are the reason for the cluster flattening. We have fit analytical models to the surface brightness profiles, and derived structural parameters. The overall analysis shows several differences between the structural properties of the M33 cluster system and cluster systems in nearby galaxies. Finally, we have performed a spectroscopic study of star clusters in the above mentioned catalog. We present high-precision velocity measures of 45 star clusters, based on observations from the 10.4m Gran Telescopio Canarias (GTC) using OSIRIS and 4.2m William Herschel Telescope (WHT) using WYFFOS. All the clusters have been previously confirmed using HST imaging, and ages and integrated photometry are known. The velocity of the clusters with respect to local disk motion increases with age for young and intermediate clusters. The mean dispersion velocity for the intermediate age clusters in our sample is significantly larger than in previous studies. Analysis of these velocities along the major axis of the galaxy show no net rotation of the intermediate age subsample. The small number of old clusters in our sample does not allow for any conclusive evidence in that age division.

A theoretical study of water equilibria: The cluster distribution versus temperature and pressure for (H2O)n, n=1-60, and ice

NASA Astrophysics Data System (ADS)

Lenz, Annika; Ojamäe, Lars

2009-10-01

The size distribution of water clusters at equilibrium is studied using quantum-chemical calculations in combination with statistical thermodynamics. The necessary energetic data is obtained by quantum-chemical B3LYP computations and through extrapolations from the B3LYP results for the larger clusters. Clusters with up to 60 molecules are included in the equilibrium computations. Populations of different cluster sizes are calculated using both an ideal gas model with noninteracting clusters and a model where a correction for the interaction energy is included analogous to the van der Waals law. In standard vapor the majority of the water molecules are monomers. For the ideal gas model at 1 atm large clusters [56-mer (0-120 K) and 28-mer (100-260 K)] dominate at low temperatures and separate to smaller clusters [21-22-mer (170-280 K) and 4-6-mer (270-320 K) and to monomers (300-350 K)] when the temperature is increased. At lower pressure the transition from clusters to monomers lies at lower temperatures and fewer cluster sizes are formed. The computed size distribution exhibits enhanced peaks for the clusters consisting of 21 and 28 water molecules; these sizes are for protonated water clusters often referred to as magic numbers. If cluster-cluster interactions are included in the model the transition from clusters to monomers is sharper (i.e., occurs over a smaller temperature interval) than when the ideal-gas model is used. Clusters with 20-22 molecules dominate in the liquid region. When a large icelike cluster is included it will dominate for temperatures up to 325 K for the noninteracting clusters model. Thermodynamic properties (Cp, ΔH) were calculated with in general good agreement with experimental values for the solid and gas phase. A formula for the number of H-bond topologies in a given cluster structure is derived. For the 20-mer it is shown that the number of topologies contributes to making the population of dodecahedron-shaped cluster larger than that of a lower-energy fused prism cluster at high temperatures.

A theoretical study of water equilibria: the cluster distribution versus temperature and pressure for (H2O)n, n = 1-60, and ice.

PubMed

Lenz, Annika; Ojamäe, Lars

2009-10-07

The size distribution of water clusters at equilibrium is studied using quantum-chemical calculations in combination with statistical thermodynamics. The necessary energetic data is obtained by quantum-chemical B3LYP computations and through extrapolations from the B3LYP results for the larger clusters. Clusters with up to 60 molecules are included in the equilibrium computations. Populations of different cluster sizes are calculated using both an ideal gas model with noninteracting clusters and a model where a correction for the interaction energy is included analogous to the van der Waals law. In standard vapor the majority of the water molecules are monomers. For the ideal gas model at 1 atm large clusters [56-mer (0-120 K) and 28-mer (100-260 K)] dominate at low temperatures and separate to smaller clusters [21-22-mer (170-280 K) and 4-6-mer (270-320 K) and to monomers (300-350 K)] when the temperature is increased. At lower pressure the transition from clusters to monomers lies at lower temperatures and fewer cluster sizes are formed. The computed size distribution exhibits enhanced peaks for the clusters consisting of 21 and 28 water molecules; these sizes are for protonated water clusters often referred to as magic numbers. If cluster-cluster interactions are included in the model the transition from clusters to monomers is sharper (i.e., occurs over a smaller temperature interval) than when the ideal-gas model is used. Clusters with 20-22 molecules dominate in the liquid region. When a large icelike cluster is included it will dominate for temperatures up to 325 K for the noninteracting clusters model. Thermodynamic properties (C(p), DeltaH) were calculated with in general good agreement with experimental values for the solid and gas phase. A formula for the number of H-bond topologies in a given cluster structure is derived. For the 20-mer it is shown that the number of topologies contributes to making the population of dodecahedron-shaped cluster larger than that of a lower-energy fused prism cluster at high temperatures.

Spatial organization of foreshocks as a tool to forecast large earthquakes.

PubMed

Lippiello, E; Marzocchi, W; de Arcangelis, L; Godano, C

2012-01-01

An increase in the number of smaller magnitude events, retrospectively named foreshocks, is often observed before large earthquakes. We show that the linear density probability of earthquakes occurring before and after small or intermediate mainshocks displays a symmetrical behavior, indicating that the size of the area fractured during the mainshock is encoded in the foreshock spatial organization. This observation can be used to discriminate spatial clustering due to foreshocks from the one induced by aftershocks and is implemented in an alarm-based model to forecast m > 6 earthquakes. A retrospective study of the last 19 years Southern California catalog shows that the daily occurrence probability presents isolated peaks closely located in time and space to the epicenters of five of the six m > 6 earthquakes. We find daily probabilities as high as 25% (in cells of size 0.04 × 0.04deg(2)), with significant probability gains with respect to standard models.

Spatial organization of foreshocks as a tool to forecast large earthquakes

PubMed Central

Lippiello, E.; Marzocchi, W.; de Arcangelis, L.; Godano, C.

2012-01-01

An increase in the number of smaller magnitude events, retrospectively named foreshocks, is often observed before large earthquakes. We show that the linear density probability of earthquakes occurring before and after small or intermediate mainshocks displays a symmetrical behavior, indicating that the size of the area fractured during the mainshock is encoded in the foreshock spatial organization. This observation can be used to discriminate spatial clustering due to foreshocks from the one induced by aftershocks and is implemented in an alarm-based model to forecast m > 6 earthquakes. A retrospective study of the last 19 years Southern California catalog shows that the daily occurrence probability presents isolated peaks closely located in time and space to the epicenters of five of the six m > 6 earthquakes. We find daily probabilities as high as 25% (in cells of size 0.04 × 0.04deg2), with significant probability gains with respect to standard models. PMID:23152938

Mass Loss from Dusty AGB and Red Supergiant Stars in the Magellanic Clouds and in the Galaxy

NASA Astrophysics Data System (ADS)

Sargent, Benjamin A.; Srinivasan, Sundar; Meixner, Margaret; Kastner, Joel

2016-01-01

Asymptotic giant branch (AGB) and red supergiant (RSG) stars are evolved stars that eject large parts of their mass in outflows of dust and gas. As part of an ongoing effort to measure mass loss from evolved stars in our Galaxy and in the Magellanic Clouds, we are modeling mass loss from AGB and RSG stars in these galaxies. Our approach is twofold. We pursue radiative transfer modeling of the spectral energy distributions (SEDs) of AGB and RSG stars in the Large Magellanic Cloud (LMC), in the Small Magellanic Cloud (SMC), and in the Galactic bulge and in globular clusters of the Milky Way. We are also constructing detailed dust opacity models of AGB and RSG stars in these galaxies for which we have infrared spectra; e.g., from the Spitzer Space Telescope Infrared Spectrograph (IRS). Our sample of infrared spectra largely comes from Spitzer-IRS observations. The detailed dust modeling of spectra informs our choice of dust properties to use in radiative transfer modeling of SEDs. We seek to determine how mass loss from these evolved stars depends upon the metallicity of their host environments. BAS acknowledges funding from NASA ADAP grant NNX15AF15G.

Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.

PubMed

Bansal, Ravi; Peterson, Bradley S

2018-06-01

Identifying regional effects of interest in MRI datasets usually entails testing a priori hypotheses across many thousands of brain voxels, requiring control for false positive findings in these multiple hypotheses testing. Recent studies have suggested that parametric statistical methods may have incorrectly modeled functional MRI data, thereby leading to higher false positive rates than their nominal rates. Nonparametric methods for statistical inference when conducting multiple statistical tests, in contrast, are thought to produce false positives at the nominal rate, which has thus led to the suggestion that previously reported studies should reanalyze their fMRI data using nonparametric tools. To understand better why parametric methods may yield excessive false positives, we assessed their performance when applied both to simulated datasets of 1D, 2D, and 3D Gaussian Random Fields (GRFs) and to 710 real-world, resting-state fMRI datasets. We showed that both the simulated 2D and 3D GRFs and the real-world data contain a small percentage (<6%) of very large clusters (on average 60 times larger than the average cluster size), which were not present in 1D GRFs. These unexpectedly large clusters were deemed statistically significant using parametric methods, leading to empirical familywise error rates (FWERs) as high as 65%: the high empirical FWERs were not a consequence of parametric methods failing to model spatial smoothness accurately, but rather of these very large clusters that are inherently present in smooth, high-dimensional random fields. In fact, when discounting these very large clusters, the empirical FWER for parametric methods was 3.24%. Furthermore, even an empirical FWER of 65% would yield on average less than one of those very large clusters in each brain-wide analysis. Nonparametric methods, in contrast, estimated distributions from those large clusters, and therefore, by construct rejected the large clusters as false positives at the nominal FWERs. Those rejected clusters were outlying values in the distribution of cluster size but cannot be distinguished from true positive findings without further analyses, including assessing whether fMRI signal in those regions correlates with other clinical, behavioral, or cognitive measures. Rejecting the large clusters, however, significantly reduced the statistical power of nonparametric methods in detecting true findings compared with parametric methods, which would have detected most true findings that are essential for making valid biological inferences in MRI data. Parametric analyses, in contrast, detected most true findings while generating relatively few false positives: on average, less than one of those very large clusters would be deemed a true finding in each brain-wide analysis. We therefore recommend the continued use of parametric methods that model nonstationary smoothness for cluster-level, familywise control of false positives, particularly when using a Cluster Defining Threshold of 2.5 or higher, and subsequently assessing rigorously the biological plausibility of the findings, even for large clusters. Finally, because nonparametric methods yielded a large reduction in statistical power to detect true positive findings, we conclude that the modest reduction in false positive findings that nonparametric analyses afford does not warrant a re-analysis of previously published fMRI studies using nonparametric techniques. Copyright © 2018 Elsevier Inc. All rights reserved.

Clustering analysis of high-redshift luminous red galaxies in Stripe 82

NASA Astrophysics Data System (ADS)

Nikoloudakis, N.; Shanks, T.; Sawangwit, U.

2013-03-01

We present a clustering analysis of luminous red galaxies (LRGs) in Stripe 82 from the Sloan Digital Sky Survey (SDSS). We study the angular two-point autocorrelation function, w(θ), of a selected sample of over 130 000 LRG candidates via colour-cut selections in izK with the K-band coverage coming from UKIRT (United Kingdom Infrared Telescope) Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS). We have used the cross-correlation technique of Newman to establish the redshift distribution of the LRGs. Cross-correlating them with SDSS quasi-stellar objects (QSOs), MegaZ-LRGs and DEEP Extragalactic Evolutionary Probe 2 (DEEP2) galaxies, implies an average redshift of the LRGs to be z ≈ 1 with space density, ng ≈ 3.20 ± 0.16 × 10-4 h3 Mpc-3. For θ ≤ 10 arcmin (corresponding to ≈10 h-1 Mpc), the LRG w(θ) significantly deviates from a conventional single power law as noted by previous clustering studies of highly biased and luminous galaxies. A double power law with a break at rb ≈ 2.4 h-1 Mpc fits the data better, with best-fitting scale length, r0, 1 = 7.63 ± 0.27 h-1 Mpc and slope γ1 = 2.01 ± 0.02 at small scales and r0, 2 = 9.92 ± 0.40 h-1 Mpc and γ2 = 1.64 ± 0.04 at large scales. Due to the flat slope at large scales, we find that a standard Λ cold dark matter (Λ CDM) linear model is accepted only at 2-3σ, with the best-fitting bias factor, b = 2.74 ± 0.07. We also fitted the halo occupation distribution (HOD) models to compare our measurements with the predictions of the dark matter clustering. The effective halo mass of Stripe 82 LRGs is estimated as Meff = 3.3 ± 0.6 × 1013 h-1 M⊙. But at large scales, the current HOD models did not help explain the power excess in the clustering signal. We then compare the w(θ) results to the results of Sawangwit et al. from three samples of photometrically selected LRGs at lower redshifts to measure clustering evolution. We find that a long-lived model may be a poorer fit than at lower redshifts, although this assumes that the Stripe 82 LRGs are luminosity-matched to the AAΩ LRGs. We find stronger evidence for evolution in the form of the z ≈ 1 LRG correlation function with the above flat two-halo slope maintaining to s ≳ 50 h- 1 Mpc. Applying the cross-correlation test of Ross et al., we find little evidence that the result is due to systematics. Otherwise, it may represent evidence for primordial non-Gaussianity in the density perturbations at early times, with flocalNL = 90 ± 30.

IMG-ABC: An Atlas of Biosynthetic Gene Clusters to Fuel the Discovery of Novel Secondary Metabolites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, I-Min; Chu, Ken; Ratner, Anna

2014-10-28

In the discovery of secondary metabolites (SMs), large-scale analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of relevant computational resources. We present IMG-ABC (https://img.jgi.doe.gov/abc/) -- An Atlas of Biosynthetic gene Clusters within the Integrated Microbial Genomes (IMG) system1. IMG-ABC is a rich repository of both validated and predicted biosynthetic clusters (BCs) in cultured isolates, single-cells and metagenomes linked with the SM chemicals they produce and enhanced with focused analysis tools within IMG. The underlying scalable framework enables traversal of phylogenetic dark matter and chemical structure space -- serving as a doorwaymore » to a new era in the discovery of novel molecules.« less

Hierarchically clustered adaptive quantization CMAC and its learning convergence.

PubMed

Teddy, S D; Lai, E M K; Quek, C

2007-11-01

The cerebellar model articulation controller (CMAC) neural network (NN) is a well-established computational model of the human cerebellum. Nevertheless, there are two major drawbacks associated with the uniform quantization scheme of the CMAC network. They are the following: (1) a constant output resolution associated with the entire input space and (2) the generalization-accuracy dilemma. Moreover, the size of the CMAC network is an exponential function of the number of inputs. Depending on the characteristics of the training data, only a small percentage of the entire set of CMAC memory cells is utilized. Therefore, the efficient utilization of the CMAC memory is a crucial issue. One approach is to quantize the input space nonuniformly. For existing nonuniformly quantized CMAC systems, there is a tradeoff between memory efficiency and computational complexity. Inspired by the underlying organizational mechanism of the human brain, this paper presents a novel CMAC architecture named hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC). HCAQ-CMAC employs hierarchical clustering for the nonuniform quantization of the input space to identify significant input segments and subsequently allocating more memory cells to these regions. The stability of the HCAQ-CMAC network is theoretically guaranteed by the proof of its learning convergence. The performance of the proposed network is subsequently benchmarked against the original CMAC network, as well as two other existing CMAC variants on two real-life applications, namely, automated control of car maneuver and modeling of the human blood glucose dynamics. The experimental results have demonstrated that the HCAQ-CMAC network offers an efficient memory allocation scheme and improves the generalization and accuracy of the network output to achieve better or comparable performances with smaller memory usages. Index Terms-Cerebellar model articulation controller (CMAC), hierarchical clustering, hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC), learning convergence, nonuniform quantization.

Parallelized traveling cluster approximation to study numerically spin-fermion models on large lattices

DOE PAGES

Mukherjee, Anamitra; Patel, Niravkumar D.; Bishop, Chris; ...

2015-06-08

Lattice spin-fermion models are quite important to study correlated systems where quantum dynamics allows for a separation between slow and fast degrees of freedom. The fast degrees of freedom are treated quantum mechanically while the slow variables, generically referred to as the “spins,” are treated classically. At present, exact diagonalization coupled with classical Monte Carlo (ED + MC) is extensively used to solve numerically a general class of lattice spin-fermion problems. In this common setup, the classical variables (spins) are treated via the standard MC method while the fermion problem is solved by exact diagonalization. The “traveling cluster approximation” (TCA)more » is a real space variant of the ED + MC method that allows to solve spin-fermion problems on lattice sizes with up to 10 3 sites. In this paper, we present a novel reorganization of the TCA algorithm in a manner that can be efficiently parallelized. Finally, this allows us to solve generic spin-fermion models easily on 10 4 lattice sites and with some effort on 10 5 lattice sites, representing the record lattice sizes studied for this family of models.« less

Parallelized traveling cluster approximation to study numerically spin-fermion models on large lattices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mukherjee, Anamitra; Patel, Niravkumar D.; Bishop, Chris

Lattice spin-fermion models are quite important to study correlated systems where quantum dynamics allows for a separation between slow and fast degrees of freedom. The fast degrees of freedom are treated quantum mechanically while the slow variables, generically referred to as the “spins,” are treated classically. At present, exact diagonalization coupled with classical Monte Carlo (ED + MC) is extensively used to solve numerically a general class of lattice spin-fermion problems. In this common setup, the classical variables (spins) are treated via the standard MC method while the fermion problem is solved by exact diagonalization. The “traveling cluster approximation” (TCA)more » is a real space variant of the ED + MC method that allows to solve spin-fermion problems on lattice sizes with up to 10 3 sites. In this paper, we present a novel reorganization of the TCA algorithm in a manner that can be efficiently parallelized. Finally, this allows us to solve generic spin-fermion models easily on 10 4 lattice sites and with some effort on 10 5 lattice sites, representing the record lattice sizes studied for this family of models.« less

The Story of Supernova “Refsdal” Told by Muse

NASA Astrophysics Data System (ADS)

Grillo, C.; Karman, W.; Suyu, S. H.; Rosati, P.; Balestra, I.; Mercurio, A.; Lombardi, M.; Treu, T.; Caminha, G. B.; Halkola, A.; Rodney, S. A.; Gavazzi, R.; Caputi, K. I.

2016-05-01

We present Multi Unit Spectroscopic Explorer (MUSE) observations in the core of the Hubble Frontier Fields (HFF) galaxy cluster MACS J1149.5+2223, where the first magnified and spatially resolved multiple images of supernova (SN) “Refsdal” at redshift 1.489 were detected. Thanks to a Director's Discretionary Time program with the Very Large Telescope and the extraordinary efficiency of MUSE, we measure 117 secure redshifts with just 4.8 hr of total integration time on a single 1 arcmin2 target pointing. We spectroscopically confirm 68 galaxy cluster members, with redshift values ranging from 0.5272 to 0.5660, and 18 multiple images belonging to seven background, lensed sources distributed in redshifts between 1.240 and 3.703. Starting from the combination of our catalog with those obtained from extensive spectroscopic and photometric campaigns using the Hubble Space Telescope (HST), we select a sample of 300 (164 spectroscopic and 136 photometric) cluster members, within approximately 500 kpc from the brightest cluster galaxy, and a set of 88 reliable multiple images associated with 10 different background source galaxies and 18 distinct knots in the spiral galaxy hosting SN “Refsdal.” We exploit this valuable information to build six detailed strong-lensing models, the best of which reproduces the observed positions of the multiple images with an rms offset of only 0.″26. We use these models to quantify the statistical and systematic errors on the predicted values of magnification and time delay of the next emerging image of SN “Refsdal.” We find that its peak luminosity should occur between 2016 March and June and should be approximately 20% fainter than the dimmest (S4) of the previously detected images but above the detection limit of the planned HST/WFC3 follow-up. We present our two-dimensional reconstruction of the cluster mass density distribution and of the SN “Refsdal” host galaxy surface brightness distribution. We outline the road map toward even better strong-lensing models with a synergetic MUSE and HST effort. This work is based in large part on data collected at ESO VLT (prog.ID 294.A-5032) and NASA HST.

A Study of Nine High-Redshift Clusters of Galaxies. II. Photometry, Spectra, and Ages of Clusters 0023+0423 and 1604+4304

NASA Astrophysics Data System (ADS)

Postman, Marc; Lubin, Lori M.; Oke, J. B.

1998-08-01

We present an extensive photometric and spectroscopic study of two high-redshift clusters of galaxies based on data obtained from the Keck 10 m telescopes and the Hubble Space Telescope. The clusters Cl 0023+0423 (z = 0.84) and Cl 1604+4304 (z = 0.90) are part of a multiwavelength program of Oke, Postman & Lubin to study nine candidate clusters at z >~ 0.6. Based on these observations, we study in detail both the field and cluster populations. From the confirmed cluster members, we find that Cl 0023+0423 actually consists of two components separated by ~2900 km s^-1. A kinematic analysis indicates that the two components are a poor cluster with ~3 x 10^14 M_⊙ and a less massive group with ~10^13 M_⊙. Cl 1604+4304 is a centrally concentrated, rich cluster at z = 0.8967 with a velocity dispersion of 1226 km s^-1 and a mass of ~3 x 10^15 M_⊙. A large percentage of the cluster members show high levels of star formation activity. Approximately 57% and 50% of the galaxies are active in Cl 0023+0423 and Cl 1604+4304, respectively. These numbers are significantly larger than those found in intermediate-redshift clusters. We also observe many old, red galaxies. Found mainly in Cl 1604+4304, they have spectra consistent with passive stellar evolution, typical of the populations of early-type galaxies in low- and intermediate-redshift clusters. We have calculated their ages by comparing their spectral energy distributions to standard Bruzual & Charlot evolutionary models. We find that their colors are consistent with models having an exponentially decreasing star formation rate with a time constant of 0.6 Gyr. We also observe a significant luminosity brightening in our brightest cluster galaxies. Compared with brightest cluster galaxies at z ~ 0.1, we find a luminosity increase of ~1 mag in the rest M_B and ~0.8 mag in the rest M_V. In the field, we find that ~76% of the galaxies with z > 0.4 show emission-line activity. These numbers are consistent with previous studies. We find that an exponentially decaying star formation rate is required to produce the observed amount of star formation for the majority of the galaxies in our sample. A time constant of tau = 0.6 Gyr appears to be optimal. We also detect several interesting galaxies at z > 1. Two of these galaxies are extremely luminous, with strong Mg ii lambda2800 absorption and Fe ii resonance-line absorption. These lines are so strong that we conclude that they must be generated within the atmospheres of a large population of young, hot stars.

Supra-galactic colour patterns in globular cluster systems

NASA Astrophysics Data System (ADS)

Forte, Juan C.

2017-07-01

An analysis of globular cluster systems associated with galaxies included in the Virgo and Fornax Hubble Space Telescope-Advanced Camera Surveys reveals distinct (g - z) colour modulation patterns. These features appear on composite samples of globular clusters and, most evidently, in galaxies with absolute magnitudes Mg in the range from -20.2 to -19.2. These colour modulations are also detectable on some samples of globular clusters in the central galaxies NGC 1399 and NGC 4486 (and confirmed on data sets obtained with different instruments and photometric systems), as well as in other bright galaxies in these clusters. After discarding field contamination, photometric errors and statistical effects, we conclude that these supra-galactic colour patterns are real and reflect some previously unknown characteristic. These features suggest that the globular cluster formation process was not entirely stochastic but included a fraction of clusters that formed in a rather synchronized fashion over large spatial scales, and in a tentative time lapse of about 1.5 Gy at redshifts z between 2 and 4. We speculate that the putative mechanism leading to that synchronism may be associated with large scale feedback effects connected with violent star-forming events and/or with supermassive black holes.

Non-Linear Cosmological Power Spectra in Real and Redshift Space

NASA Technical Reports Server (NTRS)

Taylor, A. N.; Hamilton, A. J. S.

1996-01-01

We present an expression for the non-linear evolution of the cosmological power spectrum based on Lagrangian trajectories. This is simplified using the Zel'dovich approximation to trace particle displacements, assuming Gaussian initial conditions. The model is found to exhibit the transfer of power from large to small scales expected in self-gravitating fields. Some exact solutions are found for power-law initial spectra. We have extended this analysis into red-shift space and found a solution for the non-linear, anisotropic redshift-space power spectrum in the limit of plane-parallel redshift distortions. The quadrupole-to-monopole ratio is calculated for the case of power-law initial spectra. We find that the shape of this ratio depends on the shape of the initial spectrum, but when scaled to linear theory depends only weakly on the redshift-space distortion parameter, beta. The point of zero-crossing of the quadrupole, kappa(sub o), is found to obey a simple scaling relation and we calculate this scale in the Zel'dovich approximation. This model is found to be in good agreement with a series of N-body simulations on scales down to the zero-crossing of the quadrupole, although the wavenumber at zero-crossing is underestimated. These results are applied to the quadrupole-to-monopole ratio found in the merged QDOT plus 1.2-Jy-IRAS redshift survey. Using a likelihood technique we have estimated that the distortion parameter is constrained to be beta greater than 0.5 at the 95 percent level. Our results are fairly insensitive to the local primordial spectral slope, but the likelihood analysis suggests n = -2 un the translinear regime. The zero-crossing scale of the quadrupole is k(sub 0) = 0.5 +/- 0.1 h Mpc(exp -1) and from this we infer that the amplitude of clustering is sigma(sub 8) = 0.7 +/- 0.05. We suggest that the success of this model is due to non-linear redshift-space effects arising from infall on to caustic and is not dominated by virialized cluster cores. The latter should start to dominate on scales below the zero-crossing of the quadrupole, where our model breaks down.

Wildfire cluster detection using space-time scan statistics

NASA Astrophysics Data System (ADS)

Tonini, M.; Tuia, D.; Ratle, F.; Kanevski, M.

2009-04-01

The aim of the present study is to identify spatio-temporal clusters of fires sequences using space-time scan statistics. These statistical methods are specifically designed to detect clusters and assess their significance. Basically, scan statistics work by comparing a set of events occurring inside a scanning window (or a space-time cylinder for spatio-temporal data) with those that lie outside. Windows of increasing size scan the zone across space and time: the likelihood ratio is calculated for each window (comparing the ratio "observed cases over expected" inside and outside): the window with the maximum value is assumed to be the most probable cluster, and so on. Under the null hypothesis of spatial and temporal randomness, these events are distributed according to a known discrete-state random process (Poisson or Bernoulli), which parameters can be estimated. Given this assumption, it is possible to test whether or not the null hypothesis holds in a specific area. In order to deal with fires data, the space-time permutation scan statistic has been applied since it does not require the explicit specification of the population-at risk in each cylinder. The case study is represented by Florida daily fire detection using the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product during the period 2003-2006. As result, statistically significant clusters have been identified. Performing the analyses over the entire frame period, three out of the five most likely clusters have been identified in the forest areas, on the North of the country; the other two clusters cover a large zone in the South, corresponding to agricultural land and the prairies in the Everglades. Furthermore, the analyses have been performed separately for the four years to analyze if the wildfires recur each year during the same period. It emerges that clusters of forest fires are more frequent in hot seasons (spring and summer), while in the South areas they are widely present along the whole year. The analysis of fires distribution to evaluate if they are statistically more frequent in some area or/and in some period of the year, can be useful to support fire management and to focus on prevention measures.

The Atlas of Chinese World Wide Web Ecosystem Shaped by the Collective Attention Flows.

PubMed

Lou, Xiaodan; Li, Yong; Gu, Weiwei; Zhang, Jiang

2016-01-01

The web can be regarded as an ecosystem of digital resources connected and shaped by collective successive behaviors of users. Knowing how people allocate limited attention on different resources is of great importance. To answer this, we embed the most popular Chinese web sites into a high dimensional Euclidean space based on the open flow network model of a large number of Chinese users' collective attention flows, which both considers the connection topology of hyperlinks between the sites and the collective behaviors of the users. With these tools, we rank the web sites and compare their centralities based on flow distances with other metrics. We also study the patterns of attention flow allocation, and find that a large number of web sites concentrate on the central area of the embedding space, and only a small fraction of web sites disperse in the periphery. The entire embedding space can be separated into 3 regions(core, interim, and periphery). The sites in the core (1%) occupy a majority of the attention flows (40%), and the sites (34%) in the interim attract 40%, whereas other sites (65%) only take 20% flows. What's more, we clustered the web sites into 4 groups according to their positions in the space, and found that similar web sites in contents and topics are grouped together. In short, by incorporating the open flow network model, we can clearly see how collective attention allocates and flows on different web sites, and how web sites connected each other.

Origin and evolution of the Perm Anomaly

NASA Astrophysics Data System (ADS)

Flament, N. E.; Williams, S.; Müller, D.; Gurnis, M.; Bower, D. J.

2016-12-01

Earth's lower mantle is characterized by two large-low-shear velocity provinces (LLSVPs, 15000 km in diameter, 500-1000 km high) located under Africa and the Pacific Ocean. In addition, a single, much smaller ( 1000 km in diameter, 500 km high) deep mantle structure named the "Perm Anomaly" was recently identified through the analysis of seismic tomography models. This discovery challenges current reconstructions of the evolution of the plate-mantle system that invoke plumes rising from the edges of the two LLSVPs, assumed spatially fixed and non-deforming in time. Here, we present mantle flow models constrained by tectonic reconstructions that reproduce the present-day structure of the lower mantle, and show a Perm-like anomaly. In the dynamic models, spanning 230 Myr, subducting slabs deform an initially uniform basal layer containing 2% of the volume of the mantle. Basal density, convective vigour, mantle viscosity, absolute plate motions, and relative plate motions are varied in a series of model cases. We use cluster analysis to classify equally-spaced points on Earth's surface into two groups with similar variations in present-day temperature between 1000-2800 km depth, for each model case. The procedure reveals a high-temperature cluster and a low-temperature cluster with respect to ambient mantle temperature below 2400 km depth. The spatial extent of the high-temperature cluster is in first-order agreement with the outlines of the LLSVPs and of the Perm Anomaly revealed by a similar cluster analysis of seven tomography models. Model success is quantified by computing the accuracy (between 0.56 and 0.76) of the temperature clusters in predicting the low-velocity cluster obtained from tomography, and qualified by the occurrence of a separate Perm-like anomaly. The anomaly formed in isolation prior to 150 Ma within a long-lived subduction network 22000 km in circumference composed of the Mongol-Okhotsk subduction along Eurasia to the west, northern Tethys subduction to the south, and east Asia subduction to the east, then migrated 2500 km westward at an average rate of 1.7 cm/yr, indicating a greater mobility of deep mantle structures than previously recognized. We infer that the mobile Perm Anomaly could be linked to the Emeishan volcanics, in contrast to the previously proposed Siberian Traps.

LoFEx - A local framework for calculating excitation energies: Illustrations using RI-CC2 linear response theory.

PubMed

Baudin, Pablo; Kristensen, Kasper

2016-06-14

We present a local framework for the calculation of coupled cluster excitation energies of large molecules (LoFEx). The method utilizes time-dependent Hartree-Fock information about the transitions of interest through the concept of natural transition orbitals (NTOs). The NTOs are used in combination with localized occupied and virtual Hartree-Fock orbitals to generate a reduced excitation orbital space (XOS) specific to each transition where a standard coupled cluster calculation is carried out. Each XOS is optimized to ensure that the excitation energies are determined to a predefined precision. We apply LoFEx in combination with the RI-CC2 model to calculate the lowest excitation energies of a set of medium-sized organic molecules. The results demonstrate the black-box nature of the LoFEx approach and show that significant computational savings can be gained without affecting the accuracy of CC2 excitation energies.

A polymer, random walk model for the size-distribution of large DNA fragments after high linear energy transfer radiation

NASA Technical Reports Server (NTRS)

Ponomarev, A. L.; Brenner, D.; Hlatky, L. R.; Sachs, R. K.

2000-01-01

DNA double-strand breaks (DSBs) produced by densely ionizing radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. Stochastic DSB clustering at large scales, from > 100 Mbp down to < 0.01 Mbp, is modeled using computer simulations and analytic equations. A random-walk, coarse-grained polymer model for chromatin is combined with a simple track structure model in Monte Carlo software called DNAbreak and is applied to data on alpha-particle irradiation of V-79 cells. The chromatin model neglects molecular details but systematically incorporates an increase in average spatial separation between two DNA loci as the number of base-pairs between the loci increases. Fragment-size distributions obtained using DNAbreak match data on large fragments about as well as distributions previously obtained with a less mechanistic approach. Dose-response relations, linear at small doses of high linear energy transfer (LET) radiation, are obtained. They are found to be non-linear when the dose becomes so large that there is a significant probability of overlapping or close juxtaposition, along one chromosome, for different DSB clusters from different tracks. The non-linearity is more evident for large fragments than for small. The DNAbreak results furnish an example of the RLC (randomly located clusters) analytic formalism, which generalizes the broken-stick fragment-size distribution of the random-breakage model that is often applied to low-LET data.

Large-scale exact diagonalizations reveal low-momentum scales of nuclei

NASA Astrophysics Data System (ADS)

Forssén, C.; Carlsson, B. D.; Johansson, H. T.; Sääf, D.; Bansal, A.; Hagen, G.; Papenbrock, T.

2018-03-01

Ab initio methods aim to solve the nuclear many-body problem with controlled approximations. Virtually exact numerical solutions for realistic interactions can only be obtained for certain special cases such as few-nucleon systems. Here we extend the reach of exact diagonalization methods to handle model spaces with dimension exceeding 1010 on a single compute node. This allows us to perform no-core shell model (NCSM) calculations for 6Li in model spaces up to Nmax=22 and to reveal the 4He+d halo structure of this nucleus. Still, the use of a finite harmonic-oscillator basis implies truncations in both infrared (IR) and ultraviolet (UV) length scales. These truncations impose finite-size corrections on observables computed in this basis. We perform IR extrapolations of energies and radii computed in the NCSM and with the coupled-cluster method at several fixed UV cutoffs. It is shown that this strategy enables information gain also from data that is not fully UV converged. IR extrapolations improve the accuracy of relevant bound-state observables for a range of UV cutoffs, thus making them profitable tools. We relate the momentum scale that governs the exponential IR convergence to the threshold energy for the first open decay channel. Using large-scale NCSM calculations we numerically verify this small-momentum scale of finite nuclei.

Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.

PubMed

Ferles, Christos; Beaufort, William-Scott; Ferle, Vanessa

2017-01-01

The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences in a lower-dimensional space in such a way that the clusters and relations of data elements are depicted graphically. Both operate in combination/synergy with the Self-Organizing Hidden Markov Model Map (SOHMMM). The resulting unified framework is in position to analyze automatically and directly raw sequence data. This analysis is carried out with little, or even complete absence of, prior information/domain knowledge.

The effect of clulstering of galaxies on the statistics of gravitational lenses

NASA Technical Reports Server (NTRS)

Anderson, N.; Alcock, C.

1986-01-01

It is examined whether clustering of galaxies can significantly alter the statistical properties of gravitational lenses? Only models of clustering that resemble the observed distribution of galaxies in the properties of the two-point correlation function are considered. Monte-Carlo simulations of the imaging process are described. It is found that the effect of clustering is too small to be significant, unless the mass of the deflectors is so large that gravitational lenses become common occurrences. A special model is described which was concocted to optimize the effect of clustering on gravitational lensing but still resemble the observed distribution of galaxies; even this simulation did not satisfactorily produce large numbers of wide-angle lenses.

Systematic exploration of unsupervised methods for mapping behavior

NASA Astrophysics Data System (ADS)

Todd, Jeremy G.; Kain, Jamey S.; de Bivort, Benjamin L.

2017-02-01

To fully understand the mechanisms giving rise to behavior, we need to be able to precisely measure it. When coupled with large behavioral data sets, unsupervised clustering methods offer the potential of unbiased mapping of behavioral spaces. However, unsupervised techniques to map behavioral spaces are in their infancy, and there have been few systematic considerations of all the methodological options. We compared the performance of seven distinct mapping methods in clustering a wavelet-transformed data set consisting of the x- and y-positions of the six legs of individual flies. Legs were automatically tracked by small pieces of fluorescent dye, while the fly was tethered and walking on an air-suspended ball. We find that there is considerable variation in the performance of these mapping methods, and that better performance is attained when clustering is done in higher dimensional spaces (which are otherwise less preferable because they are hard to visualize). High dimensionality means that some algorithms, including the non-parametric watershed cluster assignment algorithm, cannot be used. We developed an alternative watershed algorithm which can be used in high-dimensional spaces when a probability density estimate can be computed directly. With these tools in hand, we examined the behavioral space of fly leg postural dynamics and locomotion. We find a striking division of behavior into modes involving the fore legs and modes involving the hind legs, with few direct transitions between them. By computing behavioral clusters using the data from all flies simultaneously, we show that this division appears to be common to all flies. We also identify individual-to-individual differences in behavior and behavioral transitions. Lastly, we suggest a computational pipeline that can achieve satisfactory levels of performance without the taxing computational demands of a systematic combinatorial approach.

Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Jianbao; Ma, Zhongjun, E-mail: mzj1234402@163.com; Chen, Guanrong

All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding ormore » deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.« less

Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

NASA Astrophysics Data System (ADS)

Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong

2014-06-01

All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.

Large scale meteorological patterns and moisture sources during precipitation extremes over South Asia

NASA Astrophysics Data System (ADS)

Mehmood, S.; Ashfaq, M.; Evans, K. J.; Black, R. X.; Hsu, H. H.

2017-12-01

Extreme precipitation during summer season has shown an increasing trend across South Asia in recent decades, causing an exponential increase in weather related losses. Here we combine a cluster analyses technique (Agglomerative Hierarchical Clustering) with a Lagrangian based moisture analyses technique to investigate potential commonalities in the characteristics of the large scale meteorological patterns (LSMP) and moisture anomalies associated with the observed extreme precipitation events, and their representation in the Department of Energy model ACME. Using precipitation observations from the Indian Meteorological Department (IMD) and Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE), and atmospheric variables from Era-Interim Reanalysis, we first identify LSMP both in upper and lower troposphere that are responsible for wide spread precipitation extreme events during 1980-2015 period. For each of the selected extreme event, we perform moisture source analyses to identify major evaporative sources that sustain anomalous moisture supply during the course of the event, with a particular focus on local terrestrial moisture recycling. Further, we perform similar analyses on two sets of five-member ensemble of ACME model (1-degree and ¼ degree) to investigate the ability of ACME model in simulating precipitation extremes associated with each of the LSMP patterns and associated anomalous moisture sourcing from each of the terrestrial and oceanic evaporative region. Comparison of low and high-resolution model configurations provides insight about the influence of horizontal grid spacing in the simulation of extreme precipitation and the governing mechanisms.

Ages of intermediate-age Magellanic Cloud star clusters

NASA Technical Reports Server (NTRS)

Flower, P. J.

1984-01-01

Ages of intermediate-age Large Magellanic Cloud star clusters have been estimated without locating the faint, unevolved portion of cluster main sequences. Six clusters with established color-magnitude diagrams were selected for study: SL 868, NGC 1783, NGC 1868, NGC 2121, NGC 2209, and NGC 2231. Since red giant photometry is more accurate than the necessarily fainter main-sequence photometry, the distributions of red giants on the cluster color-magnitude diagrams were compared to a grid of 33 stellar evolutionary tracks, evolved from the main sequence through core-helium exhaustion, spanning the expected mass and metallicity range for Magellanic Cloud cluster red giants. The time-dependent behavior of the luminosity of the model red giants was used to estimate cluster ages from the observed cluster red giant luminosities. Except for the possibility of SL 868 being an old globular cluster, all clusters studied were found to have ages less than 10 to the 9th yr. It is concluded that there is currently no substantial evidence for a major cluster population of large, populous clusters greater than 10 to the 9th yr old in the Large Magellanic Cloud.

Isochrone Fitting of Hubble Photometry in UV–VIS–IR Bands

NASA Astrophysics Data System (ADS)

Barker, Hallie; Paust, Nathaniel E. Q.

2018-03-01

We present new isochrone fits to color–magnitude diagrams from Hubble Space Telescope Wide Field Camera 3 and Advanced Camera for Surveys photometry of the globular clusters M13 and M80 in five bands from the ultraviolet to near-infrared. Isochrone fits to the photometry using the Dartmouth Stellar Evolution Program (DSEP), the PAdova and TRieste Stellar Evolution Code (PARSEC), and MESA Isochrones and Stellar Tracks (MIST) are examined to study the isochrone morphology. Additionally, cluster ages, extinctions, and distances are found from the visible-infrared color–magnitude diagrams. We conduct careful qualitative analysis on the inconsistencies of the fits across twelve color combinations of the five observed bands, and find that the (F606W‑F814W) color generally produces very good fits, but that there are large discrepancies when the data is fit using colors including UV bands for all three models. We also find that the best fits in the UV are achieved using MIST isochrones, but that they require metallicities that are lower than the other two models, as well published spectroscopic values. Finally, we directly compare DSEP and PARSEC by performing isochrone-isochrone fitting, and find that, for globular cluster aged populations, similar appearing PARSEC isochrones are on average 1.5 Gyr younger than DSEP isochrones. We find that the two models become less discrepant at lower metallicities.

On the applicability of one- and many-electron quantum chemistry models for hydrated electron clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turi, László, E-mail: turi@chem.elte.hu

2016-04-21

We evaluate the applicability of a hierarchy of quantum models in characterizing the binding energy of excess electrons to water clusters. In particular, we calculate the vertical detachment energy of an excess electron from water cluster anions with methods that include one-electron pseudopotential calculations, density functional theory (DFT) based calculations, and ab initio quantum chemistry using MP2 and eom-EA-CCSD levels of theory. The examined clusters range from the smallest cluster size (n = 2) up to nearly nanosize clusters with n = 1000 molecules. The examined cluster configurations are extracted from mixed quantum-classical molecular dynamics trajectories of cluster anions withmore » n = 1000 water molecules using two different one-electron pseudopotenial models. We find that while MP2 calculations with large diffuse basis set provide a reasonable description for the hydrated electron system, DFT methods should be used with precaution and only after careful benchmarking. Strictly tested one-electron psudopotentials can still be considered as reasonable alternatives to DFT methods, especially in large systems. The results of quantum chemistry calculations performed on configurations, that represent possible excess electron binding motifs in the clusters, appear to be consistent with the results using a cavity structure preferring one-electron pseudopotential for the hydrated electron, while they are in sharp disagreement with the structural predictions of a non-cavity model.« less

On the applicability of one- and many-electron quantum chemistry models for hydrated electron clusters

NASA Astrophysics Data System (ADS)

Turi, László

2016-04-01

We evaluate the applicability of a hierarchy of quantum models in characterizing the binding energy of excess electrons to water clusters. In particular, we calculate the vertical detachment energy of an excess electron from water cluster anions with methods that include one-electron pseudopotential calculations, density functional theory (DFT) based calculations, and ab initio quantum chemistry using MP2 and eom-EA-CCSD levels of theory. The examined clusters range from the smallest cluster size (n = 2) up to nearly nanosize clusters with n = 1000 molecules. The examined cluster configurations are extracted from mixed quantum-classical molecular dynamics trajectories of cluster anions with n = 1000 water molecules using two different one-electron pseudopotenial models. We find that while MP2 calculations with large diffuse basis set provide a reasonable description for the hydrated electron system, DFT methods should be used with precaution and only after careful benchmarking. Strictly tested one-electron psudopotentials can still be considered as reasonable alternatives to DFT methods, especially in large systems. The results of quantum chemistry calculations performed on configurations, that represent possible excess electron binding motifs in the clusters, appear to be consistent with the results using a cavity structure preferring one-electron pseudopotential for the hydrated electron, while they are in sharp disagreement with the structural predictions of a non-cavity model.

NASA Find Clues that May Help Identify Dark Matter

NASA Image and Video Library

2015-03-26

Using observations from NASA’s Hubble Space Telescope and Chandra X-ray Observatory, astronomers have found that dark matter does not slow down when colliding with itself, meaning it interacts with itself less than previously thought. Researchers say this finding narrows down the options for what this mysterious substance might be. Dark matter is an invisible matter that makes up most of the mass of the universe. Because dark matter does not reflect, absorb or emit light, it can only be traced indirectly by, such as by measuring how it warps space through gravitational lensing, during which the light from a distant source is magnified and distorted by the gravity of dark matter. Read more: 1.usa.gov/1E5LcpO Caption: Here are images of six different galaxy clusters taken with NASA's Hubble Space Telescope (blue) and Chandra X-ray Observatory (pink) in a study of how dark matter in clusters of galaxies behaves when the clusters collide. A total of 72 large cluster collisions were studied. Credit: NASA and ESA mage Credit: NASA and ESA NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

New Fast Lane towards Discoveries of Clusters of Galaxies Inaugurated

NASA Astrophysics Data System (ADS)

2003-07-01

Space and Ground-Based Telescopes Cooperate to Gain Deep Cosmological Insights Summary Using the ESA XMM-Newton satellite, a team of European and Chilean astronomers [2] has obtained the world's deepest "wide-field" X-ray image of the cosmos to date. This penetrating view, when complemented with observations by some of the largest and most efficient ground-based optical telescopes, including the ESO Very Large Telescope (VLT), has resulted in the discovery of several large clusters of galaxies. These early results from an ambitious research programme are extremely promising and pave the way for a very comprehensive and thorough census of clusters of galaxies at various epochs. Relying on the foremost astronomical technology and with an unequalled observational efficiency, this project is set to provide new insights into the structure and evolution of the distant Universe. PR Photo 19a/03: First image from the XMM-LSS survey. PR Photo 19b/03: Zoom-in on PR Photo 19b/03. PR Photo 19c/03: XMM-Newton contour map of the probable extent of a cluster of galaxies, superimposed upon a CHFT I-band image. PR Photo 19d/03: Velocity distribution in the cluster field shown in PR Photo 19c/03. The universal web Unlike grains of sand on a beach, matter is not uniformly spread throughout the Universe. Instead, it is concentrated into galaxies which themselves congregate into clusters (and even clusters of clusters). These clusters are "strung" throughout the Universe in a web-like structure, cf. ESO PR 11/01. Our Galaxy, the Milky Way, for example, belongs to the so-called Local Group which also comprises "Messier 31", the Andromeda Galaxy. The Local Group contains about 30 galaxies and measures a few million light-years across. Other clusters are much larger. The Coma cluster contains thousands of galaxies and measures more than 20 million light-years. Another well known example is the Virgo cluster, covering no less than 10 degrees on the sky ! Clusters of galaxies are the most massive bound structures in the Universe. They have masses of the order of one thousand million million times the mass of our Sun. Their three-dimensional space distribution and number density change with cosmic time and provide information about the main cosmological parameters in a unique way. About one fifth of the optically invisible mass of a cluster is in the form of a diffuse hot gas in between the galaxies. This gas has a temperature of the order of several tens of million degrees and a density of the order of one atom per liter. At such high temperatures, it produces powerful X-ray emission. Observing this intergalactic gas and not just the individual galaxies is like seeing the buildings of a city in daytime, not just the lighted windows at night. This is why clusters of galaxies are best discovered using X-ray satellites. Using previous X-ray satellites, astronomers have performed limited studies of the large-scale structure of the nearby Universe. However, they so far lacked the instruments to extend the search to large volumes of the distant Universe. The XMM-Newton wide-field observations ESO PR Photo 19a/03 ESO PR Photo 19a/03 [Preview - JPEG: 575 x 400 pix - 52k [Normal - JPEG: 1130 x 800 pix - 420k] ESO PR Photo 19b/03 ESO PR Photo 19b/03 [Preview - JPEG: 400 x 489 pix - 52k [Normal - JPEG: 800 x 978 pix - 464k] Captions: PR Photo 19a/03 is the first image from the XMM-LSS X-Ray survey. It is actually a combination of fourteen separate "pointings" of this space observatory. It represents a region of the sky eight times larger than the full Moon and contains around 25 clusters. The circles represent the X-Ray sources previously known from the 1991 ROSAT All-Sky Survey. PR Photo 19b/03 zooms in on a particularly interesting region of the image shown in ESO PR Photo 19a/03 with a possible cluster identified (in box). Each point on this graph represents a single X-ray photon detected by XMM-Newton. Marguerite Pierre (CEA Saclay, France), with a European/Chilean team of astronomers known as the XMM-LSS consortium [2], used the large field-of-view and the high sensitivity of ESA's X-ray observatory XMM-Newton to search for remote clusters of galaxies and map out their distribution in space. They could see back about 7,000 million years to a cosmological era when the Universe was about half its present size and age, when clusters of galaxies were more tightly packed. Tracking down the clusters is a painstaking, multi-step process, requiring both space and ground-based telescopes. Indeed, from X-ray images with XMM, it was possible to select several tens of cluster candidate objects, identified as areas of enhanced X-radiation (cf PR Photo 19b/03). But having candidates is not enough ! They must be confirmed and further studied with ground-based telescopes. In tandem with XMM-Newton, Pierre uses the very-wide-field imager attached to the 4-m Canada-France-Hawaii Telescope, on Mauna Kea, Hawaii, to take an optical snapshot of the same region of space. A tailor-made computer programme then combs the XMM-Newton data looking for concentrations of X-rays that suggest large, extended structures. These are the clusters and represent only about 10% of the detected X-ray sources. The others are mostly distant active galaxies. Back to the Ground ESO PR Photo 19c/03 ESO PR Photo 19c/03 [Preview - JPEG: 400 x 481 pix - 84k [Normal - JPEG: 800 x 961 pix - 1M] ESO PR Photo 19d/03 ESO PR Photo 19d/03 [Preview - JPEG: 400 x 488 pix - 44k [Normal - JPEG: 800 x 976 pix - 520k] Captions: PR Photo 19c/03 represents the XMM-Newton X-ray contour map of the cluster's probable extent superimposed upon the CFHT I-band image. A concentration of distant galaxies is conspicuous, thus confirming the X-ray detection. The symbols indicate the galaxies which have been subject to a subsequent spectroscopic measurement and found to be cluster members (triangles flag emission line galaxies). The individual galaxies in the cluster can then be targeted for further observations with ESO's VLT, in order to measure its distance and locate the cluster in the universe. Following the X-ray discovery and the optical cluster identification, galaxies in the cluster field shown in ESO PR Photo 19c/03 have been spectroscopically observed at the ESO VLT using the FORS2 instrument in order to determine the cluster redshift [3]. Using two masks, each of them observed during one hour, allowing to take the spectra of 16 emission-line galaxies at a time, the cluster was found to have a redshift of 0.84, corresponding to a distance of 8,000 million light-years, and a velocity dispersion of 750 km/s. PR Photo 19d/03 shows the measured velocity distribution. This is one of the most distant known clusters of galaxies for which a velocity dispersion has been measured. When the programme finds a cluster, it zooms in on that region and converts the XMM-Newton data into a contour map of X-ray intensity, which is then superimposed upon the CFHT optical image (PR Photo 19c/03). The astronomers use this to check if anything is visible within the area of extented X-ray emission. If something is seen, the work then shifts to one of the world's prime optical/infrared telescopes, the European Southern Observatory's Very Large Telescope (VLT) at Paranal (Chile). By means of the FORS multi-mode instruments, the astronomers zoom-in on the individual galaxies in the field, taking spectral measurements that reveal their overall characteristics, in particular their redshift and hence, distance. Cluster galaxies have similar distances and these measurement ultimately provide, by averaging, the cluster's distance as well as the velocity dispersion in the cluster. The FORS instruments are among the most efficient and versatile for this type of work, taking on the average spectra of 30 galaxies at a time. The first spectroscopic observations dedicated to the identification and redshift measurement of the XMM-LSS galaxy clusters took place during three nights in the fall of 2002. As of March 2003, there were only 5 known clusters in the literature at such a large redshift with enough spectroscopically measured redshifts to allow an estimate of the velocity dispersion. But the VLT allowed obtaining the dispersion in a distant cluster in 2 hours only, raising great expectations for future work. 700 spectra... Marguerite Pierre is extremely content : Weather and working conditions at the VLT were optimal. In three nights only, 12 cluster fields were observed, yielding no less than 700 spectra of galaxies. The overall strategy proved very successful. The high observing efficiency of the VLT and FORS support our plan to perform follow-up studies of large numbers of distant clusters with relatively little observing time. This represents a most substantial increase in efficiency compared to former searches. The present research programme has begun well, clearly demonstrating the feasibility of this new multi-telescope approach and its very high efficiency. And Marguerite Pierre and her colleagues are already seeing the first tantalising results: it seems to confirm that the number of clusters 7,000 million years ago is little different from that of today. This particular behaviour is predicted by models of the Universe that expand forever, driving the galaxy clusters further and further apart. Equally important, this multi-wavelength, multi-telescope approach developed by the XMM-LSS consortium to locate clusters of galaxies also constitutes a decisive next step in the fertile synergy between space and ground-based observatories and is therefore a basic building block of the forthcoming Virtual Observatory. More information This work is based on two papers to be published in the professional astronomy journal, Astronomy and Astrophysics (The XMM-LSS survey : I. Scientific motivations, design and first results by Marguerite Pierre et al., astro-ph/0305191 and The XMM-LSS survey : II. First high redshift galaxy clusters: relaxed and collapsing systems by Ivan Valtchanov et al., astro-ph/0305192). Dr. M. Pierre will give an invited talk on this subject at the IAU Symposium 216 - Maps of the Cosmos - this Thursday July 17, 2003 during the IAU General Assembly 2003 in Sydney, Australia.

Hard X-ray emission from accretion shocks around galaxy clusters

NASA Astrophysics Data System (ADS)

Kushnir, Doron; Waxman, Eli

2010-02-01

We show that the hard X-ray (HXR) emission observed from several galaxy clusters is consistent with a simple model, in which the nonthermal emission is produced by inverse Compton scattering of cosmic microwave background photons by electrons accelerated in cluster accretion shocks: The dependence of HXR surface brightness on cluster temperature is consistent with that predicted by the model, and the observed HXR luminosity is consistent with the fraction of shock thermal energy deposited in relativistic electrons being lesssim0.1. Alternative models, where the HXR emission is predicted to be correlated with the cluster thermal emission, are disfavored by the data. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) γ-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed.

Spatio-temporal scan statistics for the detection of outbreaks involving common molecular subtypes: using human cases of Escherichia coli O157:H7 provincial PFGE pattern 8 (National Designation ECXAI.0001) in Alberta as an example.

PubMed

So, H C; Pearl, D L; von Königslöw, T; Louie, M; Chui, L; Svenson, L W

2013-08-01

Molecular typing methods have become a common part of the surveillance of foodborne pathogens. In particular, pulsed-field gel electrophoresis (PFGE) has been used successfully to identify outbreaks of Escherichia coli O157:H7 in humans from a variety of food and environmental sources. However, some PFGE patterns appear commonly in surveillance systems, making it more difficult to distinguish between outbreak and sporadic cases based on molecular data alone. In addition, it is unknown whether these common patterns might have unique epidemiological characteristics reflected in their spatial and temporal distributions. Using E. coli O157:H7 surveillance data from Alberta, collected from 2000 to 2002, we investigated whether E. coli O157:H7 with provincial PFGE pattern 8 (national designation ECXAI.0001) clustered in space, time and space-time relative to other PFGE patterns using the spatial scan statistic. Based on our purely spatial and temporal scans using a Bernoulli model, there did not appear to be strong evidence that isolates of E. coli O157:H7 with provincial PFGE pattern 8 are distributed differently from other PFGE patterns. However, we did identify space-time clusters of isolates with PFGE pattern 8, using a Bernoulli model and a space-time permutation model, which included known outbreaks and potentially unrecognized outbreaks or additional outbreak cases. There were differences between the two models in the space-time clusters identified, which suggests that the use of both models could increase the sensitivity of a quantitative surveillance system for identifying outbreaks involving isolates sharing a common PFGE pattern. © 2012 Blackwell Verlag GmbH.

A PRECISE CLUSTER MASS PROFILE AVERAGED FROM THE HIGHEST-QUALITY LENSING DATA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Umetsu, Keiichi; Broadhurst, Tom; Zitrin, Adi

2011-09-01

We outline our methods for obtaining high-precision mass profiles, combining independent weak-lensing distortion, magnification, and strong-lensing measurements. For massive clusters, the strong- and weak-lensing regimes contribute equal logarithmic coverage of the radial profile. The utility of high-quality data is limited by the cosmic noise from large-scale structure along the line of sight. This noise is overcome when stacking clusters, as too are the effects of cluster asphericity and substructure, permitting a stringent test of theoretical models. We derive a mean radial mass profile of four similar mass clusters of high-quality Hubble Space Telescope and Subaru images, in the range Rmore » = 40-2800 kpc h {sup -1}, where the inner radial boundary is sufficiently large to avoid smoothing from miscentering effects. The stacked mass profile is detected at 58{sigma} significance over the entire radial range, with the contribution from the cosmic noise included. We show that the projected mass profile has a continuously steepening gradient out to beyond the virial radius, in remarkably good agreement with the standard Navarro-Frenk-White form predicted for the family of cold dark matter (CDM) dominated halos in gravitational equilibrium. The central slope is constrained to lie in the range, -dln {rho}/dln r = 0.89{sup +0.27}{sub -0.39}. The mean concentration is c{sub vir} = 7.68{sup +0.42}{sub -0.40} (at M{sub vir} = 1.54{sup +0.11}{sub -0.10} x 10{sup 15} M{sub sun} h {sup -1}), which is high for relaxed, high-mass clusters, but consistent with {Lambda}CDM when a sizable projection bias estimated from N-body simulations is considered. This possible tension will be more definitively explored with new cluster surveys, such as CLASH, LoCuSS, Subaru Hyper Suprime-Cam, and XXM-XXL, to construct the c{sub vir}-M{sub vir} relation over a wider mass range.« less

m-BIRCH: an online clustering approach for computer vision applications

NASA Astrophysics Data System (ADS)

Madan, Siddharth K.; Dana, Kristin J.

2015-03-01

We adapt a classic online clustering algorithm called Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), to incrementally cluster large datasets of features commonly used in multimedia and computer vision. We call the adapted version modified-BIRCH (m-BIRCH). The algorithm uses only a fraction of the dataset memory to perform clustering, and updates the clustering decisions when new data comes in. Modifications made in m-BIRCH enable data driven parameter selection and effectively handle varying density regions in the feature space. Data driven parameter selection automatically controls the level of coarseness of the data summarization. Effective handling of varying density regions is necessary to well represent the different density regions in data summarization. We use m-BIRCH to cluster 840K color SIFT descriptors, and 60K outlier corrupted grayscale patches. We use the algorithm to cluster datasets consisting of challenging non-convex clustering patterns. Our implementation of the algorithm provides an useful clustering tool and is made publicly available.

Search for Carbon-Rich Asymptotic Giant Branch Stars in Milky Way Globular Clusters

NASA Astrophysics Data System (ADS)

Indahl, Briana; Pessev, P.

2014-01-01

From our current understanding of stellar evolution, it would not be expected to find carbon rich asymptotic giant branch (AGB) stars in Milky Way globular clusters. Due to the low metallicity of the population II stars making up the globular clusters and their age, stars large enough to fuse carbon should have already evolved off of the asymptotic giant branch. Recently, however, there have been serendipitous discoveries of these types of stars. Matsunaga et al. (2006) discovered a Mira variable in the globular cluster Lynga 7. It was later confirmed by Feast et al. (2012) that the star is a member of the cluster and must be a product of a stellar merger. In the same year, Sharina et al. (2012) discovered a carbon star in the low metallicity globular cluster NGC6426 and reports it to be a CH star. Five more of these types of stars have been made as serendipitous discoveries and have been reported by Harding (1962), Dickens (1972), Cote et al. (1997), and Van Loon (2007). The abundance of these types of carbon stars in Milky Way globular clusters has been unknown because the discovery of these types of objects has only ever been a serendipitous discovery. These stars could have been easily overlooked in the past as they are outside the typical parameter space of galactic globular clusters. Also advances in near-infrared instruments and observing techniques have made it possible to detect the fainter carbon stars in binary systems. Having an understanding of the abundances of carbon stars in galactic globular clusters will aid in the modeling of globular cluster and galaxy formation leading to a better understanding of these processes. To get an understanding of the abundances of these stars we conducted the first comprehensive search for AGB carbon stars into all Milky Way globular clusters listed in the Harris Catalog (expect for Pyxis). I have found 128 carbon star candidates using methods of comparing color magnitude diagrams of the clusters with the carbon stars of the Large Magellenic Clouds and picking out very red stars in the red giant branch range. Observations will need to be done of these candidates to further confirm if they are carbon stars and are members of their respective globular cluster.

Electrostatic solitary waves in current layers: from Cluster observations during a super-substorm to beam experiments at the LAPD

NASA Astrophysics Data System (ADS)

Pickett, J. S.; Chen, L.-J.; Santolík, O.; Grimald, S.; Lavraud, B.; Verkhoglyadova, O. P.; Tsurutani, B. T.; Lefebvre, B.; Fazakerley, A.; Lakhina, G. S.; Ghosh, S. S.; Grison, B.; Décréau, P. M. E.; Gurnett, D. A.; Torbert, R.; Cornilleau-Wehrlin, N.; Dandouras, I.; Lucek, E.

2009-06-01

Electrostatic Solitary Waves (ESWs) have been observed by several spacecraft in the current layers of Earth's magnetosphere since 1982. ESWs are manifested as isolated pulses (one wave period) in the high time resolution waveform data obtained on these spacecraft. They are thus nonlinear structures generated out of nonlinear instabilities and processes. We report the first observations of ESWs associated with the onset of a super-substorm that occurred on 24 August 2005 while the Cluster spacecraft were located in the magnetotail at around 18-19 RE and moving northward from the plasma sheet to the lobes. These ESWs were detected in the waveform data of the WBD plasma wave receiver on three of the Cluster spacecraft. The majority of the ESWs were detected about 5 min after the super-substorm onset during which time 1) the PEACE electron instrument detected significant field-aligned electron fluxes from a few 100 eV to 3.5 keV, 2) the EDI instrument detected bursts of field-aligned electron currents, 3) the FGM instrument detected substantial magnetic fluctuations and the presence of Alfvén waves, 4) the STAFF experiment detected broadband electric and magnetic waves, ion cyclotron waves and whistler mode waves, and 5) CIS detected nearly comparable densities of H+ and O+ ions and a large tailward H+ velocity. We compare the characteristics of the ESWs observed during this event to those created in the laboratory at the University of California-Los Angeles Plasma Device (LAPD) with an electron beam. We find that the time durations of both space and LAPD ESWs are only slightly larger than the respective local electron plasma periods, indicating that electron, and not ion, dynamics are responsible for generation of the ESWs. We have discussed possible mechanisms for generating the ESWs in space, including the beam and kinetic Buneman type instabilities and the acoustic instabilities. Future studies will examine these mechanisms in more detail using the space measurements as inputs to models, and better relate the ESW space measurements to the laboratory through PIC code models.

CHIPMUNK: A Virtual Synthesizable Small-Molecule Library for Medicinal Chemistry, Exploitable for Protein-Protein Interaction Modulators.

PubMed

Humbeck, Lina; Weigang, Sebastian; Schäfer, Till; Mutzel, Petra; Koch, Oliver

2018-03-20

A common issue during drug design and development is the discovery of novel scaffolds for protein targets. On the one hand the chemical space of purchasable compounds is rather limited; on the other hand artificially generated molecules suffer from a grave lack of accessibility in practice. Therefore, we generated a novel virtual library of small molecules which are synthesizable from purchasable educts, called CHIPMUNK (CHemically feasible In silico Public Molecular UNiverse Knowledge base). Altogether, CHIPMUNK covers over 95 million compounds and encompasses regions of the chemical space that are not covered by existing databases. The coverage of CHIPMUNK exceeds the chemical space spanned by the Lipinski rule of five to foster the exploration of novel and difficult target classes. The analysis of the generated property space reveals that CHIPMUNK is well suited for the design of protein-protein interaction inhibitors (PPIIs). Furthermore, a recently developed structural clustering algorithm (StruClus) for big data was used to partition the sub-libraries into meaningful subsets and assist scientists to process the large amount of data. These clustered subsets also contain the target space based on ChEMBL data which was included during clustering. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering.

PubMed

Ji, Shuiwang

2013-07-11

The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development. In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space. Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship.

The HST Frontier Fields: Complete High-Level Science Data Products for All 6 Clusters

NASA Astrophysics Data System (ADS)

Koekemoer, Anton M.; Mack, Jennifer; Lotz, Jennifer M.; Borncamp, David; Khandrika, Harish G.; Lucas, Ray A.; Martlin, Catherine; Porterfield, Blair; Sunnquist, Ben; Anderson, Jay; Avila, Roberto J.; Barker, Elizabeth A.; Grogin, Norman A.; Gunning, Heather C.; Hilbert, Bryan; Ogaz, Sara; Robberto, Massimo; Sembach, Kenneth; Flanagan, Kathryn; Mountain, Matt; HST Frontier Fields Team

2017-01-01

The Hubble Space Telescope Frontier Fields program (PI: J. Lotz) is a large Director's Discretionary program of 840 orbits, to obtain ultra-deep observations of six strong lensing clusters of galaxies, together with parallel deep blank fields, making use of the strong lensing amplification by these clusters of distant background galaxies to detect the faintest galaxies currently observable in the high-redshift universe. The entire program has now completed successfully for all 6 clusters, namely Abell 2744, Abell S1063, Abell 370, MACS J0416.1-2403, MACS J0717.5+3745 and MACS J1149.5+2223,. Each of these was observed over two epochs, to a total depth of 140 orbits on the main cluster and an associated parallel field, obtaining images in ACS (F435W, F606W, F814W) and WFC3/IR (F105W, F125W, F140W, F160W) on both the main cluster and the parallel field in all cases. Full sets of high-level science products have been generated for all these clusters by the team at STScI, including cumulative-depth data releases during each epoch, as well as full-depth releases after the completion of each epoch. These products include all the full-depth distortion-corrected drizzled mosaics and associated products for each cluster, which are science-ready to facilitate the construction of lensing models as well as enabling a wide range of other science projects. Many improvements beyond default calibration for ACS and WFC3/IR are implemented in these data products, including corrections for persistence, time-variable sky, and low-level dark current residuals, as well as improvements in astrometric alignment to achieve milliarcsecond-level accuracy. The full set of resulting high-level science products and mosaics are publicly delivered to the community via the Mikulski Archive for Space Telescopes (MAST) to enable the widest scientific use of these data, as well as ensuring a public legacy dataset of the highest possible quality that is of lasting value to the entire community.

The HST Frontier Fields: Complete Observations and High-Level Science Data Products for All 6 Clusters

NASA Astrophysics Data System (ADS)

Koekemoer, Anton M.; Mack, Jennifer; Lotz, Jennifer M.; Borncamp, David; Khandrika, Harish G.; Lucas, Ray A.; Martlin, Catherine; Martlin, Catherine; Porterfield, Blair; Sunnquist, Ben; Anderson, Jay; Avila, Roberto J.; Barker, Elizabeth A.; Grogin, Norman A.; Gunning, Heather C.; Hilbert, Bryan; Ogaz, Sara; Robberto, Massimo; Sembach, Kenneth; Flanagan, Kathryn; Mountain, Matt; HST Frontier Fields Team

2017-06-01

The Hubble Space Telescope Frontier Fields program is a large Director's Discretionary program of 840 orbits, to obtain ultra-deep observations of six strong lensing clusters of galaxies, together with parallel deep blank fields, making use of the strong lensing amplification by these clusters of distant background galaxies to detect the faintest galaxies currently observable in the high-redshift universe. The entire program has now completed successfully for all 6 clusters, namely Abell 2744, Abell S1063, Abell 370, MACS J0416.1-2403, MACS J0717.5+3745 and MACS J1149.5+2223,. Each of these was observed over two epochs, to a total depth of 140 orbits on the main cluster and an associated parallel field, obtaining images in ACS (F435W, F606W, F814W) and WFC3/IR (F105W, F125W, F140W, F160W) on both the main cluster and the parallel field in all cases. Full sets of high-level science products have been generated for all these clusters by the team at STScI, including cumulative-depth data releases during each epoch, as well as full-depth releases after the completion of each epoch. These products include all the full-depth distortion-corrected drizzled mosaics and associated products for each cluster, which are science-ready to facilitate the construction of lensing models as well as enabling a wide range of other science projects. Many improvements beyond default calibration for ACS and WFC3/IR are implemented in these data products, including corrections for persistence, time-variable sky, and low-level dark current residuals, as well as improvements in astrometric alignment to achieve milliarcsecond-level accuracy. The full set of resulting high-level science products and mosaics are publicly delivered to the community via the Mikulski Archive for Space Telescopes (MAST) to enable the widest scientific use of these data, as well as ensuring a public legacy dataset of the highest possible quality that is of lasting value to the entire community.

Cluster-based control of a separating flow over a smoothly contoured ramp

NASA Astrophysics Data System (ADS)

Kaiser, Eurika; Noack, Bernd R.; Spohn, Andreas; Cattafesta, Louis N.; Morzyński, Marek

2017-12-01

The ability to manipulate and control fluid flows is of great importance in many scientific and engineering applications. The proposed closed-loop control framework addresses a key issue of model-based control: The actuation effect often results from slow dynamics of strongly nonlinear interactions which the flow reveals at timescales much longer than the prediction horizon of any model. Hence, we employ a probabilistic approach based on a cluster-based discretization of the Liouville equation for the evolution of the probability distribution. The proposed methodology frames high-dimensional, nonlinear dynamics into low-dimensional, probabilistic, linear dynamics which considerably simplifies the optimal control problem while preserving nonlinear actuation mechanisms. The data-driven approach builds upon a state space discretization using a clustering algorithm which groups kinematically similar flow states into a low number of clusters. The temporal evolution of the probability distribution on this set of clusters is then described by a control-dependent Markov model. This Markov model can be used as predictor for the ergodic probability distribution for a particular control law. This probability distribution approximates the long-term behavior of the original system on which basis the optimal control law is determined. We examine how the approach can be used to improve the open-loop actuation in a separating flow dominated by Kelvin-Helmholtz shedding. For this purpose, the feature space, in which the model is learned, and the admissible control inputs are tailored to strongly oscillatory flows.

Predicting solar radiation based on available weather indicators

NASA Astrophysics Data System (ADS)

Sauer, Frank Joseph

Solar radiation prediction models are complex and require software that is not available for the household investor. The processing power within a normal desktop or laptop computer is sufficient to calculate similar models. This barrier to entry for the average consumer can be fixed by a model simple enough to be calculated by hand if necessary. Solar radiation modeling has been historically difficult to predict and accurate models have significant assumptions and restrictions on their use. Previous methods have been limited to linear relationships, location restrictions, or input data limits to one atmospheric condition. This research takes a novel approach by combining two techniques within the computational limits of a household computer; Clustering and Hidden Markov Models (HMMs). Clustering helps limit the large observation space which restricts the use of HMMs. Instead of using continuous data, and requiring significantly increased computations, the cluster can be used as a qualitative descriptor of each observation. HMMs incorporate a level of uncertainty and take into account the indirect relationship between meteorological indicators and solar radiation. This reduces the complexity of the model enough to be simply understood and accessible to the average household investor. The solar radiation is considered to be an unobservable state that each household will be unable to measure. The high temperature and the sky coverage are already available through the local or preferred source of weather information. By using the next day's prediction for high temperature and sky coverage, the model groups the data and then predicts the most likely range of radiation. This model uses simple techniques and calculations to give a broad estimate for the solar radiation when no other universal model exists for the average household.

Weak lensing calibration of mass bias in the REFLEX+BCS X-ray galaxy cluster catalogue

NASA Astrophysics Data System (ADS)

Simet, Melanie; Battaglia, Nicholas; Mandelbaum, Rachel; Seljak, Uroš

2017-04-01

The use of large, X-ray-selected Galaxy cluster catalogues for cosmological analyses requires a thorough understanding of the X-ray mass estimates. Weak gravitational lensing is an ideal method to shed light on such issues, due to its insensitivity to the cluster dynamical state. We perform a weak lensing calibration of 166 galaxy clusters from the REFLEX and BCS cluster catalogue and compare our results to the X-ray masses based on scaled luminosities from that catalogue. To interpret the weak lensing signal in terms of cluster masses, we compare the lensing signal to simple theoretical Navarro-Frenk-White models and to simulated cluster lensing profiles, including complications such as cluster substructure, projected large-scale structure and Eddington bias. We find evidence of underestimation in the X-ray masses, as expected, with = 0.75 ± 0.07 stat. ±0.05 sys. for our best-fitting model. The biases in cosmological parameters in a typical cluster abundance measurement that ignores this mass bias will typically exceed the statistical errors.

Baseline adjustments for binary data in repeated cross-sectional cluster randomized trials.

PubMed

Nixon, R M; Thompson, S G

2003-09-15

Analysis of covariance models, which adjust for a baseline covariate, are often used to compare treatment groups in a controlled trial in which individuals are randomized. Such analysis adjusts for any baseline imbalance and usually increases the precision of the treatment effect estimate. We assess the value of such adjustments in the context of a cluster randomized trial with repeated cross-sectional design and a binary outcome. In such a design, a new sample of individuals is taken from the clusters at each measurement occasion, so that baseline adjustment has to be at the cluster level. Logistic regression models are used to analyse the data, with cluster level random effects to allow for different outcome probabilities in each cluster. We compare the estimated treatment effect and its precision in models that incorporate a covariate measuring the cluster level probabilities at baseline and those that do not. In two data sets, taken from a cluster randomized trial in the treatment of menorrhagia, the value of baseline adjustment is only evident when the number of subjects per cluster is large. We assess the generalizability of these findings by undertaking a simulation study, and find that increased precision of the treatment effect requires both large cluster sizes and substantial heterogeneity between clusters at baseline, but baseline imbalance arising by chance in a randomized study can always be effectively adjusted for. Copyright 2003 John Wiley & Sons, Ltd.

Large-scale model quality assessment for improving protein tertiary structure prediction.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-06-15

Sampling structural models and ranking them are the two major challenges of protein structure prediction. Traditional protein structure prediction methods generally use one or a few quality assessment (QA) methods to select the best-predicted models, which cannot consistently select relatively better models and rank a large number of models well. Here, we develop a novel large-scale model QA method in conjunction with model clustering to rank and select protein structural models. It unprecedentedly applied 14 model QA methods to generate consensus model rankings, followed by model refinement based on model combination (i.e. averaging). Our experiment demonstrates that the large-scale model QA approach is more consistent and robust in selecting models of better quality than any individual QA method. Our method was blindly tested during the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM group. It was officially ranked third out of all 143 human and server predictors according to the total scores of the first models predicted for 78 CASP11 protein domains and second according to the total scores of the best of the five models predicted for these domains. MULTICOM's outstanding performance in the extremely competitive 2014 CASP11 experiment proves that our large-scale QA approach together with model clustering is a promising solution to one of the two major problems in protein structure modeling. The web server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/human/. © The Author 2015. Published by Oxford University Press.

Evaluating Uncertainty in GHG Emission Scenarios: Mapping IAM Outlooks With an Energy System Phase Space

NASA Astrophysics Data System (ADS)

Ritchie, W. J.; Dowlatabadi, H.

2017-12-01

Climate change modeling relies on projections of future greenhouse gas emissions and other phenomena leading to changes in planetary radiative forcing (RF). Pathways for long-run fossil energy use that map to total forcing outcomes are commonly depicted with integrated assessment models (IAMs). IAMs structure outlooks for 21st-century emissions with various theories for developments in demographics, economics, land-use, energy markets and energy service demands. These concepts are applied to understand global changes in two key factors relevant for scenarios of carbon emissions: total energy use (E) this century and the carbon intensity of that energy (F/E). A simple analytical and graphical approach can also illustrate the full range of outcomes for these variables to determine if IAMs provide sufficient coverage of the uncertainty space for future energy use. In this talk, we present a method for understanding uncertainties relevant to RF scenario components in a phase space. The phase space of a dynamic system represents significant factors as axes to capture the full range of physically possible states. A two-dimensional phase space of E and F/E presents the possible system states that can lead to various levels of total 21st-century carbon emissions. Once defined in this way, a phase space of these energy system coordinates allows for rapid characterization of large IAM scenario sets with machine learning techniques. This phase space method is applied to the levels of RF described by the Representative Concentration Pathways (RCPs). The resulting RCP phase space identifies characteristics of the baseline energy system outlooks provided by IAMs for IPCC Working Group III. We conduct a k-means cluster analysis to distinguish the major features of IAM scenarios for each RCP range. Cluster analysis finds the IAM scenarios in AR5 illustrate RCPs with consistent combinations of energy resources. This suggests IAM scenarios understate uncertainty ranges for future fossil energy combustion and are overly constrained, implying it is likely easier to achieve a 1.5˚ climate policy goal than previously demonstrated.

DISCOVERY OF A DISSOCIATIVE GALAXY CLUSTER MERGER WITH LARGE PHYSICAL SEPARATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dawson, William A.; Wittman, David; Jee, M. James

2012-03-10

We present DLSCL J0916.2+2951 (z = 0.53), a newly discovered major cluster merger in which the collisional cluster gas has become dissociated from the collisionless galaxies and dark matter (DM). We identified the cluster using optical and weak-lensing observations as part of the Deep Lens Survey. Our follow-up observations with Keck, Subaru, Hubble Space Telescope, and Chandra show that the cluster is a dissociative merger and constrain the DM self-interaction cross-section {sigma}{sub DM} m{sup -1}{sub DM} {approx}< 7 cm{sup 2} g{sup -1}. The system is observed at least 0.7 {+-} 0.2 Gyr since first pass-through, thus providing a picture ofmore » cluster mergers 2-5 times further progressed than similar systems observed to date. This improved temporal leverage has implications for our understanding of merging clusters and their impact on galaxy evolution.« less

Globular Clusters for Faint Galaxies

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2017-07-01

The origin of ultra-diffuse galaxies (UDGs) has posed a long-standing mystery for astronomers. New observations of several of these faint giants with the Hubble Space Telescope are now lending support to one theory.Faint-Galaxy MysteryHubble images of Dragonfly 44 (top) and DFX1 (bottom). The right panels show the data with greater contrast and extended objects masked. [van Dokkum et al. 2017]UDGs large, extremely faint spheroidal objects were first discovered in the Virgo galaxy cluster roughly three decades ago. Modern telescope capabilities have resulted in many more discoveries of similar faint galaxies in recent years, suggesting that they are a much more common phenomenon than we originally thought.Despite the many observations, UDGs still pose a number of unanswered questions. Chief among them: what are UDGs? Why are these objects the size of normal galaxies, yet so dim? There are two primary models that explain UDGs:UDGs were originally small galaxies, hence their low luminosity. Tidal interactions then puffed them up to the large size we observe today.UDGs are effectively failed galaxies. They formed the same way as normal galaxies of their large size, but something truncated their star formation early, preventing them from gaining the brightness that we would expect for galaxies of their size.Now a team of scientists led by Pieter van Dokkum (Yale University) has made some intriguing observations with Hubble that lend weight to one of these models.Globulars observed in 16 Coma-cluster UDGs by Hubble. The top right panel shows the galaxy identifications. The top left panel shows the derived number of globular clusters in each galaxy. [van Dokkum et al. 2017]Globulars GaloreVan Dokkum and collaborators imaged two UDGs with Hubble: Dragonfly 44 and DFX1, both located in the Coma galaxy cluster. These faint galaxies are both smooth and elongated, with no obvious irregular features, spiral arms, star-forming regions, or other indications of tidal interactions.The most striking feature of these galaxies, however, is that they are surrounded by a large number of compact objects that appear to be globular clusters. From the observations, Van Dokkum and collaborators estimate that Dragonfly 44 and DFX1 have approximately 74 and 62 globulars, respectively significantly more than the low numbers expected for galaxies of this luminosity.Armed with this knowledge, the authors went back and looked at archival observations of 14 other UDGs also located in the Coma cluster. They found that these smaller and fainter galaxies dont host quite as many globular clusters as Dragonfly 44 and DFX1, but more than half also show significant overdensities of globulars.Main panel: relation between the number of globular clusters and total absolute magnitude for Coma UDGs (solid symbols) compared to normal galaxies (open symbols). Top panel: relation between effective radius and absolute magnitude. The UDGs are significantly larger and have more globular clusters than normal galaxies of the same luminosity. [van Dokkum et al. 2017]Evidence of FailureIn general, UDGs appear to have more globular clusters than other galaxies of the same total luminosity, by a factor of nearly 7. These results are consistent with the scenario in which UDGs are failed galaxies: they likely have the halo mass to have formed a large number of globular clusters, but they were quenched before they formed a disk and bulge. Because star formation never got going in UDGs, they are now much dimmer than other galaxies of the same size.The authors suggest that the next step is to obtain dynamical measurements of the UDGs to determine whether these faint galaxies really do have the halo mass suggested by their large numbers of globulars. Future observations will continue to help us pin down the origin of these dim giants.CitationPieter van Dokkum et al 2017 ApJL 844 L11. doi:10.3847/2041-8213/aa7ca2

Aryl-Aryl Interactions in Designed Peptide Folds: Spectroscopic Characteristics and Placement Issues for Optimal Structure Stabilization

PubMed Central

Anderson, Jordan M.; Kier, Brandon; Jurban, Brice; Byrne, Aimee; Shu, Irene; Eidenschink, Lisa A.; Shcherbakov, Alexander A.; Hudson, Mike; Fesinmeyer, R. M.; Andersen, Niels H.

2017-01-01

We have extended our studies of Trp/Trp to other Aryl/Aryl through-space interactions that stabilize hairpins and other small polypeptide folds. Herein we detail the NMR and CD spectroscopic features of these types of interactions. NMR data remains the best diagnostic for characterizing the common T-shape orientation. Designated as an edge-to-face (EtF or FtE) interaction, large ring current shifts are produced at the edge aryl ring hydrogens and, in most cases, large exciton couplets appear in the far UV circular dichroic (CD) spectrum. The preference for the face aryl in FtE clusters is W≫Y≥F (there are some exceptions in the Y/F order); this sequence corresponds to the order of fold stability enhancement and always predicts the amplitude of the lower energy feature of the exciton couplet in the CD spectrum. The CD spectra for FtE W/W, W/Y, Y/W, and Y/Y pairs all include an intense feature at 225–232 nm. An additional couplet feature seen for W/Y, W/F, Y/Y and F/Y clusters, is a negative feature at 197–200 nm. Tyr/Tyr (as well as F/Y and F/F) interactions produce much smaller exciton couplet amplitudes. The Trp-cage fold was employed to search for the CD effects of other Trp/Trp and Trp/Tyr cluster geometries: several were identified. In this account, we provide additional examples of the application of cross-strand aryl/aryl clusters for the design of stable β-sheet models and a scale of fold stability increments associated with all possible FtE Ar/Ar clusters in several structural contexts. PMID:26850220

Estimating under-five mortality in space and time in a developing world context.

PubMed

Wakefield, Jon; Fuglstad, Geir-Arne; Riebler, Andrea; Godwin, Jessica; Wilson, Katie; Clark, Samuel J

2018-01-01

Accurate estimates of the under-five mortality rate in a developing world context are a key barometer of the health of a nation. This paper describes a new model to analyze survey data on mortality in this context. We are interested in both spatial and temporal description, that is wishing to estimate under-five mortality rate across regions and years and to investigate the association between the under-five mortality rate and spatially varying covariate surfaces. We illustrate the methodology by producing yearly estimates for subnational areas in Kenya over the period 1980-2014 using data from the Demographic and Health Surveys, which use stratified cluster sampling. We use a binomial likelihood with fixed effects for the urban/rural strata and random effects for the clustering to account for the complex survey design. Smoothing is carried out using Bayesian hierarchical models with continuous spatial and temporally discrete components. A key component of the model is an offset to adjust for bias due to the effects of HIV epidemics. Substantively, there has been a sharp decline in Kenya in the under-five mortality rate in the period 1980-2014, but large variability in estimated subnational rates remains. A priority for future research is understanding this variability. In exploratory work, we examine whether a variety of spatial covariate surfaces can explain the variability in under-five mortality rate. Temperature, precipitation, a measure of malaria infection prevalence, and a measure of nearness to cities were candidates for inclusion in the covariate model, but the interplay between space, time, and covariates is complex.

Jellyfish: Observational Properties of Extreme Ram-Pressure Stripping Events in Massive Galaxy Clusters

NASA Astrophysics Data System (ADS)

Conor, McPartland; Ebeling, Harald; Roediger, Elke

2015-08-01

We investigate the physical origin and observational signatures of extreme ram-pressure stripping (RPS) in 63 massive galaxy clusters at z=0.3-0.7, based on data in the F606W passband obtained with the Advanced Camera for Surveys aboard the Hubble Space Telescope. Using a training set of a dozen ``jellyfish" galaxies identified earlier in the same imaging data, we define quantitative morphological criteria to select candidate galaxies which are similar to known cases of RPS. Considering a sample of 16 ``jellyfish" galaxies (10 of which we present for the first time), we visually derive estimates of the projected direction of motion based on dynamical features such as apparent compression shocks and debris trails. Our findings suggest that the observed events occur primarily at large distances from the cluster core and involve infall trajectories featuring high impact parameters. Simple models of cluster growth show that such trajectories are consistent with two scenarios: 1) galaxy infall along filaments; and 2) infall at high velocities (≥1000 km/s) characteristic of cluster mergers. The observed distribution of events is best described by timescales of ˜few Myr in agreement with recent numerical simulations of RPS. The broader areal coverage of the Hubble Frontier Fields should provide an even larger sample of RPS events to determine the relative contributions of infall and cluster mergers. Prompted by the discovery of several jellyfish galaxies whose brightness in the F606W passband rivals or exceeds that of the respective brightest cluster galaxy, we attempt to constrain the luminosity function of galaxies undergoing RPS. The observed significant excess at the bright end compared to the luminosity functions of blue cluster members strongly suggests enhanced star formation, thus challenging theoretical and numerical studies according to which RPS merely displaces existing star-forming regions. In-depth studies of individual objects will help test our conclusions and allow a quantitative comparison with predictions of theoretical and numerical models of ram-pressure stripping.

Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates

DOE PAGES

Old, L.; Wojtak, R.; Pearce, F. R.; ...

2017-12-20

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously withmore » commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 10 14 and ≳ 20 percent for ≲ 10 13.5. Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.« less

Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Old, L.; Wojtak, R.; Pearce, F. R.

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously withmore » commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 10 14 and ≳ 20 percent for ≲ 10 13.5. Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.« less

Fascioliasis risk factors and space-time clusters in domestic ruminants in Bangladesh.

PubMed

Rahman, A K M Anisur; Islam, S K Shaheenur; Talukder, Md Hasanuzzaman; Hassan, Md Kumrul; Dhand, Navneet K; Ward, Michael P

2017-05-08

A retrospective observational study was conducted to identify fascioliasis hotspots, clusters, potential risk factors and to map fascioliasis risk in domestic ruminants in Bangladesh. Cases of fascioliasis in cattle, buffalo, sheep and goats from all districts in Bangladesh between 2011 and 2013 were identified via secondary surveillance data from the Department of Livestock Services' Epidemiology Unit. From each case report, date of report, species affected and district data were extracted. The total number of domestic ruminants in each district was used to calculate fascioliasis cases per ten thousand animals at risk per district, and this was used for cluster and hotspot analysis. Clustering was assessed with Moran's spatial autocorrelation statistic, hotspots with the local indicator of spatial association (LISA) statistic and space-time clusters with the scan statistic (Poisson model). The association between district fascioliasis prevalence and climate (temperature, precipitation), elevation, land cover and water bodies was investigated using a spatial regression model. A total of 1,723,971 cases of fascioliasis were reported in the three-year study period in cattle (1,164,560), goats (424,314), buffalo (88,924) and sheep (46,173). A total of nine hotspots were identified; one of these persisted in each of the three years. Only two local clusters were found. Five space-time clusters located within 22 districts were also identified. Annual risk maps of fascioliasis cases correlated with the hotspots and clusters detected. Cultivated and managed (P < 0.001) and artificial surface (P = 0.04) land cover areas, and elevation (P = 0.003) were positively and negatively associated with fascioliasis in Bangladesh, respectively. Results indicate that due to land use characteristics some areas of Bangladesh are at greater risk of fascioliasis. The potential risk factors, hot spots and clusters identified in this study can be used to guide science-based treatment and control decisions for fascioliasis in Bangladesh and in other similar geo-climatic zones throughout the world.

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

Complementary views on electron spectra: From fluctuation diagnostics to real-space correlations

NASA Astrophysics Data System (ADS)

Gunnarsson, O.; Merino, J.; Schäfer, T.; Sangiovanni, G.; Rohringer, G.; Toschi, A.

2018-03-01

We study the relation between the microscopic properties of a many-body system and the electron spectra, experimentally accessible by photoemission. In a recent paper [O. Gunnarsson et al., Phys. Rev. Lett. 114, 236402 (2015), 10.1103/PhysRevLett.114.236402], we introduced the "fluctuation diagnostics" approach to extract the dominant wave-vector-dependent bosonic fluctuations from the electronic self-energy. Here, we first reformulate the theory in terms of fermionic modes to render its connection with resonance valence bond (RVB) fluctuations more transparent. Second, by using a large-U expansion, where U is the Coulomb interaction, we relate the fluctuations to real-space correlations. Therefore, it becomes possible to study how electron spectra are related to charge, spin, superconductivity, and RVB-like real-space correlations, broadening the analysis of an earlier work [J. Merino and O. Gunnarsson, Phys. Rev. B 89, 245130 (2014), 10.1103/PhysRevB.89.245130]. This formalism is applied to the pseudogap physics of the two-dimensional Hubbard model, studied in the dynamical cluster approximation. We perform calculations for embedded clusters with up to 32 sites, having three inequivalent K points at the Fermi surface. We find that as U is increased, correlation functions gradually attain values consistent with an RVB state. This first happens for correlation functions involving the antinodal point and gradually spreads to the nodal point along the Fermi surface. Simultaneously, a pseudogap opens up along the Fermi surface. We relate this to a crossover from a Kondo-type state to an RVB-like localized cluster state and to the presence of RVB and spin fluctuations. These changes are caused by a strong momentum dependence in the cluster bath couplings along the Fermi surface. We also show, from a more algorithmic perspective, how the time-consuming calculations in fluctuation diagnostics can be drastically simplified.

Accelerating three-dimensional FDTD calculations on GPU clusters for electromagnetic field simulation.

PubMed

Nagaoka, Tomoaki; Watanabe, Soichi

2012-01-01

Electromagnetic simulation with anatomically realistic computational human model using the finite-difference time domain (FDTD) method has recently been performed in a number of fields in biomedical engineering. To improve the method's calculation speed and realize large-scale computing with the computational human model, we adapt three-dimensional FDTD code to a multi-GPU cluster environment with Compute Unified Device Architecture and Message Passing Interface. Our multi-GPU cluster system consists of three nodes. The seven GPU boards (NVIDIA Tesla C2070) are mounted on each node. We examined the performance of the FDTD calculation on multi-GPU cluster environment. We confirmed that the FDTD calculation on the multi-GPU clusters is faster than that on a multi-GPU (a single workstation), and we also found that the GPU cluster system calculate faster than a vector supercomputer. In addition, our GPU cluster system allowed us to perform the large-scale FDTD calculation because were able to use GPU memory of over 100 GB.

Cluster-based analysis of multi-model climate ensembles

NASA Astrophysics Data System (ADS)

Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

2018-06-01

Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and useful framework in which to assess and visualise model spread, offering insight into geographical areas of agreement among models and a measure of diversity across an ensemble. Finally, we discuss caveats of the clustering techniques and note that while we have focused on tropospheric ozone, the principles underlying the cluster-based MMMs are applicable to other prognostic variables from climate models.

VizieR Online Data Catalog: Grism Lens-Amplified Survey from Space (GLASS). I. (Treu+, 2015)

NASA Astrophysics Data System (ADS)

Treu, T.; Schmidt, K. B.; Brammer, G. B.; Vulcani, B.; Wang, X.; Bradac, M.; Dijkstra, M.; Dressler, A.; Fontana, A.; Gavazzi, R.; Henry, A. L.; Hoag, A.; Huang, K.-H.; Jones, T. A.; Kelly, P. L.; Malkan, M. A.; Mason, C.; Pentericci, L.; Poggianti, B.; Stiavelli, M.; Trenti, M.; von der Linden, A.

2016-02-01

In this paper we give an overview of Grism Lens Amplified Survey from Space (GLASS; PI Treu; GO 13459) and we present the first release of the data for MACS J0717.5+3745, the first cluster targeted by the survey. Spectra for 1151 galaxies down to magnitude HAB=24 (F140W) have been visually inspected by members of our team to ensure quality control. GLASS is a cycle-21 large program with the Hubble Space Telescope (HST), targeting 10 massive clusters, including the 6 Frontier Fields, using the WFC3 and ACS grisms. The program consists of 140 primary orbits (with the G102 and G141 grisms; range 0.81-1.69μm) and 140 parallel orbits (with the G800L grism). (2 data files).

The impact of Lyman-α radiative transfer on large-scale clustering in the Illustris simulation

NASA Astrophysics Data System (ADS)

Behrens, C.; Byrohl, C.; Saito, S.; Niemeyer, J. C.

2018-06-01

Context. Lyman-α emitters (LAEs) are a promising probe of the large-scale structure at high redshift, z ≳ 2. In particular, the Hobby-Eberly Telescope Dark Energy Experiment aims at observing LAEs at 1.9 < z < 3.5 to measure the baryon acoustic oscillation (BAO) scale and the redshift-space distortion (RSD). However, it has been pointed out that the complicated radiative transfer (RT) of the resonant Lyman-α emission line generates an anisotropic selection bias in the LAE clustering on large scales, s ≳ 10 Mpc. This effect could potentially induce a systematic error in the BAO and RSD measurements. Also, there exists a recent claim to have observational evidence of the effect in the Lyman-α intensity map, albeit statistically insignificant. Aims: We aim at quantifying the impact of the Lyman-α RT on the large-scale galaxy clustering in detail. For this purpose, we study the correlations between the large-scale environment and the ratio of an apparent Lyman-α luminosity to an intrinsic one, which we call the "observed fraction", at 2 < z < 6. Methods: We apply our Lyman-α RT code by post-processing the full Illustris simulations. We simply assume that the intrinsic luminosity of the Lyman-α emission is proportional to the star formation rate of galaxies in Illustris, yielding a sufficiently large sample of LAEs to measure the anisotropic selection bias. Results: We find little correlation between large-scale environment and the observed fraction induced by the RT, and hence a smaller anisotropic selection bias than has previously been claimed. We argue that the anisotropy was overestimated in previous work due to insufficient spatial resolution; it is important to keep the resolution such that it resolves the high-density region down to the scale of the interstellar medium, that is, 1 physical kpc. We also find that the correlation can be further enhanced by assumptions in modeling intrinsic Lyman-α emission.

Multi-Parent Clustering Algorithms from Stochastic Grammar Data Models

NASA Technical Reports Server (NTRS)

Mjoisness, Eric; Castano, Rebecca; Gray, Alexander

1999-01-01

We introduce a statistical data model and an associated optimization-based clustering algorithm which allows data vectors to belong to zero, one or several "parent" clusters. For each data vector the algorithm makes a discrete decision among these alternatives. Thus, a recursive version of this algorithm would place data clusters in a Directed Acyclic Graph rather than a tree. We test the algorithm with synthetic data generated according to the statistical data model. We also illustrate the algorithm using real data from large-scale gene expression assays.

Using Clustering to Establish Climate Regimes from PCM Output

NASA Technical Reports Server (NTRS)

Oglesby, Robert; Arnold, James E. (Technical Monitor); Hoffman, Forrest; Hargrove, W. W.; Erickson, D.

2002-01-01

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

A Sequential Ensemble Prediction System at Convection Permitting Scales

NASA Astrophysics Data System (ADS)

Milan, M.; Simmer, C.

2012-04-01

A Sequential Assimilation Method (SAM) following some aspects of particle filtering with resampling, also called SIR (Sequential Importance Resampling), is introduced and applied in the framework of an Ensemble Prediction System (EPS) for weather forecasting on convection permitting scales, with focus to precipitation forecast. At this scale and beyond, the atmosphere increasingly exhibits chaotic behaviour and non linear state space evolution due to convectively driven processes. One way to take full account of non linear state developments are particle filter methods, their basic idea is the representation of the model probability density function by a number of ensemble members weighted by their likelihood with the observations. In particular particle filter with resampling abandons ensemble members (particles) with low weights restoring the original number of particles adding multiple copies of the members with high weights. In our SIR-like implementation we substitute the likelihood way to define weights and introduce a metric which quantifies the "distance" between the observed atmospheric state and the states simulated by the ensemble members. We also introduce a methodology to counteract filter degeneracy, i.e. the collapse of the simulated state space. To this goal we propose a combination of resampling taking account of simulated state space clustering and nudging. By keeping cluster representatives during resampling and filtering, the method maintains the potential for non linear system state development. We assume that a particle cluster with initially low likelihood may evolve in a state space with higher likelihood in a subsequent filter time thus mimicking non linear system state developments (e.g. sudden convection initiation) and remedies timing errors for convection due to model errors and/or imperfect initial condition. We apply a simplified version of the resampling, the particles with highest weights in each cluster are duplicated; for the model evolution for each particle pair one particle evolves using the forward model; the second particle, however, is nudged to the radar and satellite observation during its evolution based on the forward model.

Automated modal parameter estimation using correlation analysis and bootstrap sampling

NASA Astrophysics Data System (ADS)

Yaghoubi, Vahid; Vakilzadeh, Majid K.; Abrahamsson, Thomas J. S.

2018-02-01

The estimation of modal parameters from a set of noisy measured data is a highly judgmental task, with user expertise playing a significant role in distinguishing between estimated physical and noise modes of a test-piece. Various methods have been developed to automate this procedure. The common approach is to identify models with different orders and cluster similar modes together. However, most proposed methods based on this approach suffer from high-dimensional optimization problems in either the estimation or clustering step. To overcome this problem, this study presents an algorithm for autonomous modal parameter estimation in which the only required optimization is performed in a three-dimensional space. To this end, a subspace-based identification method is employed for the estimation and a non-iterative correlation-based method is used for the clustering. This clustering is at the heart of the paper. The keys to success are correlation metrics that are able to treat the problems of spatial eigenvector aliasing and nonunique eigenvectors of coalescent modes simultaneously. The algorithm commences by the identification of an excessively high-order model from frequency response function test data. The high number of modes of this model provides bases for two subspaces: one for likely physical modes of the tested system and one for its complement dubbed the subspace of noise modes. By employing the bootstrap resampling technique, several subsets are generated from the same basic dataset and for each of them a model is identified to form a set of models. Then, by correlation analysis with the two aforementioned subspaces, highly correlated modes of these models which appear repeatedly are clustered together and the noise modes are collected in a so-called Trashbox cluster. Stray noise modes attracted to the mode clusters are trimmed away in a second step by correlation analysis. The final step of the algorithm is a fuzzy c-means clustering procedure applied to a three-dimensional feature space to assign a degree of physicalness to each cluster. The proposed algorithm is applied to two case studies: one with synthetic data and one with real test data obtained from a hammer impact test. The results indicate that the algorithm successfully clusters similar modes and gives a reasonable quantification of the extent to which each cluster is physical.

Earth Observation

NASA Image and Video Library

2014-06-12

ISS040-E-010458 (12 June 2014) --- Early morning of June 12, one of the Expedition 40 crew members aboard the International Space Station took this picture of Brazil, site of the 2014 World Cup soccer matches, which start this week. Sao Paulo is the large cluster of night lights near the coast on the right side of the frame. Rio de Janeiro is the coastal city to the left of Sao Paulo. Belo Horizonte is the cluster of lights near frame center.

Photometry Using Kepler "Superstamps" of Open Clusters NGC 6791 & NGC 6819

NASA Astrophysics Data System (ADS)

Kuehn, Charles A.; Drury, Jason A.; Bellamy, Beau R.; Stello, Dennis; Bedding, Timothy R.; Reed, Mike; Quick, Breanna

2015-09-01

The Kepler space telescope has proven to be a gold mine for the study of variable stars. Usually, Kepler only reads out a handful of pixels around each pre-selected target star, omitting a large number of stars in the Kepler field. Fortunately, for the open clusters NGC 6791 and NGC 6819, Kepler also read out larger "superstamps" which contained complete images of the central region of each cluster. These cluster images can be used to study additional stars in the open clusters that were not originally on Kepler's target list. We discuss our work on using two photometric techniques to analyze these superstamps and present sample results from this project to demonstrate the value of this technique for a wide variety of variable stars.

Discrete bivariate population balance modelling of heteroaggregation processes.

PubMed

Rollié, Sascha; Briesen, Heiko; Sundmacher, Kai

2009-08-15

Heteroaggregation in binary particle mixtures was simulated with a discrete population balance model in terms of two internal coordinates describing the particle properties. The considered particle species are of different size and zeta-potential. Property space is reduced with a semi-heuristic approach to enable an efficient solution. Aggregation rates are based on deterministic models for Brownian motion and stability, under consideration of DLVO interaction potentials. A charge-balance kernel is presented, relating the electrostatic surface potential to the property space by a simple charge balance. Parameter sensitivity with respect to the fractal dimension, aggregate size, hydrodynamic correction, ionic strength and absolute particle concentration was assessed. Results were compared to simulations with the literature kernel based on geometric coverage effects for clusters with heterogeneous surface properties. In both cases electrostatic phenomena, which dominate the aggregation process, show identical trends: impeded cluster-cluster aggregation at low particle mixing ratio (1:1), restabilisation at high mixing ratios (100:1) and formation of complex clusters for intermediate ratios (10:1). The particle mixing ratio controls the surface coverage extent of the larger particle species. Simulation results are compared to experimental flow cytometric data and show very satisfactory agreement.

Prospects for Determining the Mass Distributions of Galaxy Clusters on Large Scales Using Weak Gravitational Lensing

NASA Astrophysics Data System (ADS)

Fong, M.; Bowyer, R.; Whitehead, A.; Lee, B.; King, L.; Applegate, D.; McCarthy, I.

2018-05-01

For more than two decades, the Navarro, Frenk, and White (NFW) model has stood the test of time; it has been used to describe the distribution of mass in galaxy clusters out to their outskirts. Stacked weak lensing measurements of clusters are now revealing the distribution of mass out to and beyond their virial radii, where the NFW model is no longer applicable. In this study we assess how well the parameterised Diemer & Kravstov (DK) density profile describes the characteristic mass distribution of galaxy clusters extracted from cosmological simulations. This is determined from stacked synthetic lensing measurements of the 50 most massive clusters extracted from the Cosmo-OWLS simulations, using the Dark Matter Only run and also the run that most closely matches observations. The characteristics of the data reflect the Weighing the Giants survey and data from the future Large Synoptic Survey Telescope (LSST). In comparison with the NFW model, the DK model favored by the stacked data, in particular for the future LSST data, where the number density of background galaxies is higher. The DK profile depends on the accretion history of clusters which is specified in the current study. Eventually however subsamples of galaxy clusters with qualities indicative of disparate accretion histories could be studied.

The DAFT/FADA survey. I. Photometric redshifts along lines of sight to clusters in the z = [0.4, 0.9] interval

NASA Astrophysics Data System (ADS)

Guennou, L.; Adami, C.; Ulmer, M. P.; Lebrun, V.; Durret, F.; Johnston, D.; Ilbert, O.; Clowe, D.; Gavazzi, R.; Murphy, K.; Schrabback, T.; Allam, S.; Annis, J.; Basa, S.; Benoist, C.; Biviano, A.; Cappi, A.; Kubo, J. M.; Marshall, P.; Mazure, A.; Rostagni, F.; Russeil, D.; Slezak, E.

2010-11-01

Context. As a contribution to the understanding of the dark energy concept, the Dark energy American French Team (DAFT, in French FADA) has started a large project to characterize statistically high redshift galaxy clusters, infer cosmological constraints from weak lensing tomography, and understand biases relevant for constraining dark energy and cluster physics in future cluster and cosmological experiments. Aims: The purpose of this paper is to establish the basis of reference for the photo-z determination used in all our subsequent papers, including weak lensing tomography studies. Methods: This project is based on a sample of 91 high redshift (z ≥ 0.4), massive (⪆3 × 1014 M_⊙) clusters with existing HST imaging, for which we are presently performing complementary multi-wavelength imaging. This allows us in particular to estimate spectral types and determine accurate photometric redshifts for galaxies along the lines of sight to the first ten clusters for which all the required data are available down to a limit of IAB = 24./24.5 with the LePhare software. The accuracy in redshift is of the order of 0.05 for the range 0.2 ≤ z ≤ 1.5. Results: We verified that the technique applied to obtain photometric redshifts works well by comparing our results to with previous works. In clusters, photo-z accuracy is degraded for bright absolute magnitudes and for the latest and earliest type galaxies. The photo-z accuracy also only slightly varies as a function of the spectral type for field galaxies. As a consequence, we find evidence for an environmental dependence of the photo-z accuracy, interpreted as the standard used spectral energy distributions being not very well suited to cluster galaxies. Finally, we modeled the LCDCS 0504 mass with the strong arcs detected along this line of sight. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained from the data archive at the Space Telescope Institute and the Space Telescope European Coordinating Facility. STScI is operated by the association of Universities for Research in Astronomy, Inc. under the NASA contract NAS 5-26555. Also based on observations made with ESO Telescopes at Paranal and La Silla Observatories under programme ESO LP 166.A-0162. Also based on visiting astronomer observations, at Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy, under contract with the National Science Foundation.

Hubble tracks down a galaxy cluster's dark matter

NASA Astrophysics Data System (ADS)

2003-07-01

Unique mass map hi-res Size hi-res: 495 kb Credits: European Space Agency, NASA and Jean-Paul Kneib (Observatoire Midi-Pyrénées, France/Caltech, USA) Unique mass map This is a mass map of galaxy cluster Cl0024+1654 derived from an extensive Hubble Space Telescope campaign. The colour image is made from two images: a dark-matter map (the blue part of the image) and a 'luminous-matter' map determined from the galaxies in the cluster (the red part of the image). They were constructed by feeding Hubble and ground-based observations into advanced mathematical mass-mapping models. The map shows that dark matter is present where the galaxies clump together. The mass of the galaxies is shown in red, the mass of the dark matter in blue. The dark matter behaves like a 'glue', holding the cluster together. The dark-matter distribution in the cluster is not spherical. A secondary concentration of dark-matter mass is shown in blue to the upper right of the main concentration. Sky around galaxy cluster Cl0024+1654 hi-res Size hi-res: 3742 kb Credits: European Space Agency, NASA and Jean-Paul Kneib (Observatoire Midi-Pyrénées, France/Caltech, USA) Sky around galaxy cluster Cl0024+1654 This is a 2.5-degree field around galaxy cluster Cl0024+1654. The cluster galaxies are visible in the centre of the image in yellow. The image is a colour composite constructed from three Digitized Sky Survey 2 images: Blue (shown in blue), Red (shown in green), and Infrared (shown in red). HST observes shapes of more than 7000 faint background galaxies hi-res Size hi-res: 5593 kb Credits: European Space Agency, NASA and Jean-Paul Kneib (Observatoire Midi-Pyrénées, France/Caltech, USA) Hubble observes shapes of more than 7000 faint background galaxies Five days of observations produced the altogether 39 Hubble Wide Field and Planetary Camera 2 (WFPC2) images required to map the mass of the galaxy cluster Cl0024+1654. Each WFPC2 image has a size of about 1/150 the diameter of the full Moon. In total, the image measures 27 arc-minutes across, slightly smaller than the diameter of the Moon. The observed warped shapes of more than 7000 faint background galaxies have been converted into a unique map of the dark matter in the cluster. The images were taken through a red filter and have been reduced a factor of two in size. Ground-based image of the galaxy cluster C10024+1654 hi-res Size hi-res: 4699 kb Credits: European Space Agency, NASA and Jean-Paul Kneib (Observatoire Midi-Pyrénées, France/Caltech, USA) Ground-based image of the galaxy cluster C10024+1654 This is a colour image of the galaxy cluster C10024+1654 obtained with the CFHT12k camera at the Canada France Hawaii Telescope on Mauna Kea (Hawaii). The cluster clearly appears as a concentration of yellow galaxies in the centre of this image although cluster galaxies actually extend at least to the edge of this image. This image measures 21 x 21 arc-minutes. Clusters of galaxies are the largest stable systems in the Universe. They are like laboratories for studying the relationship between the distributions of dark and visible matter. In 1937, Fritz Zwicky realised that the visible component of a cluster (the thousands of millions of stars in each of the thousands of galaxies) represents only a tiny fraction of the total mass. About 80-85% of the matter is invisible, the so-called 'dark matter'. Although astronomers have known about the presence of dark matter for many decades, finding a technique to view its distribution is a much more recent development. Led by Drs Jean-Paul Kneib (from the Observatoire Midi-Pyrénées, France/Caltech, United States), Richard Ellis and Tommaso Treu (both Caltech, United States), the team used the NASA/ESA Hubble Space Telescope to reconstruct a unique 'mass map' of the galaxy cluster CL0024+1654. It enabled them to see for the first time on such large scales how mysterious dark matter is distributed with respect to galaxies. This comparison gives new clues on how such large clusters assemble and which role dark matter plays in cosmic evolution. Tracing dark matter is not an easy task because it does not shine. To make a map, astronomers must focus on much fainter, more distant galaxies behind the cluster. The shapes of these distant systems are distorted by the gravity of the foreground cluster. This distortion provides a measure of the cluster mass, a phenomenon known as 'weak gravitational lensing'. To map the dark matter of CL0024+1654, more than 120 hours observing time was dedicated to the team. This is the largest amount of Hubble time ever devoted to studying a galaxy cluster. Despite its distance of 4.5 thousand million light-years (about one third of the look-back time to the Big Bang) from Earth, this massive cluster is wide enough to equal the angular size of the full Moon. To make a mass map that covers the entire cluster required observations that probed 39 regions of the galaxy cluster. The investigation has resulted in the most comprehensive study of the distribution of dark matter in a galaxy cluster so far and extends more than 20 million light-years from its centre, much further than previous investigations. Many groups of researchers have tried to perform these types of measurements with ground-based telescopes. However, the technique relies heavily on finding the exact shapes of distant galaxies behind the cluster. The sharp vision of a space telescope such as NASA-ESA's Hubble is superior. The study reveals that the density of dark matter on large scales drops sharply with distance from the cluster centre. This confirms a picture that has emerged from recent detailed computer simulations. As Richard Ellis says: "Although theorists have predicted the form of dark matter in galaxy clusters from numerical simulations based on the effects of gravity alone, this is the first time we have convincing observations to back them up. Some astronomers had speculated clusters might contain large reservoirs of dark matter in their outermost regions. Assuming our cluster is representative, this is not the case." The team noticed that dark matter appears to clump together in their map. For example, they found concentrations of dark matter associated with galaxies known to be slowly falling into the system. Generally, the researchers found that the dark matter traces the cluster galaxies remarkably well and over an unprecedented range of physical scales. "When a cluster is being assembled, the dark matter will be smeared out between the galaxies where it acts like a glue," says Jean-Paul Kneib."The overall association of dark matter and 'glowing matter' is very convincing evidence that structures like CL0024+1654 grow by merging of smaller groups of galaxies that were already bound by their own dark matter components." Future investigations using Hubble's new camera, the Advanced Camera for Surveys (ACS), will extend this work when Hubble is trained on a second galaxy cluster later this year. ACS is 10 times more efficient than the Wide Field and Planetary Camera 2 used for this investigation, making it possible to study finer mass clumps in galaxy clusters and help work out how the clusters are assembled. Notes for editors The team is composed of Jean-Paul Kneib (Observatoire Midi-Pyrénées, France/Caltech, United States), Patrick Hudelot (Observatoire Midi-Pyrénées, France),Richard S. Ellis (Caltech, United States), Tommaso Treu (Caltech, United States), Graham P. Smith (Caltech, United States), Phil Marshall (MRAO, United Kingdom), Oliver Czoske (Institut für Astrophysik und Extraterrestrische Forschung, Germany), Ian Smail (University of Durham, United Kingdom) and Priya Natarajan (Yale University, United States). The ground-based observations were done with the Canada-France-Hawaii Telescope (CFHT) using the CFHT12k camera, the Keck telescopes, and the Hale 5-metre telescope at Palomar, United States, using the WIRC camera. The team will present their study at the General Assembly of the International Astronomical Union. They will also publish their results in a forthcoming issue of Astrophysical Journal. For broadcasters, animations of the discovery and general Hubble Space Telescope background footage is available from http://www.spacetelescope.org/video/releases.html Image credit: European Space Agency, NASA and Jean-Paul Kneib (Observatoire Midi-Pyrénées, France/Caltech, United States)

Spatiotemporal clusters of malaria cases at village level, northwest Ethiopia.

PubMed

Alemu, Kassahun; Worku, Alemayehu; Berhane, Yemane; Kumie, Abera

2014-06-06

Malaria attacks are not evenly distributed in space and time. In highland areas with low endemicity, malaria transmission is highly variable and malaria acquisition risk for individuals is unevenly distributed even within a neighbourhood. Characterizing the spatiotemporal distribution of malaria cases in high-altitude villages is necessary to prioritize the risk areas and facilitate interventions. Spatial scan statistics using the Bernoulli method were employed to identify spatial and temporal clusters of malaria in high-altitude villages. Daily malaria data were collected, using a passive surveillance system, from patients visiting local health facilities. Georeference data were collected at villages using hand-held global positioning system devices and linked to patient data. Bernoulli model using Bayesian approaches and Marcov Chain Monte Carlo (MCMC) methods were used to identify the effects of factors on spatial clusters of malaria cases. The deviance information criterion (DIC) was used to assess the goodness-of-fit of the different models. The smaller the DIC, the better the model fit. Malaria cases were clustered in both space and time in high-altitude villages. Spatial scan statistics identified a total of 56 spatial clusters of malaria in high-altitude villages. Of these, 39 were the most likely clusters (LLR = 15.62, p < 0.00001) and 17 were secondary clusters (LLR = 7.05, p < 0.03). The significant most likely temporal malaria clusters were detected between August and December (LLR = 17.87, p < 0.001). Travel away home, males and age above 15 years had statistically significant effect on malaria clusters at high-altitude villages. The study identified spatial clusters of malaria cases occurring at high elevation villages within the district. A patient who travelled away from home to a malaria-endemic area might be the most probable source of malaria infection in a high-altitude village. Malaria interventions in high altitude villages should address factors associated with malaria clustering.

GPU Accelerated Clustering for Arbitrary Shapes in Geoscience Data

NASA Astrophysics Data System (ADS)

Pankratius, V.; Gowanlock, M.; Rude, C. M.; Li, J. D.

2016-12-01

Clustering algorithms have become a vital component in intelligent systems for geoscience that helps scientists discover and track phenomena of various kinds. Here, we outline advances in Density-Based Spatial Clustering of Applications with Noise (DBSCAN) which detects clusters of arbitrary shape that are common in geospatial data. In particular, we propose a hybrid CPU-GPU implementation of DBSCAN and highlight new optimization approaches on the GPU that allows clustering detection in parallel while optimizing data transport during CPU-GPU interactions. We employ an efficient batching scheme between the host and GPU such that limited GPU memory is not prohibitive when processing large and/or dense datasets. To minimize data transfer overhead, we estimate the total workload size and employ an execution that generates optimized batches that will not overflow the GPU buffer. This work is demonstrated on space weather Total Electron Content (TEC) datasets containing over 5 million measurements from instruments worldwide, and allows scientists to spot spatially coherent phenomena with ease. Our approach is up to 30 times faster than a sequential implementation and therefore accelerates discoveries in large datasets. We acknowledge support from NSF ACI-1442997.

Blue straggler stars beyond the Milky Way: a non-segregated population in the Large Magellanic Cloud cluster NGC 2213

NASA Astrophysics Data System (ADS)

Li, Chengyuan; Hong, Jongsuk

2018-06-01

Using the high-resolution observations obtained by the Hubble Space Telescope, we analysed the blue straggler stars (BSSs) in the Large Magellanic Cloud cluster NGC 2213. We found that the radial distribution of BSSs is consistent with that of the normal giant stars in NGC 2213, showing no evidence of mass segregation. However, an analytic calculation carried out for these BSSs shows that they are already dynamically old, because the estimated half-mass relaxation time for these BSSs is significantly shorter than the isochronal age of the cluster. We also performed direct N-body simulations for an NGC 2213-like cluster to understand the dynamical processes that lead to this non-segregated radial distribution of BSSs. Our numerical simulation shows that the presence of black hole subsystems inside the cluster centre can significantly affect the dynamical evolution of BSSs. The combined effects of the delayed segregation, binary disruption, and exchange interactions of BSS progenitor binaries may result in this non-segregated radial distribution of BSSs in NGC 2213.

A Cluster-then-label Semi-supervised Learning Approach for Pathology Image Classification.

PubMed

Peikari, Mohammad; Salama, Sherine; Nofech-Mozes, Sharon; Martel, Anne L

2018-05-08

Completely labeled pathology datasets are often challenging and time-consuming to obtain. Semi-supervised learning (SSL) methods are able to learn from fewer labeled data points with the help of a large number of unlabeled data points. In this paper, we investigated the possibility of using clustering analysis to identify the underlying structure of the data space for SSL. A cluster-then-label method was proposed to identify high-density regions in the data space which were then used to help a supervised SVM in finding the decision boundary. We have compared our method with other supervised and semi-supervised state-of-the-art techniques using two different classification tasks applied to breast pathology datasets. We found that compared with other state-of-the-art supervised and semi-supervised methods, our SSL method is able to improve classification performance when a limited number of labeled data instances are made available. We also showed that it is important to examine the underlying distribution of the data space before applying SSL techniques to ensure semi-supervised learning assumptions are not violated by the data.

Nuclear Potential Clustering As a New Tool to Detect Patterns in High Dimensional Datasets

NASA Astrophysics Data System (ADS)

Tonkova, V.; Paulus, D.; Neeb, H.

2013-02-01

We present a new approach for the clustering of high dimensional data without prior assumptions about the structure of the underlying distribution. The proposed algorithm is based on a concept adapted from nuclear physics. To partition the data, we model the dynamic behaviour of nucleons interacting in an N-dimensional space. An adaptive nuclear potential, comprised of a short-range attractive (strong interaction) and a long-range repulsive term (Coulomb force) is assigned to each data point. By modelling the dynamics, nucleons that are densely distributed in space fuse to build nuclei (clusters) whereas single point clusters repel each other. The formation of clusters is completed when the system reaches the state of minimal potential energy. The data are then grouped according to the particles' final effective potential energy level. The performance of the algorithm is tested with several synthetic datasets showing that the proposed method can robustly identify clusters even when complex configurations are present. Furthermore, quantitative MRI data from 43 multiple sclerosis patients were analyzed, showing a reasonable splitting into subgroups according to the individual patients' disease grade. The good performance of the algorithm on such highly correlated non-spherical datasets, which are typical for MRI derived image features, shows that Nuclear Potential Clustering is a valuable tool for automated data analysis, not only in the MRI domain.

Improved Robustness and Efficiency for Automatic Visual Site Monitoring

DTIC Science & Technology

2009-09-01

the space of expected poses. To avoid having to compare each test window with the whole training corpus, he builds a template hierarchy by...directions of motion. In a second layer of clustering, it also learns how the low-level clusters co-occur with each other. An infinite mix- ture model is used...implementation. We demonstrate the utility of this detector by modeling scene-level activities with a Hierarchical

Enhanced momentum feedback from clustered supernovae

NASA Astrophysics Data System (ADS)

Gentry, Eric S.; Krumholz, Mark R.; Dekel, Avishai; Madau, Piero

2017-02-01

Young stars typically form in star clusters, so the supernovae (SNe) they produce are clustered in space and time. This clustering of SNe may alter the momentum per SN deposited in the interstellar medium (ISM) by affecting the local ISM density, which in turn affects the cooling rate. We study the effect of multiple SNe using idealized 1D hydrodynamic simulations which explore a large parameter space of the number of SNe, and the background gas density and metallicity. The results are provided as a table and an analytic fitting formula. We find that for clusters with up to ˜100 SNe, the asymptotic momentum scales superlinearly with the number of SNe, resulting in a momentum per SN which can be an order of magnitude larger than for a single SN, with a maximum efficiency for clusters with 10-100 SNe. We argue that additional physical processes not included in our simulations - self-gravity, breakout from a galactic disc, and galactic shear - can slightly reduce the momentum enhancement from clustering, but the average momentum per SN still remains a factor of 4 larger than the isolated SN value when averaged over a realistic cluster mass function for a star-forming galaxy. We conclude with a discussion of the possible role of mixing between hot and cold gas, induced by multidimensional instabilities or pre-existing density variations, as a limiting factor in the build-up of momentum by clustered SNe, and suggest future numerical experiments to explore these effects.

Application of hierarchical clustering method to classify of space-time rainfall patterns

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Chang, Tu-Je

2010-05-01

Understanding the local precipitation patterns is essential to the water resources management and flooding mitigation. The precipitation patterns can vary in space and time depending upon the factors from different spatial scales such as local topological changes and macroscopic atmospheric circulation. The spatiotemporal variation of precipitation in Taiwan is significant due to its complex terrain and its location at west pacific and subtropical area, where is the boundary between the pacific ocean and Asia continent with the complex interactions among the climatic processes. This study characterizes local-scale precipitation patterns by classifying the historical space-time precipitation records. We applied the hierarchical ascending clustering method to analyze the precipitation records from 1960 to 2008 at the six rainfall stations located in Lan-yang catchment at the northeast of the island. Our results identify the four primary space-time precipitation types which may result from distinct driving forces from the changes of atmospheric variables and topology at different space-time scales. This study also presents an important application of the statistical downscaling to combine large-scale upper-air circulation with local space-time precipitation patterns.

Million-body star cluster simulations: comparisons between Monte Carlo and direct N-body

NASA Astrophysics Data System (ADS)

Rodriguez, Carl L.; Morscher, Meagan; Wang, Long; Chatterjee, Sourav; Rasio, Frederic A.; Spurzem, Rainer

2016-12-01

We present the first detailed comparison between million-body globular cluster simulations computed with a Hénon-type Monte Carlo code, CMC, and a direct N-body code, NBODY6++GPU. Both simulations start from an identical cluster model with 106 particles, and include all of the relevant physics needed to treat the system in a highly realistic way. With the two codes `frozen' (no fine-tuning of any free parameters or internal algorithms of the codes) we find good agreement in the overall evolution of the two models. Furthermore, we find that in both models, large numbers of stellar-mass black holes (>1000) are retained for 12 Gyr. Thus, the very accurate direct N-body approach confirms recent predictions that black holes can be retained in present-day, old globular clusters. We find only minor disagreements between the two models and attribute these to the small-N dynamics driving the evolution of the cluster core for which the Monte Carlo assumptions are less ideal. Based on the overwhelming general agreement between the two models computed using these vastly different techniques, we conclude that our Monte Carlo approach, which is more approximate, but dramatically faster compared to the direct N-body, is capable of producing an accurate description of the long-term evolution of massive globular clusters even when the clusters contain large populations of stellar-mass black holes.

Performance evaluation of Space Shuttle SRB parachutes from air drop and scaled model wind tunnel tests. [Solid Rocket Booster recovery system

NASA Technical Reports Server (NTRS)

Moog, R. D.; Bacchus, D. L.; Utreja, L. R.

1979-01-01

The aerodynamic performance characteristics have been determined for the Space Shuttle Solid Rocket Booster drogue, main, and pilot parachutes. The performance evaluation on the 20-degree conical ribbon parachutes is based primarily on air drop tests of full scale prototype parachutes. In addition, parametric wind tunnel tests were performed and used in parachute configuration development and preliminary performance assessments. The wind tunnel test data are compared to the drop test results and both sets of data are used to determine the predicted performance of the Solid Rocket Booster flight parachutes. Data from other drop tests of large ribbon parachutes are also compared with the Solid Rocket Booster parachute performance characteristics. Parameters assessed include full open terminal drag coefficients, reefed drag area, opening characteristics, clustering effects, and forebody interference.

The Resolved Stellar Populations in the LEGUS Galaxies1

NASA Astrophysics Data System (ADS)

Sabbi, E.; Calzetti, D.; Ubeda, L.; Adamo, A.; Cignoni, M.; Thilker, D.; Aloisi, A.; Elmegreen, B. G.; Elmegreen, D. M.; Gouliermis, D. A.; Grebel, E. K.; Messa, M.; Smith, L. J.; Tosi, M.; Dolphin, A.; Andrews, J. E.; Ashworth, G.; Bright, S. N.; Brown, T. M.; Chandar, R.; Christian, C.; Clayton, G. C.; Cook, D. O.; Dale, D. A.; de Mink, S. E.; Dobbs, C.; Evans, A. S.; Fumagalli, M.; Gallagher, J. S., III; Grasha, K.; Herrero, A.; Hunter, D. A.; Johnson, K. E.; Kahre, L.; Kennicutt, R. C.; Kim, H.; Krumholz, M. R.; Lee, J. C.; Lennon, D.; Martin, C.; Nair, P.; Nota, A.; Östlin, G.; Pellerin, A.; Prieto, J.; Regan, M. W.; Ryon, J. E.; Sacchi, E.; Schaerer, D.; Schiminovich, D.; Shabani, F.; Van Dyk, S. D.; Walterbos, R.; Whitmore, B. C.; Wofford, A.

2018-03-01

The Legacy ExtraGalactic UV Survey (LEGUS) is a multiwavelength Cycle 21 Treasury program on the Hubble Space Telescope. It studied 50 nearby star-forming galaxies in 5 bands from the near-UV to the I-band, combining new Wide Field Camera 3 observations with archival Advanced Camera for Surveys data. LEGUS was designed to investigate how star formation occurs and develops on both small and large scales, and how it relates to the galactic environments. In this paper we present the photometric catalogs for all the apparently single stars identified in the 50 LEGUS galaxies. Photometric catalogs and mosaicked images for all filters are available for download. We present optical and near-UV color–magnitude diagrams for all the galaxies. For each galaxy we derived the distance from the tip of the red giant branch. We then used the NUV color–magnitude diagrams to identify stars more massive than 14 M ⊙, and compared their number with the number of massive stars expected from the GALEX FUV luminosity. Our analysis shows that the fraction of massive stars forming in star clusters and stellar associations is about constant with the star formation rate. This lack of a relation suggests that the timescale for evaporation of unbound structures is comparable or longer than 10 Myr. At low star formation rates this translates to an excess of mass in clustered environments as compared to model predictions of cluster evolution, suggesting that a significant fraction of stars form in unbound systems. Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by AURA Inc., under NASA contract NAS 5-26555.

Spitzer Lensing Cluster Legacy Survey

NASA Astrophysics Data System (ADS)

Soifer, Tom; Armus, Lee; Bradac, Marusa; Capak, Peter; Coe, Dan; Siana, Brian; Treu, Tommaso; Vieira, Joaquin

2015-11-01

Cluster-scale gravitational lenses act as cosmic telescopes, enabling the study of otherwise unobservable galaxies. They are critical in answering the questions such as what is the star formation history at z > 7, and whether these galaxies can reionize the Universe. Accurate knowledge of stellar masses, ages, and star formation rates at this epoch requires measuring both rest-frame UV and optical light, which only Spitzer and HST can probe at z>7-11 for a large enough sample of typical galaxies. To address this cosmic puzzle, we propose a program that obtains shallow Spitzer/IRAC imaging of a large sample of cluster lenses, followed by deep imaging of those clusters with the largest number of z > 7 candidate galaxies. This proposal will be a valuable Legacy complement to the existing IRAC deep surveys, and it will open up a new parameter space by probing the ordinary yet magnified population. Furthermore, it will enable the measurements of the stellar mass of the galaxy cluster population, thereby allowing us to chart the build-up of the cluster red sequence from z~1 to the present and to determine the physical processes responsible for this stellar mass growth.

Machine-learned cluster identification in high-dimensional data.

PubMed

Ultsch, Alfred; Lötsch, Jörn

2017-02-01

High-dimensional biomedical data are frequently clustered to identify subgroup structures pointing at distinct disease subtypes. It is crucial that the used cluster algorithm works correctly. However, by imposing a predefined shape on the clusters, classical algorithms occasionally suggest a cluster structure in homogenously distributed data or assign data points to incorrect clusters. We analyzed whether this can be avoided by using emergent self-organizing feature maps (ESOM). Data sets with different degrees of complexity were submitted to ESOM analysis with large numbers of neurons, using an interactive R-based bioinformatics tool. On top of the trained ESOM the distance structure in the high dimensional feature space was visualized in the form of a so-called U-matrix. Clustering results were compared with those provided by classical common cluster algorithms including single linkage, Ward and k-means. Ward clustering imposed cluster structures on cluster-less "golf ball", "cuboid" and "S-shaped" data sets that contained no structure at all (random data). Ward clustering also imposed structures on permuted real world data sets. By contrast, the ESOM/U-matrix approach correctly found that these data contain no cluster structure. However, ESOM/U-matrix was correct in identifying clusters in biomedical data truly containing subgroups. It was always correct in cluster structure identification in further canonical artificial data. Using intentionally simple data sets, it is shown that popular clustering algorithms typically used for biomedical data sets may fail to cluster data correctly, suggesting that they are also likely to perform erroneously on high dimensional biomedical data. The present analyses emphasized that generally established classical hierarchical clustering algorithms carry a considerable tendency to produce erroneous results. By contrast, unsupervised machine-learned analysis of cluster structures, applied using the ESOM/U-matrix method, is a viable, unbiased method to identify true clusters in the high-dimensional space of complex data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

New Constraints on a Complex Relation between Globular Cluster Colors and Environment

NASA Astrophysics Data System (ADS)

Powalka, Mathieu; Puzia, Thomas H.; Lançon, Ariane; Peng, Eric W.; Schönebeck, Frederik; Alamo-Martínez, Karla; Ángel, Simón; Blakeslee, John P.; Côté, Patrick; Cuillandre, Jean-Charles; Duc, Pierre-Alain; Durrell, Patrick; Ferrarese, Laura; Grebel, Eva K.; Guhathakurta, Puragra; Gwyn, S. D. J.; Kuntschner, Harald; Lim, Sungsoon; Liu, Chengze; Lyubenova, Mariya; Mihos, J. Christopher; Muñoz, Roberto P.; Ordenes-Briceño, Yasna; Roediger, Joel; Sánchez-Janssen, Rubén; Spengler, Chelsea; Toloba, Elisa; Zhang, Hongxin

2016-09-01

We present an analysis of high-quality photometry for globular clusters (GCs) in the Virgo cluster core region, based on data from the Next Generation Virgo Cluster Survey (NGVS) pilot field, and in the Milky Way (MW), based on Very Large Telescope/X-Shooter spectrophotometry. We find significant discrepancies in color-color diagrams between sub-samples from different environments, confirming that the environment has a strong influence on the integrated colors of GCs. GC color distributions along a single color are not sufficient to capture the differences we observe in color-color space. While the average photometric colors become bluer with increasing radial distance to the cD galaxy M87, we also find a relation between the environment and the slope and intercept of the color-color relations. A denser environment seems to produce a larger dynamic range in certain color indices. We argue that these results are not due solely to differential extinction, Initial Mass Function variations, calibration uncertainties, or overall age/metallicity variations. We therefore suggest that the relation between the environment and GC colors is, at least in part, due to chemical abundance variations, which affect stellar spectra and stellar evolution tracks. Our results demonstrate that stellar population diagnostics derived from model predictions which are calibrated on one particular sample of GCs may not be appropriate for all extragalactic GCs. These results advocate a more complex model of the assembly history of GC systems in massive galaxies that goes beyond the simple bimodality found in previous decades.

The Future of Wind Energy in California: Future Projections in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Wang, M.; Ullrich, P. A.; Millstein, D.; Collier, C.

2017-12-01

This study focuses on the wind energy characterization and future projection at five primary wind turbine sites in California. Historical (1980-2000) and mid-century (2030-2050) simulations were produced using the Variable-Resolution Community Earth System Model (VR-CESM) to analyze the trends and variations in wind energy under climate change. Datasets from Det Norske Veritas Germanischer Llyod (DNV GL), MERRA-2, CFSR, NARR, as well as surface observational data were used for model validation and comparison. Significant seasonal wind speed changes under RCP8.5 were detected from several wind farm sites. Large-scale patterns were then investigated to analyze the synoptic-scale impact on localized wind change. The agglomerative clustering method was applied to analyze and group different wind patterns. The associated meteorological background of each cluster was investigated to analyze the drivers of different wind patterns. This study improves the characterization of uncertainty around the magnitude and variability in space and time of California's wind resources in the near future, and also enhances understanding of the physical mechanisms related to the trends in wind resource variability.

Cherry-picking functionally relevant substates from long md trajectories using a stratified sampling approach.

PubMed

Chandramouli, Balasubramanian; Mancini, Giordano

2016-01-01

Classical Molecular Dynamics (MD) simulations can provide insights at the nanoscopic scale into protein dynamics. Currently, simulations of large proteins and complexes can be routinely carried out in the ns-μs time regime. Clustering of MD trajectories is often performed to identify selective conformations and to compare simulation and experimental data coming from different sources on closely related systems. However, clustering techniques are usually applied without a careful validation of results and benchmark studies involving the application of different algorithms to MD data often deal with relatively small peptides instead of average or large proteins; finally clustering is often applied as a means to analyze refined data and also as a way to simplify further analysis of trajectories. Herein, we propose a strategy to classify MD data while carefully benchmarking the performance of clustering algorithms and internal validation criteria for such methods. We demonstrate the method on two showcase systems with different features, and compare the classification of trajectories in real and PCA space. We posit that the prototype procedure adopted here could be highly fruitful in clustering large trajectories of multiple systems or that resulting especially from enhanced sampling techniques like replica exchange simulations. Copyright: © 2016 by Fabrizio Serra editore, Pisa · Roma.

Measuring consistent masses for 25 Milky Way globular clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kimmig, Brian; Seth, Anil; Ivans, Inese I.

2015-02-01

We present central velocity dispersions, masses, mass-to-light ratios (M/Ls ), and rotation strengths for 25 Galactic globular clusters (GCs). We derive radial velocities of 1951 stars in 12 GCs from single order spectra taken with Hectochelle on the MMT telescope. To this sample we add an analysis of available archival data of individual stars. For the full set of data we fit King models to derive consistent dynamical parameters for the clusters. We find good agreement between single-mass King models and the observed radial dispersion profiles. The large, uniform sample of dynamical masses we derive enables us to examine trendsmore » of M/L with cluster mass and metallicity. The overall values of M/L and the trends with mass and metallicity are consistent with existing measurements from a large sample of M31 clusters. This includes a clear trend of increasing M/L with cluster mass and lower than expected M/Ls for the metal-rich clusters. We find no clear trend of increasing rotation with increasing cluster metallicity suggested in previous work.« less

ALE OF TWO CLUSTERS YIELDS SECRETS OF STAR BIRTH IN THE EARLY UNIVERSE

NASA Technical Reports Server (NTRS)

2002-01-01

This NASA Hubble Space Telescope (HST) image shows rich detail, previously only seen in neighboring star birth regions, in a pair of star clusters 166,000 light-years away in the Large Magellanic Cloud (LMC), in the southern constellation Doradus. The field of view is 130 light-years across and was taken with the Wide Field Planetary Camera 2. HST's unique capabilities -- ultraviolet sensitivity, ability to see faint stars, and high resolution -- have been utilized fully to identify three separate populations in this concentration of nearly 10,000 stars down to the 25th magnitude (more that twice as many as can be seen over the entire sky with the naked eye on a clear night on Earth). The field of view is only 130 light-years across. Previous observations with ground-based telescopes resolve less than 1,000 stars in the same region. About 60 percent of the stars belong to the dominant yellow cluster called NGC 1850, which is estimated to be 50 million years old. A scattering of white stars in the image are massive stars that are only about 4 million years old and represent about 20 percent of the stars in the image. (The remainder are field stars in the LMC.) Besides being much younger, the white stars are much more loosely distributed than the yellow cluster. The significant difference between the two cluster ages suggests these are two separate star groups that lie along the same line of sight. The younger, more open cluster probably lies 200 light-years beyond the older cluster. If it were in the foreground, then dust contained in the white cluster would obscure stars in the older yellow cluster. To observe two well-defined star populations separated by such a small gap of space is unusual. This juxtaposition suggests that supernova explosions in the older cluster might have triggered the birth of the younger cluster. This color composite image is assembled from exposures taken in ultraviolet, visible, and near-infrared light. Yellow stars correspond to Main Sequence stars (like our Sun) with average surface temperatures of 6000 Kelvin; red stars are cool giants and supergiants (3500 K); white stars are hot young stars (25,000 K or more) that are bright in ultraviolet. Credit: R. Gilmozzi, Space Telescope Science Institute/European Space Agency; Shawn Ewald, JPL; and NASA

Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large Scale Complex Networks

PubMed Central

Mall, Raghvendra; Langone, Rocco; Suykens, Johan A. K.

2014-01-01

Kernel spectral clustering corresponds to a weighted kernel principal component analysis problem in a constrained optimization framework. The primal formulation leads to an eigen-decomposition of a centered Laplacian matrix at the dual level. The dual formulation allows to build a model on a representative subgraph of the large scale network in the training phase and the model parameters are estimated in the validation stage. The KSC model has a powerful out-of-sample extension property which allows cluster affiliation for the unseen nodes of the big data network. In this paper we exploit the structure of the projections in the eigenspace during the validation stage to automatically determine a set of increasing distance thresholds. We use these distance thresholds in the test phase to obtain multiple levels of hierarchy for the large scale network. The hierarchical structure in the network is determined in a bottom-up fashion. We empirically showcase that real-world networks have multilevel hierarchical organization which cannot be detected efficiently by several state-of-the-art large scale hierarchical community detection techniques like the Louvain, OSLOM and Infomap methods. We show that a major advantage of our proposed approach is the ability to locate good quality clusters at both the finer and coarser levels of hierarchy using internal cluster quality metrics on 7 real-life networks. PMID:24949877

Galaxy Kinematics and Mass Calibration in Massive SZE Selected Galaxy Clusters to z=1.3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Capasso, R.; et al.

The galaxy phase-space distribution in galaxy clusters provides insights into the formation and evolution of cluster galaxies, and it can also be used to measure cluster mass profiles. We present a dynamical study based onmore » $$\\sim$$3000 passive, non-emission line cluster galaxies drawn from 110 galaxy clusters. The galaxy clusters were selected using the Sunyaev-Zel'dovich effect (SZE) in the 2500 deg$^2$ SPT-SZ survey and cover the redshift range $0.2 < z < 1.3$. We model the clusters using the Jeans equation, while adopting NFW mass profiles and a broad range of velocity dispersion anisotropy profiles. The data prefer velocity dispersion anisotropy profiles that are approximately isotropic near the center and increasingly radial toward the cluster virial radius, and this is true for all redshifts and masses we study. The pseudo-phase-space density profile of the passive galaxies is consistent with expectations for dark matter particles and subhalos from cosmological $N$-body simulations. The dynamical mass constraints are in good agreement with external mass estimates of the SPT cluster sample from either weak lensing, velocity dispersions, or X-ray $$Y_X$$ measurements. However, the dynamical masses are lower (at the 2.2$$\\sigma$$ level) when compared to the mass calibration favored when fitting the SPT cluster data to a LCDM model with external cosmological priors, including CMB anisotropy data from Planck. The tension grows with redshift, where in the highest redshift bin the ratio of dynamical to SPT+Planck masses is $$\\eta=0.63^{+0.13}_{-0.08}\\pm0.05$$ (statistical and systematic), corresponding to 2.6$$\\sigma$$ tension.« less

Space station ECLSS integration analysis: Simplified General Cluster Systems Model, ECLS System Assessment Program enhancements

NASA Technical Reports Server (NTRS)

Ferguson, R. E.

1985-01-01

The data base verification of the ECLS Systems Assessment Program (ESAP) was documented and changes made to enhance the flexibility of the water recovery subsystem simulations are given. All changes which were made to the data base values are described and the software enhancements performed. The refined model documented herein constitutes the submittal of the General Cluster Systems Model. A source listing of the current version of ESAP is provided in Appendix A.

Neurolinguistic Approach to Natural Language Processing with Applications to Medical Text Analysis

PubMed Central

Matykiewicz, Paweł; Pestian, John

2008-01-01

Understanding written or spoken language presumably involves spreading neural activation in the brain. This process may be approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts that are not found directly in the text. Approximation of this process is of great practical and theoretical interest. Although activations of neural circuits involved in representation of words rapidly change in time snapshots of these activations spreading through associative networks may be captured in a vector model. Concepts of similar type activate larger clusters of neurons, priming areas in the left and right hemisphere. Analysis of recent brain imaging experiments shows the importance of the right hemisphere non-verbal clusterization. Medical ontologies enable development of a large-scale practical algorithm to re-create pathways of spreading neural activations. First concepts of specific semantic type are identified in the text, and then all related concepts of the same type are added to the text, providing expanded representations. To avoid rapid growth of the extended feature space after each step only the most useful features that increase document clusterization are retained. Short hospital discharge summaries are used to illustrate how this process works on a real, very noisy data. Expanded texts show significantly improved clustering and may be classified with much higher accuracy. Although better approximations to the spreading of neural activations may be devised a practical approach presented in this paper helps to discover pathways used by the brain to process specific concepts, and may be used in large-scale applications. PMID:18614334

Parametric Analysis of a Hover Test Vehicle using Advanced Test Generation and Data Analysis

NASA Technical Reports Server (NTRS)

Gundy-Burlet, Karen; Schumann, Johann; Menzies, Tim; Barrett, Tony

2009-01-01

Large complex aerospace systems are generally validated in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. This is due to the large parameter space, and complex, highly coupled nonlinear nature of the different systems that contribute to the performance of the aerospace system. We have addressed the factors deterring such an analysis by applying a combination of technologies to the area of flight envelop assessment. We utilize n-factor (2,3) combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. The data generated is automatically analyzed through a combination of unsupervised learning using a Bayesian multivariate clustering technique (AutoBayes) and supervised learning of critical parameter ranges using the machine-learning tool TAR3, a treatment learner. Covariance analysis with scatter plots and likelihood contours are used to visualize correlations between simulation parameters and simulation results, a task that requires tool support, especially for large and complex models. We present results of simulation experiments for a cold-gas-powered hover test vehicle.

Cross-over between discrete and continuous protein structure space: insights into automatic classification and networks of protein structures.

PubMed

Pascual-García, Alberto; Abia, David; Ortiz, Angel R; Bastolla, Ugo

2009-03-01

Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications. As a domain set, we have selected a consensus set of 2,890 domains decomposed very similarly in SCOP and CATH. As an alignment algorithm, we used a global version of MAMMOTH developed in our group, which is both rapid and accurate. As a similarity measure, we used the size-normalized contact overlap, and as a clustering algorithm, we used average linkage. The resulting automatic classification at the cross-over point was more consistent than expert ones with respect to the structure similarity measure, with 86% of the clusters corresponding to subsets of either SCOP or CATH superfamilies and fewer than 5% containing domains in distinct folds according to both SCOP and CATH. Almost 15% of SCOP superfamilies and 10% of CATH superfamilies were split, consistent with the notion of fold change in protein evolution. These results were qualitatively robust for all choices that we tested, although we did not try to use alignment algorithms developed by other groups. Folds defined in SCOP and CATH would be completely joined in the regime of large transitivity violations where clustering is more arbitrary. Consistently, the agreement between SCOP and CATH at fold level was lower than their agreement with the automatic classification obtained using as a clustering algorithm, respectively, average linkage (for SCOP) or single linkage (for CATH). The networks representing significant evolutionary and structural relationships between clusters beyond the cross-over point may allow us to perform evolutionary, structural, or functional analyses beyond the limits of classification schemes. These networks and the underlying clusters are available at http://ub.cbm.uam.es/research/ProtNet.php.

Visual Reconciliation of Alternative Similarity Spaces in Climate Modeling.

PubMed

Poco, Jorge; Dasgupta, Aritra; Wei, Yaxing; Hargrove, William; Schwalm, Christopher R; Huntzinger, Deborah N; Cook, Robert; Bertini, Enrico; Silva, Claudio T

2014-12-01

Visual data analysis often requires grouping of data objects based on their similarity. In many application domains researchers use algorithms and techniques like clustering and multidimensional scaling to extract groupings from data. While extracting these groups using a single similarity criteria is relatively straightforward, comparing alternative criteria poses additional challenges. In this paper we define visual reconciliation as the problem of reconciling multiple alternative similarity spaces through visualization and interaction. We derive this problem from our work on model comparison in climate science where climate modelers are faced with the challenge of making sense of alternative ways to describe their models: one through the output they generate, another through the large set of properties that describe them. Ideally, they want to understand whether groups of models with similar spatio-temporal behaviors share similar sets of criteria or, conversely, whether similar criteria lead to similar behaviors. We propose a visual analytics solution based on linked views, that addresses this problem by allowing the user to dynamically create, modify and observe the interaction among groupings, thereby making the potential explanations apparent. We present case studies that demonstrate the usefulness of our technique in the area of climate science.

Automated extraction and analysis of rock discontinuity characteristics from 3D point clouds

NASA Astrophysics Data System (ADS)

Bianchetti, Matteo; Villa, Alberto; Agliardi, Federico; Crosta, Giovanni B.

2016-04-01

A reliable characterization of fractured rock masses requires an exhaustive geometrical description of discontinuities, including orientation, spacing, and size. These are required to describe discontinuum rock mass structure, perform Discrete Fracture Network and DEM modelling, or provide input for rock mass classification or equivalent continuum estimate of rock mass properties. Although several advanced methodologies have been developed in the last decades, a complete characterization of discontinuity geometry in practice is still challenging, due to scale-dependent variability of fracture patterns and difficult accessibility to large outcrops. Recent advances in remote survey techniques, such as terrestrial laser scanning and digital photogrammetry, allow a fast and accurate acquisition of dense 3D point clouds, which promoted the development of several semi-automatic approaches to extract discontinuity features. Nevertheless, these often need user supervision on algorithm parameters which can be difficult to assess. To overcome this problem, we developed an original Matlab tool, allowing fast, fully automatic extraction and analysis of discontinuity features with no requirements on point cloud accuracy, density and homogeneity. The tool consists of a set of algorithms which: (i) process raw 3D point clouds, (ii) automatically characterize discontinuity sets, (iii) identify individual discontinuity surfaces, and (iv) analyse their spacing and persistence. The tool operates in either a supervised or unsupervised mode, starting from an automatic preliminary exploration data analysis. The identification and geometrical characterization of discontinuity features is divided in steps. First, coplanar surfaces are identified in the whole point cloud using K-Nearest Neighbor and Principal Component Analysis algorithms optimized on point cloud accuracy and specified typical facet size. Then, discontinuity set orientation is calculated using Kernel Density Estimation and principal vector similarity criteria. Poles to points are assigned to individual discontinuity objects using easy custom vector clustering and Jaccard distance approaches, and each object is segmented into planar clusters using an improved version of the DBSCAN algorithm. Modal set orientations are then recomputed by cluster-based orientation statistics to avoid the effects of biases related to cluster size and density heterogeneity of the point cloud. Finally, spacing values are measured between individual discontinuity clusters along scanlines parallel to modal pole vectors, whereas individual feature size (persistence) is measured using 3D convex hull bounding boxes. Spacing and size are provided both as raw population data and as summary statistics. The tool is optimized for parallel computing on 64bit systems, and a Graphic User Interface (GUI) has been developed to manage data processing, provide several outputs, including reclassified point clouds, tables, plots, derived fracture intensity parameters, and export to modelling software tools. We present test applications performed both on synthetic 3D data (simple 3D solids) and real case studies, validating the results with existing geomechanical datasets.

Structure of the starch granule--a curved crystal.

PubMed

Larsson, K

1991-09-01

A structure model of the molecular arrangement in native starch proposed earlier is further considered, with special regard to the lateral packing of cluster units. The amylopectin molecules are radially distributed, with branches concentrated in clusters. Within each cluster the polyglucan chains form double helices which are hexagonally packed. The clusters form spherically concentric crystalline layers with amylose in an amorphous form acting as a space-filler. A translational mechanism for the change of helical direction at boundaries between clusters is proposed which can account for variations in the curvature of the concentric layers. The model is related to X-ray diffraction data and optical birefringence, considering dissembly at gelatinization. The structure is also discussed in relation to biosynthesis. Some aspects of gelatinization, such as the recent glass-transition approach, are then considered.

Data-driven process decomposition and robust online distributed modelling for large-scale processes

NASA Astrophysics Data System (ADS)

Shu, Zhang; Lijuan, Li; Lijuan, Yao; Shipin, Yang; Tao, Zou

2018-02-01

With the increasing attention of networked control, system decomposition and distributed models show significant importance in the implementation of model-based control strategy. In this paper, a data-driven system decomposition and online distributed subsystem modelling algorithm was proposed for large-scale chemical processes. The key controlled variables are first partitioned by affinity propagation clustering algorithm into several clusters. Each cluster can be regarded as a subsystem. Then the inputs of each subsystem are selected by offline canonical correlation analysis between all process variables and its controlled variables. Process decomposition is then realised after the screening of input and output variables. When the system decomposition is finished, the online subsystem modelling can be carried out by recursively block-wise renewing the samples. The proposed algorithm was applied in the Tennessee Eastman process and the validity was verified.

Composition design for Laves phase-related body-centered cubic-V solid solution alloys with large hydrogen storage capacities.

PubMed

Wang, H B; Wang, Q; Dong, C; Yuan, L; Xu, F; Sun, L X

2008-03-19

This paper analyzes the characteristics of alloy compositions with large hydrogen storage capacities in Laves phase-related body-centered cubic (bcc) solid solution alloy systems using the cluster line approach. Since a dense-packed icosahedral cluster A(6)B(7) characterizes the local structure of AB(2) Laves phases, in an A-B-C ternary system, such as Ti-Cr (Mn, Fe)-V, where A-B forms AB(2) Laves phases while A-C and B-C tend to form solid solutions, a cluster line A(6)B(7)-C is constructed by linking A(6)B(7) to C. The alloy compositions with large hydrogen storage capacities are generally located near this line and are approximately expressed with the cluster-plus-glue-atom model. The cluster line alloys (Ti(6)Cr(7))(100-x)V(x) (x = 2.5-70 at.%) exhibit different structures and hence different hydrogen storage capacities with increasing V content. The alloys (Ti(6)Cr(7))(95)V(5) and Ti(30)Cr(40)V(30) with bcc solid solution structure satisfy the cluster-plus-glue-atom model.

Nonlocal screening effects on core-level photoemission spectra investigated by large-cluster models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Okada, K.; Kotani, A.

1995-08-15

The copper 2{ital p} core-level x-ray photoemission spectrum in CuO{sub 2} plane systems is calculated by means of large-cluster models to investigate in detail the nonlocal screening effects, which were pointed out by van Veenendaal {ital et} {ital al}. [Phys. Rev. B 47, 11 462 (1993)]. Calculating the hole distributions for the initial and final states of photoemission, we show that the atomic coordination in a cluster strongly affects accessible final states. Accordingly, we point out that the interpretation for Cu{sub 3}O{sub 10} given by van Veenendaal {ital et} {ital al}. is not always general. Moreover, it is shown thatmore » the spectrum can be remarkably affected by whether or not the O 2{ital p}{sub {pi}} orbits are taken into account in the calculations. We also introduce a Hartree-Fock approximation in order to treat much larger-cluster models.« less

Principal Cluster Axes: A Projection Pursuit Index for the Preservation of Cluster Structures in the Presence of Data Reduction

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.; Henson, Robert

2012-01-01

A measure of "clusterability" serves as the basis of a new methodology designed to preserve cluster structure in a reduced dimensional space. Similar to principal component analysis, which finds the direction of maximal variance in multivariate space, principal cluster axes find the direction of maximum clusterability in multivariate space.…

Disease clusters, exact distributions of maxima, and P-values.

PubMed

Grimson, R C

1993-10-01

This paper presents combinatorial (exact) methods that are useful in the analysis of disease cluster data obtained from small environments, such as buildings and neighbourhoods. Maxwell-Boltzmann and Fermi-Dirac occupancy models are compared in terms of appropriateness of representation of disease incidence patterns (space and/or time) in these environments. The methods are illustrated by a statistical analysis of the incidence pattern of bone fractures in a setting wherein fracture clustering was alleged to be occurring. One of the methodological results derived in this paper is the exact distribution of the maximum cell frequency in occupancy models.

New Constraints on the Faint End of the UV Luminosity Function at z ~ 7-8 Using the Gravitational Lensing of the Hubble Frontier Fields Cluster A2744

NASA Astrophysics Data System (ADS)

Atek, Hakim; Richard, Johan; Kneib, Jean-Paul; Jauzac, Mathilde; Schaerer, Daniel; Clement, Benjamin; Limousin, Marceau; Jullo, Eric; Natarajan, Priyamvada; Egami, Eiichi; Ebeling, Harald

2015-02-01

Exploiting the power of gravitational lensing, the Hubble Frontier Fields (HFF) program aims at observing six massive galaxy clusters to explore the distant universe far beyond the limits of blank field surveys. Using the complete Hubble Space Telescope observations of the first HFF cluster A2744, we report the detection of 50 galaxy candidates at z ~ 7 and eight candidates at z ~ 8 in a total survey area of 0.96 arcmin2 in the source plane. Three of these galaxies are multiply imaged by the lensing cluster. Using an updated model of the mass distribution in the cluster we were able to calculate the magnification factor and the effective survey volume for each galaxy in order to compute the ultraviolet galaxy luminosity function (LF) at both redshifts 7 and 8. Our new measurements reliably extend the z ~ 7 UV LF down to an absolute magnitude of M UV ~ -15.5. We find a characteristic magnitude of M\\star UV = -20.90+0.90-0.73 mag and a faint-end slope α =-2.01+0.20-0.28, close to previous determinations in blank fields. We show here for the first time that this slope remains steep down to very faint luminosities of 0.01 L sstarf. Although prone to large uncertainties, our results at z ~ 8 also seem to confirm a steep faint-end slope below 0.1 L sstarf. The HFF program is therefore providing an extremely efficient way to study the faintest galaxy populations at z > 7 that would otherwise be inaccessible with current instrumentation. The full sample of six galaxy clusters will provide even better constraints on the buildup of galaxies at early epochs and their contribution to cosmic reionization. Based on observations made with the NASA/ESA Hubble Space Telescope, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with programs 13495, 11386, 13389, and 11689. STScI is operated by the Association of Universities for Research in Astronomy, Inc. under NASA contract NAS 5-26555. The Hubble Frontier Fields data were obtained from the Mikulski Archive for Space Telescopes (MAST).

A general framework to test gravity using galaxy clusters - I. Modelling the dynamical mass of haloes in f(R) gravity

NASA Astrophysics Data System (ADS)

Mitchell, Myles A.; He, Jian-hua; Arnold, Christian; Li, Baojiu

2018-06-01

We propose a new framework for testing gravity using cluster observations, which aims to provide an unbiased constraint on modified gravity models from Sunyaev-Zel'dovich (SZ) and X-ray cluster counts and the cluster gas fraction, among other possible observables. Focusing on a popular f(R) model of gravity, we propose a novel procedure to recalibrate mass scaling relations from Λ cold dark matter (ΛCDM) to f(R) gravity for SZ and X-ray cluster observables. We find that the complicated modified gravity effects can be simply modelled as a dependence on a combination of the background scalar field and redshift, fR(z)/(1 + z), regardless of the f(R) model parameter. By employing a large suite of N-body simulations, we demonstrate that a theoretically derived tanh fitting formula is in excellent agreement with the dynamical mass enhancement of dark matter haloes for a large range of background field parameters and redshifts. Our framework is sufficiently flexible to allow for tests of other models and inclusion of further observables, and the one-parameter description of the dynamical mass enhancement can have important implications on the theoretical modelling of observables and on practical tests of gravity.

Machine learning approaches for estimation of prediction interval for the model output.

PubMed

Shrestha, Durga L; Solomatine, Dimitri P

2006-03-01

A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the prediction interval) of the underlying distribution of prediction errors. The idea is to partition the input space into different zones or clusters having similar model errors using fuzzy c-means clustering. The prediction interval is constructed for each cluster on the basis of empirical distributions of the errors associated with all instances belonging to the cluster under consideration and propagated from each cluster to the examples according to their membership grades in each cluster. Then a regression model is built for in-sample data using computed prediction limits as targets, and finally, this model is applied to estimate the prediction intervals (limits) for out-of-sample data. The method was tested on artificial and real hydrologic data sets using various machine learning techniques. Preliminary results show that the method is superior to other methods estimating the prediction interval. A new method for evaluating performance for estimating prediction interval is proposed as well.

Plug cluster engine concept for in-space missions

NASA Technical Reports Server (NTRS)

Obrien, C. J.; Aukerman, C. A.

1979-01-01

The development of a suitable orbital transfer vehicle (OTV) engine is discussed. The OTV's dimensions are limited by those of the Space Shuttle payload bay on which it will be carried. An approach to utilize the available diameter to achieve high area ratio and thus high engine performance, is presented. Unconventional nozzles, such as clusters of small thrusters around a large diameter contoured plug, are investigated to arrive at engine designs which feature lower chamber pressures, with attendant lower heat flux, lower wall temperature, longer fatigue life, and less critical turbomachinery. Attention is also given to plug nozzle technology, high area ratio module- and scarfed bell- Plug Cluster Engine (PCE) concepts, as well as PCE performance, weight, and assessment. A conceptual design of a PCE formed from a cluster of high area ratio, scarfed, bell nozzles proved to be competitive with bell and spike nozzle engines. PCE advantages cited include increased payload length due to shorter engine length, ability to increase or decrease the number of modules and thereby the thrust, and low cost due to utilization of off-the-shelf technology.

The Chandra Strong Lens Sample: Revealing Baryonic Physics In Strong Lensing Selected Clusters

NASA Astrophysics Data System (ADS)

Bayliss, Matthew

2017-08-01

We propose for Chandra imaging of the hot intra-cluster gas in a unique new sample of 29 galaxy clusters selected purely on their strong gravitational lensing signatures. This will be the first program targeting a purely strong lensing selected cluster sample, enabling new comparisons between the ICM properties and scaling relations of strong lensing and mass/ICM selected cluster samples. Chandra imaging, combined with high precision strong lens models, ensures powerful constraints on the distribution and state of matter in the cluster cores. This represents a novel angle from which we can address the role played by baryonic physics |*| the infamous |*|gastrophysics|*| in shaping the cores of massive clusters, and opens up an exciting new galaxy cluster discovery space with Chandra.

The Chandra Strong Lens Sample: Revealing Baryonic Physics In Strong Lensing Selected Clusters

NASA Astrophysics Data System (ADS)

Bayliss, Matthew

2017-09-01

We propose for Chandra imaging of the hot intra-cluster gas in a unique new sample of 29 galaxy clusters selected purely on their strong gravitational lensing signatures. This will be the first program targeting a purely strong lensing selected cluster sample, enabling new comparisons between the ICM properties and scaling relations of strong lensing and mass/ICM selected cluster samples. Chandra imaging, combined with high precision strong lens models, ensures powerful constraints on the distribution and state of matter in the cluster cores. This represents a novel angle from which we can address the role played by baryonic physics -- the infamous ``gastrophysics''-- in shaping the cores of massive clusters, and opens up an exciting new galaxy cluster discovery space with Chandra.

Jellyfish: the origin and distribution of extreme ram-pressure stripping events in massive galaxy clusters

NASA Astrophysics Data System (ADS)

McPartland, Conor; Ebeling, Harald; Roediger, Elke; Blumenthal, Kelly

2016-01-01

We investigate the observational signatures and physical origin of ram-pressure stripping (RPS) in 63 massive galaxy clusters at z = 0.3-0.7, based on images obtained with the Hubble Space Telescope. Using a training set of a dozen `jellyfish' galaxies identified earlier in the same imaging data, we define morphological criteria to select 211 additional, less obvious cases of RPS. Spectroscopic follow-up observations of 124 candidates so far confirmed 53 as cluster members. For the brightest and most favourably aligned systems, we visually derive estimates of the projected direction of motion based on the orientation of apparent compression shocks and debris trails. Our findings suggest that the onset of these events occurs primarily at large distances from the cluster core (>400 kpc), and that the trajectories of the affected galaxies feature high-impact parameters. Simple models show that such trajectories are highly improbable for galaxy infall along filaments but common for infall at high velocities, even after observational biases are accounted for, provided the duration of the resulting RPS events is ≲500 Myr. We thus tentatively conclude that extreme RPS events are preferentially triggered by cluster mergers, an interpretation that is supported by the disturbed dynamical state of many of the host clusters. This hypothesis implies that extreme RPS might occur also near the cores of merging poor clusters or even merging groups of galaxies. Finally, we present nine additional `jellyfish" galaxies at z > 0.3 discovered by us, thereby doubling the number of such systems known at intermediate redshift.

The Grism Lens-Amplified Survey from Space (GLASS). VI. Comparing the Mass and Light in MACS J0416.1-2403 Using Frontier Field Imaging and GLASS Spectroscopy

NASA Astrophysics Data System (ADS)

Hoag, A.; Huang, K.-H.; Treu, T.; Bradač, M.; Schmidt, K. B.; Wang, X.; Brammer, G. B.; Broussard, A.; Amorin, R.; Castellano, M.; Fontana, A.; Merlin, E.; Schrabback, T.; Trenti, M.; Vulcani, B.

2016-11-01

We present a model using both strong and weak gravitational lensing of the galaxy cluster MACS J0416.1-2403, constrained using spectroscopy from the Grism Lens-Amplified Survey from Space (GLASS) and Hubble Frontier Fields (HFF) imaging data. We search for emission lines in known multiply imaged sources in the GLASS spectra, obtaining secure spectroscopic redshifts of 30 multiple images belonging to 15 distinct source galaxies. The GLASS spectra provide the first spectroscopic measurements for five of the source galaxies. The weak lensing signal is acquired from 884 galaxies in the F606W HFF image. By combining the weak lensing constraints with 15 multiple image systems with spectroscopic redshifts and nine multiple image systems with photometric redshifts, we reconstruct the gravitational potential of the cluster on an adaptive grid. The resulting map of total mass density is compared with a map of stellar mass density obtained from the deep Spitzer Frontier Fields imaging data to study the relative distribution of stellar and total mass in the cluster. We find that the projected stellar mass to total mass ratio, f ⋆, varies considerably with the stellar surface mass density. The mean projected stellar mass to total mass ratio is < {f}\\star > =0.009+/- 0.003 (stat.), but with a systematic error as large as 0.004-0.005, dominated by the choice of the initial mass function. We find agreement with several recent measurements of f ⋆ in massive cluster environments. The lensing maps of convergence, shear, and magnification are made available to the broader community in the standard HFF format.

Legacy ExtraGalactic UV Survey with The Hubble Space Telescope: Stellar Cluster Catalogs and First Insights Into Cluster Formation and Evolution in NGC 628

NASA Astrophysics Data System (ADS)

Adamo, A.; Ryon, J. E.; Messa, M.; Kim, H.; Grasha, K.; Cook, D. O.; Calzetti, D.; Lee, J. C.; Whitmore, B. C.; Elmegreen, B. G.; Ubeda, L.; Smith, L. J.; Bright, S. N.; Runnholm, A.; Andrews, J. E.; Fumagalli, M.; Gouliermis, D. A.; Kahre, L.; Nair, P.; Thilker, D.; Walterbos, R.; Wofford, A.; Aloisi, A.; Ashworth, G.; Brown, T. M.; Chandar, R.; Christian, C.; Cignoni, M.; Clayton, G. C.; Dale, D. A.; de Mink, S. E.; Dobbs, C.; Elmegreen, D. M.; Evans, A. S.; Gallagher, J. S., III; Grebel, E. K.; Herrero, A.; Hunter, D. A.; Johnson, K. E.; Kennicutt, R. C.; Krumholz, M. R.; Lennon, D.; Levay, K.; Martin, C.; Nota, A.; Östlin, G.; Pellerin, A.; Prieto, J.; Regan, M. W.; Sabbi, E.; Sacchi, E.; Schaerer, D.; Schiminovich, D.; Shabani, F.; Tosi, M.; Van Dyk, S. D.; Zackrisson, E.

2017-06-01

We report the large effort that is producing comprehensive high-level young star cluster (YSC) catalogs for a significant fraction of galaxies observed with the Legacy ExtraGalactic UV Survey (LEGUS) Hubble treasury program. We present the methodology developed to extract cluster positions, verify their genuine nature, produce multiband photometry (from NUV to NIR), and derive their physical properties via spectral energy distribution fitting analyses. We use the nearby spiral galaxy NGC 628 as a test case for demonstrating the impact that LEGUS will have on our understanding of the formation and evolution of YSCs and compact stellar associations within their host galaxy. Our analysis of the cluster luminosity function from the UV to the NIR finds a steepening at the bright end and at all wavelengths suggesting a dearth of luminous clusters. The cluster mass function of NGC 628 is consistent with a power-law distribution of slopes ˜ -2 and a truncation of a few times 105 {M}⊙ . After their formation, YSCs and compact associations follow different evolutionary paths. YSCs survive for a longer time frame, confirming their being potentially bound systems. Associations disappear on timescales comparable to hierarchically organized star-forming regions, suggesting that they are expanding systems. We find mass-independent cluster disruption in the inner region of NGC 628, while in the outer part of the galaxy there is little or no disruption. We observe faster disruption rates for low mass (≤104 {M}⊙ ) clusters, suggesting that a mass-dependent component is necessary to fully describe the YSC disruption process in NGC 628. Based on observations obtained with the NASA/ESA Hubble Space Telescope, at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555.

[Application of Kohonen Self-Organizing Feature Maps in QSAR of human ADMET and kinase data sets].

PubMed

Hegymegi-Barakonyi, Bálint; Orfi, László; Kéri, György; Kövesdi, István

2013-01-01

QSAR predictions have been proven very useful in a large number of studies for drug design, such as kinase inhibitor design as targets for cancer therapy, however the overall predictability often remains unsatisfactory. To improve predictability of ADMET features and kinase inhibitory data, we present a new method using Kohonen's Self-Organizing Feature Map (SOFM) to cluster molecules based on explanatory variables (X) and separate dissimilar ones. We calculated SOFM clusters for a large number of molecules with human ADMET and kinase inhibitory data, and we showed that chemically similar molecules were in the same SOFM cluster, and within such clusters the QSAR models had significantly better predictability. We used also target variables (Y, e.g. ADMET) jointly with X variables to create a novel type of clustering. With our method, cells of loosely coupled XY data could be identified and separated into different model building sets.

Partially supervised speaker clustering.

PubMed

Tang, Hao; Chu, Stephen Mingyu; Hasegawa-Johnson, Mark; Huang, Thomas S

2012-05-01

Content-based multimedia indexing, retrieval, and processing as well as multimedia databases demand the structuring of the media content (image, audio, video, text, etc.), one significant goal being to associate the identity of the content to the individual segments of the signals. In this paper, we specifically address the problem of speaker clustering, the task of assigning every speech utterance in an audio stream to its speaker. We offer a complete treatment to the idea of partially supervised speaker clustering, which refers to the use of our prior knowledge of speakers in general to assist the unsupervised speaker clustering process. By means of an independent training data set, we encode the prior knowledge at the various stages of the speaker clustering pipeline via 1) learning a speaker-discriminative acoustic feature transformation, 2) learning a universal speaker prior model, and 3) learning a discriminative speaker subspace, or equivalently, a speaker-discriminative distance metric. We study the directional scattering property of the Gaussian mixture model (GMM) mean supervector representation of utterances in the high-dimensional space, and advocate exploiting this property by using the cosine distance metric instead of the euclidean distance metric for speaker clustering in the GMM mean supervector space. We propose to perform discriminant analysis based on the cosine distance metric, which leads to a novel distance metric learning algorithm—linear spherical discriminant analysis (LSDA). We show that the proposed LSDA formulation can be systematically solved within the elegant graph embedding general dimensionality reduction framework. Our speaker clustering experiments on the GALE database clearly indicate that 1) our speaker clustering methods based on the GMM mean supervector representation and vector-based distance metrics outperform traditional speaker clustering methods based on the “bag of acoustic features” representation and statistical model-based distance metrics, 2) our advocated use of the cosine distance metric yields consistent increases in the speaker clustering performance as compared to the commonly used euclidean distance metric, 3) our partially supervised speaker clustering concept and strategies significantly improve the speaker clustering performance over the baselines, and 4) our proposed LSDA algorithm further leads to state-of-the-art speaker clustering performance.

DDO 216-A1: A Central Globular Cluster in a Low-luminosity Transition-type Galaxy

NASA Astrophysics Data System (ADS)

Cole, Andrew A.; Weisz, Daniel R.; Skillman, Evan D.; Leaman, Ryan; Williams, Benjamin F.; Dolphin, Andrew E.; Johnson, L. Clifton; McConnachie, Alan W.; Boylan-Kolchin, Michael; Dalcanton, Julianne; Governato, Fabio; Madau, Piero; Shen, Sijing; Vogelsberger, Mark

2017-03-01

We confirm that the object DDO 216-A1 is a substantial globular cluster at the center of Local Group galaxy DDO 216 (the Pegasus dwarf irregular), using Hubble Space Telescope ACS imaging. By fitting isochrones, we find the cluster metallicity [M/H] = -1.6 ± 0.2, for reddening E(B-V) = 0.16 ± 0.02 the best-fit age is 12.3 ± 0.8 Gyr. There are ≈ 30 RR Lyrae variables in the cluster; the magnitude of the fundamental mode pulsators gives a distance modulus of 24.77 ± 0.08—identical to the host galaxy. The ratio of overtone to fundamental mode variables and their mean periods make DDO 216-A1 an Oosterhoff Type I cluster. We find a central surface brightness of 20.85 ± 0.17 F814W mag arcsec-2, a half-light radius of 3\\buildrel{\\prime\\prime}\\over{.} 1 (13.4 pc), and an absolute magnitude M814 = -7.90 ± 0.16 (M/{M}⊙ ≈ 105). King models fit to the cluster give the core radius and concentration index, r c = 2\\buildrel{\\prime\\prime}\\over{.} 1 ± 0\\buildrel{\\prime\\prime}\\over{.} 9 and c = 1.24 ± 0.39. The cluster is an “extended” cluster somewhat typical of some dwarf galaxies and the outer halo of the Milky Way. The cluster is projected ≲30 pc south of the center of DDO 216, unusually central compared to most dwarf galaxy globular clusters. Analytical models of dynamical friction and tidal destruction suggest that it probably formed at a larger distance, up to ˜1 kpc, and migrated inward. DDO 216 has an unexceptional specific cluster frequency, S N = 10. DDO 216 is the lowest-luminosity Local Group galaxy to host a 105 {M}⊙ globular cluster and the only transition-type (dSph/dIrr) galaxy in the Local Group with a globular cluster. Based on observations made with the NASA/ESA Hubble Space Telesope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. These observations were obtained under program GO-13768.

Considering Decision Variable Diversity in Multi-Objective Optimization: Application in Hydrologic Model Calibration

NASA Astrophysics Data System (ADS)

Sahraei, S.; Asadzadeh, M.

2017-12-01

Any modern multi-objective global optimization algorithm should be able to archive a well-distributed set of solutions. While the solution diversity in the objective space has been explored extensively in the literature, little attention has been given to the solution diversity in the decision space. Selection metrics such as the hypervolume contribution and crowding distance calculated in the objective space would guide the search toward solutions that are well-distributed across the objective space. In this study, the diversity of solutions in the decision-space is used as the main selection criteria beside the dominance check in multi-objective optimization. To this end, currently archived solutions are clustered in the decision space and the ones in less crowded clusters are given more chance to be selected for generating new solution. The proposed approach is first tested on benchmark mathematical test problems. Second, it is applied to a hydrologic model calibration problem with more than three objective functions. Results show that the chance of finding more sparse set of high-quality solutions increases, and therefore the analyst would receive a well-diverse set of options with maximum amount of information. Pareto Archived-Dynamically Dimensioned Search, which is an efficient and parsimonious multi-objective optimization algorithm for model calibration, is utilized in this study.

HRLSim: a high performance spiking neural network simulator for GPGPU clusters.

PubMed

Minkovich, Kirill; Thibeault, Corey M; O'Brien, Michael John; Nogin, Aleksey; Cho, Youngkwan; Srinivasa, Narayan

2014-02-01

Modeling of large-scale spiking neural models is an important tool in the quest to understand brain function and subsequently create real-world applications. This paper describes a spiking neural network simulator environment called HRL Spiking Simulator (HRLSim). This simulator is suitable for implementation on a cluster of general purpose graphical processing units (GPGPUs). Novel aspects of HRLSim are described and an analysis of its performance is provided for various configurations of the cluster. With the advent of inexpensive GPGPU cards and compute power, HRLSim offers an affordable and scalable tool for design, real-time simulation, and analysis of large-scale spiking neural networks.

CLASH: Joint analysis of strong-lensing, weak-lensing shear, and magnification data for 20 galaxy clusters*

DOE PAGES

Umetsu, Keiichi; Zitrin, Adi; Gruen, Daniel; ...

2016-04-20

Here, we present a comprehensive analysis of strong-lensing, weak-lensing shear and magnification data for a sample of 16 X-ray-regular and 4 high-magnification galaxy clusters atmore » $$0.19\\lesssim z\\lesssim 0.69$$ selected from Cluster Lensing And Supernova survey with Hubble (CLASH). Our analysis combines constraints from 16-band Hubble Space Telescope observations and wide-field multi-color imaging taken primarily with Suprime-Cam on the Subaru Telescope, spanning a wide range of cluster radii (10''–16'). We reconstruct surface mass density profiles of individual clusters from a joint analysis of the full lensing constraints, and determine masses and concentrations for all of the clusters. We find the internal consistency of the ensemble mass calibration to be ≤5% ± 6% in the one-halo regime (200–2000 kpc h –1) compared to the CLASH weak-lensing-only measurements of Umetsu et al. For the X-ray-selected subsample of 16 clusters, we examine the concentration–mass (c–M) relation and its intrinsic scatter using a Bayesian regression approach. Our model yields a mean concentration of $$c{| }_{z=0.34}=3.95\\pm 0.35$$ at M200c sime 14 × 1014 M⊙ and an intrinsic scatter of $$\\sigma (\\mathrm{ln}{c}_{200{\\rm{c}}})=0.13\\pm 0.06$$, which is in excellent agreement with Λ cold dark matter predictions when the CLASH selection function based on X-ray morphological regularity and the projection effects are taken into account. We also derive an ensemble-averaged surface mass density profile for the X-ray-selected subsample by stacking their individual profiles. The stacked lensing signal is detected at 33σ significance over the entire radial range ≤4000 kpc h –1, accounting for the effects of intrinsic profile variations and uncorrelated large-scale structure along the line of sight. The stacked mass profile is well described by a family of density profiles predicted for cuspy dark-matter-dominated halos in gravitational equilibrium, namely, the Navarro–Frenk–White (NFW), Einasto, and DARKexp models, whereas the single power-law, cored isothermal and Burkert density profiles are disfavored by the data. We show that cuspy halo models that include the large-scale two-halo term provide improved agreement with the data. For the NFW halo model, we measure a mean concentration of $${c}_{200{\\rm{c}}}={3.79}_{-0.28}^{+0.30}$$ at $${M}_{200{\\rm{c}}}={14.1}_{-1.0}^{+1.0}\\times {10}^{14}\\;{M}_{\\odot }$$, demonstrating consistency between the complementary analysis methods.« less

Precise weak lensing constraints from deep high-resolution Ks images: VLT/HAWK-I analysis of the super-massive galaxy cluster RCS2 J 232727.7-020437 at z = 0.70

NASA Astrophysics Data System (ADS)

Schrabback, Tim; Schirmer, Mischa; van der Burg, Remco F. J.; Hoekstra, Henk; Buddendiek, Axel; Applegate, Douglas; Bradač, Maruša; Eifler, Tim; Erben, Thomas; Gladders, Michael D.; Hernández-Martín, Beatriz; Hildebrandt, Hendrik; Hoag, Austin; Klaes, Dominik; von der Linden, Anja; Marchesini, Danilo; Muzzin, Adam; Sharon, Keren; Stefanon, Mauro

2018-03-01

We demonstrate that deep good-seeing VLT/HAWK-I Ks images complemented with g + z-band photometry can yield a sensitivity for weak lensing studies of massive galaxy clusters at redshifts 0.7 ≲ z ≲ 1.1, which is almost identical to the sensitivity of HST/ACS mosaics of single-orbit depth. Key reasons for this good performance are the excellent image quality frequently achievable for Ks imaging from the ground, a highly effective photometric selection of background galaxies, and a galaxy ellipticity dispersion that is noticeably lower than for optically observed high-redshift galaxy samples. Incorporating results from the 3D-HST and UltraVISTA surveys we also obtained a more accurate calibration of the source redshift distribution than previously achieved for similar optical weak lensing data sets. Here we studied the extremely massive galaxy cluster RCS2 J232727.7-020437 (z = 0.699), combining deep VLT/HAWK-I Ks images (point spread function with a 0.''35 full width at half maximum) with LBT/LBC photometry. The resulting weak lensing mass reconstruction suggests that the cluster consists of a single overdensity, which is detected with a peak significance of 10.1σ. We constrained the cluster mass to M200c/(1015 M⊙) = 2.06-0.26+0.28(stat.) ± 0.12(sys.) assuming a spherical Navarro, Frenk & White model and simulation-based priors on the concentration, making it one of the most massive galaxy clusters known in the z ≳ 0.7 Universe. We also cross-checked the HAWK-I measurements through an analysis of overlapping HST/ACS images, yielding fully consistent estimates of the lensing signal. Based on observations conducted with the ESO Very Large Telescope, the Large Binocular Telescope, and the NASA/ESA Hubble Space Telescope, as detailed in the acknowledgements.

Clustered DNA damages induced in isolated DNA and in human cells by low doses of ionizing radiation

NASA Technical Reports Server (NTRS)

Sutherland, B. M.; Bennett, P. V.; Sidorkina, O.; Laval, J.; Lowenstein, D. I. (Principal Investigator)

2000-01-01

Clustered DNA damages-two or more closely spaced damages (strand breaks, abasic sites, or oxidized bases) on opposing strands-are suspects as critical lesions producing lethal and mutagenic effects of ionizing radiation. However, as a result of the lack of methods for measuring damage clusters induced by ionizing radiation in genomic DNA, neither the frequencies of their production by physiological doses of radiation, nor their repairability, nor their biological effects are known. On the basis of methods that we developed for quantitating damages in large DNAs, we have devised and validated a way of measuring ionizing radiation-induced clustered lesions in genomic DNA, including DNA from human cells. DNA is treated with an endonuclease that induces a single-strand cleavage at an oxidized base or abasic site. If there are two closely spaced damages on opposing strands, such cleavage will reduce the size of the DNA on a nondenaturing gel. We show that ionizing radiation does induce clustered DNA damages containing abasic sites, oxidized purines, or oxidized pyrimidines. Further, the frequency of each of these cluster classes is comparable to that of frank double-strand breaks; among all complex damages induced by ionizing radiation, double-strand breaks are only about 20%, with other clustered damage constituting some 80%. We also show that even low doses (0.1-1 Gy) of high linear energy transfer ionizing radiation induce clustered damages in human cells.

The Atlas of Chinese World Wide Web Ecosystem Shaped by the Collective Attention Flows

PubMed Central

Lou, Xiaodan; Li, Yong; Gu, Weiwei; Zhang, Jiang

2016-01-01

The web can be regarded as an ecosystem of digital resources connected and shaped by collective successive behaviors of users. Knowing how people allocate limited attention on different resources is of great importance. To answer this, we embed the most popular Chinese web sites into a high dimensional Euclidean space based on the open flow network model of a large number of Chinese users’ collective attention flows, which both considers the connection topology of hyperlinks between the sites and the collective behaviors of the users. With these tools, we rank the web sites and compare their centralities based on flow distances with other metrics. We also study the patterns of attention flow allocation, and find that a large number of web sites concentrate on the central area of the embedding space, and only a small fraction of web sites disperse in the periphery. The entire embedding space can be separated into 3 regions(core, interim, and periphery). The sites in the core (1%) occupy a majority of the attention flows (40%), and the sites (34%) in the interim attract 40%, whereas other sites (65%) only take 20% flows. What’s more, we clustered the web sites into 4 groups according to their positions in the space, and found that similar web sites in contents and topics are grouped together. In short, by incorporating the open flow network model, we can clearly see how collective attention allocates and flows on different web sites, and how web sites connected each other. PMID:27812133

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

Network visualization of conformational sampling during molecular dynamics simulation.

PubMed

Ahlstrom, Logan S; Baker, Joseph Lee; Ehrlich, Kent; Campbell, Zachary T; Patel, Sunita; Vorontsov, Ivan I; Tama, Florence; Miyashita, Osamu

2013-11-01

Effective data reduction methods are necessary for uncovering the inherent conformational relationships present in large molecular dynamics (MD) trajectories. Clustering algorithms provide a means to interpret the conformational sampling of molecules during simulation by grouping trajectory snapshots into a few subgroups, or clusters, but the relationships between the individual clusters may not be readily understood. Here we show that network analysis can be used to visualize the dominant conformational states explored during simulation as well as the connectivity between them, providing a more coherent description of conformational space than traditional clustering techniques alone. We compare the results of network visualization against 11 clustering algorithms and principal component conformer plots. Several MD simulations of proteins undergoing different conformational changes demonstrate the effectiveness of networks in reaching functional conclusions. Copyright © 2013 Elsevier Inc. All rights reserved.

Automatic Selection of Order Parameters in the Analysis of Large Scale Molecular Dynamics Simulations.

PubMed

Sultan, Mohammad M; Kiss, Gert; Shukla, Diwakar; Pande, Vijay S

2014-12-09

Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states.

Space-time clustering analysis of wildfires: The influence of dataset characteristics, fire prevention policy decisions, weather and climate.

PubMed

Parente, Joana; Pereira, Mário G; Tonini, Marj

2016-07-15

The present study focuses on the dependence of the space-time permutation scan statistics (STPSS) (1) on the input database's characteristics and (2) on the use of this methodology to assess changes on the fire regime due to different type of climate and fire management activities. Based on the very strong relationship between weather and the fire incidence in Portugal, the detected clusters will be interpreted in terms of the atmospheric conditions. Apart from being the country most affected by the fires in the European context, Portugal meets all the conditions required to carry out this study, namely: (i) two long and comprehensive official datasets, i.e. the Portuguese Rural Fire Database (PRFD) and the National Mapping Burnt Areas (NMBA), respectively based on ground and satellite measurements; (ii) the two types of climate (Csb in the north and Csa in the south) that characterizes the Mediterranean basin regions most affected by the fires also divide the mainland Portuguese area; and, (iii) the national plan for the defence of forest against fires was approved a decade ago and it is now reasonable to assess its impacts. Results confirmed (1) the influence of the dataset's characteristics on the detected clusters, (2) the existence of two different fire regimes in the country promoted by the different types of climate, (3) the positive impacts of the fire prevention policy decisions and (4) the ability of the STPSS to correctly identify clusters, regarding their number, location, and space-time size in spite of eventual space and/or time splits of the datasets. Finally, the role of the weather on days when clustered fires were active was confirmed for the classes of small, medium and large fires. Copyright © 2016 Elsevier B.V. All rights reserved.

The Hidden Fortress: structure and substructure of the complex strong lensing cluster SDSS J1029+2623

NASA Astrophysics Data System (ADS)

Oguri, Masamune; Schrabback, Tim; Jullo, Eric; Ota, Naomi; Kochanek, Christopher S.; Dai, Xinyu; Ofek, Eran O.; Richards, Gordon T.; Blandford, Roger D.; Falco, Emilio E.; Fohlmeister, Janine

2013-02-01

We present Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) and Wide Field Camera 3 (WFC3) observations of SDSS J1029+2623, a three-image quasar lens system produced by a foreground cluster at z = 0.584. Our strong lensing analysis reveals six additional multiply imaged galaxies in addition to the multiply imaged quasar. We confirm the complex nature of the mass distribution of the lensing cluster, with a bimodal dark matter distribution which deviates from the Chandra X-ray surface brightness distribution. The Einstein radius of the lensing cluster is estimated to be θE = 15.2 ± 0.5 arcsec for the quasar redshift of z = 2.197. We derive a radial mass distribution from the combination of strong lensing, HST/ACS weak lensing and Subaru/Suprime-cam weak lensing analysis results, finding a best-fitting virial mass of Mvir = 1.55+ 0.40- 0.35 × 1014 h- 1 M⊙ and a concentration parameter of cvir = 25.7+ 14.1- 7.5. The lensing mass estimate at the outer radius is smaller than the X-ray mass estimate by a factor of ˜2. We ascribe this large mass discrepancy to shock heating of the intracluster gas during a merger, which is also suggested by the complex mass and gas distributions and the high value of the concentration parameter. In the HST image, we also identify a probable galaxy, GX, in the vicinity of the faintest quasar image C. In strong lens models, the inclusion of GX explains the anomalous flux ratios between the quasar images. The morphology of the highly elongated quasar host galaxy is also well reproduced. The best-fitting model suggests large total magnifications of 30 for the quasar and 35 for the quasar host galaxy, and has an AB time delay consistent with the measured value.

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering

PubMed Central

2013-01-01

Background The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development. Results In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space. Conclusions Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship. PMID:23845024

Testing the consistency of three-point halo clustering in Fourier and configuration space

NASA Astrophysics Data System (ADS)

Hoffmann, K.; Gaztañaga, E.; Scoccimarro, R.; Crocce, M.

2018-05-01

We compare reduced three-point correlations Q of matter, haloes (as proxies for galaxies) and their cross-correlations, measured in a total simulated volume of ˜100 (h-1 Gpc)3, to predictions from leading order perturbation theory on a large range of scales in configuration space. Predictions for haloes are based on the non-local bias model, employing linear (b1) and non-linear (c2, g2) bias parameters, which have been constrained previously from the bispectrum in Fourier space. We also study predictions from two other bias models, one local (g2 = 0) and one in which c2 and g2 are determined by b1 via approximately universal relations. Overall, measurements and predictions agree when Q is derived for triangles with (r1r2r3)1/3 ≳60 h-1 Mpc, where r1 - 3 are the sizes of the triangle legs. Predictions for Qmatter, based on the linear power spectrum, show significant deviations from the measurements at the BAO scale (given our small measurement errors), which strongly decrease when adding a damping term or using the non-linear power spectrum, as expected. Predictions for Qhalo agree best with measurements at large scales when considering non-local contributions. The universal bias model works well for haloes and might therefore be also useful for tightening constraints on b1 from Q in galaxy surveys. Such constraints are independent of the amplitude of matter density fluctuation (σ8) and hence break the degeneracy between b1 and σ8, present in galaxy two-point correlations.

Patterning in time and space: HoxB cluster gene expression in the developing chick embryo.

PubMed

Gouveia, Analuce; Marcelino, Hugo M; Gonçalves, Lisa; Palmeirim, Isabel; Andrade, Raquel P

2015-01-01

The developing embryo is a paradigmatic model to study molecular mechanisms of time control in Biology. Hox genes are key players in the specification of tissue identity during embryo development and their expression is under strict temporal regulation. However, the molecular mechanisms underlying timely Hox activation in the early embryo remain unknown. This is hindered by the lack of a rigorous temporal framework of sequential Hox expression within a single cluster. Herein, a thorough characterization of HoxB cluster gene expression was performed over time and space in the early chick embryo. Clear temporal collinearity of HoxB cluster gene expression activation was observed. Spatial collinearity of HoxB expression was evidenced in different stages of development and in multiple tissues. Using embryo explant cultures we showed that HoxB2 is cyclically expressed in the rostral presomitic mesoderm with the same periodicity as somite formation, suggesting a link between timely tissue specification and somite formation. We foresee that the molecular framework herein provided will facilitate experimental approaches aimed at identifying the regulatory mechanisms underlying Hox expression in Time and Space.

Patterning in time and space: HoxB cluster gene expression in the developing chick embryo

PubMed Central

Gouveia, Analuce; Marcelino, Hugo M; Gonçalves, Lisa; Palmeirim, Isabel; Andrade, Raquel P

2015-01-01

The developing embryo is a paradigmatic model to study molecular mechanisms of time control in Biology. Hox genes are key players in the specification of tissue identity during embryo development and their expression is under strict temporal regulation. However, the molecular mechanisms underlying timely Hox activation in the early embryo remain unknown. This is hindered by the lack of a rigorous temporal framework of sequential Hox expression within a single cluster. Herein, a thorough characterization of HoxB cluster gene expression was performed over time and space in the early chick embryo. Clear temporal collinearity of HoxB cluster gene expression activation was observed. Spatial collinearity of HoxB expression was evidenced in different stages of development and in multiple tissues. Using embryo explant cultures we showed that HoxB2 is cyclically expressed in the rostral presomitic mesoderm with the same periodicity as somite formation, suggesting a link between timely tissue specification and somite formation. We foresee that the molecular framework herein provided will facilitate experimental approaches aimed at identifying the regulatory mechanisms underlying Hox expression in Time and Space. PMID:25602523

The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration

ERIC Educational Resources Information Center

McNeish, Daniel M.; Stapleton, Laura M.

2016-01-01

Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the…

GraphTeams: a method for discovering spatial gene clusters in Hi-C sequencing data.

PubMed

Schulz, Tizian; Stoye, Jens; Doerr, Daniel

2018-05-08

Hi-C sequencing offers novel, cost-effective means to study the spatial conformation of chromosomes. We use data obtained from Hi-C experiments to provide new evidence for the existence of spatial gene clusters. These are sets of genes with associated functionality that exhibit close proximity to each other in the spatial conformation of chromosomes across several related species. We present the first gene cluster model capable of handling spatial data. Our model generalizes a popular computational model for gene cluster prediction, called δ-teams, from sequences to graphs. Following previous lines of research, we subsequently extend our model to allow for several vertices being associated with the same label. The model, called δ-teams with families, is particular suitable for our application as it enables handling of gene duplicates. We develop algorithmic solutions for both models. We implemented the algorithm for discovering δ-teams with families and integrated it into a fully automated workflow for discovering gene clusters in Hi-C data, called GraphTeams. We applied it to human and mouse data to find intra- and interchromosomal gene cluster candidates. The results include intrachromosomal clusters that seem to exhibit a closer proximity in space than on their chromosomal DNA sequence. We further discovered interchromosomal gene clusters that contain genes from different chromosomes within the human genome, but are located on a single chromosome in mouse. By identifying δ-teams with families, we provide a flexible model to discover gene cluster candidates in Hi-C data. Our analysis of Hi-C data from human and mouse reveals several known gene clusters (thus validating our approach), but also few sparsely studied or possibly unknown gene cluster candidates that could be the source of further experimental investigations.

Spatio-temporal cluster detection of chickenpox in Valencia, Spain in the period 2008-2012.

PubMed

Iftimi, Adina; Martínez-Ruiz, Francisco; Míguez Santiyán, Ana; Montes, Francisco

2015-05-18

Chickenpox is a highly contagious airborne disease caused by Varicella zoster, which affects nearly all non-immune children worldwide with an annual incidence estimated at 80-90 million cases. To analyze the spatiotemporal pattern of the chickenpox incidence in the city of Valencia, Spain two complementary statistical approaches were used. First, we evaluated the existence of clusters and spatio-temporal interaction; secondly, we used this information to find the locations of the spatio-temporal clusters via the space-time permutation model. The first method used detects any aggregation in our data but does not provide the spatial and temporal information. The second method gives the locations, areas and time-frame for the spatio-temporal clusters. An overall decreasing time trend, a pronounced 12-monthly periodicity and two complementary periods were observed. Several areas with high incidence, surrounding the center of the city were identified. The existence of aggregation in time and space was observed, and a number of spatio-temporal clusters were located.

Low-temperature transonic cooling flows in galaxy clusters

NASA Technical Reports Server (NTRS)

Sulkanen, Martin E.; Burns, Jack O.; Norman, Michael L.

1989-01-01

Calculations are presented which demonstrate that cooling flow models with large sonic radii may be consistent with observed cluster gas properties. It is found that plausible cluster parameters and cooling flow mass accretion rates can produce sonic radii of 10-20 kpc for sonic point temperatures of 1-3 x 10 to the 6th K. The numerical calculations match these cooling flows to hydrostatic atmosphere solutions for the cluster gas beyond the cooling flow region. The cooling flows produce no appreciable 'holes' in the surface brightness toward the cluster center, and the model can be made to match the observed X-ray surface brightness of three clusters in which cooling flows had been believed to be absent. It is suggested that clusters with low velocity dispersion may be the natural location for such 'cool' cooling flows, and fits of these models to the X-ray surface brightness profiles for three clusters are presented.

Hydration of a Large Anionic Charge Distribution - Naphthalene-Water Cluster Anions

NASA Astrophysics Data System (ADS)

Weber, J. Mathias; Adams, Christopher L.

2010-06-01

We report the infrared spectra of anionic clusters of naphthalene with up to three water molecules. Comparison of the experimental infrared spectra with theoretically predicted spectra from quantum chemistry calculations allow conclusions regarding the structures of the clusters under study. The first water molecule forms two hydrogen bonds with the π electron system of the naphthalene moiety. Subsequent water ligands interact with both the naphthalene and the other water ligands to form hydrogen bonded networks, similar to other hydrated anion clusters. Naphthalene-water anion clusters illustrate how water interacts with negative charge delocalized over a large π electron system. The clusters are interesting model systems that are discussed in the context of wetting of graphene surfaces and polyaromatic hydrocarbons.

An Approach to Cluster EU Member States into Groups According to Pathways of Salmonella in the Farm-to-Consumption Chain for Pork Products.

PubMed

Vigre, Håkan; Domingues, Ana Rita Coutinho Calado; Pedersen, Ulrik Bo; Hald, Tine

2016-03-01

The aim of the project as the cluster analysis was to in part to develop a generic structured quantitative microbiological risk assessment (QMRA) model of human salmonellosis due to pork consumption in EU member states (MSs), and the objective of the cluster analysis was to group the EU MSs according to the relative contribution of different pathways of Salmonella in the farm-to-consumption chain of pork products. In the development of the model, by selecting a case study MS from each cluster the model was developed to represent different aspects of pig production, pork production, and consumption of pork products across EU states. The objective of the cluster analysis was to aggregate MSs into groups of countries with similar importance of different pathways of Salmonella in the farm-to-consumption chain using available, and where possible, universal register data related to the pork production and consumption in each country. Based on MS-specific information about distribution of (i) small and large farms, (ii) small and large slaughterhouses, (iii) amount of pork meat consumed, and (iv) amount of sausages consumed we used nonhierarchical and hierarchical cluster analysis to group the MSs. The cluster solutions were validated internally using statistic measures and externally by comparing the clustered MSs with an estimated human incidence of salmonellosis due to pork products in the MSs. Finally, each cluster was characterized qualitatively using the centroids of the clusters. © 2016 Society for Risk Analysis.

Kinetic model for binary homogeneous nucleation in the H2O-H2SO4 system: comparison with experiments and classical theory of nucleation.

PubMed

Sorokin, A; Vancassel, X; Mirabel, P

2005-12-22

A kinetic model to predict nucleation rates in the sulfuric acid-water system is presented. It allows calculating steady-state nucleation rates and the corresponding time lag, using a direct solution of a system of kinetic equations that describe the populations of sub- and near-critical clusters. This kinetic model takes into account cluster-cluster collisions and decay of clusters into smaller clusters. The model results are compared with some predictions obtained with the classical nucleation theory (CNT) and also with available measurement data obtained in smog chambers or flow tubes. It is shown that in the case of slow nucleation processes, the kinetic model and the CNT as used by Shugard et al. [J. Chem. Phys. 75, 5298 (1974)] give the same results. However, in the case of intensive nucleation, a large part of the nucleation flux is due to cluster-cluster collisions and the CNT underestimates the nucleation rates.

Record-breaking ancient galaxy clusters

NASA Astrophysics Data System (ADS)

2003-12-01

A tale of two record-breaking clusters hi-res Size hi-res: 768 kb Credits: for RDCS1252: NASA, ESA, J.Blakeslee (Johns Hopkins Univ.), M.Postman (Space Telescope Science Inst.) and P.Rosati, Chris Lidman & Ricardo Demarco (European Southern Observ.) for TNJ1338: NASA, ESA, G.Miley (Leiden Observ.) and R.Overzier (Leiden Obs) A tale of two record-breaking clusters Looking back in time to when the universe was in its formative youth, the Advanced Camera for Surveys (ACS) aboard the NASA/ESA Hubble Space Telescope captured these revealing images of two galaxy clusters. The image at left, which is made with an additional infrared exposure taken with the European Southern Observatory’s Very Large Telescope, shows mature galaxies in a massive cluster that existed when the cosmos was 5000 million years old. The cluster, called RDCS1252.9-2927, is as massive as ‘300 trillion’ suns and is the most massive known cluster for its epoch. The image reveals the core of the cluster and is part of a much larger mosaic of the entire cluster. Dominating the core are a pair of large, reddish elliptical galaxies [near centre of image]. Their red colour indicates an older population of stars. Most of the stars are at least 1000 million years old. The two galaxies appear to be interacting and may eventually merge to form a larger galaxy that is comparable to the brightest galaxies seen in present-day clusters. The red galaxies surrounding the central pair are also cluster members. The cluster probably contains many thousands of galaxies, but only about 50 can be seen in this image. The full mosaic (heic0313d) reveals several hundred cluster members. Many of the other galaxies in the image, including several of the blue galaxies, are foreground or background galaxies. The colour-composite image was assembled from two observations (through i and z filters) taken between May and June 2002 by the ACS Wide Field Camera, and one image with the ISAAC instrument on the VLT taken in 2002 (combined from a J filter exposure and a K filter exposure). In the image at right, astronomers are seeing an embryonic cluster as it was when the universe was 1500 million years old. The young system, called TNJ1338-1942, is the most distant known developing cluster, or proto-cluster. It is dominated by a massive ‘baby galaxy’ - the green object. The cluster RDCS1252.9-2927 hi-res Size hi-res: 2611 kb Credits: NASA, ESA, J. Blakeslee (Johns Hopkins University), M. Postman (Space Telescope Science Institute) and P. Rosati, Chris Lidman & Ricardo Demarco (European Southern Observatory) The cluster RDCS1252.9-2927 Looking back in time to when the Universe was in its formative youth, the Advanced Camera for Surveys (ACS) aboard the NASA/ESA Hubble Space Telescope captured this revealing image of the galaxy cluster RDCS1252.9-2927. The image shows the entire cluster (1/15 of a degree, corresponding to about 7 million light-years, across). The cluster probably contains many thousands of galaxies. Most of the other galaxies in the image, including most of the blue galaxies, are foreground or background galaxies. The image, which is made with an additional infrared exposure taken with the European Southern Observatory’s Very Large Telescope, shows mature galaxies in a massive cluster that existed when the cosmos was 5000 million years old. The cluster, called RDCS1252.9-2927, is as massive as ‘300 trillion’ suns and is the most massive known cluster for its epoch. Dominating the core are a pair of large, reddish elliptical galaxies [near centre of image]. Their red colour indicates an older population of stars. Most of the stars are at least 1000 million years old. The two galaxies appear to be interacting and may eventually merge to form a larger galaxy that is comparable to the brightest galaxies seen in present-day clusters. The red galaxies surrounding the central pair are also cluster members. The colour-composite image was assembled from two observations (through i and z filters) taken between May and June 2002 by the ACS Wide Field Camera, and one image with the ISAAC instrument on the VLT taken in 2002 (combined from a J filter exposure and a K filter exposure). The embryonic cluster TNJ1338-1942 hi-res Size hi-res: 154 kb Credits: NASA, ESA, G. Miley (Leiden Observatory) and R. Overzier (Leiden Observatory) The embryonic cluster TNJ1338-1942 In this image astronomers are seeing an embryonic cluster as it was when the universe was 1500 million years old. The young system, called TNJ1338-1942, is the most distant known developing cluster, or proto-cluster. It is dominated by a massive ‘baby galaxy’ - the green object in the centre. The galaxy is producing powerful radio emissions, and is the brightest galaxy in the proto-cluster. The green colour indicates that the galaxy is emitting glowing hydrogen gas. Its clumpy appearance suggests that it is still in the process of forming. Smaller developing galaxies are scattered around the massive galaxy. The galaxy on the left of the massive galaxy is a foreground galaxy. The bright object in the upper half of the image is a foreground star. This colour-composite image was assembled from observations taken between July 8 and 12, 2002 by the ACS Wide Field Camera. The cluster RDCS1252.9-2927 hi-res Size hi-res: 259 kb Credits: NASA, ESA, J. Blakeslee (Johns Hopkins University), M. Postman (Space Telescope Science Institute) and P. Rosati, Chris Lidman & Ricardo Demarco (European Southern Observatory) The cluster RDCS1252.9-2927 Looking back in time to when the universe was in its formative youth, the Advanced Camera for Surveys (ACS) aboard the NASA/ESA Hubble Space Telescope captured this revealing image of the galaxy cluster RDCS1252.9-2927. This image is made with an additional infrared exposure taken with the European Southern Observatory’s Very Large Telescope, shows mature galaxies in a massive cluster that existed when the cosmos was 5000 million years old. The cluster, called RDCS1252.9-2927, is as massive as ‘300 trillion’ suns and is the most massive known cluster for its epoch. The image reveals the core of the cluster and is part of a much larger mosaic of the entire cluster. Dominating the core are a pair of large, reddish elliptical galaxies [near centre of image]. Their red colour indicates an older population of stars. Most of the stars are at least 1 000 million years old. The two galaxies appear to be interacting and may eventually merge to form a larger galaxy that is comparable to the brightest galaxies seen in present-day clusters. The red galaxies surrounding the central pair are also cluster members. The cluster probably contains many thousands of galaxies, but only about 50 can be seen in this image. The full mosaic reveals several hundred cluster members. Many of the other galaxies in the image, including several of the blue galaxies, are foreground or background galaxies. The colour-composite image was assembled from two observations (through i and z filters) taken between May and June 2002 by the ACS Wide Field Camera, and one image with the ISAAC instrument on the VLT taken in 2002 (combined from a J filter exposure and a K filter exposure). Looking back in time nearly 9000 million years, an international team of astronomers found mature galaxies in a young Universe. The galaxies are members of a cluster of galaxies that existed when the Universe was only 5000 million years old, or about 35 percent of its present age. This is compelling evidence that galaxies must have started forming just after the Big Bang and is bolstered by observations made by the same team of astronomers when they peered even farther back in time. The team found embryonic galaxies a mere 1500 million years after the birth of the cosmos, or 10 percent of the Universe's present age. The ‘baby galaxies’ reside in a still developing cluster, the most distant proto-cluster ever found. The Advanced Camera for Surveys (ACS) aboard the NASA/ESA Hubble Space Telescope was used to make the observations of the massive cluster, RDCS1252.9-2927, and the proto-cluster, TNJ1338-1942. Observations by NASA’s Chandra X-ray Observatory yielded the mass and heavy element content of RDCS1252.9-2927, the most massive known cluster for that epoch. These observations are part of a co-ordinated effort by the ACS science team to track the formation and evolution of clusters of galaxies over a broad span of cosmic time. The ACS was specially built for such studies of very distant objects. These findings support the theory that galaxies formed relatively early in the history of the cosmos. The existence of such massive clusters in the early Universe agrees with a cosmological model wherein clusters form by the merger of many sub-clusters in a Universe dominated by cold dark matter. The precise nature of cold dark matter, however, is still not known. The first Hubble study estimated that the galaxies in RCDS1252 formed the bulk of their stars more than 11 000 million years ago (redshifts greater than 3). The results were published in the 20 October 2003, issue of the Astrophysical Journal. The paper's lead author is John Blakeslee of the Johns Hopkins University in Baltimore, USA. The second Hubble study uncovered, for the first time, a proto-cluster of ‘infant galaxies’ that existed more than 12 000 million years ago (redshift 4.1). These galaxies are so young that astronomers can still see a flurry of stars forming within them. The galaxies are grouped around one large galaxy. These results will be published in the January 1, 2004 issue of Nature. The paper's lead author is George Miley of Leiden Observatory in the Netherlands. "Until recently people didn't think that clusters existed when the Universe was only about 5000 million years old," Blakeslee explained. "Even if there were such clusters," Miley added, "until recently astronomers thought it was almost impossible to find clusters that existed 8000 million years ago. In fact, no one really knew when clustering began. Now we can witness it." Both studies led the astronomers to conclude that these systems are the progenitors of the galaxy clusters seen today. "The cluster RDCS1252 looks like a present-day cluster," said Marc Postman of the Space Telescope Science Institute in Baltimore, USA, and co-author of both research papers. "In fact, if you were to put it next to a present-day cluster you wouldn't know which is which." ‘A tale of two clusters’ How can galaxies grow so fast after the Big Bang? "It is a case of the rich getting richer," Blakeslee said. "These clusters grew quickly because they are located in very dense regions, so there is enough material to build up the member galaxies very fast." This idea is bolstered by X-ray observations of the massive cluster RDCS1252. Chandra and the European Space Agency's XMM-Newton provided astronomers with the most accurate measurements to date of the properties of an enormous cloud of hot gas that pervades the massive cluster. This 70 million °C gas is a reservoir of most of the heavy elements in the cluster, and an accurate tracer of its total mass. A paper by Piero Rosati of the European Southern Observatory (ESO) and colleagues that presents the X-ray observations of RDCS1252 will be published in January 2004 in the Astronomical Journal. "Chandra's sharp vision resolved the shape of the hot gas halo and showed that RDCS1252 is very mature for its age," said Rosati, who discovered the cluster with the ROSAT X-ray telescope. RDCS1252 may contain many thousands of galaxies. Most of those galaxies, however, are too faint to detect, although the powerful ‘eyes’ of the ACS pinpointed several hundred of them. Observations using ESO's Very Large Telescope (VLT) provided a precise measurement of the distance to the cluster. The ACS enabled the researchers to determine the shapes and the colours of the 100 galaxies accurately, providing information on the ages of the stars residing in them. The ACS team estimated that most of the stars in the cluster were already formed by the time the Universe was about 2000 million years old. In addition X-ray observations showed that 5 000 million years after the Big Bang the surrounding hot gas had been enriched with heavy elements from these stars and swept away from the galaxies. If most of the galaxies in RDCS1252 have reached maturity and are settling into a quiet adulthood, the galaxies forming in the distant proto-cluster are in their energetic, unruly youth. The proto-cluster TN J1338 contains a massive embryonic galaxy surrounded by smaller developing galaxies, which look like dots in the Hubble image. The dominant galaxy is producing spectacular radio-emitting jets, fuelled by a supermassive black hole deep within the galaxy's nucleus. Interaction between these jets and the gas can stimulate a torrent of star birth. The discovery of the energetic radio galaxy by radio telescopes prompted astronomers to hunt for the smaller galaxies that make up the bulk of the cluster. "Massive clusters are the cities of the Universe, and the radio galaxies within them are the smokestacks we can use for finding them when they are just beginning to form," Miley said. The two findings underscore the power of combining observations from many different telescopes to provide views of the distant Universe over a range of wavelengths. Hubble’s advanced camera provided critical information on the structure of both distant galaxy clusters. Chandra's and XMM-Newton’s X-ray vision furnished the essential measurements of the primordial gas in which the galaxies in RDCS1252 are embedded, and accurate estimates of the total mass contained within that cluster. Large ground-based telescopes, like the VLT, provided precise measurements of the distance of both clusters as well as the chemical composition of the galaxies in them. The ACS team is conducting further observations of distant clusters to solidify our understanding of how these young clusters and their galaxies evolve into the shape of things seen today. Their planned observations include using near-infrared observations to analyse the star-formation rates in some of their clusters, including RDCS1252, in order to measure the cosmic history of star formation in these massive structures. The team is also searching the regions around several ultra-distant radio galaxies for additional examples of proto-clusters. The team's ultimate scientific goal is to establish a complete picture of cluster evolution beginning with their formation at the earliest epochs and detailing their evolution up to the present time.

NoSOCS in SDSS - VI. The environmental dependence of AGN in clusters and field in the local Universe

NASA Astrophysics Data System (ADS)

Lopes, P. A. A.; Ribeiro, A. L. B.; Rembold, S. B.

2017-11-01

We investigated the variation in the fraction of optical active galactic nuclei (AGNs) hosts with stellar mass, as well as their local and global environments. Our sample is composed of cluster members and field galaxies at z ≤ 0.1 and we consider only strong AGN. We find a strong variation in the AGN fraction (FAGN) with stellar mass. The field population comprises a higher AGN fraction compared to the global cluster population, especially for objects with log M* > 10.6. Hence, we restricted our analysis to more massive objects. We detected a smooth variation in the FAGN with local stellar mass density for cluster objects, reaching a plateau in the field environment. As a function of cluster-centric distance we verify that FAGN is roughly constant for R > R200, but show a steep decline inwards. We have also verified the dependence of the AGN population on cluster velocity dispersion, finding a constant behaviour for low mass systems (σP ≲ 650-700 km s-1). However, there is a strong decline in FAGN for higher mass clusters (>700 km s-1). When comparing the FAGN in clusters with or without substructure, we only find different results for objects at large radii (R > R200), in the sense that clusters with substructure present some excess in the AGN fraction. Finally, we have found that the phase-space distribution of AGN cluster members is significantly different than other populations. Due to the environmental dependence of FAGN and their phase-space distribution, we interpret AGN to be the result of galaxy interactions, favoured in environments where the relative velocities are low, typical of the field, low mass groups or cluster outskirts.

Nature of multiple-nucleus cluster galaxies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merritt, D.

1984-05-01

In models for the evolution of galaxy clusters which include dynamical friction with the dark binding matter, the distribution of galaxies becomes more concentrated to the cluster center with time. In a cluster like Coma, this evolution could increase by a factor of approximately 3 the probability of finding a galaxy very close to the cluster center, without decreasing the typical velocity of such a galaxy significantly below the cluster mean. Such an enhancement is roughly what is needed to explain the large number of first-ranked cluster galaxies which are observed to have extra ''nuclei''; it is also consistent withmore » the high velocities typically measured for these ''nuclei.'' Unlike the cannibalism model, this model predicts that the majority of multiple-nucleus systems are transient phenomena, and not galaxies in the process of merging.« less

THE BLUE HOOK POPULATIONS OF MASSIVE GLOBULAR CLUSTERS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Thomas M.; Smith, Ed; Sweigart, Allen V.

2010-08-01

We present new Hubble Space Telescope ultraviolet color-magnitude diagrams of five massive Galactic globular clusters: NGC 2419, NGC 6273, NGC 6715, NGC 6388, and NGC 6441. These observations were obtained to investigate the 'blue hook' (BH) phenomenon previously observed in UV images of the globular clusters {omega} Cen and NGC 2808. Blue hook stars are a class of hot (approximately 35,000 K) subluminous horizontal branch stars that occupy a region of the HR diagram that is unexplained by canonical stellar evolution theory. By coupling new stellar evolution models to appropriate non-LTE synthetic spectra, we investigate various theoretical explanations for thesemore » stars. Specifically, we compare our photometry to canonical models at standard cluster abundances, canonical models with enhanced helium (consistent with cluster self-enrichment at early times), and flash-mixed models formed via a late helium-core flash on the white dwarf cooling curve. We find that flash-mixed models are required to explain the faint luminosity of the BH stars, although neither the canonical models nor the flash-mixed models can explain the range of color observed in such stars, especially those in the most metal-rich clusters. Aside from the variation in the color range, no clear trends emerge in the morphology of the BH population with respect to metallicity.« less

The Dark Matter Crisis: Falsification of the Current Standard Model of Cosmology

NASA Astrophysics Data System (ADS)

Kroupa, P.

2012-06-01

The current standard model of cosmology (SMoC) requires The Dual Dwarf Galaxy Theorem to be true according to which two types of dwarf galaxies must exist: primordial dark-matter (DM) dominated (type A) dwarf galaxies, and tidal-dwarf and ram-pressure-dwarf (type B) galaxies void of DM. Type A dwarfs surround the host approximately spherically, while type B dwarfs are typically correlated in phase-space. Type B dwarfs must exist in any cosmological theory in which galaxies interact. Only one type of dwarf galaxy is observed to exist on the baryonic Tully-Fisher plot and in the radius-mass plane. The Milky Way satellite system forms a vast phase-space-correlated structure that includes globular clusters and stellar and gaseous streams. Other galaxies also have phase-space correlated satellite systems. Therefore, The Dual Dwarf Galaxy Theorem is falsified by observation and dynamically relevant cold or warm DM cannot exist. It is shown that the SMoC is incompatible with a large set of other extragalactic observations. Other theoretical solutions to cosmological observations exist. In particular, alone the empirical mass-discrepancy-acceleration correlation constitutes convincing evidence that galactic-scale dynamics must be Milgromian. Major problems with inflationary big bang cosmologies remain unresolved.

A Fast Implementation of the ISOCLUS Algorithm

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Mount, David M.; Netanyahu, Nathan S.; LeMoigne, Jacqueline

2003-01-01

Unsupervised clustering is a fundamental building block in numerous image processing applications. One of the most popular and widely used clustering schemes for remote sensing applications is the ISOCLUS algorithm, which is based on the ISODATA method. The algorithm is given a set of n data points in d-dimensional space, an integer k indicating the initial number of clusters, and a number of additional parameters. The general goal is to compute the coordinates of a set of cluster centers in d-space, such that those centers minimize the mean squared distance from each data point to its nearest center. This clustering algorithm is similar to another well-known clustering method, called k-means. One significant feature of ISOCLUS over k-means is that the actual number of clusters reported might be fewer or more than the number supplied as part of the input. The algorithm uses different heuristics to determine whether to merge lor split clusters. As ISOCLUS can run very slowly, particularly on large data sets, there has been a growing .interest in the remote sensing community in computing it efficiently. We have developed a faster implementation of the ISOCLUS algorithm. Our improvement is based on a recent acceleration to the k-means algorithm of Kanungo, et al. They showed that, by using a kd-tree data structure for storing the data, it is possible to reduce the running time of k-means. We have adapted this method for the ISOCLUS algorithm, and we show that it is possible to achieve essentially the same results as ISOCLUS on large data sets, but with significantly lower running times. This adaptation involves computing a number of cluster statistics that are needed for ISOCLUS but not for k-means. Both the k-means and ISOCLUS algorithms are based on iterative schemes, in which nearest neighbors are calculated until some convergence criterion is satisfied. Each iteration requires that the nearest center for each data point be computed. Naively, this requires O(kn) time, where k denotes the current number of centers. Traditional techniques for accelerating nearest neighbor searching involve storing the k centers in a data structure. However, because of the iterative nature of the algorithm, this data structure would need to be rebuilt with each new iteration. Our approach is to store the data points in a kd-tree data structure. The assignment of points to nearest neighbors is carried out by a filtering process, which successively eliminates centers that can not possibly be the nearest neighbor for a given region of space. This algorithm is significantly faster, because large groups of data points can be assigned to their nearest center in a single operation. Preliminary results on a number of real Landsat datasets show that our revised ISOCLUS-like scheme runs about twice as fast.

Working Around Cosmic Variance: Remote Quadrupole Measurements of the CMB

NASA Astrophysics Data System (ADS)

Adil, Arsalan; Bunn, Emory

2018-01-01

Anisotropies in the CMB maps continue to revolutionize our understanding of the Cosmos. However, the statistical interpretation of these anisotropies is tainted with a posteriori statistics. The problem is particularly emphasized for lower order multipoles, i.e. in the cosmic variance regime of the power spectrum. Naturally, the solution lies in acquiring a new data set – a rather difficult task given the sample size of the Universe.The CMB temperature, in theory, depends on: the direction of photon propagation, the time at which the photons are observed, and the observer’s location in space. In existing CMB data, only the first parameter varies. However, as first pointed out by Kamionkowski and Loeb, a solution lies in making the so-called “Remote Quadrupole Measurements” by analyzing the secondary polarization produced by incoming CMB photons via the Sunyaev-Zel’dovich (SZ) effect. These observations allow us to measure the projected CMB quadrupole at the location and look-back time of a galaxy cluster.At low redshifts, the remote quadrupole is strongly correlated to the CMB anisotropy from our last scattering surface. We provide here a formalism for computing the covariance and relation matrices for both the two-point correlation function on the last scattering surface of a galaxy cluster and the cross correlation of the remote quadrupole with the local CMB. We then calculate these matrices based on a fiducial model and a non-standard model that suppresses power at large angles for ~104 clusters up to z=2. We anticipate to make a priori predictions of the differences between our expectations for the standard and non-standard models. Such an analysis is timely in the wake of the CMB S4 era which will provide us with an extensive SZ cluster catalogue.

The VLT LBG Redshift Survey - III. The clustering and dynamics of Lyman-break galaxies at z ˜ 3

NASA Astrophysics Data System (ADS)

Bielby, R.; Hill, M. D.; Shanks, T.; Crighton, N. H. M.; Infante, L.; Bornancini, C. G.; Francke, H.; Héraudeau, P.; Lambas, D. G.; Metcalfe, N.; Minniti, D.; Padilla, N.; Theuns, T.; Tummuangpak, P.; Weilbacher, P.

2013-03-01

We present a catalogue of 2135 galaxy redshifts from the VLT LBG Redshift Survey (VLRS), a spectroscopic survey of z ≈ 3 galaxies in wide fields centred on background quasi-stellar objects. We have used deep optical imaging to select galaxies via the Lyman-break technique. Spectroscopy of the Lyman-break galaxies (LBGs) was then made using the Very Large Telescope (VLT) Visible Multi-Object Spectrograph (VIMOS) instrument, giving a mean redshift of z = 2.79. We analyse the clustering properties of the VLRS sample and also of the VLRS sample combined with the smaller area Keck-based survey of Steidel et al. From the semiprojected correlation function, wp(σ), for the VLRS and combined surveys, we find that the results are well fit with a single power-law model, with clustering scale lengths of r0 = 3.46 ± 0.41 and 3.83 ± 0.24 h-1 Mpc, respectively. We note that the corresponding combined ξ(r) slope is flatter than for local galaxies at γ = 1.5-1.6 rather than γ = 1.8. This flat slope is confirmed by the z-space correlation function, ξ(s), and in the range 10 < s < 100 h-1 Mpc the VLRS shows an ≈2.5σ excess over the Λ cold dark matter (ΛCDM) linear prediction. This excess may be consistent with recent evidence for non-Gaussianity in clustering results at z ≈ 1. We then analyse the LBG z-space distortions using the 2D correlation function, ξ(σ, π), finding for the combined sample a large-scale infall parameter of β = 0.38 ± 0.19 and a velocity dispersion of sqrt{< w_z^2rangle }=420^{+140}_{-160} km s^{-1}. Based on our measured β, we are able to determine the gravitational growth rate, finding a value of f(z = 3) = 0.99 ± 0.50 (or fσ8 = 0.26 ± 0.13), which is the highest redshift measurement of the growth rate via galaxy clustering and is consistent with ΛCDM. Finally, we constrain the mean halo mass for the LBG population, finding that the VLRS and combined sample suggest mean halo masses of log(MDM/M⊙) = 11.57 ± 0.15 and 11.73 ± 0.07, respectively.

Galaxy Clusters

NASA Astrophysics Data System (ADS)

Miller, Christopher J. Miller

2012-03-01

There are many examples of clustering in astronomy. Stars in our own galaxy are often seen as being gravitationally bound into tight globular or open clusters. The Solar System's Trojan asteroids cluster at the gravitational Langrangian in front of Jupiter’s orbit. On the largest of scales, we find gravitationally bound clusters of galaxies, the Virgo cluster (in the constellation of Virgo at a distance of ˜50 million light years) being a prime nearby example. The Virgo cluster subtends an angle of nearly 8◦ on the sky and is known to contain over a thousand member galaxies. Galaxy clusters play an important role in our understanding of theUniverse. Clusters exist at peaks in the three-dimensional large-scale matter density field. Their sky (2D) locations are easy to detect in astronomical imaging data and their mean galaxy redshifts (redshift is related to the third spatial dimension: distance) are often better (spectroscopically) and cheaper (photometrically) when compared with the entire galaxy population in large sky surveys. Photometric redshift (z) [Photometric techniques use the broad band filter magnitudes of a galaxy to estimate the redshift. Spectroscopic techniques use the galaxy spectra and emission/absorption line features to measure the redshift] determinations of galaxies within clusters are accurate to better than delta_z = 0.05 [7] and when studied as a cluster population, the central galaxies form a line in color-magnitude space (called the the E/S0 ridgeline and visible in Figure 16.3) that contains galaxies with similar stellar populations [15]. The shape of this E/S0 ridgeline enables astronomers to measure the cluster redshift to within delta_z = 0.01 [23]. The most accurate cluster redshift determinations come from spectroscopy of the member galaxies, where only a fraction of the members need to be spectroscopically observed [25,42] to get an accurate redshift to the whole system. If light traces mass in the Universe, then the locations of galaxy clusters will be at locations of the peaks in the true underlying (mostly) dark matter density field. Kaiser (1984) [19] called this the high-peak model, which we demonstrate in Figure 16.1. We show a two-dimensional representation of a density field created by summing plane-waves with a predetermined power and with random wave-vector directions. In the left panel, we plot only the largest modes, where we see the density peaks (black) and valleys (white) in the combined field. In the right panel, we allow for smaller modes. You can see that the highest density peaks in the left panel contain smaller-scale, but still high-density peaks. These are the locations of future galaxy clusters. The bottom panel shows just these cluster-scale peaks. As you can see, the peaks themselves are clustered, and instead of just one large high-density peak in the original density field (see the left panel), the smaller modes show that six peaks are "born" within the broader, underlying large-scale density modes. This exemplifies the "bias" or amplified structure that is traced by galaxy clusters [19]. Clusters are rare, easy to find, and their member galaxies provide good distance estimates. In combination with their amplified clustering signal described above, galaxy clusters are considered an efficient and precise tracer of the large-scale matter density field in the Universe. Galaxy clusters can also be used to measure the baryon content of the Universe [43]. They can be used to identify gravitational lenses [38] and map the distribution of matter in clusters. The number and spatial distribution of galaxy clusters can be used to constrain cosmological parameters, like the fraction of the energy density in the Universe due to matter (Omega_matter) or the variation in the density field on fixed physical scales (sigma_8) [26,33]. The individual clusters act as “Island Universes” and as such are laboratories here we can study the evolution of the properties of the cluster, like the hot, gaseous intra-cluster medium or shapes, colors, and star-formation histories of the member galaxies [17].

Accelerating semantic graph databases on commodity clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morari, Alessandro; Castellana, Vito G.; Haglin, David J.

We are developing a full software system for accelerating semantic graph databases on commodity cluster that scales to hundreds of nodes while maintaining constant query throughput. Our framework comprises a SPARQL to C++ compiler, a library of parallel graph methods and a custom multithreaded runtime layer, which provides a Partitioned Global Address Space (PGAS) programming model with fork/join parallelism and automatic load balancing over a commodity clusters. We present preliminary results for the compiler and for the runtime.

Detecting space-time disease clusters with arbitrary shapes and sizes using a co-clustering approach.

PubMed

Ullah, Sami; Daud, Hanita; Dass, Sarat C; Khan, Habib Nawaz; Khalil, Alamgir

2017-11-06

Ability to detect potential space-time clusters in spatio-temporal data on disease occurrences is necessary for conducting surveillance and implementing disease prevention policies. Most existing techniques use geometrically shaped (circular, elliptical or square) scanning windows to discover disease clusters. In certain situations, where the disease occurrences tend to cluster in very irregularly shaped areas, these algorithms are not feasible in practise for the detection of space-time clusters. To address this problem, a new algorithm is proposed, which uses a co-clustering strategy to detect prospective and retrospective space-time disease clusters with no restriction on shape and size. The proposed method detects space-time disease clusters by tracking the changes in space-time occurrence structure instead of an in-depth search over space. This method was utilised to detect potential clusters in the annual and monthly malaria data in Khyber Pakhtunkhwa Province, Pakistan from 2012 to 2016 visualising the results on a heat map. The results of the annual data analysis showed that the most likely hotspot emerged in three sub-regions in the years 2013-2014. The most likely hotspots in monthly data appeared in the month of July to October in each year and showed a strong periodic trend.

Constraints on the dark matter neutralinos from the radio emissions of galaxy clusters

NASA Astrophysics Data System (ADS)

Kiew, Ching-Yee; Hwang, Chorng-Yuan; Zainal Abibin, Zamri

2017-05-01

By assuming the dark matter to be composed of neutralinos, we used the detection of upper limit on diffuse radio emission in a sample of galaxy clusters to put constraint on the properties of neutralinos. We showed the upper limit constraint on <σv>-mχ space with neutralino annihilation through b\\bar{b} and μ+μ- channels. The best constraint is from the galaxy clusters A2199 and A1367. We showed the uncertainty due to the density profile and cluster magnetic field. The largest uncertainty comes from the uncertainty in dark matter spatial distribution. We also investigated the constraints on minimal Supergravity (mSUGRA) and minimal supersymmetric standard model (MSSM) parameter space by scanning the parameters using the darksusy package. By using the current radio observation, we managed to exclude 40 combinations of mSUGRA parameters. On the other hand, 573 combinations of MSSM parameters can be excluded by current observation.

Exploring gravitational lensing model variations in the Frontier Fields galaxy clusters

NASA Astrophysics Data System (ADS)

Harris James, Nicholas John; Raney, Catie; Brennan, Sean; Keeton, Charles

2018-01-01

Multiple groups have been working on modeling the mass distributions of the six lensing galaxy clusters in the Hubble Space Telescope Frontier Fields data set. The magnification maps produced from these mass models will be important for the future study of the lensed background galaxies, but there exists significant variation in the different groups’ models and magnification maps. We explore the use of two-dimensional histograms as a tool for visualizing these magnification map variations. Using a number of simple, one- or two-halo singular isothermal sphere models, we explore the features that are produced in 2D histogram model comparisons when parameters such as halo mass, ellipticity, and location are allowed to vary. Our analysis demonstrates the potential of 2D histograms as a means of observing the full range of differences between the Frontier Fields groups’ models.This work has been supported by funding from National Science Foundation grants PHY-1560077 and AST-1211385, and from the Space Telescope Science Institute.

Power and money in cluster randomized trials: when is it worth measuring a covariate?

PubMed

Moerbeek, Mirjam

2006-08-15

The power to detect a treatment effect in cluster randomized trials can be increased by increasing the number of clusters. An alternative is to include covariates into the regression model that relates treatment condition to outcome. In this paper, formulae are derived in order to evaluate both strategies on basis of their costs. It is shown that the strategy that uses covariates is more cost-efficient in detecting a treatment effect when the costs to measure these covariates are small and the correlation between the covariates and outcome is sufficiently large. The minimum required correlation depends on the cluster size, and the costs to recruit a cluster and to measure the covariate, relative to the costs to recruit a person. Measuring a covariate that varies at the person level only is recommended when cluster sizes are small and the costs to recruit and measure a cluster are large. Measuring a cluster level covariate is recommended when cluster sizes are large and the costs to recruit and measure a cluster are small. An illustrative example shows the use of the formulae in a practical setting. Copyright 2006 John Wiley & Sons, Ltd.

Interacting star clusters in the Large Magellanic Cloud. Overmerging problem solved by cluster group formation

NASA Astrophysics Data System (ADS)

Leon, Stéphane; Bergond, Gilles; Vallenari, Antonella

1999-04-01

We present the tidal tail distributions of a sample of candidate binary clusters located in the bar of the Large Magellanic Cloud (LMC). One isolated cluster, SL 268, is presented in order to study the effect of the LMC tidal field. All the candidate binary clusters show tidal tails, confirming that the pairs are formed by physically linked objects. The stellar mass in the tails covers a large range, from 1.8x 10(3) to 3x 10(4) \\msun. We derive a total mass estimate for SL 268 and SL 356. At large radii, the projected density profiles of SL 268 and SL 356 fall off as r(-gamma ) , with gamma = 2.27 and gamma =3.44, respectively. Out of 4 pairs or multiple systems, 2 are older than the theoretical survival time of binary clusters (going from a few 10(6) years to 10(8) years). A pair shows too large age difference between the components to be consistent with classical theoretical models of binary cluster formation (Fujimoto & Kumai \\cite{fujimoto97}). We refer to this as the ``overmerging'' problem. A different scenario is proposed: the formation proceeds in large molecular complexes giving birth to groups of clusters over a few 10(7) years. In these groups the expected cluster encounter rate is larger, and tidal capture has higher probability. Cluster pairs are not born together through the splitting of the parent cloud, but formed later by tidal capture. For 3 pairs, we tentatively identify the star cluster group (SCG) memberships. The SCG formation, through the recent cluster starburst triggered by the LMC-SMC encounter, in contrast with the quiescent open cluster formation in the Milky Way can be an explanation to the paucity of binary clusters observed in our Galaxy. Based on observations collected at the European Southern Observatory, La Silla, Chile}

fast_protein_cluster: parallel and optimized clustering of large-scale protein modeling data.

PubMed

Hung, Ling-Hong; Samudrala, Ram

2014-06-15

fast_protein_cluster is a fast, parallel and memory efficient package used to cluster 60 000 sets of protein models (with up to 550 000 models per set) generated by the Nutritious Rice for the World project. fast_protein_cluster is an optimized and extensible toolkit that supports Root Mean Square Deviation after optimal superposition (RMSD) and Template Modeling score (TM-score) as metrics. RMSD calculations using a laptop CPU are 60× faster than qcprot and 3× faster than current graphics processing unit (GPU) implementations. New GPU code further increases the speed of RMSD and TM-score calculations. fast_protein_cluster provides novel k-means and hierarchical clustering methods that are up to 250× and 2000× faster, respectively, than Clusco, and identify significantly more accurate models than Spicker and Clusco. fast_protein_cluster is written in C++ using OpenMP for multi-threading support. Custom streaming Single Instruction Multiple Data (SIMD) extensions and advanced vector extension intrinsics code accelerate CPU calculations, and OpenCL kernels support AMD and Nvidia GPUs. fast_protein_cluster is available under the M.I.T. license. (http://software.compbio.washington.edu/fast_protein_cluster) © The Author 2014. Published by Oxford University Press.

Spatial clustering of mental disorders and associated characteristics of the neighbourhood context in Malmö, Sweden, in 2001

PubMed Central

Chaix, Basile; Leyland, Alastair H; Sabel, Clive E; Chauvin, Pierre; Råstam, Lennart; Kristersson, Håkan; Merlo, Juan

2006-01-01

Study objective Previous research provides preliminary evidence of spatial variations of mental disorders and associations between neighbourhood social context and mental health. This study expands past literature by (1) using spatial techniques, rather than multilevel models, to compare the spatial distributions of two groups of mental disorders (that is, disorders due to psychoactive substance use, and neurotic, stress related, and somatoform disorders); and (2) investigating the independent impact of contextual deprivation and neighbourhood social disorganisation on mental health, while assessing both the magnitude and the spatial scale of these effects. Design Using different spatial techniques, the study investigated mental disorders due to psychoactive substance use, and neurotic disorders. Participants All 89 285 persons aged 40–69 years residing in Malmö, Sweden, in 2001, geolocated to their place of residence. Main results The spatial scan statistic identified a large cluster of increased prevalence in a similar location for the two mental disorders in the northern part of Malmö. However, hierarchical geostatistical models showed that the two groups of disorders exhibited a different spatial distribution, in terms of both magnitude and spatial scale. Mental disorders due to substance consumption showed larger neighbourhood variations, and varied in space on a larger scale, than neurotic disorders. After adjustment for individual factors, the risk of substance related disorders increased with neighbourhood deprivation and neighbourhood social disorganisation. The risk of neurotic disorders only increased with contextual deprivation. Measuring contextual factors across continuous space, it was found that these associations operated on a local scale. Conclusions Taking space into account in the analyses permitted deeper insight into the contextual determinants of mental disorders. PMID:16614334

Mass Modeling of Frontier Fields Cluster MACS J1149.5+2223 Using Strong and Weak Lensing

NASA Astrophysics Data System (ADS)

Finney, Emily Quinn; Bradač, Maruša; Huang, Kuang-Han; Hoag, Austin; Morishita, Takahiro; Schrabback, Tim; Treu, Tommaso; Borello Schmidt, Kasper; Lemaux, Brian C.; Wang, Xin; Mason, Charlotte

2018-05-01

We present a gravitational-lensing model of MACS J1149.5+2223 using ultra-deep Hubble Frontier Fields imaging data and spectroscopic redshifts from HST grism and Very Large Telescope (VLT)/MUSE spectroscopic data. We create total mass maps using 38 multiple images (13 sources) and 608 weak-lensing galaxies, as well as 100 multiple images of 31 star-forming regions in the galaxy that hosts supernova Refsdal. We find good agreement with a range of recent models within the HST field of view. We present a map of the ratio of projected stellar mass to total mass (f ⋆) and find that the stellar mass fraction for this cluster peaks on the primary BCG. Averaging within a radius of 0.3 Mpc, we obtain a value of < {f}\\star > ={0.012}-0.003+0.004, consistent with other recent results for this ratio in cluster environments, though with a large global error (up to δf ⋆ = 0.005) primarily due to the choice of IMF. We compare values of f ⋆ and measures of star formation efficiency for this cluster to other Hubble Frontier Fields clusters studied in the literature, finding that MACS1149 has a higher stellar mass fraction than these other clusters but a star formation efficiency typical of massive clusters.

Fusion And Inference From Multiple And Massive Disparate Distributed Dynamic Data Sets

DTIC Science & Technology

2017-07-01

principled methodology for two-sample graph testing; designed a provably almost-surely perfect vertex clustering algorithm for block model graphs; proved...3.7 Semi-Supervised Clustering Methodology ...................................................................... 9 3.8 Robust Hypothesis Testing...dimensional Euclidean space – allows the full arsenal of statistical and machine learning methodology for multivariate Euclidean data to be deployed for

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sehgal, Ray M.; Maroudas, Dimitrios, E-mail: maroudas@ecs.umass.edu, E-mail: ford@ecs.umass.edu; Ford, David M., E-mail: maroudas@ecs.umass.edu, E-mail: ford@ecs.umass.edu

We have developed a coarse-grained description of the phase behavior of the isolated 38-atom Lennard-Jones cluster (LJ{sub 38}). The model captures both the solid-solid polymorphic transitions at low temperatures and the complex cluster breakup and melting transitions at higher temperatures. For this coarse model development, we employ the manifold learning technique of diffusion mapping. The outcome of the diffusion mapping analysis over a broad temperature range indicates that two order parameters are sufficient to describe the cluster's phase behavior; we have chosen two such appropriate order parameters that are metrics of condensation and overall crystallinity. In this well-justified coarse-variable space,more » we calculate the cluster's free energy landscape (FEL) as a function of temperature, employing Monte Carlo umbrella sampling. These FELs are used to quantify the phase behavior and onsets of phase transitions of the LJ{sub 38} cluster.« less

Neutrino masses, scale-dependent growth, and redshift-space distortions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hernández, Oscar F., E-mail: oscarh@physics.mcgill.ca

2017-06-01

Massive neutrinos leave a unique signature in the large scale clustering of matter. We investigate the wavenumber dependence of the growth factor arising from neutrino masses and use a Fisher analysis to determine the aspects of a galaxy survey needed to measure this scale dependence.

Variations of cosmic large-scale structure covariance matrices across parameter space

NASA Astrophysics Data System (ADS)

Reischke, Robert; Kiessling, Alina; Schäfer, Björn Malte

2017-03-01

The likelihood function for cosmological parameters, given by e.g. weak lensing shear measurements, depends on contributions to the covariance induced by the non-linear evolution of the cosmic web. As highly non-linear clustering to date has only been described by numerical N-body simulations in a reliable and sufficiently precise way, the necessary computational costs for estimating those covariances at different points in parameter space are tremendous. In this work, we describe the change of the matter covariance and the weak lensing covariance matrix as a function of cosmological parameters by constructing a suitable basis, where we model the contribution to the covariance from non-linear structure formation using Eulerian perturbation theory at third order. We show that our formalism is capable of dealing with large matrices and reproduces expected degeneracies and scaling with cosmological parameters in a reliable way. Comparing our analytical results to numerical simulations, we find that the method describes the variation of the covariance matrix found in the SUNGLASS weak lensing simulation pipeline within the errors at one-loop and tree-level for the spectrum and the trispectrum, respectively, for multipoles up to ℓ ≤ 1300. We show that it is possible to optimize the sampling of parameter space where numerical simulations should be carried out by minimizing interpolation errors and propose a corresponding method to distribute points in parameter space in an economical way.

JELLYFISH: EVIDENCE OF EXTREME RAM-PRESSURE STRIPPING IN MASSIVE GALAXY CLUSTERS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ebeling, H.; Stephenson, L. N.; Edge, A. C.

Ram-pressure stripping by the gaseous intracluster medium has been proposed as the dominant physical mechanism driving the rapid evolution of galaxies in dense environments. Detailed studies of this process have, however, largely been limited to relatively modest examples affecting only the outermost gas layers of galaxies in nearby and/or low-mass galaxy clusters. We here present results from our search for extreme cases of gas-galaxy interactions in much more massive, X-ray selected clusters at z > 0.3. Using Hubble Space Telescope snapshots in the F606W and F814W passbands, we have discovered dramatic evidence of ram-pressure stripping in which copious amounts ofmore » gas are first shock compressed and then removed from galaxies falling into the cluster. Vigorous starbursts triggered by this process across the galaxy-gas interface and in the debris trail cause these galaxies to temporarily become some of the brightest cluster members in the F606W passband, capable of outshining even the Brightest Cluster Galaxy. Based on the spatial distribution and orientation of systems viewed nearly edge-on in our survey, we speculate that infall at large impact parameter gives rise to particularly long-lasting stripping events. Our sample of six spectacular examples identified in clusters from the Massive Cluster Survey, all featuring M {sub F606W} < –21 mag, doubles the number of such systems presently known at z > 0.2 and facilitates detailed quantitative studies of the most violent galaxy evolution in clusters.« less

Large-Scale Clustering of Galaxies in the CFA Survey

NASA Astrophysics Data System (ADS)

Park, Changbom

1992-03-01

The power spectrum of the galaxy distribution is accuarately measured up to wavelengths over 100h-1 Mpc from the CfA 1 and 2 catalogs. We find that our results agree with power spectra calculated by others from smaller samples of optical, radio and infrared galaxies. The power spectrum of an open CDM model (Omega h = 0.2 and delta8 = 1; see below for definitions) best approximates the observed power spectrum. The power spectrum of the standard CDM model(Omega h = 0.5 and delta8 = 1) is inconsistent with the observed one at the 99% confidence level. Our best estimation of the corresponding correlation function in real space is Xi(r) = (r/6.2h-1 Mpc)^-1.8 for r < 20h-1 Mpc.

Field O stars: formed in situ or as runaways?

NASA Astrophysics Data System (ADS)

Gvaramadze, V. V.; Weidner, C.; Kroupa, P.; Pflamm-Altenburg, J.

2012-08-01

A significant fraction of massive stars in the Milky Way and other galaxies are located far from star clusters and star-forming regions. It is known that some of these stars are runaways, i.e. possess high space velocities (determined through the proper motion and/or radial velocity measurements), and therefore most likely were formed in embedded clusters and then ejected into the field because of dynamical few-body interactions or binary-supernova explosions. However, there exists a group of field O stars whose runaway status is difficult to prove via direct proper motion measurements (e.g. in the Magellanic Clouds) or whose (measured) low space velocities and/or young ages appear to be incompatible with their large separation from known star clusters. The existence of this group led some authors to believe that field O stars can form in situ. Since the question of whether or not O stars can form in isolation is of crucial importance for star formation theory, it is important to thoroughly test candidates of such stars in order to improve the theory. In this paper, we examine the runaway status of the best candidates for isolated formation of massive stars in the Milky Way and the Magellanic Clouds by searching for bow shocks around them, by using the new reduction of the Hipparcos data, and by searching for stellar systems from which they could originate within their lifetimes. We show that most of the known O stars thought to have formed in isolation are instead very likely runaways. We show also that the field must contain a population of O stars whose low space velocities and/or young ages are in apparent contradiction to the large separation of these stars from their parent clusters and/or the ages of these clusters. These stars (the descendants of runaway massive binaries) cannot be traced back to their parent clusters and therefore can be mistakenly considered as having formed in situ. We argue also that some field O stars could be detected in optical wavelengths only because they are runaways, while their cousins residing in the deeply embedded parent clusters might still remain totally obscured. The main conclusion of our study is that there is no significant evidence whatsoever in support of the in situ proposal on the origin of massive stars.

Mixed-Initiative Clustering

ERIC Educational Resources Information Center

Huang, Yifen

2010-01-01

Mixed-initiative clustering is a task where a user and a machine work collaboratively to analyze a large set of documents. We hypothesize that a user and a machine can both learn better clustering models through enriched communication and interactive learning from each other. The first contribution or this thesis is providing a framework of…

Modeling of the Modulation by Buffers of Ca2+ Release through Clusters of IP3 Receptors

PubMed Central

Zeller, S.; Rüdiger, S.; Engel, H.; Sneyd, J.; Warnecke, G.; Parker, I.; Falcke, M.

2009-01-01

Abstract Intracellular Ca2+ release is a versatile second messenger system. It is modeled here by reaction-diffusion equations for the free Ca2+ and Ca2+ buffers, with spatially discrete clusters of stochastic IP3 receptor channels (IP3Rs) controlling the release of Ca2+ from the endoplasmic reticulum. IP3Rs are activated by a small rise of the cytosolic Ca2+ concentration and inhibited by large concentrations. Buffering of cytosolic Ca2+ shapes global Ca2+ transients. Here we use a model to investigate the effect of buffers with slow and fast reaction rates on single release spikes. We find that, depending on their diffusion coefficient, fast buffers can either decouple clusters or delay inhibition. Slow buffers have little effect on Ca2+ release, but affect the time course of the signals from the fluorescent Ca2+ indicator mainly by competing for Ca2+. At low [IP3], fast buffers suppress fluorescence signals, slow buffers increase the contrast between bulk signals and signals at open clusters, and large concentrations of buffers, either fast or slow, decouple clusters. PMID:19686646

Validity of the classical monte carlo method to model the magnetic properties of a large transition-metal cluster: Mn19.

PubMed

Lima, Nicola; Caneschi, Andrea; Gatteschi, Dante; Kritikos, Mikael; Westin, L Gunnar

2006-03-20

The susceptibility of the large transition-metal cluster [Mn19O12(MOE)14(MOEH)10].MOEH (MOE = OC2H2O-CH3) has been fitted through classical Monte Carlo simulation, and an estimation of the exchange coupling constants has been done. With these results, it has been possible to perform a full-matrix diagonalization of the cluster core, which was used to provide information on the nature of the low-lying levels.

A space-time scan statistic for detecting emerging outbreaks.

PubMed

Tango, Toshiro; Takahashi, Kunihiko; Kohriyama, Kazuaki

2011-03-01

As a major analytical method for outbreak detection, Kulldorff's space-time scan statistic (2001, Journal of the Royal Statistical Society, Series A 164, 61-72) has been implemented in many syndromic surveillance systems. Since, however, it is based on circular windows in space, it has difficulty correctly detecting actual noncircular clusters. Takahashi et al. (2008, International Journal of Health Geographics 7, 14) proposed a flexible space-time scan statistic with the capability of detecting noncircular areas. It seems to us, however, that the detection of the most likely cluster defined in these space-time scan statistics is not the same as the detection of localized emerging disease outbreaks because the former compares the observed number of cases with the conditional expected number of cases. In this article, we propose a new space-time scan statistic which compares the observed number of cases with the unconditional expected number of cases, takes a time-to-time variation of Poisson mean into account, and implements an outbreak model to capture localized emerging disease outbreaks more timely and correctly. The proposed models are illustrated with data from weekly surveillance of the number of absentees in primary schools in Kitakyushu-shi, Japan, 2006. © 2010, The International Biometric Society.

Assessing SaTScan ability to detect space-time clusters in wildfires

NASA Astrophysics Data System (ADS)

Costa, Ricardo; Pereira, Mário; Caramelo, Liliana; Vega Orozco, Carmen; Kanevski, Mikhail

2013-04-01

Besides classical cluster analysis techniques which are able to analyse spatial and temporal data, SaTScan software analyses space-time data using the spatial, temporal or space-time scan statistics. This software requires the spatial coordinates of the fire, but since in the Rural Fire Portuguese Database (PRFD) (Pereira et al, 2011) the location of each fire is the parish where the ignition occurs, the fire spatial coordinates were considered as coordinates of the centroid of the parishes. Moreover, in general, the northern region is characterized by a large number of small parishes while the southern comprises parish much larger. The objectives of this study are: (i) to test the ability of SaTScan to detect the correct space-time clusters, in what respects to spatial and temporal location and size; and, (ii) to evaluate the effect of the dimensions of the parishes and of aggregating all fires occurred in a parish in a single point. Results obtained with a synthetic database where clusters were artificially created with different densities, in different regions of the country and with different sizes and durations, allow to conclude: the ability of SaTScan to correctly identify the clusters (location, shape and spatial and temporal dimension); and objectively assess the influence of the size of the parishes and windows used in space-time detection. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692, the project FLAIR (PTDC/AAC-AMB/104702/2008) and the EU 7th Framework Program through FUME (contract number 243888).

Design and analysis of forward and reverse models for predicting defect accumulation, defect energetics, and irradiation conditions

DOE PAGES

Stewart, James A.; Kohnert, Aaron A.; Capolungo, Laurent; ...

2018-03-06

The complexity of radiation effects in a material’s microstructure makes developing predictive models a difficult task. In principle, a complete list of all possible reactions between defect species being considered can be used to elucidate damage evolution mechanisms and its associated impact on microstructure evolution. However, a central limitation is that many models use a limited and incomplete catalog of defect energetics and associated reactions. Even for a given model, estimating its input parameters remains a challenge, especially for complex material systems. Here, we present a computational analysis to identify the extent to which defect accumulation, energetics, and irradiation conditionsmore » can be determined via forward and reverse regression models constructed and trained from large data sets produced by cluster dynamics simulations. A global sensitivity analysis, via Sobol’ indices, concisely characterizes parameter sensitivity and demonstrates how this can be connected to variability in defect evolution. Based on this analysis and depending on the definition of what constitutes the input and output spaces, forward and reverse regression models are constructed and allow for the direct calculation of defect accumulation, defect energetics, and irradiation conditions. Here, this computational analysis, exercised on a simplified cluster dynamics model, demonstrates the ability to design predictive surrogate and reduced-order models, and provides guidelines for improving model predictions within the context of forward and reverse engineering of mathematical models for radiation effects in a materials’ microstructure.« less

Design and analysis of forward and reverse models for predicting defect accumulation, defect energetics, and irradiation conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stewart, James A.; Kohnert, Aaron A.; Capolungo, Laurent

The complexity of radiation effects in a material’s microstructure makes developing predictive models a difficult task. In principle, a complete list of all possible reactions between defect species being considered can be used to elucidate damage evolution mechanisms and its associated impact on microstructure evolution. However, a central limitation is that many models use a limited and incomplete catalog of defect energetics and associated reactions. Even for a given model, estimating its input parameters remains a challenge, especially for complex material systems. Here, we present a computational analysis to identify the extent to which defect accumulation, energetics, and irradiation conditionsmore » can be determined via forward and reverse regression models constructed and trained from large data sets produced by cluster dynamics simulations. A global sensitivity analysis, via Sobol’ indices, concisely characterizes parameter sensitivity and demonstrates how this can be connected to variability in defect evolution. Based on this analysis and depending on the definition of what constitutes the input and output spaces, forward and reverse regression models are constructed and allow for the direct calculation of defect accumulation, defect energetics, and irradiation conditions. Here, this computational analysis, exercised on a simplified cluster dynamics model, demonstrates the ability to design predictive surrogate and reduced-order models, and provides guidelines for improving model predictions within the context of forward and reverse engineering of mathematical models for radiation effects in a materials’ microstructure.« less

Analysis of the seismicity preceding large earthquakes

NASA Astrophysics Data System (ADS)

Stallone, Angela; Marzocchi, Warner

2017-04-01

The most common earthquake forecasting models assume that the magnitude of the next earthquake is independent from the past. This feature is probably one of the most severe limitations of the capability to forecast large earthquakes. In this work, we investigate empirically on this specific aspect, exploring whether variations in seismicity in the space-time-magnitude domain encode some information on the size of the future earthquakes. For this purpose, and to verify the stability of the findings, we consider seismic catalogs covering quite different space-time-magnitude windows, such as the Alto Tiberina Near Fault Observatory (TABOO) catalogue, the California and Japanese seismic catalog. Our method is inspired by the statistical methodology proposed by Baiesi & Paczuski (2004) and elaborated by Zaliapin et al. (2008) to distinguish between triggered and background earthquakes, based on a pairwise nearest-neighbor metric defined by properly rescaled temporal and spatial distances. We generalize the method to a metric based on the k-nearest-neighbors that allows us to consider the overall space-time-magnitude distribution of k-earthquakes, which are the strongly correlated ancestors of a target event. Finally, we analyze the statistical properties of the clusters composed by the target event and its k-nearest-neighbors. In essence, the main goal of this study is to verify if different classes of target event magnitudes are characterized by distinctive "k-foreshocks" distributions. The final step is to show how the findings of this work may (or not) improve the skill of existing earthquake forecasting models.

Computationally-efficient stochastic cluster dynamics method for modeling damage accumulation in irradiated materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoang, Tuan L.; Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, CA 94550; Marian, Jaime, E-mail: jmarian@ucla.edu

2015-11-01

An improved version of a recently developed stochastic cluster dynamics (SCD) method (Marian and Bulatov, 2012) [6] is introduced as an alternative to rate theory (RT) methods for solving coupled ordinary differential equation (ODE) systems for irradiation damage simulations. SCD circumvents by design the curse of dimensionality of the variable space that renders traditional ODE-based RT approaches inefficient when handling complex defect population comprised of multiple (more than two) defect species. Several improvements introduced here enable efficient and accurate simulations of irradiated materials up to realistic (high) damage doses characteristic of next-generation nuclear systems. The first improvement is a proceduremore » for efficiently updating the defect reaction-network and event selection in the context of a dynamically expanding reaction-network. Next is a novel implementation of the τ-leaping method that speeds up SCD simulations by advancing the state of the reaction network in large time increments when appropriate. Lastly, a volume rescaling procedure is introduced to control the computational complexity of the expanding reaction-network through occasional reductions of the defect population while maintaining accurate statistics. The enhanced SCD method is then applied to model defect cluster accumulation in iron thin films subjected to triple ion-beam (Fe{sup 3+}, He{sup +} and H{sup +}) irradiations, for which standard RT or spatially-resolved kinetic Monte Carlo simulations are prohibitively expensive.« less

Computationally-efficient stochastic cluster dynamics method for modeling damage accumulation in irradiated materials

NASA Astrophysics Data System (ADS)

Hoang, Tuan L.; Marian, Jaime; Bulatov, Vasily V.; Hosemann, Peter

2015-11-01

An improved version of a recently developed stochastic cluster dynamics (SCD) method (Marian and Bulatov, 2012) [6] is introduced as an alternative to rate theory (RT) methods for solving coupled ordinary differential equation (ODE) systems for irradiation damage simulations. SCD circumvents by design the curse of dimensionality of the variable space that renders traditional ODE-based RT approaches inefficient when handling complex defect population comprised of multiple (more than two) defect species. Several improvements introduced here enable efficient and accurate simulations of irradiated materials up to realistic (high) damage doses characteristic of next-generation nuclear systems. The first improvement is a procedure for efficiently updating the defect reaction-network and event selection in the context of a dynamically expanding reaction-network. Next is a novel implementation of the τ-leaping method that speeds up SCD simulations by advancing the state of the reaction network in large time increments when appropriate. Lastly, a volume rescaling procedure is introduced to control the computational complexity of the expanding reaction-network through occasional reductions of the defect population while maintaining accurate statistics. The enhanced SCD method is then applied to model defect cluster accumulation in iron thin films subjected to triple ion-beam (Fe3+, He+ and H+) irradiations, for which standard RT or spatially-resolved kinetic Monte Carlo simulations are prohibitively expensive.

Stimuli Reduce the Dimensionality of Cortical Activity

PubMed Central

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models. PMID:26924968

Stimuli Reduce the Dimensionality of Cortical Activity.

PubMed

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models.

Novel method to construct large-scale design space in lubrication process utilizing Bayesian estimation based on a small-scale design-of-experiment and small sets of large-scale manufacturing data.

PubMed

Maeda, Jin; Suzuki, Tatsuya; Takayama, Kozo

2012-12-01

A large-scale design space was constructed using a Bayesian estimation method with a small-scale design of experiments (DoE) and small sets of large-scale manufacturing data without enforcing a large-scale DoE. The small-scale DoE was conducted using various Froude numbers (X(1)) and blending times (X(2)) in the lubricant blending process for theophylline tablets. The response surfaces, design space, and their reliability of the compression rate of the powder mixture (Y(1)), tablet hardness (Y(2)), and dissolution rate (Y(3)) on a small scale were calculated using multivariate spline interpolation, a bootstrap resampling technique, and self-organizing map clustering. The constant Froude number was applied as a scale-up rule. Three experiments under an optimal condition and two experiments under other conditions were performed on a large scale. The response surfaces on the small scale were corrected to those on a large scale by Bayesian estimation using the large-scale results. Large-scale experiments under three additional sets of conditions showed that the corrected design space was more reliable than that on the small scale, even if there was some discrepancy in the pharmaceutical quality between the manufacturing scales. This approach is useful for setting up a design space in pharmaceutical development when a DoE cannot be performed at a commercial large manufacturing scale.

A novel harmony search-K means hybrid algorithm for clustering gene expression data

PubMed Central

Nazeer, KA Abdul; Sebastian, MP; Kumar, SD Madhu

2013-01-01

Recent progress in bioinformatics research has led to the accumulation of huge quantities of biological data at various data sources. The DNA microarray technology makes it possible to simultaneously analyze large number of genes across different samples. Clustering of microarray data can reveal the hidden gene expression patterns from large quantities of expression data that in turn offers tremendous possibilities in functional genomics, comparative genomics, disease diagnosis and drug development. The k- ¬means clustering algorithm is widely used for many practical applications. But the original k-¬means algorithm has several drawbacks. It is computationally expensive and generates locally optimal solutions based on the random choice of the initial centroids. Several methods have been proposed in the literature for improving the performance of the k-¬means algorithm. A meta-heuristic optimization algorithm named harmony search helps find out near-global optimal solutions by searching the entire solution space. Low clustering accuracy of the existing algorithms limits their use in many crucial applications of life sciences. In this paper we propose a novel Harmony Search-K means Hybrid (HSKH) algorithm for clustering the gene expression data. Experimental results show that the proposed algorithm produces clusters with better accuracy in comparison with the existing algorithms. PMID:23390351

A novel harmony search-K means hybrid algorithm for clustering gene expression data.

PubMed

Nazeer, Ka Abdul; Sebastian, Mp; Kumar, Sd Madhu

2013-01-01

Recent progress in bioinformatics research has led to the accumulation of huge quantities of biological data at various data sources. The DNA microarray technology makes it possible to simultaneously analyze large number of genes across different samples. Clustering of microarray data can reveal the hidden gene expression patterns from large quantities of expression data that in turn offers tremendous possibilities in functional genomics, comparative genomics, disease diagnosis and drug development. The k- ¬means clustering algorithm is widely used for many practical applications. But the original k-¬means algorithm has several drawbacks. It is computationally expensive and generates locally optimal solutions based on the random choice of the initial centroids. Several methods have been proposed in the literature for improving the performance of the k-¬means algorithm. A meta-heuristic optimization algorithm named harmony search helps find out near-global optimal solutions by searching the entire solution space. Low clustering accuracy of the existing algorithms limits their use in many crucial applications of life sciences. In this paper we propose a novel Harmony Search-K means Hybrid (HSKH) algorithm for clustering the gene expression data. Experimental results show that the proposed algorithm produces clusters with better accuracy in comparison with the existing algorithms.

Strong Lens Models for Massive Galaxy Clusters in the Reionization Lensing Cluster Survey

NASA Astrophysics Data System (ADS)

Cerny, Catherine; Sharon, Keren; Coe, Dan A.; Paterno-Mahler, Rachel; Jones, Christine; Czakon, Nicole G.; Umetsu, Keiichi; Stark, Daniel; Bradley, Larry D.; Trenti, Michele; Johnson, Traci; Bradac, Marusa; Dawson, William; Rodney, Steven A.; Strolger, Louis-Gregory; RELICS Team

2017-01-01

We present strong lensing models for five galaxy clusters from the Planck SZ cluster catalog as a part of the Reionization Lensing Cluster Survey (RELICS), a program that seeks to constrain the galaxy luminosity function past z~9 by conducting a wide field survey of massive galaxy clusters with HST (GO-14096, PI: Coe). The strong gravitational lensing effects of these clusters significantly magnify background galaxies, which enhances our ability to discover the large numbers of high redshift galaxies at z~9-12 needed to create a representative sample. We use strong lensing models for these clusters to study their mass distribution and magnification, which allows us to quantify the lensing effect on the background galaxies. These models can then be utilized in the RELICS survey in order to identify high redshift galaxy candidates that may be lensed by the clusters. The intrinsic properties of these galaxy candidates can be derived by removing the lensing effect as predicted by our models, which will meet the science goals of the RELICS survey. We use HST WFC3 and ACS imaging to create lensing models for the clusters RXC J0142.9+4438, ACO-2537, ACO-2163, RXCJ2211.7-0349, and ACT-CLJ0102-49151.

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation

PubMed Central

Sherfey, Jason S.; Soplata, Austin E.; Ardid, Salva; Roberts, Erik A.; Stanley, David A.; Pittman-Polletta, Benjamin R.; Kopell, Nancy J.

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community. PMID:29599715

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation.

PubMed

Sherfey, Jason S; Soplata, Austin E; Ardid, Salva; Roberts, Erik A; Stanley, David A; Pittman-Polletta, Benjamin R; Kopell, Nancy J

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.

Clustering of galaxies near damped Lyman-alpha systems with (z) = 2.6

NASA Technical Reports Server (NTRS)

Wolfe, A. M

1993-01-01

The galaxy two-point correlation function, xi, at (z) = 2.6 is determined by comparing the number of Ly-alpha-emitting galaxies in narrowband CCD fields selected for the presence of damped L-alpha absorption to their number in randomly selected control fields. Comparisons between the presented determination of (xi), a density-weighted volume average of xi, and model predictions for (xi) at large redshifts show that models in which the clustering pattern is fixed in proper coordinates are highly unlikely, while better agreement is obtained if the clustering pattern is fixed in comoving coordinates. Therefore, clustering of Ly-alpha-emitting galaxies around damped Ly-alpha systems at large redshifts is strong. It is concluded that the faint blue galaxies are drawn from a parent population different from normal galaxies, the presumed offspring of damped Ly-alpha systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geiger, K.; Longacre, R.; Srivastava, D.K.

VNI is a general-purpose Monte-Carlo event-generator, which includes the simulation of lepton-lepton, lepton-hadron, lepton-nucleus, hadron-hadron, hadron-nucleus, and nucleus-nucleus collisions. It uses the real-time evolution of parton cascades in conjunction with a self-consistent hadronization scheme, as well as the development of hadron cascades after hadronization. The causal evolution from a specific initial state (determined by the colliding beam particles) is followed by the time-development of the phase-space densities of partons, pre-hadronic parton clusters, and final-state hadrons, in position-space, momentum-space and color-space. The parton-evolution is described in terms of a space-time generalization of the familiar momentum-space description of multiple (semi)hard interactions inmore » QCD, involving 2 {r_arrow} 2 parton collisions, 2 {r_arrow} 1 parton fusion processes, and 1 {r_arrow} 2 radiation processes. The formation of color-singlet pre-hadronic clusters and their decays into hadrons, on the other hand, is treated by using a spatial criterion motivated by confinement and a non-perturbative model for hadronization. Finally, the cascading of produced prehadronic clusters and of hadrons includes a multitude of 2 {r_arrow} n processes, and is modeled in parallel to the parton cascade description. This paper gives a brief review of the physics underlying VNI, as well as a detailed description of the program itself. The latter program description emphasizes easy-to-use pragmatism and explains how to use the program (including simple examples), annotates input and control parameters, and discusses output data provided by it.« less

No energy equipartition in globular clusters

NASA Astrophysics Data System (ADS)

Trenti, Michele; van der Marel, Roeland

2013-11-01

It is widely believed that globular clusters evolve over many two-body relaxation times towards a state of energy equipartition, so that velocity dispersion scales with stellar mass as σ ∝ m-η with η = 0.5. We show here that this is incorrect, using a suite of direct N-body simulations with a variety of realistic initial mass functions and initial conditions. No simulated system ever reaches a state close to equipartition. Near the centre, the luminous main-sequence stars reach a maximum ηmax ≈ 0.15 ± 0.03. At large times, all radial bins convergence on an asymptotic value η∞ ≈ 0.08 ± 0.02. The development of this `partial equipartition' is strikingly similar across our simulations, despite the range of different initial conditions employed. Compact remnants tend to have higher η than main-sequence stars (but still η < 0.5), due to their steeper (evolved) mass function. The presence of an intermediate-mass black hole (IMBH) decreases η, consistent with our previous findings of a quenching of mass segregation under these conditions. All these results can be understood as a consequence of the Spitzer instability for two-component systems, extended by Vishniac to a continuous mass spectrum. Mass segregation (the tendency of heavier stars to sink towards the core) has often been studied observationally, but energy equipartition has not. Due to the advent of high-quality proper motion data sets from the Hubble Space Telescope, it is now possible to measure η for real clusters. Detailed data-model comparisons open up a new observational window on globular cluster dynamics and evolution. A first comparison of our simulations to observations of Omega Cen yields good agreement, supporting the view that globular clusters are not generally in energy equipartition. Modelling techniques that assume equipartition by construction (e.g. multi-mass Michie-King models) are approximate at best.

Adaptive Automation Design and Implementation

DTIC Science & Technology

2015-09-17

Study : Space Navigator This section demonstrates the player modeling paradigm, focusing specifically on the response generation section of the player ...human-machine system, a real-time player modeling framework for imitating a specific person’s task performance, and the Adaptive Automation System...Model . . . . . . . . . . . . . . . . . . . . . . . 13 Clustering-Based Real-Time Player Modeling . . . . . . . . . . . . . . . . . . . . . . 15 An

Evolution of phenotypic clusters through competition and local adaptation along an environmental gradient.

PubMed

Leimar, Olof; Doebeli, Michael; Dieckmann, Ulf

2008-04-01

We have analyzed the evolution of a quantitative trait in populations that are spatially extended along an environmental gradient, with gene flow between nearby locations. In the absence of competition, there is stabilizing selection toward a locally best-adapted trait that changes gradually along the gradient. According to traditional ideas, gradual spatial variation in environmental conditions is expected to lead to gradual variation in the evolved trait. A contrasting possibility is that the trait distribution instead breaks up into discrete clusters. Doebeli and Dieckmann (2003) argued that competition acting locally in trait space and geographical space can promote such clustering. We have investigated this possibility using deterministic population dynamics for asexual populations, analyzing our model numerically and through an analytical approximation. We examined how the evolution of clusters is affected by the shape of competition kernels, by the presence of Allee effects, and by the strength of gene flow along the gradient. For certain parameter ranges clustering was a robust outcome, and for other ranges there was no clustering. Our analysis shows that the shape of competition kernels is important for clustering: the sign structure of the Fourier transform of a competition kernel determines whether the kernel promotes clustering. Also, we found that Allee effects promote clustering, whereas gene flow can have a counteracting influence. In line with earlier findings, we could demonstrate that phenotypic clustering was favored by gradients of intermediate slope.

Deciphering the underlying mechanisms of Diesun Miaofang in traumatic injury from a systems pharmacology perspective

PubMed Central

ZHENG, CHUN-SONG; FU, CHANG-LONG; PAN, CAI-BIN; BAO, HONG-JUAN; CHEN, XING-QIANG; YE, HONG-ZHI; YE, JIN-XIA; WU, GUANG-WEN; LI, XI-HAI; XU, HUI-FENG; XU, XIAO-JIE; LIU, XIAN-XIANG

2015-01-01

Diesun Miaofang (DSMF) is a traditional herbal formula, which has been reported to activate blood, remove stasis, promote qi circulation and relieve pain. DSMF holds a great promise for the treatment of traumatic injury in an integrative and holistic manner. However, its underlying mechanisms remain to be elucidated. In the present study, a systems pharmacology model, which integrated cluster ligands, human intestinal absorption and aqueous solution prediction, chemical space mapping, molecular docking and network pharmacology techniques were used. The compounds from DSMF were diverse in the clusters and chemical space. The majority of the compounds exhibited drug-like properties. A total of 59 compounds were identified to interact with 16 potential targets. In the herb-compound-target network, the majority of compounds acted on only one target; however, a small number of compounds acted on a large number of targets, up to a maximum of 12. The comparison of key topological properties in compound-target networks associated with the above efficacy intuitively demonstrated that potential active compounds possessed diverse functions. These results successfully explained the polypharmcological mechanism underlying the efficiency of DSMF for the treatment of traumatic injury as well as provided insight into potential novel therapeutic strategies for traumatic injury from herbal medicine. PMID:25891262

Theta and Alpha Oscillations Are Traveling Waves in the Human Neocortex.

PubMed

Zhang, Honghui; Watrous, Andrew J; Patel, Ansh; Jacobs, Joshua

2018-06-01

Human cognition requires the coordination of neural activity across widespread brain networks. Here, we describe a new mechanism for large-scale coordination in the human brain: traveling waves of theta and alpha oscillations. Examining direct brain recordings from neurosurgical patients performing a memory task, we found contiguous clusters of cortex in individual patients with oscillations at specific frequencies within 2 to 15 Hz. These oscillatory clusters displayed spatial phase gradients, indicating that they formed traveling waves that propagated at ∼0.25-0.75 m/s. Traveling waves were relevant behaviorally because their propagation correlated with task events and was more consistent when subjects performed the task well. Human traveling theta and alpha waves can be modeled by a network of coupled oscillators because the direction of wave propagation correlated with the spatial orientation of local frequency gradients. Our findings suggest that oscillations support brain connectivity by organizing neural processes across space and time. Copyright © 2018 Elsevier Inc. All rights reserved.

Performance Characterization of Global Address Space Applications: A Case Study with NWChem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammond, Jeffrey R.; Krishnamoorthy, Sriram; Shende, Sameer

The use of global address space languages and one-sided communication for complex applications is gaining attention in the parallel computing community. However, lack of good evaluative methods to observe multiple levels of performance makes it difficult to isolate the cause of performance deficiencies and to understand the fundamental limitations of system and application design for future improvement. NWChem is a popular computational chemistry package which depends on the Global Arrays/ ARMCI suite for partitioned global address space functionality to deliver high-end molecular modeling capabilities. A workload characterization methodology was developed to support NWChem performance engineering on large-scale parallel platforms. Themore » research involved both the integration of performance instrumentation and measurement in the NWChem software, as well as the analysis of one-sided communication performance in the context of NWChem workloads. Scaling studies were conducted for NWChem on Blue Gene/P and on two large-scale clusters using different generation Infiniband interconnects and x86 processors. The performance analysis and results show how subtle changes in the runtime parameters related to the communication subsystem could have significant impact on performance behavior. The tool has successfully identified several algorithmic bottlenecks which are already being tackled by computational chemists to improve NWChem performance.« less

Analysis of EEG-fMRI data in focal epilepsy based on automated spike classification and Signal Space Projection.

PubMed

Liston, Adam D; De Munck, Jan C; Hamandi, Khalid; Laufs, Helmut; Ossenblok, Pauly; Duncan, John S; Lemieux, Louis

2006-07-01

Simultaneous acquisition of EEG and fMRI data enables the investigation of the hemodynamic correlates of interictal epileptiform discharges (IEDs) during the resting state in patients with epilepsy. This paper addresses two issues: (1) the semi-automation of IED classification in statistical modelling for fMRI analysis and (2) the improvement of IED detection to increase experimental fMRI efficiency. For patients with multiple IED generators, sensitivity to IED-correlated BOLD signal changes can be improved when the fMRI analysis model distinguishes between IEDs of differing morphology and field. In an attempt to reduce the subjectivity of visual IED classification, we implemented a semi-automated system, based on the spatio-temporal clustering of EEG events. We illustrate the technique's usefulness using EEG-fMRI data from a subject with focal epilepsy in whom 202 IEDs were visually identified and then clustered semi-automatically into four clusters. Each cluster of IEDs was modelled separately for the purpose of fMRI analysis. This revealed IED-correlated BOLD activations in distinct regions corresponding to three different IED categories. In a second step, Signal Space Projection (SSP) was used to project the scalp EEG onto the dipoles corresponding to each IED cluster. This resulted in 123 previously unrecognised IEDs, the inclusion of which, in the General Linear Model (GLM), increased the experimental efficiency as reflected by significant BOLD activations. We have also shown that the detection of extra IEDs is robust in the face of fluctuations in the set of visually detected IEDs. We conclude that automated IED classification can result in more objective fMRI models of IEDs and significantly increased sensitivity.

First assembly times and equilibration in stochastic coagulation-fragmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

D’Orsogna, Maria R.; Department of Mathematics, CSUN, Los Angeles, California 91330-8313; Lei, Qi

2015-07-07

We develop a fully stochastic theory for coagulation and fragmentation (CF) in a finite system with a maximum cluster size constraint. The process is modeled using a high-dimensional master equation for the probabilities of cluster configurations. For certain realizations of total mass and maximum cluster sizes, we find exact analytical results for the expected equilibrium cluster distributions. If coagulation is fast relative to fragmentation and if the total system mass is indivisible by the mass of the largest allowed cluster, we find a mean cluster-size distribution that is strikingly broader than that predicted by the corresponding mass-action equations. Combinations ofmore » total mass and maximum cluster size under which equilibration is accelerated, eluding late-stage coarsening, are also delineated. Finally, we compute the mean time it takes particles to first assemble into a maximum-sized cluster. Through careful state-space enumeration, the scaling of mean assembly times is derived for all combinations of total mass and maximum cluster size. We find that CF accelerates assembly relative to monomer kinetic only in special cases. All of our results hold in the infinite system limit and can be only derived from a high-dimensional discrete stochastic model, highlighting how classical mass-action models of self-assembly can fail.« less

Images From Hubbles's ACS Tell A Tale Of Two Record-Breaking Galaxy Clusters

NASA Astrophysics Data System (ADS)

2004-01-01

Looking back in time nearly 9 billion years, an international team of astronomers found mature galaxies in a young universe. The galaxies are members of a cluster of galaxies that existed when the universe was only 5 billion years old, or about 35 percent of its present age. This compelling evidence that galaxies must have started forming just after the big bang was bolstered by observations made by the same team of astronomers when they peered even farther back in time. The team found embryonic galaxies a mere 1.5 billion years after the birth of the cosmos, or 10 percent of the universe's present age. The "baby galaxies" reside in a still-developing cluster, the most distant proto-cluster ever found. The Advanced Camera for Surveys (ACS) aboard NASA's Hubble Space Telescope was used to make observations of the massive cluster, RDCS 1252.9-2927, and the proto-cluster, TN J1338-1942. Observations by NASA's Chandra X-ray Observatory yielded the mass and heavy element content of RDCS 1252, the most massive known cluster for that epoch. These observations are part of a coordinated effort by the ACS science team to track the formation and evolution of clusters of galaxies over a broad range of cosmic time. The ACS was built especially for studies of such distant objects. These findings further support observations and theories that galaxies formed relatively early in the history of the cosmos. The existence of such massive clusters in the early universe agrees with a cosmological model wherein clusters form from the merger of many sub-clusters in a universe dominated by cold dark matter. The precise nature of cold dark matter, however, is still not known. The first Hubble study estimated that galaxies in RDCS 1252 formed the bulk of their stars more than 11 billion years ago (at redshifts greater than 3). The results were published in the Oct. 20, 2003 issue of the Astrophysical Journal. The paper's lead author is John Blakeslee of the Johns Hopkins University in Baltimore, Md. Optical Image of RDCS 1252.9-2927 HST Optical Image of RDCS 1252.9-2927 The second Hubble study uncovered, for the first time, a proto-cluster of "infant galaxies" that existed more than 12 billion years ago (at redshift 4.1). These galaxies are so young that astronomers can still see a flurry of stars forming within them. The galaxies are grouped around one large galaxy. These results will be published in the Jan. 1, 2004 issue of Nature. The paper's lead author is George Miley of Leiden Observatory in the Netherlands. "Until recently people didn't think that clusters existed when the universe was only about 5 billion years old," Blakeslee explained. "Even if there were such clusters," Miley added, "until recently astronomers thought it was almost impossible to find clusters that existed 8 billion years ago. In fact, no one really knew when clustering began. Now we can witness it." Both studies led the astronomers to conclude that these systems are the progenitors of the galaxy clusters seen today. "The cluster RDCS 1252 looks like a present-day cluster," said Marc Postman of the Space Telescope Science Institute in Baltimore, Md., and co-author of both research papers. "In fact, if you were to put it next to a present-day cluster, you wouldn't know which is which." A Tale of Two Clusters How can galaxies grow so fast after the big bang? "It is a case of the rich getting richer," Blakeslee said. "These clusters grew quickly because they are located in very dense regions, so there is enough material to build up the member galaxies very fast." This idea is strengthened by X-ray observations of the massive cluster RDCS 1252. Chandra and the European Space Agency's XMM-Newton provided astronomers with the most accurate measurements to date of the properties of an enormous cloud of hot gas that pervades the massive cluster. This 160-million-degree Fahrenheit (70-million-degree Celsius) gas is a reservoir of most of the heavy elements in the cluster and an accurate tracer of its total mass. A paper by Piero Rosati of the European Southern Observatory (ESO) and colleagues that presents the X-ray observations of RDCS 1252 will be published in January 2004 in the Astronomical Journal. "Chandra's sharp vision resolved the shape of the hot gas halo and showed that RDCS 1252 is very mature for its age," said Rosati, who discovered the cluster with the ROSAT X-ray telescope. RDCS 1252 may contain many thousands of galaxies. Most of these galaxies, however, are too faint to detect. But the powerful "eyes" of the ACS pinpointed several hundred of them. Observations using ESO's Very Large Telescope (VLT) provided a precise measurement of the distance to the cluster. The ACS enabled the researchers to accurately determine the shapes and colors of the 100 galaxies, providing information on the ages of the stars residing in them. The ACS team estimated that most of the stars in the cluster were already formed when the universe was about 2 billion years old. X-ray observations, furthermore, showed that 5 billion years after the big bang the surrounding hot gas had been enriched with heavy elements from these stars and had been swept away from the galaxies. If most of the galaxies in RDCS 1252 have reached maturity and are settling into a quiet adulthood, the forming galaxies in the distant proto-cluster are in their energetic, unruly youth. The proto-cluster TN J1338 contains a massive embryonic galaxy surrounded by smaller developing galaxies, which look like dots in the Hubble image. The dominant galaxy is producing spectacular radio-emitting jets, fueled by a supermassive black hole deep within the galaxy's nucleus. Interaction between these jets and the gas can stimulate a torrent of star birth. The energetic radio galaxy's discovery by radio telescopes prompted astronomers to hunt for the smaller galaxies that make up the bulk of the cluster. "Massive clusters are the cities of the universe, and the radio galaxies within them are the smokestacks we can use for finding them when they are just beginning to form," Miley said. The two findings underscore the power of combining observations from many different telescopes that provided views of the distant universe in a range of wavelengths. Hubble's advanced camera provided critical information on the structure of both distant galaxy clusters. Chandra's and XMM-Newton's X-ray vision furnished the essential measurements of the primordial gas in which the galaxies in RDCS 1252 are embedded, and accurate estimates of the total mass contained within that cluster. Large ground-based telescopes, like the VLT, provided precise measurements of the distance of both clusters as well as the chemical composition of the galaxies in them. The ACS team is conducting further observations of distant clusters to solidify our understanding of how these young clusters and their galaxies evolve into the shape of things seen today. Their planned observations include using near-infrared observations to analyze the star-formation rates in some of the target clusters, including RDCS 1252, to measure the cosmic history of star formation in these massive structures. The team is also searching the regions around several ultra-distant radio galaxies for additional examples of proto-clusters. The team's ultimate scientific goal is to establish a complete picture of cluster evolution beginning with the formation at the earliest epochs and detailing the evolution up to today. Electronic image files and additional information are available at http://hubblesite.org/newscenter/newsdesk/archive/releases/2004/01/ The Space Telescope Science Institute (STScI) is operated by the Association of Universities for Research in Astronomy, Inc. (AURA), for NASA, under contract with the Goddard Space Flight Center, Greenbelt, MD. The Hubble Space Telescope is a project of international cooperation between NASA and the European Space Agency (ESA).

NEW CONSTRAINTS ON A COMPLEX RELATION BETWEEN GLOBULAR CLUSTER COLORS AND ENVIRONMENT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Powalka, Mathieu; Lançon, Ariane; Puzia, Thomas H.

We present an analysis of high-quality photometry for globular clusters (GCs) in the Virgo cluster core region, based on data from the Next Generation Virgo Cluster Survey (NGVS) pilot field, and in the Milky Way (MW), based on Very Large Telescope/X-Shooter spectrophotometry. We find significant discrepancies in color–color diagrams between sub-samples from different environments, confirming that the environment has a strong influence on the integrated colors of GCs. GC color distributions along a single color are not sufficient to capture the differences we observe in color–color space. While the average photometric colors become bluer with increasing radial distance to themore » cD galaxy M87, we also find a relation between the environment and the slope and intercept of the color–color relations. A denser environment seems to produce a larger dynamic range in certain color indices. We argue that these results are not due solely to differential extinction, Initial Mass Function variations, calibration uncertainties, or overall age/metallicity variations. We therefore suggest that the relation between the environment and GC colors is, at least in part, due to chemical abundance variations, which affect stellar spectra and stellar evolution tracks. Our results demonstrate that stellar population diagnostics derived from model predictions which are calibrated on one particular sample of GCs may not be appropriate for all extragalactic GCs. These results advocate a more complex model of the assembly history of GC systems in massive galaxies that goes beyond the simple bimodality found in previous decades.« less

Magnetic islands produced by reconnection in large current layers: A statistical approach to modeling at global scales

NASA Astrophysics Data System (ADS)

Fermo, Raymond Luis Lachica

2011-12-01

Magnetic reconnection is a process responsible for the conversion of magnetic energy into plasma flows in laboratory, space, and astrophysical plasmas. A product of reconnection, magnetic islands have been observed in long current layers for various space plasmas, including the magnetopause, the magnetotail, and the solar corona. In this thesis, a statistical model is developed for the dynamics of magnetic islands in very large current layers, for which conventional plasma simulations prove inadequate. An island distribution function f characterizes islands by the flux they contain psi and the area they enclose A. An integro-differential evolution equation for f describes their creation at small scales, growth due to quasi-steady reconnection, convection along the current sheet, and their coalescence with one another. The steady-state solution of the evolution equation predicts a distribution of islands in which the signature of island merging is an asymmetry in psi-- r phase space. A Hall MHD (magnetohydrodynamic) simulation of a very long current sheet with large numbers of magnetic islands is used to explore their dynamics, specifically their growth via two distinct mechanisms: quasi-steady reconnection and merging. The results of the simulation enable validation of the statistical model and benchmarking of its parameters. A PIC (particle-in-cell) simulation investigates how secondary islands form in guide field reconnection, revealing that they are born at electron skin depth scales not as islands from the tearing instability but as vortices from a flow instability. A database of 1,098 flux transfer events (FTEs) observed by Cluster between 2001 and 2003 compares favorably with the model's predictions, and also suggests island merging plays a significant role in the magnetopause. Consequently, the magnetopause is likely populated by many FTEs too small to be recognized by spacecraft instrumentation. The results of this research suggest that a complete theory of reconnection in large current sheets should account for the disparate separation of scales---from the kinetic scales at which islands are produced to the macroscale objects observed in the systems in question.