Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks

DOE PAGES

Gu, Yi; Wu, Qishi; Rao, Nageswara S. V.

2010-01-01

Many complex sensor network applications require deploying a large number of inexpensive and small sensors in a vast geographical region to achieve quality through quantity. Hierarchical clustering is generally considered as an efficient and scalable way to facilitate the management and operation of such large-scale networks and minimize the total energy consumption for prolonged lifetime. Judicious selection of cluster heads for data integration and communication is critical to the success of applications based on hierarchical sensor networks organized as layered clusters. We investigate the problem of selecting sensor nodes in a predeployed sensor network to be the cluster heads tomore » minimize the total energy needed for data gathering. We rigorously derive an analytical formula to optimize the number of cluster heads in sensor networks under uniform node distribution, and propose a Distance-based Crowdedness Clustering algorithm to determine the cluster heads in sensor networks under general node distribution. The results from an extensive set of experiments on a large number of simulated sensor networks illustrate the performance superiority of the proposed solution over the clustering schemes based on k -means algorithm.« less

Large scale structure in universes dominated by cold dark matter

NASA Technical Reports Server (NTRS)

Bond, J. Richard

1986-01-01

The theory of Gaussian random density field peaks is applied to a numerical study of the large-scale structure developing from adiabatic fluctuations in models of biased galaxy formation in universes with Omega = 1, h = 0.5 dominated by cold dark matter (CDM). The angular anisotropy of the cross-correlation function demonstrates that the far-field regions of cluster-scale peaks are asymmetric, as recent observations indicate. These regions will generate pancakes or filaments upon collapse. One-dimensional singularities in the large-scale bulk flow should arise in these CDM models, appearing as pancakes in position space. They are too rare to explain the CfA bubble walls, but pancakes that are just turning around now are sufficiently abundant and would appear to be thin walls normal to the line of sight in redshift space. Large scale streaming velocities are significantly smaller than recent observations indicate. To explain the reported 700 km/s coherent motions, mass must be significantly more clustered than galaxies with a biasing factor of less than 0.4 and a nonlinear redshift at cluster scales greater than one for both massive neutrino and cold models.

Scaling of cluster growth for coagulating active particles

NASA Astrophysics Data System (ADS)

Cremer, Peet; Löwen, Hartmut

2014-02-01

Cluster growth in a coagulating system of active particles (such as microswimmers in a solvent) is studied by theory and simulation. In contrast to passive systems, the net velocity of a cluster can have various scalings dependent on the propulsion mechanism and alignment of individual particles. Additionally, the persistence length of the cluster trajectory typically increases with size. As a consequence, a growing cluster collects neighboring particles in a very efficient way and thus amplifies its growth further. This results in unusual large growth exponents for the scaling of the cluster size with time and, for certain conditions, even leads to "explosive" cluster growth where the cluster becomes macroscopic in a finite amount of time.

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

PubMed Central

Azad, Ariful; Ouzounis, Christos A; Kyrpides, Nikos C; Buluç, Aydin

2018-01-01

Abstract Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times and memory demands. Here, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ∼70 million nodes with ∼68 billion edges in ∼2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license. PMID:29315405

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

DOE PAGES

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.; ...

2018-01-05

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

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

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

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

Ben-Naim, Eli; Krapivsky, Paul

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

The Origin of Clusters and Large-Scale Structures: Panoramic View of the High-z Universe

NASA Astrophysics Data System (ADS)

Ouchi, Masami

We will report results of our on-going survey for proto-clusters and large-scale structures at z=3-6. We carried out very wide and deep optical imaging down to i=27 for a 1 deg^2 field of the Subaru/XMM Deep Field with 8.2m Subaru Telescope. We obtain maps of the Universe traced by ~1,000 Ly-a galaxies at z=3, 4, and 6 and by ~10,000 Lyman break galaxies at z=3-6. These cosmic maps have a transverse dimension of ~150 Mpc x 150 Mpc in comoving units at these redshifts, and provide us, for the first time, a panoramic view of the high-z Universe from the scales of galaxies, clusters to large-scale structures. Major results and implications will be presented in our talk. (Part of this work is subject to press embargo.)

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

Mapping Dark Matter in Simulated Galaxy Clusters

NASA Astrophysics Data System (ADS)

Bowyer, Rachel

2018-01-01

Galaxy clusters are the most massive bound objects in the Universe with most of their mass being dark matter. Cosmological simulations of structure formation show that clusters are embedded in a cosmic web of dark matter filaments and large scale structure. It is thought that these filaments are found preferentially close to the long axes of clusters. We extract galaxy clusters from the simulations "cosmo-OWLS" in order to study their properties directly and also to infer their properties from weak gravitational lensing signatures. We investigate various stacking procedures to enhance the signal of the filaments and large scale structure surrounding the clusters to better understand how the filaments of the cosmic web connect with galaxy clusters. This project was supported in part by the NSF REU grant AST-1358980 and by the Nantucket Maria Mitchell Association.

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

Kim, Junghyun; Gangwon, Jo; Jaehoon, Jung

Applications written solely in OpenCL or CUDA cannot execute on a cluster as a whole. Most previous approaches that extend these programming models to clusters are based on a common idea: designating a centralized host node and coordinating the other nodes with the host for computation. However, the centralized host node is a serious performance bottleneck when the number of nodes is large. In this paper, we propose a scalable and distributed OpenCL framework called SnuCL-D for large-scale clusters. SnuCL-D's remote device virtualization provides an OpenCL application with an illusion that all compute devices in a cluster are confined inmore » a single node. To reduce the amount of control-message and data communication between nodes, SnuCL-D replicates the OpenCL host program execution and data in each node. We also propose a new OpenCL host API function and a queueing optimization technique that significantly reduce the overhead incurred by the previous centralized approaches. To show the effectiveness of SnuCL-D, we evaluate SnuCL-D with a microbenchmark and eleven benchmark applications on a large-scale CPU cluster and a medium-scale GPU cluster.« less

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

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.

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,…

Tracing Large Scale Structure with a Redshift Survey of Rich Clusters of Galaxies

NASA Astrophysics Data System (ADS)

Batuski, D.; Slinglend, K.; Haase, S.; Hill, J. M.

1993-12-01

Rich clusters of galaxies from Abell's catalog show evidence of structure on scales of 100 Mpc and hold promise of confirming the existence of structure in the more immediate universe on scales corresponding to COBE results (i.e., on the order of 10% or more of the horizon size of the universe). However, most Abell clusters do not as yet have measured redshifts (or, in the case of most low redshift clusters, have only one or two galaxies measured), so present knowledge of their three dimensional distribution has quite large uncertainties. The shortage of measured redshifts for these clusters may also mask a problem of projection effects corrupting the membership counts for the clusters, perhaps even to the point of spurious identifications of some of the clusters themselves. Our approach in this effort has been to use the MX multifiber spectrometer to measure redshifts of at least ten galaxies in each of about 80 Abell cluster fields with richness class R>= 1 and mag10 <= 16.8. This work will result in a somewhat deeper, much more complete (and reliable) sample of positions of rich clusters. Our primary use for the sample is for two-point correlation and other studies of the large scale structure traced by these clusters. We are also obtaining enough redshifts per cluster so that a much better sample of reliable cluster velocity dispersions will be available for other studies of cluster properties. To date, we have collected such data for 40 clusters, and for most of them, we have seven or more cluster members with redshifts, allowing for reliable velocity dispersion calculations. Velocity histograms for several interesting cluster fields are presented, along with summary tables of cluster redshift results. Also, with 10 or more redshifts in most of our cluster fields (30({') } square, just about an `Abell diameter' at z ~ 0.1) we have investigated the extent of projection effects within the Abell catalog in an effort to quantify and understand how this may effect the Abell sample.

Galaxy clusters in local Universe simulations without density constraints: a long uphill struggle

NASA Astrophysics Data System (ADS)

Sorce, Jenny G.

2018-06-01

Galaxy clusters are excellent cosmological probes provided that their formation and evolution within the large scale environment are precisely understood. Therefore studies with simulated galaxy clusters have flourished. However detailed comparisons between simulated and observed clusters and their population - the galaxies - are complicated by the diversity of clusters and their surrounding environment. An original way initiated by Bertschinger as early as 1987, to legitimize the one-to-one comparison exercise down to the details, is to produce simulations constrained to resemble the cluster under study within its large scale environment. Subsequently several methods have emerged to produce simulations that look like the local Universe. This paper highlights one of these methods and its essential steps to get simulations that not only resemble the local Large Scale Structure but also that host the local clusters. It includes a new modeling of the radial peculiar velocity uncertainties to remove the observed correlation between the decreases of the simulated cluster masses and of the amount of data used as constraints with the distance from us. This method has the particularity to use solely radial peculiar velocities as constraints: no additional density constraints are required to get local cluster simulacra. The new resulting simulations host dark matter halos that match the most prominent local clusters such as Coma. Zoom-in simulations of the latter and of a volume larger than the 30h-1 Mpc radius inner sphere become now possible to study local clusters and their effects. Mapping the local Sunyaev-Zel'dovich and Sachs-Wolfe effects can follow.

Cross-correlating the γ-ray Sky with Catalogs of Galaxy Clusters

NASA Astrophysics Data System (ADS)

Branchini, Enzo; Camera, Stefano; Cuoco, Alessandro; Fornengo, Nicolao; Regis, Marco; Viel, Matteo; Xia, Jun-Qing

2017-01-01

We report the detection of a cross-correlation signal between Fermi Large Area Telescope diffuse γ-ray maps and catalogs of clusters. In our analysis, we considered three different catalogs: WHL12, redMaPPer, and PlanckSZ. They all show a positive correlation with different amplitudes, related to the average mass of the objects in each catalog, which also sets the catalog bias. The signal detection is confirmed by the results of a stacking analysis. The cross-correlation signal extends to rather large angular scales, around 1°, that correspond, at the typical redshift of the clusters in these catalogs, to a few to tens of megaparsecs, I.e., the typical scale-length of the large-scale structures in the universe. Most likely this signal is contributed by the cumulative emission from active galactic nuclei (AGNs) associated with the filamentary structures that converge toward the high peaks of the matter density field in which galaxy clusters reside. In addition, our analysis reveals the presence of a second component, more compact in size and compatible with a point-like emission from within individual clusters. At present, we cannot distinguish between the two most likely interpretations for such a signal, I.e., whether it is produced by AGNs inside clusters or if it is a diffuse γ-ray emission from the intracluster medium. We argue that this latter, intriguing, hypothesis might be tested by applying this technique to a low-redshift large-mass cluster sample.

Merging Clusters, Cluster Outskirts, and Large Scale Filaments

NASA Astrophysics Data System (ADS)

Randall, Scott; Alvarez, Gabriella; Bulbul, Esra; Jones, Christine; Forman, William; Su, Yuanyuan; Miller, Eric D.; Bourdin, Herve; Scott Randall

2018-01-01

Recent X-ray observations of the outskirts of clusters show that entropy profiles of the intracluster medium (ICM) generally flatten and lie below what is expected from purely gravitational structure formation near the cluster's virial radius. Possible explanations include electron/ion non-equilibrium, accretion shocks that weaken during cluster formation, and the presence of unresolved cool gas clumps. Some of these mechanisms are expected to correlate with large scale structure (LSS), such that the entropy is lower in regions where the ICM interfaces with LSS filaments and, presumably, the warm-hot intergalactic medium (WHIM). Major, binary cluster mergers are expected to take place at the intersection of LSS filaments, with the merger axis initially oriented along a filament. We present results from deep X-ray observations of the virialization regions of binary, early-stage merging clusters, including a possible detection of the dense end of the WHIM along a LSS filament.

Effect of small versus large clusters of fish school on the yield of a purse-seine small pelagic fishery including a marine protected area.

PubMed

Hieu, Nguyen Trong; Brochier, Timothée; Tri, Nguyen-Huu; Auger, Pierre; Brehmer, Patrice

2014-09-01

We consider a fishery model with two sites: (1) a marine protected area (MPA) where fishing is prohibited and (2) an area where the fish population is harvested. We assume that fish can migrate from MPA to fishing area at a very fast time scale and fish spatial organisation can change from small to large clusters of school at a fast time scale. The growth of the fish population and the catch are assumed to occur at a slow time scale. The complete model is a system of five ordinary differential equations with three time scales. We take advantage of the time scales using aggregation of variables methods to derive a reduced model governing the total fish density and fishing effort at the slow time scale. We analyze this aggregated model and show that under some conditions, there exists an equilibrium corresponding to a sustainable fishery. Our results suggest that in small pelagic fisheries the yield is maximum for a fish population distributed among both small and large clusters of school.

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.

Kinetics of Aggregation with Choice

DOE PAGES

Ben-Naim, Eli; Krapivsky, Paul

2016-12-01

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

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 dynamics and evolution of clusters of galaxies

NASA Technical Reports Server (NTRS)

Geller, Margaret; Huchra, John P.

1987-01-01

Research was undertaken to produce a coherent picture of the formation and evolution of large-scale structures in the universe. The program is divided into projects which examine four areas: the relationship between individual galaxies and their environment; the structure and evolution of individual rich clusters of galaxies; the nature of superclusters; and the large-scale distribution of individual galaxies. A brief review of results in each area is provided.

N-body simulations of gravitational redshifts and other relativistic distortions of galaxy clustering

NASA Astrophysics Data System (ADS)

Zhu, Hongyu; Alam, Shadab; Croft, Rupert A. C.; Ho, Shirley; Giusarma, Elena

2017-10-01

Large redshift surveys of galaxies and clusters are providing the first opportunities to search for distortions in the observed pattern of large-scale structure due to such effects as gravitational redshift. We focus on non-linear scales and apply a quasi-Newtonian approach using N-body simulations to predict the small asymmetries in the cross-correlation function of two galaxy different populations. Following recent work by Bonvin et al., Zhao and Peacock and Kaiser on galaxy clusters, we include effects which enter at the same order as gravitational redshift: the transverse Doppler effect, light-cone effects, relativistic beaming, luminosity distance perturbation and wide-angle effects. We find that all these effects cause asymmetries in the cross-correlation functions. Quantifying these asymmetries, we find that the total effect is dominated by the gravitational redshift and luminosity distance perturbation at small and large scales, respectively. By adding additional subresolution modelling of galaxy structure to the large-scale structure information, we find that the signal is significantly increased, indicating that structure on the smallest scales is important and should be included. We report on comparison of our simulation results with measurements from the SDSS/BOSS galaxy redshift survey in a companion paper.

A link between nonlinear self-organization and dissipation in drift-wave turbulence

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

Manz, P.; Birkenmeier, G.; Stroth, U.

Structure formation and self-organization in two-dimensional drift-wave turbulence show up in many different faces. Fluctuation data from a magnetized plasma are analyzed and three mechanisms transferring kinetic energy to large-scale structures are identified. Beside the common vortex merger, clustering of vortices constituting a large-scale strain field and vortex thinning, where due to the interactions of vortices of different scales larger vortices are amplified by the smaller ones, are observed. The vortex thinning mechanism appears to be the most efficient one to generate large scale structures in drift-wave turbulence. Vortex merging as well as vortex clustering are accompanied by strong energymore » transfer to small-scale noncoherent fluctuations (dissipation) balancing the negative entropy generation due to the self-organization process.« less

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation Among Gene Classes from Large-Scale Expression Data

NASA Technical Reports Server (NTRS)

Mjolsness, Eric; Castano, Rebecca; Mann, Tobias; Wold, Barbara

2000-01-01

We provide preliminary evidence that existing algorithms for inferring small-scale gene regulation networks from gene expression data can be adapted to large-scale gene expression data coming from hybridization microarrays. The essential steps are (I) clustering many genes by their expression time-course data into a minimal set of clusters of co-expressed genes, (2) theoretically modeling the various conditions under which the time-courses are measured using a continuous-time analog recurrent neural network for the cluster mean time-courses, (3) fitting such a regulatory model to the cluster mean time courses by simulated annealing with weight decay, and (4) analysing several such fits for commonalities in the circuit parameter sets including the connection matrices. This procedure can be used to assess the adequacy of existing and future gene expression time-course data sets for determining transcriptional regulatory relationships such as coregulation.

STAR FORMATION AND SUPERCLUSTER ENVIRONMENT OF 107 NEARBY GALAXY CLUSTERS

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

Cohen, Seth A.; Hickox, Ryan C.; Wegner, Gary A.

We analyze the relationship between star formation (SF), substructure, and supercluster environment in a sample of 107 nearby galaxy clusters using data from the Sloan Digital Sky Survey. Previous works have investigated the relationships between SF and cluster substructure, and cluster substructure and supercluster environment, but definitive conclusions relating all three of these variables has remained elusive. We find an inverse relationship between cluster SF fraction ( f {sub SF}) and supercluster environment density, calculated using the Galaxy luminosity density field at a smoothing length of 8 h {sup −1} Mpc (D8). The slope of f {sub SF} versus D8more » is −0.008 ± 0.002. The f {sub SF} of clusters located in low-density large-scale environments, 0.244 ± 0.011, is higher than for clusters located in high-density supercluster cores, 0.202 ± 0.014. We also divide superclusters, according to their morphology, into filament- and spider-type systems. The inverse relationship between cluster f {sub SF} and large-scale density is dominated by filament- rather than spider-type superclusters. In high-density cores of superclusters, we find a higher f {sub SF} in spider-type superclusters, 0.229 ± 0.016, than in filament-type superclusters, 0.166 ± 0.019. Using principal component analysis, we confirm these results and the direct correlation between cluster substructure and SF. These results indicate that cluster SF is affected by both the dynamical age of the cluster (younger systems exhibit higher amounts of SF); the large-scale density of the supercluster environment (high-density core regions exhibit lower amounts of SF); and supercluster morphology (spider-type superclusters exhibit higher amounts of SF at high densities).« less

Megatux

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

2012-09-25

The Megatux platform enables the emulation of large scale (multi-million node) distributed systems. In particular, it allows for the emulation of large-scale networks interconnecting a very large number of emulated computer systems. It does this by leveraging virtualization and associated technologies to allow hundreds of virtual computers to be hosted on a single moderately sized server or workstation. Virtualization technology provided by modern processors allows for multiple guest OSs to run at the same time, sharing the hardware resources. The Megatux platform can be deployed on a single PC, a small cluster of a few boxes or a large clustermore » of computers. With a modest cluster, the Megatux platform can emulate complex organizational networks. By using virtualization, we emulate the hardware, but run actual software enabling large scale without sacrificing fidelity.« less

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

CROSS-CORRELATING THE γ-RAY SKY WITH CATALOGS OF GALAXY CLUSTERS

DOE PAGES

Branchini, Enzo; Camera, Stefano; Cuoco, Alessandro; ...

2017-01-18

In this article, we report the detection of a cross-correlation signal between Fermi Large Area Telescope diffuse γ-ray maps and catalogs of clusters. In our analysis, we considered three different catalogs: WHL12, redMaPPer, and PlanckSZ. They all show a positive correlation with different amplitudes, related to the average mass of the objects in each catalog, which also sets the catalog bias. The signal detection is confirmed by the results of a stacking analysis. The cross-correlation signal extends to rather large angular scales, around 1°, that correspond, at the typical redshift of the clusters in these catalogs, to a few tomore » tens of megaparsecs, i.e., the typical scale-length of the large-scale structures in the universe. Most likely this signal is contributed by the cumulative emission from active galactic nuclei (AGNs) associated with the filamentary structures that converge toward the high peaks of the matter density field in which galaxy clusters reside. In addition, our analysis reveals the presence of a second component, more compact in size and compatible with a point-like emission from within individual clusters. At present, we cannot distinguish between the two most likely interpretations for such a signal, i.e., whether it is produced by AGNs inside clusters or if it is a diffuse γ-ray emission from the intracluster medium. Lastly, we argue that this latter, intriguing, hypothesis might be tested by applying this technique to a low-redshift large-mass cluster sample.« less

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].

The properties of the disk system of globular clusters

NASA Technical Reports Server (NTRS)

Armandroff, Taft E.

1989-01-01

A large refined data sample is used to study the properties and origin of the disk system of globular clusters. A scale height for the disk cluster system of 800-1500 pc is found which is consistent with scale-height determinations for samples of field stars identified with the Galactic thick disk. A rotational velocity of 193 + or - 29 km/s and a line-of-sight velocity dispersion of 59 + or - 14 km/s have been found for the metal-rich clusters.

Enabling Diverse Software Stacks on Supercomputers using High Performance Virtual Clusters.

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

Younge, Andrew J.; Pedretti, Kevin; Grant, Ryan

While large-scale simulations have been the hallmark of the High Performance Computing (HPC) community for decades, Large Scale Data Analytics (LSDA) workloads are gaining attention within the scientific community not only as a processing component to large HPC simulations, but also as standalone scientific tools for knowledge discovery. With the path towards Exascale, new HPC runtime systems are also emerging in a way that differs from classical distributed com- puting models. However, system software for such capabilities on the latest extreme-scale DOE supercomputing needs to be enhanced to more appropriately support these types of emerging soft- ware ecosystems. In thismore » paper, we propose the use of Virtual Clusters on advanced supercomputing resources to enable systems to support not only HPC workloads, but also emerging big data stacks. Specifi- cally, we have deployed the KVM hypervisor within Cray's Compute Node Linux on a XC-series supercomputer testbed. We also use libvirt and QEMU to manage and provision VMs directly on compute nodes, leveraging Ethernet-over-Aries network emulation. To our knowledge, this is the first known use of KVM on a true MPP supercomputer. We investigate the overhead our solution using HPC benchmarks, both evaluating single-node performance as well as weak scaling of a 32-node virtual cluster. Overall, we find single node performance of our solution using KVM on a Cray is very efficient with near-native performance. However overhead increases by up to 20% as virtual cluster size increases, due to limitations of the Ethernet-over-Aries bridged network. Furthermore, we deploy Apache Spark with large data analysis workloads in a Virtual Cluster, ef- fectively demonstrating how diverse software ecosystems can be supported by High Performance Virtual Clusters.« less

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

Branchini, Enzo; Camera, Stefano; Cuoco, Alessandro

In this article, we report the detection of a cross-correlation signal between Fermi Large Area Telescope diffuse γ-ray maps and catalogs of clusters. In our analysis, we considered three different catalogs: WHL12, redMaPPer, and PlanckSZ. They all show a positive correlation with different amplitudes, related to the average mass of the objects in each catalog, which also sets the catalog bias. The signal detection is confirmed by the results of a stacking analysis. The cross-correlation signal extends to rather large angular scales, around 1°, that correspond, at the typical redshift of the clusters in these catalogs, to a few tomore » tens of megaparsecs, i.e., the typical scale-length of the large-scale structures in the universe. Most likely this signal is contributed by the cumulative emission from active galactic nuclei (AGNs) associated with the filamentary structures that converge toward the high peaks of the matter density field in which galaxy clusters reside. In addition, our analysis reveals the presence of a second component, more compact in size and compatible with a point-like emission from within individual clusters. At present, we cannot distinguish between the two most likely interpretations for such a signal, i.e., whether it is produced by AGNs inside clusters or if it is a diffuse γ-ray emission from the intracluster medium. Lastly, we argue that this latter, intriguing, hypothesis might be tested by applying this technique to a low-redshift large-mass cluster sample.« less

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

Branchini, Enzo; Camera, Stefano; Cuoco, Alessandro

We report the detection of a cross-correlation signal between Fermi Large Area Telescope diffuse γ -ray maps and catalogs of clusters. In our analysis, we considered three different catalogs: WHL12, redMaPPer, and PlanckSZ. They all show a positive correlation with different amplitudes, related to the average mass of the objects in each catalog, which also sets the catalog bias. The signal detection is confirmed by the results of a stacking analysis. The cross-correlation signal extends to rather large angular scales, around 1°, that correspond, at the typical redshift of the clusters in these catalogs, to a few to tens ofmore » megaparsecs, i.e., the typical scale-length of the large-scale structures in the universe. Most likely this signal is contributed by the cumulative emission from active galactic nuclei (AGNs) associated with the filamentary structures that converge toward the high peaks of the matter density field in which galaxy clusters reside. In addition, our analysis reveals the presence of a second component, more compact in size and compatible with a point-like emission from within individual clusters. At present, we cannot distinguish between the two most likely interpretations for such a signal, i.e., whether it is produced by AGNs inside clusters or if it is a diffuse γ -ray emission from the intracluster medium. We argue that this latter, intriguing, hypothesis might be tested by applying this technique to a low-redshift large-mass cluster sample.« less

Reconstruction of halo power spectrum from redshift-space galaxy distribution: cylinder-grouping method and halo exclusion effect

NASA Astrophysics Data System (ADS)

Okumura, Teppei; Takada, Masahiro; More, Surhud; Masaki, Shogo

2017-07-01

The peculiar velocity field measured by redshift-space distortions (RSD) in galaxy surveys provides a unique probe of the growth of large-scale structure. However, systematic effects arise when including satellite galaxies in the clustering analysis. Since satellite galaxies tend to reside in massive haloes with a greater halo bias, the inclusion boosts the clustering power. In addition, virial motions of the satellite galaxies cause a significant suppression of the clustering power due to non-linear RSD effects. We develop a novel method to recover the redshift-space power spectrum of haloes from the observed galaxy distribution by minimizing the contamination of satellite galaxies. The cylinder-grouping method (CGM) we study effectively excludes satellite galaxies from a galaxy sample. However, we find that this technique produces apparent anisotropies in the reconstructed halo distribution over all the scales which mimic RSD. On small scales, the apparent anisotropic clustering is caused by exclusion of haloes within the anisotropic cylinder used by the CGM. On large scales, the misidentification of different haloes in the large-scale structures, aligned along the line of sight, into the same CGM group causes the apparent anisotropic clustering via their cross-correlation with the CGM haloes. We construct an empirical model for the CGM halo power spectrum, which includes correction terms derived using the CGM window function at small scales as well as the linear matter power spectrum multiplied by a simple anisotropic function at large scales. We apply this model to a mock galaxy catalogue at z = 0.5, designed to resemble Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxies, and find that our model can predict both the monopole and quadrupole power spectra of the host haloes up to k < 0.5 {{h Mpc^{-1}}} to within 5 per cent.

Determination of bulk properties of tropical cloud clusters from large scale heat and moisture budgets, appendix B

NASA Technical Reports Server (NTRS)

Yanai, M.; Esbensen, S.; Chu, J.

1972-01-01

The bulk properties of tropical cloud clusters, as the vertical mass flux, the excess temperature, and moisture and the liquid water content of the clouds, are determined from a combination of the observed large-scale heat and moisture budgets over an area covering the cloud cluster, and a model of a cumulus ensemble which exchanges mass, heat, vapor and liquid water with the environment through entrainment and detrainment. The method also provides an understanding of how the environmental air is heated and moistened by the cumulus convection. An estimate of the average cloud cluster properties and the heat and moisture balance of the environment, obtained from 1956 Marshall Islands data, is presented.

On the linearity of tracer bias around voids

NASA Astrophysics Data System (ADS)

Pollina, Giorgia; Hamaus, Nico; Dolag, Klaus; Weller, Jochen; Baldi, Marco; Moscardini, Lauro

2017-07-01

The large-scale structure of the Universe can be observed only via luminous tracers of the dark matter. However, the clustering statistics of tracers are biased and depend on various properties, such as their host-halo mass and assembly history. On very large scales, this tracer bias results in a constant offset in the clustering amplitude, known as linear bias. Towards smaller non-linear scales, this is no longer the case and tracer bias becomes a complicated function of scale and time. We focus on tracer bias centred on cosmic voids, I.e. depressions of the density field that spatially dominate the Universe. We consider three types of tracers: galaxies, galaxy clusters and active galactic nuclei, extracted from the hydrodynamical simulation Magneticum Pathfinder. In contrast to common clustering statistics that focus on auto-correlations of tracers, we find that void-tracer cross-correlations are successfully described by a linear bias relation. The tracer-density profile of voids can thus be related to their matter-density profile by a single number. We show that it coincides with the linear tracer bias extracted from the large-scale auto-correlation function and expectations from theory, if sufficiently large voids are considered. For smaller voids we observe a shift towards higher values. This has important consequences on cosmological parameter inference, as the problem of unknown tracer bias is alleviated up to a constant number. The smallest scales in existing data sets become accessible to simpler models, providing numerous modes of the density field that have been disregarded so far, but may help to further reduce statistical errors in constraining cosmology.

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.

Exploratory Item Classification Via Spectral Graph Clustering

PubMed Central

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2017-01-01

Large-scale assessments are supported by a large item pool. An important task in test development is to assign items into scales that measure different characteristics of individuals, and a popular approach is cluster analysis of items. Classical methods in cluster analysis, such as the hierarchical clustering, K-means method, and latent-class analysis, often induce a high computational overhead and have difficulty handling missing data, especially in the presence of high-dimensional responses. In this article, the authors propose a spectral clustering algorithm for exploratory item cluster analysis. The method is computationally efficient, effective for data with missing or incomplete responses, easy to implement, and often outperforms traditional clustering algorithms in the context of high dimensionality. The spectral clustering algorithm is based on graph theory, a branch of mathematics that studies the properties of graphs. The algorithm first constructs a graph of items, characterizing the similarity structure among items. It then extracts item clusters based on the graphical structure, grouping similar items together. The proposed method is evaluated through simulations and an application to the revised Eysenck Personality Questionnaire. PMID:29033476

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%.

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.

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

NASA Astrophysics Data System (ADS)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Large-Scale Cooperative Task Distribution on Peer-to-Peer Networks

DTIC Science & Technology

2012-01-01

SUBTITLE Large-scale cooperative task distribution on peer-to-peer networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...of agents, and each agent attempts to form a coalition with its most profitable partner. The second algorithm builds upon the Shapley for- mula [37...ters at the second layer. These Category Layer clusters each represent a single resource, and agents join one or more clusters based on their

Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study

PubMed Central

2013-01-01

Background There is a rising public and political demand for prospective cancer cluster monitoring. But there is little empirical evidence on the performance of established cluster detection tests under conditions of small and heterogeneous sample sizes and varying spatial scales, such as are the case for most existing population-based cancer registries. Therefore this simulation study aims to evaluate different cluster detection methods, implemented in the open soure environment R, in their ability to identify clusters of lung cancer using real-life data from an epidemiological cancer registry in Germany. Methods Risk surfaces were constructed with two different spatial cluster types, representing a relative risk of RR = 2.0 or of RR = 4.0, in relation to the overall background incidence of lung cancer, separately for men and women. Lung cancer cases were sampled from this risk surface as geocodes using an inhomogeneous Poisson process. The realisations of the cancer cases were analysed within small spatial (census tracts, N = 1983) and within aggregated large spatial scales (communities, N = 78). Subsequently, they were submitted to the cluster detection methods. The test accuracy for cluster location was determined in terms of detection rates (DR), false-positive (FP) rates and positive predictive values. The Bayesian smoothing models were evaluated using ROC curves. Results With moderate risk increase (RR = 2.0), local cluster tests showed better DR (for both spatial aggregation scales > 0.90) and lower FP rates (both < 0.05) than the Bayesian smoothing methods. When the cluster RR was raised four-fold, the local cluster tests showed better DR with lower FPs only for the small spatial scale. At a large spatial scale, the Bayesian smoothing methods, especially those implementing a spatial neighbourhood, showed a substantially lower FP rate than the cluster tests. However, the risk increases at this scale were mostly diluted by data aggregation. Conclusion High resolution spatial scales seem more appropriate as data base for cancer cluster testing and monitoring than the commonly used aggregated scales. We suggest the development of a two-stage approach that combines methods with high detection rates as a first-line screening with methods of higher predictive ability at the second stage. PMID:24314148

Robustness of serial clustering of extra-tropical cyclones to the choice of tracking method

NASA Astrophysics Data System (ADS)

Pinto, Joaquim G.; Ulbrich, Sven; Karremann, Melanie K.; Stephenson, David B.; Economou, Theodoros; Shaffrey, Len C.

2016-04-01

Cyclone families are a frequent synoptic weather feature in the Euro-Atlantic area in winter. Given appropriate large-scale conditions, the occurrence of such series (clusters) of storms may lead to large socio-economic impacts and cumulative losses. Recent studies analyzing Reanalysis data using single cyclone tracking methods have shown that serial clustering of cyclones occurs on both flanks and downstream regions of the North Atlantic storm track. This study explores the sensitivity of serial clustering to the choice of tracking method. With this aim, the IMILAST cyclone track database based on ERA-interim data is analysed. Clustering is estimated by the dispersion (ratio of variance to mean) of winter (DJF) cyclones passages near each grid point over the Euro-Atlantic area. Results indicate that while the general pattern of clustering is identified for all methods, there are considerable differences in detail. This can primarily be attributed to the differences in the variance of cyclone counts between the methods, which range up to one order of magnitude. Nevertheless, clustering over the Eastern North Atlantic and Western Europe can be identified for all methods and can thus be generally considered as a robust feature. The statistical links between large-scale patterns like the NAO and clustering are obtained for all methods, though with different magnitudes. We conclude that the occurrence of cyclone clustering over the Eastern North Atlantic and Western Europe is largely independent from the choice of tracking method and hence from the definition of a cyclone.

bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor Laboratory Press.

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.

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.

Evaluating tests of virialization and substructure using galaxy clusters in the ORELSE survey

NASA Astrophysics Data System (ADS)

Rumbaugh, N.; Lemaux, B. C.; Tomczak, A. R.; Shen, L.; Pelliccia, D.; Lubin, L. M.; Kocevski, D. D.; Wu, P.-F.; Gal, R. R.; Mei, S.; Fassnacht, C. D.; Squires, G. K.

2018-07-01

We evaluated the effectiveness of different indicators of cluster virialization using 12 large-scale structures in the Observations of Redshift Evolution in Large-Scale Environments survey spanning from 0.7

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.

Scalable clustering algorithms for continuous environmental flow cytometry.

PubMed

Hyrkas, Jeremy; Clayton, Sophie; Ribalet, Francois; Halperin, Daniel; Armbrust, E Virginia; Howe, Bill

2016-02-01

Recent technological innovations in flow cytometry now allow oceanographers to collect high-frequency flow cytometry data from particles in aquatic environments on a scale far surpassing conventional flow cytometers. The SeaFlow cytometer continuously profiles microbial phytoplankton populations across thousands of kilometers of the surface ocean. The data streams produced by instruments such as SeaFlow challenge the traditional sample-by-sample approach in cytometric analysis and highlight the need for scalable clustering algorithms to extract population information from these large-scale, high-frequency flow cytometers. We explore how available algorithms commonly used for medical applications perform at classification of such a large-scale, environmental flow cytometry data. We apply large-scale Gaussian mixture models to massive datasets using Hadoop. This approach outperforms current state-of-the-art cytometry classification algorithms in accuracy and can be coupled with manual or automatic partitioning of data into homogeneous sections for further classification gains. We propose the Gaussian mixture model with partitioning approach for classification of large-scale, high-frequency flow cytometry data. Source code available for download at https://github.com/jhyrkas/seaflow_cluster, implemented in Java for use with Hadoop. hyrkas@cs.washington.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Impact of SZ cluster residuals in CMB maps and CMB-LSS cross-correlations

NASA Astrophysics Data System (ADS)

Chen, T.; Remazeilles, M.; Dickinson, C.

2018-06-01

Residual foreground contamination in cosmic microwave background (CMB) maps, such as the residual contamination from thermal Sunyaev-Zeldovich (SZ) effect in the direction of galaxy clusters, can bias the cross-correlation measurements between CMB and large-scale structure optical surveys. It is thus essential to quantify those residuals and, if possible, to null out SZ cluster residuals in CMB maps. We quantify for the first time the amount of SZ cluster contamination in the released Planck 2015 CMB maps through (i) the stacking of CMB maps in the direction of the clusters, and (ii) the computation of cross-correlation power spectra between CMB maps and the SDSS-IV large-scale structure data. Our cross-power spectrum analysis yields a 30σ detection at the cluster scale (ℓ = 1500-2500) and a 39σ detection on larger scales (ℓ = 500-1500) due to clustering of SZ clusters, giving an overall 54σ detection of SZ cluster residuals in the Planck CMB maps. The Planck 2015 NILC CMB map is shown to have 44 ± 4% of thermal SZ foreground emission left in it. Using the 'Constrained ILC' component separation technique, we construct an alternative Planck CMB map, the 2D-ILC map, which is shown to have negligible SZ contamination, at the cost of being slightly more contaminated by Galactic foregrounds and noise. We also discuss the impact of the SZ residuals in CMB maps on the measurement of the ISW effect, which is shown to be negligible based on our analysis.

Discovery of a large-scale clumpy structure of the Lynx supercluster at z[similar]1.27

NASA Astrophysics Data System (ADS)

Nakata, Fumiaki; Kodama, Tadayuki; Shimasaku, Kazuhiro; Doi, Mamoru; Furusawa, Hisanori; Hamabe, Masaru; Kimura, Masahiko; Komiyama, Yutaka; Miyazaki, Satoshi; Okamura, Sadanori; Ouchi, Masami; Sekiguchi, Maki; Yagi, Masafumi; Yasuda, Naoki

2004-07-01

We report the discovery of a probable large-scale structure composed of many galaxy clumps around the known twin clusters at z=1.26 and z=1.27 in the Lynx region. Our analysis is based on deep, panoramic, and multi-colour imaging with the Suprime-Cam on the 8.2 m Subaru telescope. We apply a photometric redshift technique to extract plausible cluster members at z˜1.27 down to ˜ M*+2.5. From the 2-D distribution of these photometrically selected galaxies, we newly identify seven candidates of galaxy groups or clusters where the surface density of red galaxies is significantly high (>5σ), in addition to the two known clusters, comprising the largest most distant supercluster ever identified.

Clustering on very small scales from a large sample of confirmed quasar pairs: does quasar clustering track from Mpc to kpc scales?

NASA Astrophysics Data System (ADS)

Eftekharzadeh, S.; Myers, A. D.; Hennawi, J. F.; Djorgovski, S. G.; Richards, G. T.; Mahabal, A. A.; Graham, M. J.

2017-06-01

We present the most precise estimate to date of the clustering of quasars on very small scales, based on a sample of 47 binary quasars with magnitudes of g < 20.85 and proper transverse separations of ˜25 h-1 kpc. Our sample of binary quasars, which is about six times larger than any previous spectroscopically confirmed sample on these scales, is targeted using a kernel density estimation (KDE) technique applied to Sloan Digital Sky Survey (SDSS) imaging over most of the SDSS area. Our sample is 'complete' in that all of the KDE target pairs with 17.0 ≲ R ≲ 36.2 h-1 kpc in our area of interest have been spectroscopically confirmed from a combination of previous surveys and our own long-slit observational campaign. We catalogue 230 candidate quasar pairs with angular separations of <8 arcsec, from which our binary quasars were identified. We determine the projected correlation function of quasars (\\bar{W}_p) in four bins of proper transverse scale over the range 17.0 ≲ R ≲ 36.2 h-1 kpc. The implied small-scale quasar clustering amplitude from the projected correlation function, integrated across our entire redshift range, is A = 24.1 ± 3.6 at ˜26.6 h-1 kpc. Our sample is the first spectroscopically confirmed sample of quasar pairs that is sufficiently large to study how quasar clustering evolves with redshift at ˜25 h-1 kpc. We find that empirical descriptions of how quasar clustering evolves with redshift at ˜25 h-1 Mpc also adequately describe the evolution of quasar clustering at ˜25 h-1 kpc.

Temporal Clustering of Regional-Scale Extreme Precipitation Events in Southern Switzerland

NASA Astrophysics Data System (ADS)

Barton, Yannick; Giannakaki, Paraskevi; Von Waldow, Harald; Chevalier, Clément; Pfhal, Stephan; Martius, Olivia

2017-04-01

Temporal clustering of extreme precipitation events on subseasonal time scales is a form of compound extremes and is of crucial importance for the formation of large-scale flood events. Here, the temporal clustering of regional-scale extreme precipitation events in southern Switzerland is studied. These precipitation events are relevant for the flooding of lakes in southern Switzerland and northern Italy. This research determines whether temporal clustering is present and then identifies the dynamics that are responsible for the clustering. An observation-based gridded precipitation dataset of Swiss daily rainfall sums and ECMWF reanalysis datasets are used. To analyze the clustering in the precipitation time series a modified version of Ripley's K function is used. It determines the average number of extreme events in a time period, to characterize temporal clustering on subseasonal time scales and to determine the statistical significance of the clustering. Significant clustering of regional-scale precipitation extremes is found on subseasonal time scales during the fall season. Four high-impact clustering episodes are then selected and the dynamics responsible for the clustering are examined. During the four clustering episodes, all heavy precipitation events were associated with an upperlevel breaking Rossby wave over western Europe and in most cases strong diabatic processes upstream over the Atlantic played a role in the amplification of these breaking waves. Atmospheric blocking downstream over eastern Europe supported this wave breaking during two of the clustering episodes. During one of the clustering periods, several extratropical transitions of tropical cyclones in the Atlantic contributed to the formation of high-amplitude ridges over the Atlantic basin and downstream wave breaking. During another event, blocking over Alaska assisted the phase locking of the Rossby waves downstream over the Atlantic.

MaRaCluster: A Fragment Rarity Metric for Clustering Fragment Spectra in Shotgun Proteomics.

PubMed

The, Matthew; Käll, Lukas

2016-03-04

Shotgun proteomics experiments generate large amounts of fragment spectra as primary data, normally with high redundancy between and within experiments. Here, we have devised a clustering technique to identify fragment spectra stemming from the same species of peptide. This is a powerful alternative method to traditional search engines for analyzing spectra, specifically useful for larger scale mass spectrometry studies. As an aid in this process, we propose a distance calculation relying on the rarity of experimental fragment peaks, following the intuition that peaks shared by only a few spectra offer more evidence than peaks shared by a large number of spectra. We used this distance calculation and a complete-linkage scheme to cluster data from a recent large-scale mass spectrometry-based study. The clusterings produced by our method have up to 40% more identified peptides for their consensus spectra compared to those produced by the previous state-of-the-art method. We see that our method would advance the construction of spectral libraries as well as serve as a tool for mining large sets of fragment spectra. The source code and Ubuntu binary packages are available at https://github.com/statisticalbiotechnology/maracluster (under an Apache 2.0 license).

Adaptive Scaling of Cluster Boundaries for Large-Scale Social Media Data Clustering.

PubMed

Meng, Lei; Tan, Ah-Hwee; Wunsch, Donald C

2016-12-01

The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptive resonance theory (Fuzzy ART) that have linear computational complexity, use a single parameter, i.e., the vigilance parameter to identify data clusters, and are robust to modest parameter settings. The contribution of this paper lies in two aspects. First, we theoretically demonstrate how complement coding, commonly known as a normalization method, changes the clustering mechanism of Fuzzy ART, and discover the vigilance region (VR) that essentially determines how a cluster in the Fuzzy ART system recognizes similar patterns in the feature space. The VR gives an intrinsic interpretation of the clustering mechanism and limitations of Fuzzy ART. Second, we introduce the idea of allowing different clusters in the Fuzzy ART system to have different vigilance levels in order to meet the diverse nature of the pattern distribution of social media data. To this end, we propose three vigilance adaptation methods, namely, the activation maximization (AM) rule, the confliction minimization (CM) rule, and the hybrid integration (HI) rule. With an initial vigilance value, the resulting clustering algorithms, namely, the AM-ART, CM-ART, and HI-ART, can automatically adapt the vigilance values of all clusters during the learning epochs in order to produce better cluster boundaries. Experiments on four social media data sets show that AM-ART, CM-ART, and HI-ART are more robust than Fuzzy ART to the initial vigilance value, and they usually achieve better or comparable performance and much faster speed than the state-of-the-art clustering algorithms that also do not require a predefined number of clusters.

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2009-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...pilot study to utilize large scale parallel Grid computing to harness the nationwide cluster infrastructure for optimization of medical image ... analysis parameters. Additionally, we investigated the use of cutting edge dataanalysis/ mining techniques as applied to Ultrasound, FFDM, and DCE-MRI Breast

Large-scale dynamics associated with clustering of extratropical cyclones affecting Western Europe

NASA Astrophysics Data System (ADS)

Pinto, Joaquim G.; Gómara, Iñigo; Masato, Giacomo; Dacre, Helen F.; Woollings, Tim; Caballero, Rodrigo

2015-04-01

Some recent winters in Western Europe have been characterized by the occurrence of multiple extratropical cyclones following a similar path. The occurrence of such cyclone clusters leads to large socio-economic impacts due to damaging winds, storm surges, and floods. Recent studies have statistically characterized the clustering of extratropical cyclones over the North Atlantic and Europe and hypothesized potential physical mechanisms responsible for their formation. Here we analyze 4 months characterized by multiple cyclones over Western Europe (February 1990, January 1993, December 1999, and January 2007). The evolution of the eddy driven jet stream, Rossby wave-breaking, and upstream/downstream cyclone development are investigated to infer the role of the large-scale flow and to determine if clustered cyclones are related to each other. Results suggest that optimal conditions for the occurrence of cyclone clusters are provided by a recurrent extension of an intensified eddy driven jet toward Western Europe lasting at least 1 week. Multiple Rossby wave-breaking occurrences on both the poleward and equatorward flanks of the jet contribute to the development of these anomalous large-scale conditions. The analysis of the daily weather charts reveals that upstream cyclone development (secondary cyclogenesis, where new cyclones are generated on the trailing fronts of mature cyclones) is strongly related to cyclone clustering, with multiple cyclones developing on a single jet streak. The present analysis permits a deeper understanding of the physical reasons leading to the occurrence of cyclone families over the North Atlantic, enabling a better estimation of the associated cumulative risk over Europe.

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 Relationship Between Galaxies and the Large-Scale Structure of the Universe

NASA Astrophysics Data System (ADS)

Coil, Alison L.

2018-06-01

I will describe our current understanding of the relationship between galaxies and the large-scale structure of the Universe, often called the galaxy-halo connection. Galaxies are thought to form and evolve in the centers of dark matter halos, which grow along with the galaxies they host. Large galaxy redshift surveys have revealed clear observational signatures of connections between galaxy properties and their clustering properties on large scales. For example, older, quiescent galaxies are known to cluster more strongly than younger, star-forming galaxies, which are more likely to be found in galactic voids and filaments rather than the centers of galaxy clusters. I will show how cosmological numerical simulations have aided our understanding of this galaxy-halo connection and what is known from a statistical point of view about how galaxies populate dark matter halos. This knowledge both helps us learn about galaxy evolution and is fundamental to our ability to use galaxy surveys to reveal cosmological information. I will talk briefly about some of the current open questions in the field, including galactic conformity and assembly bias.

Mpc-scale diffuse radio emission in two massive cool-core clusters of galaxies

NASA Astrophysics Data System (ADS)

Sommer, Martin W.; Basu, Kaustuv; Intema, Huib; Pacaud, Florian; Bonafede, Annalisa; Babul, Arif; Bertoldi, Frank

2017-04-01

Radio haloes are diffuse synchrotron sources on scales of ˜1 Mpc that are found in merging clusters of galaxies, and are believed to be powered by electrons re-accelerated by merger-driven turbulence. We present measurements of extended radio emission on similarly large scales in two clusters of galaxies hosting cool cores: Abell 2390 and Abell 2261. The analysis is based on interferometric imaging with the Karl G. Jansky Very Large Array, Very Large Array and Giant Metrewave Radio Telescope. We present detailed radio images of the targets, subtract the compact emission components and measure the spectral indices for the diffuse components. The radio emission in A2390 extends beyond a known sloshing-like brightness discontinuity, and has a very steep in-band spectral slope at 1.5 GHz that is similar to some known ultrasteep spectrum radio haloes. The diffuse signal in A2261 is more extended than in A2390 but has lower luminosity. X-ray morphological indicators, derived from XMM-Newton X-ray data, place these clusters in the category of relaxed or regular systems, although some asymmetric features that can indicate past minor mergers are seen in the X-ray brightness images. If these two Mpc-scale radio sources are categorized as giant radio haloes, they question the common assumption of radio haloes occurring exclusively in clusters undergoing violent merging activity, in addition to commonly used criteria for distinguishing between radio haloes and minihaloes.

Relative dispersion of clustered drifters in a small micro-tidal estuary

NASA Astrophysics Data System (ADS)

Suara, Kabir; Chanson, Hubert; Borgas, Michael; Brown, Richard J.

2017-07-01

Small tide-dominated estuaries are affected by large scale flow structures which combine with the underlying bed generated smaller scale turbulence to significantly increase the magnitude of horizontal diffusivity. Field estimates of horizontal diffusivity and its associated scales are however rare due to limitations in instrumentation. Data from multiple deployments of low and high resolution clusters of GPS-drifters are used to examine the dynamics of a surface flow in a small micro-tidal estuary through relative dispersion analyses. During the field study, cluster diffusivity, which combines both large- and small-scale processes ranged between, 0.01 and 3.01 m2/s for spreading clusters and, -0.06 and -4.2 m2/s for contracting clusters. Pair-particle dispersion, Dp2, was scale dependent and grew as Dp2 ∼ t1.83 in streamwise and Dp2 ∼ t0.8 in cross-stream directions. At small separation scale, pair-particle (d < 0.5 m) relative diffusivity followed the Richardson's 4/3 power law and became weaker as separation scale increases. Pair-particle diffusivity was described as Kp ∼ d1.01 and Kp ∼ d0.85 in the streamwise and cross-stream directions, respectively for separation scales ranging from 0.1 to 10 m. Two methods were used to identify the mechanism responsible for dispersion within the channel. The results clearly revealed the importance of strain fields (stretching and shearing) in the spreading of particles within a small micro-tidal channel. The work provided input for modelling dispersion of passive particle in shallow micro-tidal estuaries where these were not previously experimentally studied.

Does lower Omega allow a resolution of the large-scale structure problem?

NASA Technical Reports Server (NTRS)

Silk, Joseph; Vittorio, Nicola

1987-01-01

The intermediate angular scale anisotropy of the cosmic microwave background, peculiar velocities, density correlations, and mass fluctuations for both neutrino and baryon-dominated universes with Omega less than one are evaluated. The large coherence length associated with a low-Omega, hot dark matter-dominated universe provides substantial density fluctuations on scales up to 100 Mpc: there is a range of acceptable models that are capable of producing large voids and superclusters of galaxies and the clustering of galaxy clusters, with Omega roughly 0.3, without violating any observational constraint. Low-Omega, cold dark matter-dominated cosmologies are also examined. All of these models may be reconciled with the inflationary requirement of a flat universe by introducing a cosmological constant 1-Omega.

Open star clusters and Galactic structure

NASA Astrophysics Data System (ADS)

Joshi, Yogesh C.

2018-04-01

In order to understand the Galactic structure, we perform a statistical analysis of the distribution of various cluster parameters based on an almost complete sample of Galactic open clusters yet available. The geometrical and physical characteristics of a large number of open clusters given in the MWSC catalogue are used to study the spatial distribution of clusters in the Galaxy and determine the scale height, solar offset, local mass density and distribution of reddening material in the solar neighbourhood. We also explored the mass-radius and mass-age relations in the Galactic open star clusters. We find that the estimated parameters of the Galactic disk are largely influenced by the choice of cluster sample.

First results from the IllustrisTNG simulations: matter and galaxy clustering

NASA Astrophysics Data System (ADS)

Springel, Volker; Pakmor, Rüdiger; Pillepich, Annalisa; Weinberger, Rainer; Nelson, Dylan; Hernquist, Lars; Vogelsberger, Mark; Genel, Shy; Torrey, Paul; Marinacci, Federico; Naiman, Jill

2018-03-01

Hydrodynamical simulations of galaxy formation have now reached sufficient volume to make precision predictions for clustering on cosmologically relevant scales. Here, we use our new IllustrisTNG simulations to study the non-linear correlation functions and power spectra of baryons, dark matter, galaxies, and haloes over an exceptionally large range of scales. We find that baryonic effects increase the clustering of dark matter on small scales and damp the total matter power spectrum on scales up to k ˜ 10 h Mpc-1 by 20 per cent. The non-linear two-point correlation function of the stellar mass is close to a power-law over a wide range of scales and approximately invariant in time from very high redshift to the present. The two-point correlation function of the simulated galaxies agrees well with Sloan Digital Sky Survey at its mean redshift z ≃ 0.1, both as a function of stellar mass and when split according to galaxy colour, apart from a mild excess in the clustering of red galaxies in the stellar mass range of109-1010 h-2 M⊙. Given this agreement, the TNG simulations can make valuable theoretical predictions for the clustering bias of different galaxy samples. We find that the clustering length of the galaxy autocorrelation function depends strongly on stellar mass and redshift. Its power-law slope γ is nearly invariant with stellar mass, but declines from γ ˜ 1.8 at redshift z = 0 to γ ˜ 1.6 at redshift z ˜ 1, beyond which the slope steepens again. We detect significant scale dependences in the bias of different observational tracers of large-scale structure, extending well into the range of the baryonic acoustic oscillations and causing nominal (yet fortunately correctable) shifts of the acoustic peaks of around ˜ 5 per cent.

What drives the formation of massive stars and clusters?

NASA Astrophysics Data System (ADS)

Ochsendorf, Bram; Meixner, Margaret; Roman-Duval, Julia; Evans, Neal J., II; Rahman, Mubdi; Zinnecker, Hans; Nayak, Omnarayani; Bally, John; Jones, Olivia C.; Indebetouw, Remy

2018-01-01

Galaxy-wide surveys allow to study star formation in unprecedented ways. In this talk, I will discuss our analysis of the Large Magellanic Cloud (LMC) and the Milky Way, and illustrate how studying both the large and small scale structure of galaxies are critical in addressing the question: what drives the formation of massive stars and clusters?I will show that ‘turbulence-regulated’ star formation models do not reproduce massive star formation properties of GMCs in the LMC and Milky Way: this suggests that theory currently does not capture the full complexity of star formation on small scales. I will also report on the discovery of a massive star forming complex in the LMC, which in many ways manifests itself as an embedded twin of 30 Doradus: this may shed light on the formation of R136 and 'Super Star Clusters' in general. Finally, I will highlight what we can expect in the next years in the field of star formation with large-scale sky surveys, ALMA, and our JWST-GTO program.

The Role of Large-Scale Structure and Assembly in the Quenching of Star Formation in Cluster Galaxies at z 0.2

NASA Astrophysics Data System (ADS)

Moran, Sean; Smith, G.; Haines, C.; Egami, E.; Hardegree-Ullman, E.; Heckman, T.

2010-01-01

We present results from LoCuSS, the Local Cluster Substructure Survey, on the distribution and abundance of cluster galaxies showing signatures of recently quenched star formation, within a sample of 15 z 0.2 clusters. Combining LoCuSS' wide-field UV through NIR photometry with weak-lensing derived mass maps for these clusters, we identify passive galaxies that have undergone recent quenching via both rapid (100Myr) and slow (1Gyr) mechanisms. By studying their abundance in a statistically significant sample of z 0.2 clusters, we explore how the effectiveness of environmental quenching of star formation varies as a function of the level of cluster substructure, in addition to global cluster characteristics such as mass or X-ray luminosity and temperature, with the aim of understanding the role that pre-processing of galaxies within groups and filaments plays in the overall buildup of the morphology-density and SFR-density relations. We find that clusters with large levels of substructure indicative of recent assembly or cluster-cluster mergers host a higher fraction of galaxies with signs of recent ram-pressure stripping by the hot intra-cluster gas. In addition, we find that the fraction of post-starburst galaxies increases with cluster mass (M500), but fractions of optically-selected AGN and GALEX-defined "Green Valley" galaxies show the opposite trend, being most abundant in rather low-mass clusters. These trends suggest a picture where quenching of star formation occurs most vigorously in actively assembling structures, with comparatively little activity in the most massive structures where most of the nearby large-scale structure has already been accreted and Virialized into the main cluster body.

Platinum clusters with precise numbers of atoms for preparative-scale catalysis.

PubMed

Imaoka, Takane; Akanuma, Yuki; Haruta, Naoki; Tsuchiya, Shogo; Ishihara, Kentaro; Okayasu, Takeshi; Chun, Wang-Jae; Takahashi, Masaki; Yamamoto, Kimihisa

2017-09-25

Subnanometer noble metal clusters have enormous potential, mainly for catalytic applications. Because a difference of only one atom may cause significant changes in their reactivity, a preparation method with atomic-level precision is essential. Although such a precision with enough scalability has been achieved by gas-phase synthesis, large-scale preparation is still at the frontier, hampering practical applications. We now show the atom-precise and fully scalable synthesis of platinum clusters on a milligram scale from tiara-like platinum complexes with various ring numbers (n = 5-13). Low-temperature calcination of the complexes on a carbon support under hydrogen stream affords monodispersed platinum clusters, whose atomicity is equivalent to that of the precursor complex. One of the clusters (Pt 10 ) exhibits high catalytic activity in the hydrogenation of styrene compared to that of the other clusters. This method opens an avenue for the application of these clusters to preparative-scale catalysis.The catalytic activity of a noble metal nanocluster is tied to its atomicity. Here, the authors report an atom-precise, fully scalable synthesis of platinum clusters from molecular ring precursors, and show that a variation of only one atom can dramatically change a cluster's reactivity.

A fast learning method for large scale and multi-class samples of SVM

NASA Astrophysics Data System (ADS)

Fan, Yu; Guo, Huiming

2017-06-01

A multi-class classification SVM(Support Vector Machine) fast learning method based on binary tree is presented to solve its low learning efficiency when SVM processing large scale multi-class samples. This paper adopts bottom-up method to set up binary tree hierarchy structure, according to achieved hierarchy structure, sub-classifier learns from corresponding samples of each node. During the learning, several class clusters are generated after the first clustering of the training samples. Firstly, central points are extracted from those class clusters which just have one type of samples. For those which have two types of samples, cluster numbers of their positive and negative samples are set respectively according to their mixture degree, secondary clustering undertaken afterwards, after which, central points are extracted from achieved sub-class clusters. By learning from the reduced samples formed by the integration of extracted central points above, sub-classifiers are obtained. Simulation experiment shows that, this fast learning method, which is based on multi-level clustering, can guarantee higher classification accuracy, greatly reduce sample numbers and effectively improve learning efficiency.

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.

Suppressed star formation by a merging cluster system

DOE PAGES

Mansheim, A. S.; Lemaux, B. C.; Tomczak, A. R.; ...

2017-03-24

We examine the effects of an impending cluster merger on galaxies in the large scale structure (LSS) RX J0910 at z =1.105. Using multi-wavelength data, including 102 spectral members drawn from the Observations of Redshift Evolution in Large Scale Environments (ORELSE) survey and precise photometric redshifts, we calculate star formation rates and map the specific star formation rate density of the LSS galaxies. These analyses along with an investigation of the color-magnitude properties of LSS galaxies indicate lower levels of star formation activity in the region between the merging clusters relative to the outskirts of the system. We suggest thatmore » gravitational tidal forces due to the potential of the merging halos may be the physical mechanism responsible for the observed suppression of star formation in galaxies caught between the merging clusters.« less

The impact of baryonic matter on gravitational lensing by galaxy clusters

NASA Astrophysics Data System (ADS)

Lee, Brandyn E.; King, Lindsay; Applegate, Douglas; McCarthy, Ian

2017-01-01

Since the bulk of the matter comprising galaxy clusters exists in the form of dark matter, gravitational N-body simulations have historically been an effective way to investigate large scale structure formation and the astrophysics of galaxy clusters. However, upcoming telescopes such as the Large Synoptic Survey Telescope are expected to have lower systematic errors than older generations, reducing measurement uncertainties and requiring that astrophysicists better quantify the impact of baryonic matter on the cluster lensing signal. Here we outline the effects of baryonic processes on cluster density profiles and on weak lensing mass and concentration estimates. Our analysis is done using clusters grown in the suite of cosmological hydrodynamical simulations known as cosmo-OWLS.

Witnessing the growth of the nearest galaxy cluster: thermodynamics of the Virgo Cluster outskirts

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

Simionescu, A.; Werner, N.; Mantz, A.

Here, we present results from Suzaku Key Project observations of the Virgo Cluster, the nearest galaxy cluster to us, mapping its X-ray properties along four long ‘arms’ extending beyond the virial radius. The entropy profiles along all four azimuths increase with radius, then level out beyond ~0.5r 200, while the average pressure at large radii exceeds Planck Sunyaev–Zel'dovich measurements. These results can be explained by enhanced gas density fluctuations (clumping) in the cluster's outskirts. Using a standard Navarro, Frenk and White model, we estimate a virial mass, radius and concentration parameter of M 200 = 1.05 ± 0.02 × 10more » 14 M⊙, r 200 = 974.1 ± 5.7 kpc and c = 8.8 ± 0.2, respectively. The inferred cumulative baryon fraction exceeds the cosmic mean at r ~r 200 along the major axis, suggesting enhanced gas clumping possibly sourced by a candidate large-scale structure filament along the north–south direction. The Suzaku data reveal a large-scale sloshing pattern, with two new cold fronts detected at radii of 233 and 280 kpc along the western and southern arms, respectively. Two high-temperature regions are also identified 1 Mpc towards the south and 605 kpc towards the west of M87, likely representing shocks associated with the ongoing cluster growth. Although systematic uncertainties in measuring the metallicity for low-temperature plasma remain, the data at large radii appear consistent with a uniform metal distribution on scales of ~90 × 180 kpc and larger, providing additional support for the early chemical enrichment scenario driven by galactic winds at redshifts of 2–3.« less

Witnessing the growth of the nearest galaxy cluster: thermodynamics of the Virgo Cluster outskirts

DOE PAGES

Simionescu, A.; Werner, N.; Mantz, A.; ...

2017-04-17

Here, we present results from Suzaku Key Project observations of the Virgo Cluster, the nearest galaxy cluster to us, mapping its X-ray properties along four long ‘arms’ extending beyond the virial radius. The entropy profiles along all four azimuths increase with radius, then level out beyond ~0.5r 200, while the average pressure at large radii exceeds Planck Sunyaev–Zel'dovich measurements. These results can be explained by enhanced gas density fluctuations (clumping) in the cluster's outskirts. Using a standard Navarro, Frenk and White model, we estimate a virial mass, radius and concentration parameter of M 200 = 1.05 ± 0.02 × 10more » 14 M⊙, r 200 = 974.1 ± 5.7 kpc and c = 8.8 ± 0.2, respectively. The inferred cumulative baryon fraction exceeds the cosmic mean at r ~r 200 along the major axis, suggesting enhanced gas clumping possibly sourced by a candidate large-scale structure filament along the north–south direction. The Suzaku data reveal a large-scale sloshing pattern, with two new cold fronts detected at radii of 233 and 280 kpc along the western and southern arms, respectively. Two high-temperature regions are also identified 1 Mpc towards the south and 605 kpc towards the west of M87, likely representing shocks associated with the ongoing cluster growth. Although systematic uncertainties in measuring the metallicity for low-temperature plasma remain, the data at large radii appear consistent with a uniform metal distribution on scales of ~90 × 180 kpc and larger, providing additional support for the early chemical enrichment scenario driven by galactic winds at redshifts of 2–3.« less

Constraining the baryon-dark matter relative velocity with the large-scale 3-point correlation function of the SDSS BOSS DR12 CMASS galaxies

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

Slepian, Zachary; Slosar, Anze; Eisenstein, Daniel J.

We search for a galaxy clustering bias due to a modulation of galaxy number with the baryon-dark matter relative velocity resulting from recombination-era physics. We find no detected signal and place the constraint bv <0.01 on the relative velocity bias for the CMASS galaxies. This bias is an important potential systematic of Baryon Acoustic Oscillation (BAO) method measurements of the cosmic distance scale using the 2-point clustering. Our limit on the relative velocity bias indicates a systematic shift of no more than 0.3% rms in the distance scale inferred from the BAO feature in the BOSS 2-point clustering, well belowmore » the 1% statistical error of this measurement. In conclusion, this constraint is the most stringent currently available and has important implications for the ability of upcoming large-scale structure surveys such as DESI to self-protect against the relative velocity as a possible systematic.« less

The void spectrum in two-dimensional numerical simulations of gravitational clustering

NASA Technical Reports Server (NTRS)

Kauffmann, Guinevere; Melott, Adrian L.

1992-01-01

An algorithm for deriving a spectrum of void sizes from two-dimensional high-resolution numerical simulations of gravitational clustering is tested, and it is verified that it produces the correct results where those results can be anticipated. The method is used to study the growth of voids as clustering proceeds. It is found that the most stable indicator of the characteristic void 'size' in the simulations is the mean fractional area covered by voids of diameter d, in a density field smoothed at its correlation length. Very accurate scaling behavior is found in power-law numerical models as they evolve. Eventually, this scaling breaks down as the nonlinearity reaches larger scales. It is shown that this breakdown is a manifestation of the undesirable effect of boundary conditions on simulations, even with the very large dynamic range possible here. A simple criterion is suggested for deciding when simulations with modest large-scale power may systematically underestimate the frequency of larger voids.

Constraining the baryon-dark matter relative velocity with the large-scale 3-point correlation function of the SDSS BOSS DR12 CMASS galaxies

DOE PAGES

Slepian, Zachary; Slosar, Anze; Eisenstein, Daniel J.; ...

2017-10-24

We search for a galaxy clustering bias due to a modulation of galaxy number with the baryon-dark matter relative velocity resulting from recombination-era physics. We find no detected signal and place the constraint bv <0.01 on the relative velocity bias for the CMASS galaxies. This bias is an important potential systematic of Baryon Acoustic Oscillation (BAO) method measurements of the cosmic distance scale using the 2-point clustering. Our limit on the relative velocity bias indicates a systematic shift of no more than 0.3% rms in the distance scale inferred from the BAO feature in the BOSS 2-point clustering, well belowmore » the 1% statistical error of this measurement. In conclusion, this constraint is the most stringent currently available and has important implications for the ability of upcoming large-scale structure surveys such as DESI to self-protect against the relative velocity as a possible systematic.« less

Constraining the baryon-dark matter relative velocity with the large-scale three-point correlation function of the SDSS BOSS DR12 CMASS galaxies

NASA Astrophysics Data System (ADS)

Slepian, Zachary; Eisenstein, Daniel J.; Blazek, Jonathan A.; Brownstein, Joel R.; Chuang, Chia-Hsun; Gil-Marín, Héctor; Ho, Shirley; Kitaura, Francisco-Shu; McEwen, Joseph E.; Percival, Will J.; Ross, Ashley J.; Rossi, Graziano; Seo, Hee-Jong; Slosar, Anže; Vargas-Magaña, Mariana

2018-02-01

We search for a galaxy clustering bias due to a modulation of galaxy number with the baryon-dark matter relative velocity resulting from recombination-era physics. We find no detected signal and place the constraint bv < 0.01 on the relative velocity bias for the CMASS galaxies. This bias is an important potential systematic of baryon acoustic oscillation (BAO) method measurements of the cosmic distance scale using the two-point clustering. Our limit on the relative velocity bias indicates a systematic shift of no more than 0.3 per cent rms in the distance scale inferred from the BAO feature in the BOSS two-point clustering, well below the 1 per cent statistical error of this measurement. This constraint is the most stringent currently available and has important implications for the ability of upcoming large-scale structure surveys such as the Dark Energy Spectroscopic Instrument (DESI) to self-protect against the relative velocity as a possible systematic.

The X-ray luminosity functions of Abell clusters from the Einstein Cluster Survey

NASA Technical Reports Server (NTRS)

Burg, R.; Giacconi, R.; Forman, W.; Jones, C.

1994-01-01

We have derived the present epoch X-ray luminosity function of northern Abell clusters using luminosities from the Einstein Cluster Survey. The sample is sufficiently large that we can determine the luminosity function for each richness class separately with sufficient precision to study and compare the different luminosity functions. We find that, within each richness class, the range of X-ray luminosity is quite large and spans nearly a factor of 25. Characterizing the luminosity function for each richness class with a Schechter function, we find that the characteristic X-ray luminosity, L(sub *), scales with richness class as (L(sub *) varies as N(sub*)(exp gamma), where N(sub *) is the corrected, mean number of galaxies in a richness class, and the best-fitting exponent is gamma = 1.3 +/- 0.4. Finally, our analysis suggests that there is a lower limit to the X-ray luminosity of clusters which is determined by the integrated emission of the cluster member galaxies, and this also scales with richness class. The present sample forms a baseline for testing cosmological evolution of Abell-like clusters when an appropriate high-redshift cluster sample becomes available.

EMBEDDED CLUSTERS IN THE LARGE MAGELLANIC CLOUD USING THE VISTA MAGELLANIC CLOUDS SURVEY

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

Romita, Krista; Lada, Elizabeth; Cioni, Maria-Rosa, E-mail: k.a.romita@ufl.edu, E-mail: elada@ufl.edu, E-mail: mcioni@aip.de

We present initial results of the first large-scale survey of embedded star clusters in molecular clouds in the Large Magellanic Cloud (LMC) using near-infrared imaging from the Visible and Infrared Survey Telescope for Astronomy Magellanic Clouds Survey. We explored a ∼1.65 deg{sup 2} area of the LMC, which contains the well-known star-forming region 30 Doradus as well as ∼14% of the galaxy’s CO clouds, and identified 67 embedded cluster candidates, 45 of which are newly discovered as clusters. We have determined the sizes, luminosities, and masses for these embedded clusters, examined the star formation rates (SFRs) of their corresponding molecularmore » clouds, and made a comparison between the LMC and the Milky Way. Our preliminary results indicate that embedded clusters in the LMC are generally larger, more luminous, and more massive than those in the local Milky Way. We also find that the surface densities of both embedded clusters and molecular clouds is ∼3 times higher than in our local environment, the embedded cluster mass surface density is ∼40 times higher, the SFR is ∼20 times higher, and the star formation efficiency is ∼10 times higher. Despite these differences, the SFRs of the LMC molecular clouds are consistent with the SFR scaling law presented in Lada et al. This consistency indicates that while the conditions of embedded cluster formation may vary between environments, the overall process within molecular clouds may be universal.« less

The two-point correlation function for groups of galaxies in the Center for Astrophysics redshift survey

NASA Technical Reports Server (NTRS)

Ramella, Massimo; Geller, Margaret J.; Huchra, John P.

1990-01-01

The large-scale distribution of groups of galaxies selected from complete slices of the CfA redshift survey extension is examined. The survey is used to reexamine the contribution of group members to the galaxy correlation function. The relationship between the correlation function for groups and those calculated for rich clusters is discussed, and the results for groups are examined as an extension of the relation between correlation function amplitude and richness. The group correlation function indicates that groups and individual galaxies are equivalent tracers of the large-scale matter distribution. The distribution of group centers is equivalent to random sampling of the galaxy distribution. The amplitude of the correlation function for groups is consistent with an extrapolation of the amplitude-richness relation for clusters. The amplitude scaled by the mean intersystem separation is also consistent with results for richer clusters.

Obscuring and Feeding Supermassive Black Holes with Evolving Nuclear Star Clusters

NASA Astrophysics Data System (ADS)

Schartmann, M.; Burkert, A.; Krause, M.; Camenzind, M.; Meisenheimer, K.; Davies, R. I.

2010-05-01

Recently, high-resolution observations made with the help of the near-infrared adaptive optics integral field spectrograph SINFONI at the VLT proved the existence of massive and young nuclear star clusters in the centers of a sample of Seyfert galaxies. With the help of high-resolution hydrodynamical simulations with the pluto code, we follow the evolution of such clusters, especially focusing on mass and energy feedback from young stars. This leads to a filamentary inflow of gas on large scales (tens of parsecs), whereas a turbulent and very dense disk builds up on the parsec scale. Here we concentrate on the long-term evolution of the nuclear disk in NGC 1068 with the help of an effective viscous disk model, using the mass input from the large-scale simulations and accounting for star formation in the disk. This two-stage modeling enables us to connect the tens-of-parsecs scale region (observable with SINFONI) with the parsec-scale environment (MIDI observations). At the current age of the nuclear star cluster, our simulations predict disk sizes of the order 0.8 to 0.9 pc, gas masses of order 106 M⊙, and mass transfer rates through the inner boundary of order 0.025 M⊙ yr-1, in good agreement with values derived from observations.

Cluster Tails for Critical Power-Law Inhomogeneous Random Graphs

NASA Astrophysics Data System (ADS)

van der Hofstad, Remco; Kliem, Sandra; van Leeuwaarden, Johan S. H.

2018-04-01

Recently, the scaling limit of cluster sizes for critical inhomogeneous random graphs of rank-1 type having finite variance but infinite third moment degrees was obtained in Bhamidi et al. (Ann Probab 40:2299-2361, 2012). It was proved that when the degrees obey a power law with exponent τ \\in (3,4), the sequence of clusters ordered in decreasing size and multiplied through by n^{-(τ -2)/(τ -1)} converges as n→ ∞ to a sequence of decreasing non-degenerate random variables. Here, we study the tails of the limit of the rescaled largest cluster, i.e., the probability that the scaling limit of the largest cluster takes a large value u, as a function of u. This extends a related result of Pittel (J Combin Theory Ser B 82(2):237-269, 2001) for the Erdős-Rényi random graph to the setting of rank-1 inhomogeneous random graphs with infinite third moment degrees. We make use of delicate large deviations and weak convergence arguments.

Weak gravitational lensing due to large-scale structure of the universe

NASA Technical Reports Server (NTRS)

Jaroszynski, Michal; Park, Changbom; Paczynski, Bohdan; Gott, J. Richard, III

1990-01-01

The effect of the large-scale structure of the universe on the propagation of light rays is studied. The development of the large-scale density fluctuations in the omega = 1 universe is calculated within the cold dark matter scenario using a smooth particle approximation. The propagation of about 10 to the 6th random light rays between the redshift z = 5 and the observer was followed. It is found that the effect of shear is negligible, and the amplification of single images is dominated by the matter in the beam. The spread of amplifications is very small. Therefore, the filled-beam approximation is very good for studies of strong lensing by galaxies or clusters of galaxies. In the simulation, the column density was averaged over a comoving area of approximately (1/h Mpc)-squared. No case of a strong gravitational lensing was found, i.e., no 'over-focused' image that would suggest that a few images might be present. Therefore, the large-scale structure of the universe as it is presently known does not produce multiple images with gravitational lensing on a scale larger than clusters of galaxies.

Sloan Digital Sky Survey III photometric quasar clustering: Probing the initial conditions of the Universe

DOE PAGES

Ho, Shirley; Agarwal, Nishant; Myers, Adam D.; ...

2015-05-22

Here, the Sloan Digital Sky Survey has surveyed 14,555 square degrees of the sky, and delivered over a trillion pixels of imaging data. We present the large-scale clustering of 1.6 million quasars between z=0.5 and z=2.5 that have been classified from this imaging, representing the highest density of quasars ever studied for clustering measurements. This data set spans 0~ 11,00 square degrees and probes a volume of 80 h –3 Gpc 3. In principle, such a large volume and medium density of tracers should facilitate high-precision cosmological constraints. We measure the angular clustering of photometrically classified quasars using an optimalmore » quadratic estimator in four redshift slices with an accuracy of ~ 25% over a bin width of δ l ~ 10–15 on scales corresponding to matter-radiation equality and larger (0ℓ ~ 2–3).« less

Analysis of large-scale gene expression data.

PubMed

Sherlock, G

2000-04-01

The advent of cDNA and oligonucleotide microarray technologies has led to a paradigm shift in biological investigation, such that the bottleneck in research is shifting from data generation to data analysis. Hierarchical clustering, divisive clustering, self-organizing maps and k-means clustering have all been recently used to make sense of this mass of data.

Clustering biomolecular complexes by residue contacts similarity.

PubMed

Rodrigues, João P G L M; Trellet, Mikaël; Schmitz, Christophe; Kastritis, Panagiotis; Karaca, Ezgi; Melquiond, Adrien S J; Bonvin, Alexandre M J J

2012-07-01

Inaccuracies in computational molecular modeling methods are often counterweighed by brute-force generation of a plethora of putative solutions. These are then typically sieved via structural clustering based on similarity measures such as the root mean square deviation (RMSD) of atomic positions. Albeit widely used, these measures suffer from several theoretical and technical limitations (e.g., choice of regions for fitting) that impair their application in multicomponent systems (N > 2), large-scale studies (e.g., interactomes), and other time-critical scenarios. We present here a simple similarity measure for structural clustering based on atomic contacts--the fraction of common contacts--and compare it with the most used similarity measure of the protein docking community--interface backbone RMSD. We show that this method produces very compact clusters in remarkably short time when applied to a collection of binary and multicomponent protein-protein and protein-DNA complexes. Furthermore, it allows easy clustering of similar conformations of multicomponent symmetrical assemblies in which chain permutations can occur. Simple contact-based metrics should be applicable to other structural biology clustering problems, in particular for time-critical or large-scale endeavors. Copyright © 2012 Wiley Periodicals, Inc.

Nonlocal and collective relaxation in stellar systems

NASA Technical Reports Server (NTRS)

Weinberg, Martin D.

1993-01-01

The modal response of stellar systems to fluctuations at large scales is presently investigated by means of analytic theory and n-body simulation; the stochastic excitation of these modes is shown to increase the relaxation rate even for a system which is moderately far from instability. The n-body simulations, when designed to suppress relaxation at small scales, clearly show the effects of large-scale fluctuations. It is predicted that large-scale fluctuations will be largest for such marginally bound systems as forming star clusters and associations.

Dark matter, long-range forces, and large-scale structure

NASA Technical Reports Server (NTRS)

Gradwohl, Ben-Ami; Frieman, Joshua A.

1992-01-01

If the dark matter in galaxies and clusters is nonbaryonic, it can interact with additional long-range fields that are invisible to experimental tests of the equivalence principle. We discuss the astrophysical and cosmological implications of a long-range force coupled only to the dark matter and find rather tight constraints on its strength. If the force is repulsive (attractive), the masses of galaxy groups and clusters (and the mean density of the universe inferred from them) have been systematically underestimated (overestimated). We explore the consequent effects on the two-point correlation function, large-scale velocity flows, and microwave background anisotropies, for models with initial scale-invariant adiabatic perturbations and cold dark matter.

Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.

PubMed

Wu, Dingming; Wang, Dongfang; Zhang, Michael Q; Gu, Jin

2015-12-01

One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data. In this study, we proposed a novel low-rank approximation based integrative probabilistic model to fast find the shared principal subspace across multiple data types: the convexity of the low-rank regularized likelihood function of the probabilistic model ensures efficient and stable model fitting. Candidate molecular subtypes can be identified by unsupervised clustering hundreds of cancer samples in the reduced low-dimensional subspace. On testing datasets, our method LRAcluster (low-rank approximation based multi-omics data clustering) runs much faster with better clustering performances than the existing method. Then, we applied LRAcluster on large-scale cancer multi-omics data from TCGA. The pan-cancer analysis results show that the cancers of different tissue origins are generally grouped as independent clusters, except squamous-like carcinomas. While the single cancer type analysis suggests that the omics data have different subtyping abilities for different cancer types. LRAcluster is a very useful method for fast dimension reduction and unsupervised clustering of large-scale multi-omics data. LRAcluster is implemented in R and freely available via http://bioinfo.au.tsinghua.edu.cn/software/lracluster/ .

Dispersion and Cluster Scales in the Ocean

NASA Astrophysics Data System (ADS)

Kirwan, A. D., Jr.; Chang, H.; Huntley, H.; Carlson, D. F.; Mensa, J. A.; Poje, A. C.; Fox-Kemper, B.

2017-12-01

Ocean flow space scales range from centimeters to thousands of kilometers. Because of their large Reynolds number these flows are considered turbulent. However, because of rotation and stratification constraints they do not conform to classical turbulence scaling theory. Mesoscale and large-scale motions are well described by geostrophic or "2D turbulence" theory, however extending this theory to submesoscales has proved to be problematic. One obvious reason is the difficulty in obtaining reliable data over many orders of magnitude of spatial scales in an ocean environment. The goal of this presentation is to provide a preliminary synopsis of two recent experiments that overcame these obstacles. The first experiment, the Grand LAgrangian Deployment (GLAD) was conducted during July 2012 in the eastern half of the Gulf of Mexico. Here approximately 300 GPS-tracked drifters were deployed with the primary goal to determine whether the relative dispersion of an initially densely clustered array was driven by processes acting at local pair separation scales or by straining imposed by mesoscale motions. The second experiment was a component of the LAgrangian Submesoscale Experiment (LASER) conducted during the winter of 2016. Here thousands of bamboo plates were tracked optically from an Aerostat. Together these two deployments provided an unprecedented data set on dispersion and clustering processes from 1 to 106 meter scales. Calculations of statistics such as two point separations, structure functions, and scale dependent relative diffusivities showed: inverse energy cascade as expected for scales above 10 km, a forward energy cascade at scales below 10 km with a possible energy input at Langmuir circulation scales. We also find evidence from structure function calculations for surface flow convergence at scales less than 10 km that account for material clustering at the ocean surface.

Anomalies in the GRBs' distribution

NASA Astrophysics Data System (ADS)

Bagoly, Zsolt; Horvath, Istvan; Hakkila, Jon; Toth, Viktor

2015-08-01

Gamma-ray bursts (GRBs) are the most luminous objects known: they outshine their host galaxies making them ideal candidates for probing large-scale structure. Earlier, the angular distribution of different GRBs (long, intermediate and short) has been studied in detail with different methods and it has been found that the short and intermediate groups showed deviation from the full randomness at different levels (e.g. Vavrek, R., et al. 2008). However these result based only angular measurements of the BATSE experiment, without any spatial distance indicator involved.Currently we have more than 361 GRBs with measured precise position, optical afterglow and redshift, mainly due to the observations of the Swift mission. This sample is getting large enough that it its homogeneous and isotropic distribution a large scale can be checked. We have recently (Horvath, I. et al., 2014) identified a large clustering of gamma-ray bursts at redshift z ~ 2 in the general direction of the constellations of Hercules and Corona Borealis. This angular excess cannot be entirely attributed to known selection biases, making its existence due to chance unlikely. The scale on which the clustering occurs is disturbingly large, about 2-3 Gpc: the underlying distribution of matter suggested by this cluster is big enough to question standard assumptions about Universal homogeneity and isotropy.

Multilevel Analysis of Trachomatous Trichiasis and Corneal Opacity in Nigeria: The Role of Environmental and Climatic Risk Factors on the Distribution of Disease.

PubMed

Smith, Jennifer L; Sivasubramaniam, Selvaraj; Rabiu, Mansur M; Kyari, Fatima; Solomon, Anthony W; Gilbert, Clare

2015-01-01

The distribution of trachoma in Nigeria is spatially heterogeneous, with large-scale trends observed across the country and more local variation within areas. Relative contributions of individual and cluster-level risk factors to the geographic distribution of disease remain largely unknown. The primary aim of this analysis is to assess the relationship between climatic factors and trachomatous trichiasis (TT) and/or corneal opacity (CO) due to trachoma in Nigeria, while accounting for the effects of individual risk factors and spatial correlation. In addition, we explore the relative importance of variation in the risk of trichiasis and/or corneal opacity (TT/CO) at different levels. Data from the 2007 National Blindness and Visual Impairment Survey were used for this analysis, which included a nationally representative sample of adults aged 40 years and above. Complete data were available from 304 clusters selected using a multi-stage stratified cluster-random sampling strategy. All participants (13,543 individuals) were interviewed and examined by an ophthalmologist for the presence or absence of TT and CO. In addition to field-collected data, remotely sensed climatic data were extracted for each cluster and used to fit Bayesian hierarchical logistic models to disease outcome. The risk of TT/CO was associated with factors at both the individual and cluster levels, with approximately 14% of the total variation attributed to the cluster level. Beyond established individual risk factors (age, gender and occupation), there was strong evidence that environmental/climatic factors at the cluster-level (lower precipitation, higher land surface temperature, higher mean annual temperature and rural classification) were also associated with a greater risk of TT/CO. This study establishes the importance of large-scale risk factors in the geographical distribution of TT/CO in Nigeria, supporting anecdotal evidence that environmental conditions are associated with increased risk in this context and highlighting their potential use in improving estimates of disease burden at large scales.

Dynamic structural disorder in supported nanoscale catalysts

NASA Astrophysics Data System (ADS)

Rehr, J. J.; Vila, F. D.

2014-04-01

We investigate the origin and physical effects of "dynamic structural disorder" (DSD) in supported nano-scale catalysts. DSD refers to the intrinsic fluctuating, inhomogeneous structure of such nano-scale systems. In contrast to bulk materials, nano-scale systems exhibit substantial fluctuations in structure, charge, temperature, and other quantities, as well as large surface effects. The DSD is driven largely by the stochastic librational motion of the center of mass and fluxional bonding at the nanoparticle surface due to thermal coupling with the substrate. Our approach for calculating and understanding DSD is based on a combination of real-time density functional theory/molecular dynamics simulations, transient coupled-oscillator models, and statistical mechanics. This approach treats thermal and dynamic effects over multiple time-scales, and includes bond-stretching and -bending vibrations, and transient tethering to the substrate at longer ps time-scales. Potential effects on the catalytic properties of these clusters are briefly explored. Model calculations of molecule-cluster interactions and molecular dissociation reaction paths are presented in which the reactant molecules are adsorbed on the surface of dynamically sampled clusters. This model suggests that DSD can affect both the prefactors and distribution of energy barriers in reaction rates, and thus can significantly affect catalytic activity at the nano-scale.

Laboratory Study of Air Turbulence-Particle Coupling

NASA Astrophysics Data System (ADS)

Petersen, A.; Baker, L.; Coletti, F.

2017-12-01

Inertial particles suspended in a turbulent flow are unable to follow the fluid's rapid velocity fluctuations, leading to high concentrations in regions where fluid strain dominates vorticity. This phenomenon is known as preferential concentration or clustering and is thought to affect natural processes ranging from the collisional growth of raindrops to the formation of planetesimals in proto-planetary nebulas. In the present study, we use a large jet-stirred chamber to generate homogeneous air turbulence into which we drop particles with an aerodynamic response time comparable to the flow time scales. Using laser imaging we find that turbulence can lead to a multi-fold increase of settling velocity compared to still-air conditions. We then employ Voronoi tessellation to examine the particle spatial distribution, finding strong evidence of turbulence-driven particle clustering over a wide range of experimental conditions. We observe individual clusters of a larger size range than seen previously, sometimes beyond the integral length scale of the turbulence. We also investigate cluster topology and find that they (i) exhibit a fractal structure, (ii) have a nearly constant particle concentration over their entire size range, and (iii) are most often vertically oriented. Furthermore, clustered particles tend to fall faster than those outside clusters, and larger clusters fall faster on average than smaller ones. Finally, by simultaneous measurement of particle and air velocity fields, we provide the first experimental evidence of preferential sweeping, a mechanism previously proposed to explain the increase in particle settling velocity found in numerical simulations, and find it especially effective for clustered particles. These results are significant for the micro-scale physics of atmospheric clouds. The large cluster size range has implications for how droplets will influence the local environment through condensation, evaporation, drag and latent heat effects. Our results also suggest that large collections of droplets will interact due to differential settling, possibly enhancing raindrop formation.

Spatial correlations, clustering and percolation-like transitions in homicide crimes

NASA Astrophysics Data System (ADS)

Alves, L. G. A.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2015-07-01

The spatial dynamics of criminal activities has been recently studied through statistical physics methods; however, models and results have been focusing on local scales (city level) and much less is known about these patterns at larger scales, e.g. at a country level. Here we report on a characterization of the spatial dynamics of the homicide crimes along the Brazilian territory using data from all cities (˜5000) in a period of more than thirty years. Our results show that the spatial correlation function in the per capita homicides decays exponentially with the distance between cities and that the characteristic correlation length displays an acute increasing trend in the latest years. We also investigate the formation of spatial clusters of cities via a percolation-like analysis, where clustering of cities and a phase-transition-like behavior describing the size of the largest cluster as a function of a homicide threshold are observed. This transition-like behavior presents evolutive features characterized by an increasing in the homicide threshold (where the transitions occur) and by a decreasing in the transition magnitudes (length of the jumps in the cluster size). We believe that our work sheds new light on the spatial patterns of criminal activities at large scales, which may contribute for better political decisions and resources allocation as well as opens new possibilities for modeling criminal activities by setting up fundamental empirical patterns at large scales.

Supermassive Black Hole Binaries in High Performance Massively Parallel Direct N-body Simulations on Large GPU Clusters

NASA Astrophysics Data System (ADS)

Spurzem, R.; Berczik, P.; Zhong, S.; Nitadori, K.; Hamada, T.; Berentzen, I.; Veles, A.

2012-07-01

Astrophysical Computer Simulations of Dense Star Clusters in Galactic Nuclei with Supermassive Black Holes are presented using new cost-efficient supercomputers in China accelerated by graphical processing cards (GPU). We use large high-accuracy direct N-body simulations with Hermite scheme and block-time steps, parallelised across a large number of nodes on the large scale and across many GPU thread processors on each node on the small scale. A sustained performance of more than 350 Tflop/s for a science run on using simultaneously 1600 Fermi C2050 GPUs is reached; a detailed performance model is presented and studies for the largest GPU clusters in China with up to Petaflop/s performance and 7000 Fermi GPU cards. In our case study we look at two supermassive black holes with equal and unequal masses embedded in a dense stellar cluster in a galactic nucleus. The hardening processes due to interactions between black holes and stars, effects of rotation in the stellar system and relativistic forces between the black holes are simultaneously taken into account. The simulation stops at the complete relativistic merger of the black holes.

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

PubMed

Shen, Lili; Guo, Jiming; Wang, Lei

2018-06-06

The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

Evolution of the Contact Area with Normal Load for Rough Surfaces: from Atomic to Macroscopic Scales.

PubMed

Huang, Shiping

2017-11-13

The evolution of the contact area with normal load for rough surfaces has great fundamental and practical importance, ranging from earthquake dynamics to machine wear. This work bridges the gap between the atomic scale and the macroscopic scale for normal contact behavior. The real contact area, which is formed by a large ensemble of discrete contacts (clusters), is proven to be much smaller than the apparent surface area. The distribution of the discrete contact clusters and the interaction between them are key to revealing the mechanism of the contacting solids. To this end, Green's function molecular dynamics (GFMD) is used to study both how the contact cluster evolves from the atomic scale to the macroscopic scale and the interaction between clusters. It is found that the interaction between clusters has a strong effect on their formation. The formation and distribution of the contact clusters is far more complicated than that predicted by the asperity model. Ignorance of the interaction between them leads to overestimating the contacting force. In real contact, contacting clusters are smaller and more discrete due to the interaction between the asperities. Understanding the exact nature of the contact area with the normal load is essential to the following research on friction.

Evolution of the Contact Area with Normal Load for Rough Surfaces: from Atomic to Macroscopic Scales

NASA Astrophysics Data System (ADS)

Huang, Shiping

2017-11-01

The evolution of the contact area with normal load for rough surfaces has great fundamental and practical importance, ranging from earthquake dynamics to machine wear. This work bridges the gap between the atomic scale and the macroscopic scale for normal contact behavior. The real contact area, which is formed by a large ensemble of discrete contacts (clusters), is proven to be much smaller than the apparent surface area. The distribution of the discrete contact clusters and the interaction between them are key to revealing the mechanism of the contacting solids. To this end, Green's function molecular dynamics (GFMD) is used to study both how the contact cluster evolves from the atomic scale to the macroscopic scale and the interaction between clusters. It is found that the interaction between clusters has a strong effect on their formation. The formation and distribution of the contact clusters is far more complicated than that predicted by the asperity model. Ignorance of the interaction between them leads to overestimating the contacting force. In real contact, contacting clusters are smaller and more discrete due to the interaction between the asperities. Understanding the exact nature of the contact area with the normal load is essential to the following research on friction.

Cognitive Model Exploration and Optimization: A New Challenge for Computational Science

DTIC Science & Technology

2010-03-01

the generation and analysis of computational cognitive models to explain various aspects of cognition. Typically the behavior of these models...computational scale of a workstation, so we have turned to high performance computing (HPC) clusters and volunteer computing for large-scale...computational resources. The majority of applications on the Department of Defense HPC clusters focus on solving partial differential equations (Post

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-Gaussian shape discrimination with spectroscopic galaxy surveys

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

Byun, Joyce; Bean, Rachel, E-mail: byun@astro.cornell.edu, E-mail: rbean@astro.cornell.edu

2015-03-01

We consider how galaxy clustering data, from Mpc to Gpc scales, from upcoming large scale structure surveys, such as Euclid and DESI, can provide discriminating information about the bispectrum shape arising from a variety of inflationary scenarios. Through exploring in detail the weighting of shape properties in the calculation of the halo bias and halo mass function we show how they probe a broad range of configurations, beyond those in the squeezed limit, that can help distinguish between shapes with similar large scale bias behaviors. We assess the impact, on constraints for a diverse set of non-Gaussian shapes, of galaxymore » clustering information in the mildly non-linear regime, and surveys that span multiple redshifts and employ different galactic tracers of the dark matter distribution. Fisher forecasts are presented for a Euclid-like spectroscopic survey of Hα-selected emission line galaxies (ELGs), and a DESI-like survey, of luminous red galaxies (LRGs) and [O-II] doublet-selected ELGs, in combination with Planck-like CMB temperature and polarization data.While ELG samples provide better probes of shapes that are divergent in the squeezed limit, LRG constraints, centered below z<1, yield stronger constraints on shapes with scale-independent large-scale halo biases, such as the equilateral template. The ELG and LRG samples provide complementary degeneracy directions for distinguishing between different shapes. For Hα-selected galaxies, we note that recent revisions of the expected Hα luminosity function reduce the halo bias constraints on the local shape, relative to the CMB. For galaxy clustering constraints to be comparable to those from the CMB, additional information about the Gaussian galaxy bias is needed, such as can be determined from the galaxy clustering bispectrum or probing the halo power spectrum directly through weak lensing. If the Gaussian galaxy bias is constrained to better than a percent level then the LSS and CMB data could provide complementary constraints that will enable differentiation of bispectrum with distinct theoretical origins but with similar large scale, squeezed-limit properties.« less

REVIEWS OF TOPICAL PROBLEMS: Large-scale star formation in galaxies

NASA Astrophysics Data System (ADS)

Efremov, Yurii N.; Chernin, Artur D.

2003-01-01

A brief review is given of the history of modern ideas on the ongoing star formation process in the gaseous disks of galaxies. Recent studies demonstrate the key role of the interplay between the gas self-gravitation and its turbulent motions. The large scale supersonic gas flows create structures of enhanced density which then give rise to the gravitational condensation of gas into stars and star clusters. Formation of star clusters, associations and complexes is considered, as well as the possibility of isolated star formation. Special emphasis is placed on star formation under the action of ram pressure.

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.

Analysis of Helium Segregation on Surfaces of Plasma-Exposed Tungsten

NASA Astrophysics Data System (ADS)

Maroudas, Dimitrios; Hu, Lin; Hammond, Karl; Wirth, Brian

2015-11-01

We report a systematic theoretical and atomic-scale computational study of implanted helium segregation on surfaces of tungsten, which is considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations, including molecular statics to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile helium clusters (of 1-7 He atoms) in the near-surface region are attracted to the surface due to an elastic interaction force. This thermodynamic driving force induces drift fluxes of these mobile clusters toward the surface, facilitating helium segregation. Moreover, the clusters' drift toward the surface enables cluster reactions, most importantly trap mutation, at rates much higher than in the bulk material. This cluster dynamics has significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure.

Clustering fossils in solid inflation

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

Akhshik, Mohammad, E-mail: m.akhshik@ipm.ir

In solid inflation the single field non-Gaussianity consistency condition is violated. As a result, the long tenor perturbation induces observable clustering fossils in the form of quadrupole anisotropy in large scale structure power spectrum. In this work we revisit the bispectrum analysis for the scalar-scalar-scalar and tensor-scalar-scalar bispectrum for the general parameter space of solid. We consider the parameter space of the model in which the level of non-Gaussianity generated is consistent with the Planck constraints. Specializing to this allowed range of model parameter we calculate the quadrupole anisotropy induced from the long tensor perturbations on the power spectrum ofmore » the scalar perturbations. We argue that the imprints of clustering fossil from primordial gravitational waves on large scale structures can be detected from the future galaxy surveys.« less

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.

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.

The Scale Sizes of Globular Clusters: Tidal Limits, Evolution, and the Outer Halo

NASA Astrophysics Data System (ADS)

Harris, William

2011-10-01

The physical factors that determine the linear sizes of massive star clusters are not well understood. Their scale sizes were long thought to be governed by the tidal field of the parent galaxy, but major questions are now emerging. Globular clusters, for example, have mean sizes nearly independent of location in the halo. Paradoxically, the recently discovered "anomalous extended clusters" in M31 and elsewhere have scale sizes that fit much better with tidal theory, but they are puzzlingly rare. Lastly, the persistent size difference between metal-poor and metal-rich clusters still lacks a quantitative explanation. Many aspects of these observations call for better modelling of dynamical evolution in the outskirts of clusters, and also their conditions of formation including the early rapid mass loss phase of protoclusters. A new set of accurate measurements of scale sizes and structural parameters, for a large and homogeneous set of globular clusters, would represent a major advance in this subject. We propose to carry out a {WFC3+ACS} imaging survey of the globular clusters in the supergiant Virgo elliptical M87 to cover the complete run of the halo. M87 is an optimum target system because of its huge numbers of clusters and HST's ability to resolve the cluster profiles accurately. We will derive cluster effective radii, central concentrations, luminosities, and colors for more than 4000 clusters using PSF-convolved King-model profile fitting. In parallel, we are developing theoretical tools to model the expected distribution of cluster sizes versus galactocentric distance as functions of cluster mass, concentration, and orbital anisotropy.

Large-scale structure from cosmic-string loops in a baryon-dominated universe

NASA Technical Reports Server (NTRS)

Melott, Adrian L.; Scherrer, Robert J.

1988-01-01

The results are presented of a numerical simulation of the formation of large-scale structure in a universe with Omega(0) = 0.2 and h = 0.5 dominated by baryons in which cosmic strings provide the initial density perturbations. The numerical model yields a power spectrum. Nonlinear evolution confirms that the model can account for 700 km/s bulk flows and a strong cluster-cluster correlation, but does rather poorly on smaller scales. There is no visual 'filamentary' structure, and the two-point correlation has too steep a logarithmic slope. The value of G mu = 4 x 10 to the -6th is significantly lower than previous estimates for the value of G mu in baryon-dominated cosmic string models.

Efficient electronic structure theory via hierarchical scale-adaptive coupled-cluster formalism: I. Theory and computational complexity analysis

NASA Astrophysics Data System (ADS)

Lyakh, Dmitry I.

2018-03-01

A novel reduced-scaling, general-order coupled-cluster approach is formulated by exploiting hierarchical representations of many-body tensors, combined with the recently suggested formalism of scale-adaptive tensor algebra. Inspired by the hierarchical techniques from the renormalisation group approach, H/H2-matrix algebra and fast multipole method, the computational scaling reduction in our formalism is achieved via coarsening of quantum many-body interactions at larger interaction scales, thus imposing a hierarchical structure on many-body tensors of coupled-cluster theory. In our approach, the interaction scale can be defined on any appropriate Euclidean domain (spatial domain, momentum-space domain, energy domain, etc.). We show that the hierarchically resolved many-body tensors can reduce the storage requirements to O(N), where N is the number of simulated quantum particles. Subsequently, we prove that any connected many-body diagram consisting of a finite number of arbitrary-order tensors, e.g. an arbitrary coupled-cluster diagram, can be evaluated in O(NlogN) floating-point operations. On top of that, we suggest an additional approximation to further reduce the computational complexity of higher order coupled-cluster equations, i.e. equations involving higher than double excitations, which otherwise would introduce a large prefactor into formal O(NlogN) scaling.

Effectiveness and cost-effectiveness of telehealthcare for chronic obstructive pulmonary disease: study protocol for a cluster randomized controlled trial.

PubMed

Udsen, Flemming Witt; Lilholt, Pernille Heyckendorff; Hejlesen, Ole; Ehlers, Lars Holger

2014-05-21

Several feasibility studies show promising results of telehealthcare on health outcomes and health-related quality of life for patients suffering from chronic obstructive pulmonary disease, and some of these studies show that telehealthcare may even lower healthcare costs. However, the only large-scale trial we have so far - the Whole System Demonstrator Project in England - has raised doubts about these results since it conclude that telehealthcare as a supplement to usual care is not likely to be cost-effective compared with usual care alone. The present study is known as 'TeleCare North' in Denmark. It seeks to address these doubts by implementing a large-scale, pragmatic, cluster-randomized trial with nested economic evaluation. The purpose of the study is to assess the effectiveness and the cost-effectiveness of a telehealth solution for patients suffering from chronic obstructive pulmonary disease compared to usual practice. General practitioners will be responsible for recruiting eligible participants (1,200 participants are expected) for the trial in the geographical area of the North Denmark Region. Twenty-six municipality districts in the region define the randomization clusters. The primary outcomes are changes in health-related quality of life, and the incremental cost-effectiveness ratio measured from baseline to follow-up at 12 months. Secondary outcomes are changes in mortality and physiological indicators (diastolic and systolic blood pressure, pulse, oxygen saturation, and weight). There has been a call for large-scale clinical trials with rigorous cost-effectiveness assessments in telehealthcare research. This study is meant to improve the international evidence base for the effectiveness and cost-effectiveness of telehealthcare to patients suffering from chronic obstructive pulmonary disease by implementing a large-scale pragmatic cluster-randomized clinical trial. Clinicaltrials.gov, http://NCT01984840, November 14, 2013.

pycola: N-body COLA method code

NASA Astrophysics Data System (ADS)

Tassev, Svetlin; Eisenstein, Daniel J.; Wandelt, Benjamin D.; Zaldarriagag, Matias

2015-09-01

pycola is a multithreaded Python/Cython N-body code, implementing the Comoving Lagrangian Acceleration (COLA) method in the temporal and spatial domains, which trades accuracy at small-scales to gain computational speed without sacrificing accuracy at large scales. This is especially useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing. The COLA method achieves its speed by calculating the large-scale dynamics exactly using LPT while letting the N-body code solve for the small scales, without requiring it to capture exactly the internal dynamics of halos.

Cluster richness-mass calibration with cosmic microwave background lensing

NASA Astrophysics Data System (ADS)

Geach, James E.; Peacock, John A.

2017-11-01

Identifying galaxy clusters through overdensities of galaxies in photometric surveys is the oldest1,2 and arguably the most economical and mass-sensitive detection method3,4, compared with X-ray5-7 and Sunyaev-Zel'dovich effect8 surveys that detect the hot intracluster medium. However, a perennial problem has been the mapping of optical `richness' measurements onto total cluster mass3,9-12. Emitted at a conformal distance of 14 gigaparsecs, the cosmic microwave background acts as a backlight to all intervening mass in the Universe, and therefore has been gravitationally lensed13-15. Experiments such as the Atacama Cosmology Telescope16, South Pole Telescope17-19 and the Planck20 satellite have now detected gravitational lensing of the cosmic microwave background and produced large-area maps of the foreground deflecting structures. Here we present a calibration of cluster optical richness at the 10% level by measuring the average cosmic microwave background lensing measured by Planck towards the positions of large numbers of optically selected clusters, detecting the deflection of photons by structures of total mass of order 1014 M⊙. Although mainly aimed at the study of larger-scale structures, the Planck estimate of the cosmic microwave background lensing field can be used to recover a nearly unbiased lensing signal for stacked clusters on arcminute scales15,21. This approach offers a clean measure of total cluster masses over most of cosmic history, largely independent of baryon physics.

Clusters of Galaxies at High Redshift

NASA Astrophysics Data System (ADS)

Fort, Bernard

For a long time, the small number of clusters at z > 0.3 in the Abell survey catalogue and simulations of the standard CDM formation of large scale structures provided a paradigm where clusters were considered as young merging structures. At earlier times, loose concentrations of galaxy clumps were mostly anticipated. Recent observations broke the taboo. Progressively we became convinced that compact and massive clusters at z = 1 or possibly beyond exist and should be searched for.

Cluster Lensing with the BTC

NASA Astrophysics Data System (ADS)

Fischer, P.

1997-12-01

Weak distortions of background galaxies are rapidly emerging as a powerful tool for the measurement of galaxy cluster mass distributions. Lensing based studies have the advantage of being direct measurements of mass and are not model-dependent as are other techniques (X-ray, radial velocities). To date studies have been limited by CCD field size meaning that full coverage of the clusters out to the virial radii and beyond has not been possible. Probing this large radius region is essential for testing models of large scale structure formation. New wide field CCD mosaics, for the first time, allow mass measurements out to very large radius. We have obtained images for a sample of clusters with the ``Big Throughput Camera'' (BTC) on the CTIO 4m. This camera comprises four thinned SITE 2048(2) CCDs, each 15arcmin on a side for a total area of one quarter of a square degree. We have developed an automated reduction pipeline which: 1) corrects for spatial distortions, 2) corrects for PSF anisotropy, 3) determines relative scaling and background levels, and 4) combines multiple exposures. In this poster we will present some preliminary results of our cluster lensing study. This will include radial mass and light profiles and 2-d mass and galaxy density maps.

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

The Impact of Non-Thermal Processes in the Intracluster Medium on Cosmological Cluster Observables

NASA Astrophysics Data System (ADS)

Battaglia, Nicholas Ambrose

In this thesis we describe the generation and analysis of hydrodynamical simulations of galaxy clusters and their intracluster medium (ICM), using large cosmological boxes to generate large samples, in conjunction with individual cluster computations. The main focus is the exploration of the non-thermal processes in the ICM and the effect they have on the interpretation of observations used for cosmological constraints. We provide an introduction to the cosmological structure formation framework for our computations and an overview of the numerical simulations and observations of galaxy clusters. We explore the cluster magnetic field observables through radio relics, extended entities in the ICM characterized by their of diffuse radio emission. We show that statistical quantities such as radio relic luminosity functions and rotation measure power spectra are sensitive to magnetic field models. The spectral index of the radio relic emission provides information on structure formation shocks, e.g., on their Mach number. We develop a coarse grained stochastic model of active galaxy nucleus (AGN) feed-back in clusters and show the impact of such inhomogeneous feedback on the thermal pressure profile. We explore variations in the pressure profile as a function of cluster mass, redshift, and radius and provide a constrained fitting function for this profile. We measure the degree of the non-thermal pressure in the gas from internal cluster bulk motions and show it has an impact on the slope and scatter of the Sunyaev-Zel'dovich (SZ) scaling relation. We also find that the gross shape of the ICM, as characterized by scaled moment of inertia tensors, affects the SZ scaling relation. We demonstrate that the shape and the amplitude of the SZ angular power spectrum is sensitive to AGN feedback, and this affects the cosmological parameters determined from high resolution ACT and SPT cosmic microwave background data. We compare analytic, semi-analytic, and simulation-based methods for calculating the SZ power spectrum, and characterize their differences. All the methods must rely, one way or another, on high resolution large-scale hydrodynamical simulations with varying assumptions for modelling the gas of the sort presented here. We show how our results can be used to interpret the latest ACT and SPT power spectrum results. We provide an outlook for the future, describing follow-up work we are undertaking to further advance the theory of cluster science.

A scaling theory for number-flux distributions generated during steady-state coagulation and settling and application to particles in Lake Zurich, Switzerland.

PubMed

Boehm, Alexandria B

2002-10-15

In this study, we extend the established scaling theory for cluster size distributions generated during unsteady coagulation to number-flux distributions that arise during steady-state coagulation and settling in an unmixed water mass. The scaling theory predicts self-similar number-flux distributions and power-law decay of total number flux with depth. The shape of the number-flux distributions and the power-law exponent describing the decay of the total number flux are shown to depend on the homogeneity and small i/j limit of the coagulation kernel and the exponent kappa, which describes the variation in settling velocity with cluster volume. Particle field measurements from Lake Zurich, collected by U. Weilenmann and co-workers (Limnol. Oceanogr.34, 1 (1989)), are used to illustrate how the scaling predictions can be applied to a natural system. This effort indicates that within the mid-depth region of Lake Zurich, clusters of the same size preferentially interact and large clusters react with one another more quickly than small ones, indicative of clusters coagulating in a reaction-limited regime.

Sparse maps—A systematic infrastructure for reduced-scaling electronic structure methods. II. Linear scaling domain based pair natural orbital coupled cluster theory

NASA Astrophysics Data System (ADS)

Riplinger, Christoph; Pinski, Peter; Becker, Ute; Valeev, Edward F.; Neese, Frank

2016-01-01

Domain based local pair natural orbital coupled cluster theory with single-, double-, and perturbative triple excitations (DLPNO-CCSD(T)) is a highly efficient local correlation method. It is known to be accurate and robust and can be used in a black box fashion in order to obtain coupled cluster quality total energies for large molecules with several hundred atoms. While previous implementations showed near linear scaling up to a few hundred atoms, several nonlinear scaling steps limited the applicability of the method for very large systems. In this work, these limitations are overcome and a linear scaling DLPNO-CCSD(T) method for closed shell systems is reported. The new implementation is based on the concept of sparse maps that was introduced in Part I of this series [P. Pinski, C. Riplinger, E. F. Valeev, and F. Neese, J. Chem. Phys. 143, 034108 (2015)]. Using the sparse map infrastructure, all essential computational steps (integral transformation and storage, initial guess, pair natural orbital construction, amplitude iterations, triples correction) are achieved in a linear scaling fashion. In addition, a number of additional algorithmic improvements are reported that lead to significant speedups of the method. The new, linear-scaling DLPNO-CCSD(T) implementation typically is 7 times faster than the previous implementation and consumes 4 times less disk space for large three-dimensional systems. For linear systems, the performance gains and memory savings are substantially larger. Calculations with more than 20 000 basis functions and 1000 atoms are reported in this work. In all cases, the time required for the coupled cluster step is comparable to or lower than for the preceding Hartree-Fock calculation, even if this is carried out with the efficient resolution-of-the-identity and chain-of-spheres approximations. The new implementation even reduces the error in absolute correlation energies by about a factor of two, compared to the already accurate previous implementation.

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.

UPDATED MASS SCALING RELATIONS FOR NUCLEAR STAR CLUSTERS AND A COMPARISON TO SUPERMASSIVE BLACK HOLES

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

Scott, Nicholas; Graham, Alister W.

2013-02-15

We investigate whether or not nuclear star clusters and supermassive black holes (SMBHs) follow a common set of mass scaling relations with their host galaxy's properties, and hence can be considered to form a single class of central massive object (CMO). We have compiled a large sample of galaxies with measured nuclear star cluster masses and host galaxy properties from the literature and fit log-linear scaling relations. We find that nuclear star cluster mass, M {sub NC}, correlates most tightly with the host galaxy's velocity dispersion: log M {sub NC} = (2.11 {+-} 0.31)log ({sigma}/54) + (6.63 {+-} 0.09), butmore » has a slope dramatically shallower than the relation defined by SMBHs. We find that the nuclear star cluster mass relations involving host galaxy (and spheroid) luminosity and stellar and dynamical mass, intercept with but are in general shallower than the corresponding black hole scaling relations. In particular, M {sub NC}{proportional_to}M {sup 0.55{+-}0.15} {sub Gal,dyn}; the nuclear cluster mass is not a constant fraction of its host galaxy or spheroid mass. We conclude that nuclear stellar clusters and SMBHs do not form a single family of CMOs.« less

Quantitative analysis of voids in percolating structures in two-dimensional N-body simulations

NASA Technical Reports Server (NTRS)

Harrington, Patrick M.; Melott, Adrian L.; Shandarin, Sergei F.

1993-01-01

We present in this paper a quantitative method for defining void size in large-scale structure based on percolation threshold density. Beginning with two-dimensional gravitational clustering simulations smoothed to the threshold of nonlinearity, we perform percolation analysis to determine the large scale structure. The resulting objective definition of voids has a natural scaling property, is topologically interesting, and can be applied immediately to redshift surveys.

Examining the Emergence of Large-Scale Structures in Collaboration Networks: Methods in Sociological Analysis

ERIC Educational Resources Information Center

Ghosh, Jaideep; Kshitij, Avinash

2017-01-01

This article introduces a number of methods that can be useful for examining the emergence of large-scale structures in collaboration networks. The study contributes to sociological research by investigating how clusters of research collaborators evolve and sometimes percolate in a collaboration network. Typically, we find that in our networks,…

Nonlinear modulation of the HI power spectrum on ultra-large scales. I

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

Umeh, Obinna; Maartens, Roy; Santos, Mario, E-mail: umeobinna@gmail.com, E-mail: roy.maartens@gmail.com, E-mail: mgrsantos@uwc.ac.za

2016-03-01

Intensity mapping of the neutral hydrogen brightness temperature promises to provide a three-dimensional view of the universe on very large scales. Nonlinear effects are typically thought to alter only the small-scale power, but we show how they may bias the extraction of cosmological information contained in the power spectrum on ultra-large scales. For linear perturbations to remain valid on large scales, we need to renormalize perturbations at higher order. In the case of intensity mapping, the second-order contribution to clustering from weak lensing dominates the nonlinear contribution at high redshift. Renormalization modifies the mean brightness temperature and therefore the evolutionmore » bias. It also introduces a term that mimics white noise. These effects may influence forecasting analysis on ultra-large scales.« less

The MUSIC of galaxy clusters - II. X-ray global properties and scaling relations

NASA Astrophysics Data System (ADS)

Biffi, V.; Sembolini, F.; De Petris, M.; Valdarnini, R.; Yepes, G.; Gottlöber, S.

2014-03-01

We present the X-ray properties and scaling relations of a large sample of clusters extracted from the Marenostrum MUltidark SImulations of galaxy Clusters (MUSIC) data set. We focus on a sub-sample of 179 clusters at redshift z ˜ 0.11, with 3.2 × 1014 h-1 M⊙ < Mvir < 2 × 1015 h-1 M⊙, complete in mass. We employed the X-ray photon simulator PHOX to obtain synthetic Chandra observations and derive observable-like global properties of the intracluster medium (ICM), as X-ray temperature (TX) and luminosity (LX). TX is found to slightly underestimate the true mass-weighted temperature, although tracing fairly well the cluster total mass. We also study the effects of TX on scaling relations with cluster intrinsic properties: total (M500 and gas Mg,500 mass; integrated Compton parameter (YSZ) of the Sunyaev-Zel'dovich (SZ) thermal effect; YX = Mg,500 TX. We confirm that YX is a very good mass proxy, with a scatter on M500-YX and YSZ-YX lower than 5 per cent. The study of scaling relations among X-ray, intrinsic and SZ properties indicates that simulated MUSIC clusters reasonably resemble the self-similar prediction, especially for correlations involving TX. The observational approach also allows for a more direct comparison with real clusters, from which we find deviations mainly due to the physical description of the ICM, affecting TX and, particularly, LX.

HIGH-ENERGY NEUTRINOS FROM SOURCES IN CLUSTERS OF GALAXIES

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

Fang, Ke; Olinto, Angela V.

2016-09-01

High-energy cosmic rays can be accelerated in clusters of galaxies, by mega-parsec scale shocks induced by the accretion of gas during the formation of large-scale structures, or by powerful sources harbored in clusters. Once accelerated, the highest energy particles leave the cluster via almost rectilinear trajectories, while lower energy ones can be confined by the cluster magnetic field up to cosmological time and interact with the intracluster gas. Using a realistic model of the baryon distribution and the turbulent magnetic field in clusters, we studied the propagation and hadronic interaction of high-energy protons in the intracluster medium. We report themore » cumulative cosmic-ray and neutrino spectra generated by galaxy clusters, including embedded sources, and demonstrate that clusters can contribute a significant fraction of the observed IceCube neutrinos above 30 TeV while remaining undetected in high-energy cosmic rays and γ rays for reasonable choices of parameters and source scenarios.« less

A quasi-static approach to structure formation in black hole universes

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

Durk, Jessie; Clifton, Timothy, E-mail: j.durk@qmul.ac.uk, E-mail: t.clifton@qmul.ac.uk

Motivated by the existence of hierarchies of structure in the Universe, we present four new families of exact initial data for inhomogeneous cosmological models at their maximum of expansion. These data generalise existing black hole lattice models to situations that contain clusters of masses, and hence allow the consequences of cosmological structures to be considered in a well-defined and non-perturbative fashion. The degree of clustering is controlled by a parameter λ, in such a way that for λ ∼ 0 or 1 we have very tightly clustered masses, whilst for λ ∼ 0.5 all masses are separated by cosmological distancemore » scales. We study the consequences of structure formation on the total net mass in each of our clusters, as well as calculating the cosmological consequences of the interaction energies both within and between clusters. The locations of the shared horizons that appear around groups of black holes, when they are brought sufficiently close together, are also identified and studied. We find that clustering can have surprisingly large effects on the scale of the cosmology, with models that contain thousands of black holes sometimes being as little as 30% of the size of comparable Friedmann models with the same total proper mass. This deficit is comparable to what might be expected to occur from neglecting gravitational interaction energies in Friedmann cosmology, and suggests that these quantities may have a significant influence on the properties of the large-scale cosmology.« less

A roadmap for natural product discovery based on large-scale genomics and metabolomics

USDA-ARS?s Scientific Manuscript database

Actinobacteria encode a wealth of natural product biosynthetic gene clusters, whose systematic study is complicated by numerous repetitive motifs. By combining several metrics we developed a method for global classification of these gene clusters into families (GCFs) and analyzed the biosynthetic ca...

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

Clusters of Galaxies

NASA Astrophysics Data System (ADS)

Huchtmeier, W. K.; Richter, O. G.; Materne, J.

1981-09-01

The large-scale structure of the universe is dominated by clustering. Most galaxies seem to be members of pairs, groups, clusters, and superclusters. To that degree we are able to recognize a hierarchical structure of the universe. Our local group of galaxies (LG) is centred on two large spiral galaxies: the Andromeda nebula and our own galaxy. Three sr:naller galaxies - like M 33 - and at least 23 dwarf galaxies (KraanKorteweg and Tammann, 1979, Astronomische Nachrichten, 300, 181) can be found in the evironment of these two large galaxies. Neighbouring groups have comparable sizes (about 1 Mpc in extent) and comparable numbers of bright members. Small dwarf galaxies cannot at present be observed at great distances.

Descriptor Fingerprints and Their Application to WhiteWine Clustering and Discrimination.

NASA Astrophysics Data System (ADS)

Bangov, I. P.; Moskovkina, M.; Stojanov, B. P.

2018-03-01

This study continues the attempt to use the statistical process for a large-scale analytical data. A group of 3898 white wines, each with 11 analytical laboratory benchmarks was analyzed by a fingerprint similarity search in order to be grouped into separate clusters. A characterization of the wine's quality in each individual cluster was carried out according to individual laboratory parameters.

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).

Large-Scale Structure Studies with the REFLEX Cluster Survey

NASA Astrophysics Data System (ADS)

Schuecker, P.; Bohringer, H.; Guzzo, L.; Collins, C.; Neumann, D. M.; Schindler, S.; Voges, W.

1998-12-01

First preliminary results of the ROSAT ESO Flux-Limited X-Ray (REFLEX) Cluster Survey are described. The survey covers 13,924 square degrees of the southern hemisphere. The present sample consists of about 470 rich clusters (1/3 non Abell/ACO clusters) with X-ray fluxes S >= 3.0 times 10^{-12} erg s^{-1} cm^{-2} (0.1-2.4 keV) and redshifts z <= 0.3. In contrast to other low-redshift surveys, the cumulative flux-number counts have an almost Euclidean slope. Comoving cluster number densities are found to be almost redshift-independent throughout the total survey volume. The X-ray luminosity function is well described by a Schechter function. The power spectrum of the number density fluctuations could be measured on scales up to 400 h^{-1} Mpc. A deeper survey with about 800 galaxy clusters in the same area is in progress.

Collisions in Compact Star Clusters.

NASA Astrophysics Data System (ADS)

Portegies Zwart, S. F.

The high stellar densities in young compact star clusters, such as the star cluster R136 in the 30 Doradus region, may lead to a large number of stellar collisions. Such collisions were recently found to be much more frequent than previous estimates. The number of collisions scales with the number of stars for clusters with the same initial relaxation time. These collisions take place in a few million years. The collision products may finally collapse into massive black holes. The fraction of the total mass in the star cluster which ends up in a single massive object scales with the total mass of the cluster and its relaxation time. This mass fraction is rather constant, within a factor two or so. Wild extrapolation from the relatively small masses of the studied systems to the cores of galactic nuclei may indicate that the massive black holes in these systems have formed in a similar way.

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.

Atomic-scale structure and electronic properties of GaN/GaAs superlattices

NASA Astrophysics Data System (ADS)

Goldman, R. S.; Feenstra, R. M.; Briner, B. G.; O'Steen, M. L.; Hauenstein, R. J.

1996-12-01

We have investigated the atomic-scale structure and electronic properties of GaN/GaAs superlattices produced by nitridation of a molecular beam epitaxially grown GaAs surface. Using cross-sectional scanning tunneling microscopy (STM) and spectroscopy, we show that the nitrided layers are laterally inhomogeneous, consisting of groups of atomic-scale defects and larger clusters. Analysis of x-ray diffraction data in terms of fractional area of clusters (determined by STM), reveals a cluster lattice constant similar to bulk GaN. In addition, tunneling spectroscopy on the defects indicates a conduction band state associated with an acceptor level of NAs in GaAs. Therefore, we identify the clusters and defects as nearly pure GaN and NAs, respectively. Together, the results reveal phase segregation in these arsenide/nitride structures, in agreement with the large miscibility gap predicted for GaAsN.

DISCOVERY OF A LARGE NUMBER OF CANDIDATE PROTOCLUSTERS TRACED BY ∼15 Mpc-SCALE GALAXY OVERDENSITIES IN COSMOS

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

Chiang, Yi-Kuan; Gebhardt, Karl; Overzier, Roderik

2014-02-10

To demonstrate the feasibility of studying the epoch of massive galaxy cluster formation in a more systematic manner using current and future galaxy surveys, we report the discovery of a large sample of protocluster candidates in the 1.62 deg{sup 2} COSMOS/UltraVISTA field traced by optical/infrared selected galaxies using photometric redshifts. By comparing properly smoothed three-dimensional galaxy density maps of the observations and a set of matched simulations incorporating the dominant observational effects (galaxy selection and photometric redshift uncertainties), we first confirm that the observed ∼15 comoving Mpc-scale galaxy clustering is consistent with ΛCDM models. Using further the relation between high-z overdensitymore » and the present day cluster mass calibrated in these matched simulations, we found 36 candidate structures at 1.6 < z < 3.1, showing overdensities consistent with the progenitors of M{sub z} {sub =} {sub 0} ∼ 10{sup 15} M {sub ☉} clusters. Taking into account the significant upward scattering of lower mass structures, the probabilities for the candidates to have at least M{sub z=} {sub 0} ∼ 10{sup 14} M {sub ☉} are ∼70%. For each structure, about 15%-40% of photometric galaxy candidates are expected to be true protocluster members that will merge into a cluster-scale halo by z = 0. With solely photometric redshifts, we successfully rediscover two spectroscopically confirmed structures in this field, suggesting that our algorithm is robust. This work generates a large sample of uniformly selected protocluster candidates, providing rich targets for spectroscopic follow-up and subsequent studies of cluster formation. Meanwhile, it demonstrates the potential for probing early cluster formation with upcoming redshift surveys such as the Hobby-Eberly Telescope Dark Energy Experiment and the Subaru Prime Focus Spectrograph survey.« less

Graph Based Models for Unsupervised High Dimensional Data Clustering and Network Analysis

DTIC Science & Technology

2015-01-01

ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for...algorithms we proposed improve the time e ciency signi cantly for large scale datasets. In the last chapter, we also propose an incremental reseeding...plume detection in hyper-spectral video data. These graph based clustering algorithms we proposed improve the time efficiency significantly for large

SEEDisCs: How Clusters Form and Galaxies Transform in the Cosmic Web

NASA Astrophysics Data System (ADS)

Jablonka, P.

2017-08-01

This presentation introduces a new survey, the Spatial Extended EDisCS Survey (SEEDisCS), which aims at understanding how clusters assemble and the level at which galaxies are preprocessed before falling on the cluster cores. I focus on the changes in galaxy properties in the cluster large scale environments, and how we can get constraints on the timescale of star formation quenching. I also discuss new ALMA CO observations, which trace the fate of the galaxy cold gas content along the infalling paths towards the cluster cores.

Galaxy clusters in simulations of the local Universe: a matter of constraints

NASA Astrophysics Data System (ADS)

Sorce, Jenny G.; Tempel, Elmo

2018-06-01

To study the full formation and evolution history of galaxy clusters and their population, high-resolution simulations of the latter are flourishing. However, comparing observed clusters to the simulated ones on a one-to-one basis to refine the models and theories down to the details is non-trivial. The large variety of clusters limits the comparisons between observed and numerical clusters. Simulations resembling the local Universe down to the cluster scales permit pushing the limit. Simulated and observed clusters can be matched on a one-to-one basis for direct comparisons provided that clusters are well reproduced besides being in the proper large-scale environment. Comparing random and local Universe-like simulations obtained with differently grouped observational catalogues of peculiar velocities, this paper shows that the grouping scheme used to remove non-linear motions in the catalogues that constrain the simulations affects the quality of the numerical clusters. With a less aggressive grouping scheme - galaxies still falling on to clusters are preserved - combined with a bias minimization scheme, the mass of the dark matter haloes, simulacra for five local clusters - Virgo, Centaurus, Coma, Hydra, and Perseus - is increased by 39 per cent closing the gap with observational mass estimates. Simulacra are found on average in 89 per cent of the simulations, an increase of 5 per cent with respect to the previous grouping scheme. The only exception is Perseus. Since the Perseus-Pisces region is not well covered by the used peculiar velocity catalogue, the latest release lets us foresee a better simulacrum for Perseus in a near future.

Ecological Consistency of SSU rRNA-Based Operational Taxonomic Units at a Global Scale

PubMed Central

Schmidt, Thomas S. B.; Matias Rodrigues, João F.; von Mering, Christian

2014-01-01

Operational Taxonomic Units (OTUs), usually defined as clusters of similar 16S/18S rRNA sequences, are the most widely used basic diversity units in large-scale characterizations of microbial communities. However, it remains unclear how well the various proposed OTU clustering algorithms approximate ‘true’ microbial taxa. Here, we explore the ecological consistency of OTUs – based on the assumption that, like true microbial taxa, they should show measurable habitat preferences (niche conservatism). In a global and comprehensive survey of available microbial sequence data, we systematically parse sequence annotations to obtain broad ecological descriptions of sampling sites. Based on these, we observe that sequence-based microbial OTUs generally show high levels of ecological consistency. However, different OTU clustering methods result in marked differences in the strength of this signal. Assuming that ecological consistency can serve as an objective external benchmark for cluster quality, we conclude that hierarchical complete linkage clustering, which provided the most ecologically consistent partitions, should be the default choice for OTU clustering. To our knowledge, this is the first approach to assess cluster quality using an external, biologically meaningful parameter as a benchmark, on a global scale. PMID:24763141

Galaxy Evolution Viewed as Functions of Environment and Mass

NASA Astrophysics Data System (ADS)

Kodama, Tadayuki; Tanaka, Masayuki; Tanaka, Ichi; Kajisawa, Masaru

We present two large surveys of distant clusters currently being carried out with Subaru, making use of its great capability of wide-field study both in the optical and in the near-infrared. The optical surveys, called PISCES, have mapped out large scale structures in and around 8 distant clusters at 0.4 < z <1.3, composed of multiple filaments and clumps extended over 15-30 Mpc scale. From the photometric and spectroscopic properties of galaxies over a wide range in environment, we find that the truncation of galaxies is seen in the outskirts of clusters rather than in the cluster cores.We also see a clear environmental dependence of the down-sizing (progressively later quenching of star formation in smaller galaxies). The near-infrared surveys are being conducted with a new wide-field instrument targeting proto-clusters around high-zradio-loud galaxies up to z ~4. Most of these field are known to show a large number of Lyαand/or Hαemitters at the same redshifts of the radio galaxies. We see a clear excess of near-infrared selected galaxies (JHK s -selected galaxies as well as DRG) in these fields, and they are indeed proto-clusters with not only young emitters but also evolved populations. Spatial distribution of such NIR selected galaxies is filamentary and track similar structures traced by the emitters. There is an hint that the bright-end of the red sequence first appeared between z= 3 and 2.

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

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.

The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth

ERIC Educational Resources Information Center

Steyvers, Mark; Tenenbaum, Joshua B.

2005-01-01

We present statistical analyses of the large-scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small-world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of…

The separate and combined effects of baryon physics and neutrino free streaming on large-scale structure

NASA Astrophysics Data System (ADS)

Mummery, Benjamin O.; McCarthy, Ian G.; Bird, Simeon; Schaye, Joop

2017-10-01

We use the cosmo-OWLS and bahamas suites of cosmological hydrodynamical simulations to explore the separate and combined effects of baryon physics (particularly feedback from active galactic nuclei, AGN) and free streaming of massive neutrinos on large-scale structure. We focus on five diagnostics: (I) the halo mass function, (II) halo mass density profiles, (III) the halo mass-concentration relation, (IV) the clustering of haloes and (v) the clustering of matter, and we explore the extent to which the effects of baryon physics and neutrino free streaming can be treated independently. Consistent with previous studies, we find that both AGN feedback and neutrino free streaming suppress the total matter power spectrum, although their scale and redshift dependences differ significantly. The inclusion of AGN feedback can significantly reduce the masses of groups and clusters, and increase their scale radii. These effects lead to a decrease in the amplitude of the mass-concentration relation and an increase in the halo autocorrelation function at fixed mass. Neutrinos also lower the masses of groups and clusters while having no significant effect on the shape of their density profiles (thus also affecting the mass-concentration relation and halo clustering in a qualitatively similar way to feedback). We show that, with only a small number of exceptions, the combined effects of baryon physics and neutrino free streaming on all five diagnostics can be estimated to typically better than a few per cent accuracy by treating these processes independently (I.e. by multiplying their separate effects).

Basic Equations Interrelate Atomic and Nuclear Properties to Patterns at the Size Scales of the Cosmos, Extended Clusters of Galaxies, Galaxies, and Nebulae

NASA Astrophysics Data System (ADS)

Allen, Rob

2016-09-01

Structures within molecules and nuclei have relationships to astronomical patterns. The COBE cosmic scale plots, and large scale surveys of galaxy clusters have patterns also repeating and well known at atomic scales. The Induction, Strong Force, and Nuclear Binding Energy Periods within the Big Bang are revealed to have played roles in the formation of these large scale distributions. Equations related to the enormous patterns also model chemical bonds and likely nucleus and nucleon substructures. ratios of the forces that include gravity are accurately calculated from the distributions and shapes. In addition, particle masses and a great many physical constants can be derived with precision and accuracy from astrophysical shapes. A few very basic numbers can do modelling from nucleon internals to molecules to super novae, and up to the Visible Universe. Equations are also provided along with possible structural configurations for some Cold Dark Matter and Dark Energy.

Detecting communities in large networks

NASA Astrophysics Data System (ADS)

Capocci, A.; Servedio, V. D. P.; Caldarelli, G.; Colaiori, F.

2005-07-01

We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.

Formation of large-scale structure from cosmic strings and massive neutrinos

NASA Technical Reports Server (NTRS)

Scherrer, Robert J.; Melott, Adrian L.; Bertschinger, Edmund

1989-01-01

Numerical simulations of large-scale structure formation from cosmic strings and massive neutrinos are described. The linear power spectrum in this model resembles the cold-dark-matter power spectrum. Galaxy formation begins early, and the final distribution consists of isolated density peaks embedded in a smooth background, leading to a natural bias in the distribution of luminous matter. The distribution of clustered matter has a filamentary appearance with large voids.

DISPLACEMENT CASCADE SIMULATION IN TUNGSTEN UP TO 200 KEV OF DAMAGE ENERGY AT 300, 1025, AND 2050 K

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

Setyawan, Wahyu; Nandipati, Giridhar; Roche, Kenneth J.

2015-09-22

We generated molecular dynamics database of primary defects that adequately covers the range of tungsten recoil energy imparted by 14-MeV neutrons. During this semi annual period, cascades at 150 and 200 keV at 300 and 1025 K were simulated. Overall, we included damage energy up to 200 keV at 300 and 1025 K, and up to 100 keV at 2050 K. We report the number of surviving Frenkel pairs (NF) and the size distribution of defect clusters. The slope of the NF curve versus cascade damage energy (EMD), on a log-log scale, changes at a transition energy (μ). For EMDmore » > μ, the cascade forms interconnected damage regions that facilitate the formation of large clusters of defects. At 300 K and EMD = 200 keV, the largest size of interstitial cluster and vacancy cluster is 266 and 335, respectively. Similarly, at 1025 K and EMD = 200 keV, the largest size of interstitial cluster and vacancy cluster is 296 and 338, respectively. At 2050 K, large interstitial clusters also routinely form, but practically no large vacancy clusters do« less

Prokaryotic Gene Clusters: A Rich Toolbox for Synthetic Biology

PubMed Central

Fischbach, Michael; Voigt, Christopher A.

2014-01-01

Bacteria construct elaborate nanostructures, obtain nutrients and energy from diverse sources, synthesize complex molecules, and implement signal processing to react to their environment. These complex phenotypes require the coordinated action of multiple genes, which are often encoded in a contiguous region of the genome, referred to as a gene cluster. Gene clusters sometimes contain all of the genes necessary and sufficient for a particular function. As an evolutionary mechanism, gene clusters facilitate the horizontal transfer of the complete function between species. Here, we review recent work on a number of clusters whose functions are relevant to biotechnology. Engineering these clusters has been hindered by their regulatory complexity, the need to balance the expression of many genes, and a lack of tools to design and manipulate DNA at this scale. Advances in synthetic biology will enable the large-scale bottom-up engineering of the clusters to optimize their functions, wake up cryptic clusters, or to transfer them between organisms. Understanding and manipulating gene clusters will move towards an era of genome engineering, where multiple functions can be “mixed-and-matched” to create a designer organism. PMID:21154668

A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network

PubMed Central

Chen, Yuzhong; Weng, Shining; Guo, Wenzhong; Xiong, Naixue

2016-01-01

Vehicular ad hoc networks (VANETs) have an important role in urban management and planning. The effective integration of vehicle information in VANETs is critical to traffic analysis, large-scale vehicle route planning and intelligent transportation scheduling. However, given the limitations in the precision of the output information of a single sensor and the difficulty of information sharing among various sensors in a highly dynamic VANET, effectively performing data aggregation in VANETs remains a challenge. Moreover, current studies have mainly focused on data aggregation in large-scale environments but have rarely discussed the issue of intra-cluster data aggregation in VANETs. In this study, we propose a multi-player game theory algorithm for intra-cluster data aggregation in VANETs by analyzing the competitive and cooperative relationships among sensor nodes. Several sensor-centric metrics are proposed to measure the data redundancy and stability of a cluster. We then study the utility function to achieve efficient intra-cluster data aggregation by considering both data redundancy and cluster stability. In particular, we prove the existence of a unique Nash equilibrium in the game model, and conduct extensive experiments to validate the proposed algorithm. Results demonstrate that the proposed algorithm has advantages over typical data aggregation algorithms in both accuracy and efficiency. PMID:26907272

A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network.

PubMed

Chen, Yuzhong; Weng, Shining; Guo, Wenzhong; Xiong, Naixue

2016-02-19

Vehicular ad hoc networks (VANETs) have an important role in urban management and planning. The effective integration of vehicle information in VANETs is critical to traffic analysis, large-scale vehicle route planning and intelligent transportation scheduling. However, given the limitations in the precision of the output information of a single sensor and the difficulty of information sharing among various sensors in a highly dynamic VANET, effectively performing data aggregation in VANETs remains a challenge. Moreover, current studies have mainly focused on data aggregation in large-scale environments but have rarely discussed the issue of intra-cluster data aggregation in VANETs. In this study, we propose a multi-player game theory algorithm for intra-cluster data aggregation in VANETs by analyzing the competitive and cooperative relationships among sensor nodes. Several sensor-centric metrics are proposed to measure the data redundancy and stability of a cluster. We then study the utility function to achieve efficient intra-cluster data aggregation by considering both data redundancy and cluster stability. In particular, we prove the existence of a unique Nash equilibrium in the game model, and conduct extensive experiments to validate the proposed algorithm. Results demonstrate that the proposed algorithm has advantages over typical data aggregation algorithms in both accuracy and efficiency.

Using the morphology and magnetic fields of tailed radio galaxies as environmental probes

NASA Astrophysics Data System (ADS)

Johnston-Hollitt, M.; Dehghan, S.; Pratley, L.

2015-03-01

Bent-tailed (BT) radio sources have long been known to trace over densities in the Universe up to z ~ 1 and there is increasing evidence this association persists out to redshifts of 2. The morphology of the jets in BT galaxies is primarily a function of the environment that they have resided in and so BTs provide invaluable clues as to their local conditions. Thus, not only can samples of BT galaxies be used as signposts of large-scale structure, but are also valuable for obtaining a statistical measurement of properties of the intra-cluster medium including the presence of cluster accretion shocks & winds, and as historical anemometers, preserving the dynamical history of their surroundings in their jets. We discuss the use of BTs to unveil large-scale structure and provide an example in which a BT was used to unlock the dynamical history of its host cluster. In addition to their use as density and dynamical indicators, BTs are useful probes of the magnetic field on their environment on scales which are inaccessible to other methods. Here we discuss a novel way in which a particular sub-class of BTs, the so-called `corkscrew' galaxies might further elucidate the coherence lengths of the magnetic fields in their vicinity. Given that BTs are estimated to make up a large population in next generation surveys we posit that the use of jets in this way could provide a unique source of environmental information for clusters and groups up to z = 2.

Helium segregation on surfaces of plasma-exposed tungsten

DOE PAGES

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; ...

2016-01-21

Here we report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He-n (1 <= n <= 7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides themore » thermodynamic driving force for surface segregation. Elastic interaction force induces drift fluxes of these mobile Hen clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters' drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. Moreover, these near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.« less

Modulated Modularity Clustering as an Exploratory Tool for Functional Genomic Inference

PubMed Central

Stone, Eric A.; Ayroles, Julien F.

2009-01-01

In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC), seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity) that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation. PMID:19424432

Modeling and Testing Dark Energy and Gravity with Galaxy Cluster Data

NASA Astrophysics Data System (ADS)

Rapetti, David; Cataneo, Matteo; Heneka, Caroline; Mantz, Adam; Allen, Steven W.; Von Der Linden, Anja; Schmidt, Fabian; Lombriser, Lucas; Li, Baojiu; Applegate, Douglas; Kelly, Patrick; Morris, Glenn

2018-06-01

The abundance of galaxy clusters is a powerful probe to constrain the properties of dark energy and gravity at large scales. We employed a self-consistent analysis that includes survey, observable-mass scaling relations and weak gravitational lensing data to obtain constraints on f(R) gravity, which are an order of magnitude tighter than the best previously achieved, as well as on cold dark energy of negligible sound speed. The latter implies clustering of the dark energy fluid at all scales, allowing us to measure the effects of dark energy perturbations at cluster scales. For this study, we recalibrated the halo mass function using the following non-linear characteristic quantities: the spherical collapse threshold, the virial overdensity and an additional mass contribution for cold dark energy. We also presented a new modeling of the f(R) gravity halo mass function that incorporates novel corrections to capture key non-linear effects of the Chameleon screening mechanism, as found in high resolution N-body simulations. All these results permit us to predict, as I will also exemplify, and eventually obtain the next generation of cluster constraints on such models, and provide us with frameworks that can also be applied to other proposed dark energy and modified gravity models using cluster abundance observations.

A quantitative approach to the topology of large-scale structure. [for galactic clustering computation

NASA Technical Reports Server (NTRS)

Gott, J. Richard, III; Weinberg, David H.; Melott, Adrian L.

1987-01-01

A quantitative measure of the topology of large-scale structure: the genus of density contours in a smoothed density distribution, is described and applied. For random phase (Gaussian) density fields, the mean genus per unit volume exhibits a universal dependence on threshold density, with a normalizing factor that can be calculated from the power spectrum. If large-scale structure formed from the gravitational instability of small-amplitude density fluctuations, the topology observed today on suitable scales should follow the topology in the initial conditions. The technique is illustrated by applying it to simulations of galaxy clustering in a flat universe dominated by cold dark matter. The technique is also applied to a volume-limited sample of the CfA redshift survey and to a model in which galaxies reside on the surfaces of polyhedral 'bubbles'. The topology of the evolved mass distribution and 'biased' galaxy distribution in the cold dark matter models closely matches the topology of the density fluctuations in the initial conditions. The topology of the observational sample is consistent with the random phase, cold dark matter model.

Thermodynamics of the Coma Cluster Outskirts

NASA Astrophysics Data System (ADS)

Simionescu, A.; Werner, N.; Urban, O.; Allen, S. W.; Fabian, A. C.; Mantz, A.; Matsushita, K.; Nulsen, P. E. J.; Sanders, J. S.; Sasaki, T.; Sato, T.; Takei, Y.; Walker, S. A.

2013-09-01

We present results from a large mosaic of Suzaku observations of the Coma Cluster, the nearest and X-ray brightest hot (~8 keV), dynamically active, non-cool core system, focusing on the thermodynamic properties of the intracluster medium on large scales. For azimuths not aligned with an infalling subcluster toward the southwest, our measured temperature and X-ray brightness profiles exhibit broadly consistent radial trends, with the temperature decreasing from about 8.5 keV at the cluster center to about 2 keV at a radius of 2 Mpc, which is the edge of our detection limit. The southwest merger significantly boosts the surface brightness, allowing us to detect X-ray emission out to ~2.2 Mpc along this direction. Apart from the southwestern infalling subcluster, the surface brightness profiles show multiple edges around radii of 30-40 arcmin. The azimuthally averaged temperature profile, as well as the deprojected density and pressure profiles, all show a sharp drop consistent with an outwardly-propagating shock front located at 40 arcmin, corresponding to the outermost edge of the giant radio halo observed at 352 MHz with the Westerbork Synthesis Radio Telescope. The shock front may be powering this radio emission. A clear entropy excess inside of r 500 reflects the violent merging events linked with these morphological features. Beyond r 500, the entropy profiles of the Coma Cluster along the relatively relaxed directions are consistent with the power-law behavior expected from simple models of gravitational large-scale structure formation. The pressure is also in agreement at these radii with the expected values measured from Sunyaev-Zel'dovich data from the Planck satellite. However, due to the large uncertainties associated with the Coma Cluster measurements, we cannot yet exclude an entropy flattening in this system consistent with that seen in more relaxed cool core clusters.

The topology of large-scale structure. I - Topology and the random phase hypothesis. [galactic formation models

NASA Technical Reports Server (NTRS)

Weinberg, David H.; Gott, J. Richard, III; Melott, Adrian L.

1987-01-01

Many models for the formation of galaxies and large-scale structure assume a spectrum of random phase (Gaussian), small-amplitude density fluctuations as initial conditions. In such scenarios, the topology of the galaxy distribution on large scales relates directly to the topology of the initial density fluctuations. Here a quantitative measure of topology - the genus of contours in a smoothed density distribution - is described and applied to numerical simulations of galaxy clustering, to a variety of three-dimensional toy models, and to a volume-limited sample of the CfA redshift survey. For random phase distributions the genus of density contours exhibits a universal dependence on threshold density. The clustering simulations show that a smoothing length of 2-3 times the mass correlation length is sufficient to recover the topology of the initial fluctuations from the evolved galaxy distribution. Cold dark matter and white noise models retain a random phase topology at shorter smoothing lengths, but massive neutrino models develop a cellular topology.

Atomistic modeling of dropwise condensation

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

Sikarwar, B. S., E-mail: bssikarwar@amity.edu; Singh, P. L.; Muralidhar, K.

The basic aim of the atomistic modeling of condensation of water is to determine the size of the stable cluster and connect phenomena occurring at atomic scale to the macroscale. In this paper, a population balance model is described in terms of the rate equations to obtain the number density distribution of the resulting clusters. The residence time is taken to be large enough so that sufficient time is available for all the adatoms existing in vapor-phase to loose their latent heat and get condensed. The simulation assumes clusters of a given size to be formed from clusters of smallermore » sizes, but not by the disintegration of the larger clusters. The largest stable cluster size in the number density distribution is taken to be representative of the minimum drop radius formed in a dropwise condensation process. A numerical confirmation of this result against predictions based on a thermodynamic model has been obtained. Results show that the number density distribution is sensitive to the surface diffusion coefficient and the rate of vapor flux impinging on the substrate. The minimum drop radius increases with the diffusion coefficient and the impinging vapor flux; however, the dependence is weak. The minimum drop radius predicted from thermodynamic considerations matches the prediction of the cluster model, though the former does not take into account the effect of the surface properties on the nucleation phenomena. For a chemically passive surface, the diffusion coefficient and the residence time are dependent on the surface texture via the coefficient of friction. Thus, physical texturing provides a means of changing, within limits, the minimum drop radius. The study reveals that surface texturing at the scale of the minimum drop radius does not provide controllability of the macro-scale dropwise condensation at large timescales when a dynamic steady-state is reached.« less

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.

An Empirical Comparison of Variable Standardization Methods in Cluster Analysis.

ERIC Educational Resources Information Center

Schaffer, Catherine M.; Green, Paul E.

1996-01-01

The common marketing research practice of standardizing the columns of a persons-by-variables data matrix prior to clustering the entities corresponding to the rows was evaluated with 10 large-scale data sets. Results indicate that the column standardization practice may be problematic for some kinds of data that marketing researchers used for…

Testing Gravity and Cosmic Acceleration with Galaxy Clustering

NASA Astrophysics Data System (ADS)

Kazin, Eyal; Tinker, J.; Sanchez, A. G.; Blanton, M.

2012-01-01

The large-scale structure contains vast amounts of cosmological information that can help understand the accelerating nature of the Universe and test gravity on large scales. Ongoing and future sky surveys are designed to test these using various techniques applied on clustering measurements of galaxies. We present redshift distortion measurements of the Sloan Digital Sky Survey II Luminous Red Galaxy sample. We find that when combining the normalized quadrupole Q with the projected correlation function wp(rp) along with cluster counts (Rapetti et al. 2010), results are consistent with General Relativity. The advantage of combining Q and wp is the addition of the bias information, when using the Halo Occupation Distribution framework. We also present improvements to the standard technique of measuring Hubble expansion rates H(z) and angular diameter distances DA(z) when using the baryonic acoustic feature as a standard ruler. We introduce clustering wedges as an alternative basis to the multipole expansion and show that it yields similar constraints. This alternative basis serves as a useful technique to test for systematics, and ultimately improve measurements of the cosmic acceleration.

Statistical Analysis of Small-Scale Magnetic Flux Emergence Patterns: A Useful Subsurface Diagnostic?

NASA Astrophysics Data System (ADS)

Lamb, Derek A.

2016-10-01

While sunspots follow a well-defined pattern of emergence in space and time, small-scale flux emergence is assumed to occur randomly at all times in the quiet Sun. HMI's full-disk coverage, high cadence, spatial resolution, and duty cycle allow us to probe that basic assumption. Some case studies of emergence suggest that temporal clustering on spatial scales of 50-150 Mm may occur. If clustering is present, it could serve as a diagnostic of large-scale subsurface magnetic field structures. We present the results of a manual survey of small-scale flux emergence events over a short time period, and a statistical analysis addressing the question of whether these events show spatio-temporal behavior that is anything other than random.

Estimating Ω from Galaxy Redshifts: Linear Flow Distortions and Nonlinear Clustering

NASA Astrophysics Data System (ADS)

Bromley, B. C.; Warren, M. S.; Zurek, W. H.

1997-02-01

We propose a method to determine the cosmic mass density Ω from redshift-space distortions induced by large-scale flows in the presence of nonlinear clustering. Nonlinear structures in redshift space, such as fingers of God, can contaminate distortions from linear flows on scales as large as several times the small-scale pairwise velocity dispersion σv. Following Peacock & Dodds, we work in the Fourier domain and propose a model to describe the anisotropy in the redshift-space power spectrum; tests with high-resolution numerical data demonstrate that the model is robust for both mass and biased galaxy halos on translinear scales and above. On the basis of this model, we propose an estimator of the linear growth parameter β = Ω0.6/b, where b measures bias, derived from sampling functions that are tuned to eliminate distortions from nonlinear clustering. The measure is tested on the numerical data and found to recover the true value of β to within ~10%. An analysis of IRAS 1.2 Jy galaxies yields β=0.8+0.4-0.3 at a scale of 1000 km s-1, which is close to optimal given the shot noise and finite size of the survey. This measurement is consistent with dynamical estimates of β derived from both real-space and redshift-space information. The importance of the method presented here is that nonlinear clustering effects are removed to enable linear correlation anisotropy measurements on scales approaching the translinear regime. We discuss implications for analyses of forthcoming optical redshift surveys in which the dispersion is more than a factor of 2 greater than in the IRAS data.

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

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

PubMed Central

Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

PubMed

Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.

Active Galactic Nucleus Feedback with the Square Kilometre Array and Implications for Cluster Physics and Cosmology

NASA Astrophysics Data System (ADS)

Iqbal, Asif; Kale, Ruta; Majumdar, Subhabrata; Nath, Biman B.; Pandge, Mahadev; Sharma, Prateek; Malik, Manzoor A.; Raychaudhury, Somak

2017-12-01

Active Galactic Nuclei (AGN) feedback is regarded as an important non-gravitational process in galaxy clusters, providing useful constraints on large-scale structure formation. It modifies the structure and energetics of the intra-cluster medium (ICM) and hence its understanding is crucially needed in order to use clusters as high precision cosmological probes. In this context, particularly keeping in mind the upcoming high quality radio data expected from radio surveys like Square Kilometre Array (SKA) with its higher sensitivity, high spatial and spectral resolutions, we review our current understanding of AGN feedback, its cosmological implications and the impact that SKA can have in revolutionizing our understanding of AGN feedback in large-scale structures. Recent developments regarding the AGN outbursts and its possible contribution to excess entropy in the hot atmospheres of groups and clusters, its correlation with the feedback energy in ICM, quenching of cooling flows and the possible connection between cool core clusters and radio mini-halos, are discussed. We describe current major issues regarding modeling of AGN feedback and its impact on the surrounding medium. With regard to the future of AGN feedback studies, we examine the possible breakthroughs that can be expected from SKA observations. In the context of cluster cosmology, for example, we point out the importance of SKA observations for cluster mass calibration by noting that most of z>1 clusters discovered by eROSITA X-ray mission can be expected to be followed up through a 1000 hour SKA1-mid programme. Moreover, approximately 1000 radio mini halos and ˜ 2500 radio halos at z<0.6 can be potentially detected by SKA1 and SKA2 and used as tracers of galaxy clusters and determination of cluster selection function.

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

The challenge of turbulent acceleration of relativistic particles in the intra-cluster medium

NASA Astrophysics Data System (ADS)

Brunetti, Gianfranco

2016-01-01

Acceleration of cosmic-ray electrons (CRe) in the intra-cluster medium (ICM) is probed by radio observations that detect diffuse, megaparsec-scale, synchrotron sources in a fraction of galaxy clusters. Giant radio halos are the most spectacular manifestations of non-thermal activity in the ICM and are currently explained assuming that turbulence, driven during massive cluster-cluster mergers, reaccelerates CRe at several giga-electron volts. This scenario implies a hierarchy of complex mechanisms in the ICM that drain energy from large scales into electromagnetic fluctuations in the plasma and collisionless mechanisms of particle acceleration at much smaller scales. In this paper we focus on the physics of acceleration by compressible turbulence. The spectrum and damping mechanisms of the electromagnetic fluctuations, and the mean free path (mfp) of CRe, are the most relevant ingredients that determine the efficiency of acceleration. These ingredients in the ICM are, however, poorly known, and we show that calculations of turbulent acceleration are also sensitive to these uncertainties. On the other hand this fact implies that the non-thermal properties of galaxy clusters probe the complex microphysics and the weakly collisional nature of the ICM.

The case for electron re-acceleration at galaxy cluster shocks

NASA Astrophysics Data System (ADS)

van Weeren, Reinout J.; Andrade-Santos, Felipe; Dawson, William A.; Golovich, Nathan; Lal, Dharam V.; Kang, Hyesung; Ryu, Dongsu; Brìggen, Marcus; Ogrean, Georgiana A.; Forman, William R.; Jones, Christine; Placco, Vinicius M.; Santucci, Rafael M.; Wittman, David; Jee, M. James; Kraft, Ralph P.; Sobral, David; Stroe, Andra; Fogarty, Kevin

2017-01-01

On the largest scales, the Universe consists of voids and filaments making up the cosmic web. Galaxy clusters are located at the knots in this web, at the intersection of filaments. Clusters grow through accretion from these large-scale filaments and by mergers with other clusters and groups. In a growing number of galaxy clusters, elongated Mpc-sized radio sources have been found1,2 . Also known as radio relics, these regions of diffuse radio emission are thought to trace relativistic electrons in the intracluster plasma accelerated by low-Mach-number shocks generated by cluster-cluster merger events 3 . A long-standing problem is how low-Mach-number shocks can accelerate electrons so efficiently to explain the observed radio relics. Here, we report the discovery of a direct connection between a radio relic and a radio galaxy in the merging galaxy cluster Abell 3411-3412 by combining radio, X-ray and optical observations. This discovery indicates that fossil relativistic electrons from active galactic nuclei are re-accelerated at cluster shocks. It also implies that radio galaxies play an important role in governing the non-thermal component of the intracluster medium in merging clusters.

Slow-Down in Diffusion in Crowded Protein Solutions Correlates with Transient Cluster Formation.

PubMed

Nawrocki, Grzegorz; Wang, Po-Hung; Yu, Isseki; Sugita, Yuji; Feig, Michael

2017-12-14

For a long time, the effect of a crowded cellular environment on protein dynamics has been largely ignored. Recent experiments indicate that proteins diffuse more slowly in a living cell than in a diluted solution, and further studies suggest that the diffusion depends on the local surroundings. Here, detailed insight into how diffusion depends on protein-protein contacts is presented based on extensive all-atom molecular dynamics simulations of concentrated villin headpiece solutions. After force field adjustments in the form of increased protein-water interactions to reproduce experimental data, translational and rotational diffusion was analyzed in detail. Although internal protein dynamics remained largely unaltered, rotational diffusion was found to slow down more significantly than translational diffusion as the protein concentration increased. The decrease in diffusion is interpreted in terms of a transient formation of protein clusters. These clusters persist on sub-microsecond time scales and follow distributions that increasingly shift toward larger cluster size with increasing protein concentrations. Weighting diffusion coefficients estimated for different clusters extracted from the simulations with the distribution of clusters largely reproduces the overall observed diffusion rates, suggesting that transient cluster formation is a primary cause for a slow-down in diffusion upon crowding with other proteins.

Helium segregation on surfaces of plasma-exposed tungsten

NASA Astrophysics Data System (ADS)

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; Hammond, Karl D.; Wirth, Brian D.

2016-02-01

We report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He n (1  ⩽  n  ⩽  7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides the thermodynamic driving force for surface segregation. This elastic interaction force induces drift fluxes of these mobile He n clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters’ drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. These near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.

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.

Statistical Analysis of Large Scale Structure by the Discrete Wavelet Transform

NASA Astrophysics Data System (ADS)

Pando, Jesus

1997-10-01

The discrete wavelet transform (DWT) is developed as a general statistical tool for the study of large scale structures (LSS) in astrophysics. The DWT is used in all aspects of structure identification including cluster analysis, spectrum and two-point correlation studies, scale-scale correlation analysis and to measure deviations from Gaussian behavior. The techniques developed are demonstrated on 'academic' signals, on simulated models of the Lymanα (Lyα) forests, and on observational data of the Lyα forests. This technique can detect clustering in the Ly-α clouds where traditional techniques such as the two-point correlation function have failed. The position and strength of these clusters in both real and simulated data is determined and it is shown that clusters exist on scales as large as at least 20 h-1 Mpc at significance levels of 2-4 σ. Furthermore, it is found that the strength distribution of the clusters can be used to distinguish between real data and simulated samples even where other traditional methods have failed to detect differences. Second, a method for measuring the power spectrum of a density field using the DWT is developed. All common features determined by the usual Fourier power spectrum can be calculated by the DWT. These features, such as the index of a power law or typical scales, can be detected even when the samples are geometrically complex, the samples are incomplete, or the mean density on larger scales is not known (the infrared uncertainty). Using this method the spectra of Ly-α forests in both simulated and real samples is calculated. Third, a method for measuring hierarchical clustering is introduced. Because hierarchical evolution is characterized by a set of rules of how larger dark matter halos are formed by the merging of smaller halos, scale-scale correlations of the density field should be one of the most sensitive quantities in determining the merging history. We show that these correlations can be completely determined by the correlations between discrete wavelet coefficients on adjacent scales and at nearly the same spatial position, Cj,j+12/cdot2. Scale-scale correlations on two samples of the QSO Ly-α forests absorption spectra are computed. Lastly, higher order statistics are developed to detect deviations from Gaussian behavior. These higher order statistics are necessary to fully characterize the Ly-α forests because the usual 2nd order statistics, such as the two-point correlation function or power spectrum, give inconclusive results. It is shown how this technique takes advantage of the locality of the DWT to circumvent the central limit theorem. A non-Gaussian spectrum is defined and this spectrum reveals not only the magnitude, but the scales of non-Gaussianity. When applied to simulated and observational samples of the Ly-α clouds, it is found that different popular models of structure formation have different spectra while two, independent observational data sets, have the same spectra. Moreover, the non-Gaussian spectra of real data sets are significantly different from the spectra of various possible random samples. (Abstract shortened by UMI.)

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

X-ray morphological study of the ESZ sample

NASA Astrophysics Data System (ADS)

Lovisari, L.; Forman, W.; Jones, C.; Andrade-Santos, F.; Democles, J.; Pratt, G.; Ettori, S.; Arnaud, M.; Randall, S.; Kraft, R.

2017-10-01

An accurate knowledge of the scaling relations between X-ray observables and cluster mass is a crucial step for studies that aim to constrain cosmological parameters using galaxy clusters. The measure of the dynamical state of the systems offers important information to obtain precise scaling relations and understand their scatter. Unfortunately, characterize the dynamical state of a galaxy cluster requires to access a large set of information in different wavelength which are available only for a few individual systems. An alternative is to compute well defined morphological parameters making use of the relatively cheap X-ray images and profiles. Due to different projection effects none of the methods is good in all the cases and a combination of them is more effective to quantify the level of substructures. I will present the cluster morphologies that we derived for the ESZ sample. I will show their dependence on different cluster properties like total mass, redshift, and luminosity and how they differ from the ones obtained for X-ray selected clusters.

COLAcode: COmoving Lagrangian Acceleration code

NASA Astrophysics Data System (ADS)

Tassev, Svetlin V.

2016-02-01

COLAcode is a serial particle mesh-based N-body code illustrating the COLA (COmoving Lagrangian Acceleration) method; it solves for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). It differs from standard N-body code by trading accuracy at small-scales to gain computational speed without sacrificing accuracy at large scales. This is useful for generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing; such catalogs are needed to perform detailed error analysis for ongoing and future surveys of LSS.

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.

Automatic three-dimensional measurement of large-scale structure based on vision metrology.

PubMed

Zhu, Zhaokun; Guan, Banglei; Zhang, Xiaohu; Li, Daokui; Yu, Qifeng

2014-01-01

All relevant key techniques involved in photogrammetric vision metrology for fully automatic 3D measurement of large-scale structure are studied. A new kind of coded target consisting of circular retroreflective discs is designed, and corresponding detection and recognition algorithms based on blob detection and clustering are presented. Then a three-stage strategy starting with view clustering is proposed to achieve automatic network orientation. As for matching of noncoded targets, the concept of matching path is proposed, and matches for each noncoded target are found by determination of the optimal matching path, based on a novel voting strategy, among all possible ones. Experiments on a fixed keel of airship have been conducted to verify the effectiveness and measuring accuracy of the proposed methods.

Dark energy and modified gravity in the Effective Field Theory of Large-Scale Structure

NASA Astrophysics Data System (ADS)

Cusin, Giulia; Lewandowski, Matthew; Vernizzi, Filippo

2018-04-01

We develop an approach to compute observables beyond the linear regime of dark matter perturbations for general dark energy and modified gravity models. We do so by combining the Effective Field Theory of Dark Energy and Effective Field Theory of Large-Scale Structure approaches. In particular, we parametrize the linear and nonlinear effects of dark energy on dark matter clustering in terms of the Lagrangian terms introduced in a companion paper [1], focusing on Horndeski theories and assuming the quasi-static approximation. The Euler equation for dark matter is sourced, via the Newtonian potential, by new nonlinear vertices due to modified gravity and, as in the pure dark matter case, by the effects of short-scale physics in the form of the divergence of an effective stress tensor. The effective fluid introduces a counterterm in the solution to the matter continuity and Euler equations, which allows a controlled expansion of clustering statistics on mildly nonlinear scales. We use this setup to compute the one-loop dark-matter power spectrum.

The merger remnant NGC 3610 and its globular cluster system: a large-scale study

NASA Astrophysics Data System (ADS)

Bassino, Lilia P.; Caso, Juan P.

2017-04-01

We present a photometric study of the prototype merger remnant NGC 3610 and its globular cluster (GC) system, based on new Gemini/GMOS and Advanced Camera for Surveys/Hubble Space Telescope archival images. Thanks to the large field of view of our GMOS data, larger than previous studies, we are able to detect a 'classical' bimodal GC colour distribution, corresponding to metal-poor and metal-rich GCs, at intermediate radii and a small subsample of likely young clusters of intermediate colours, mainly located in the outskirts. The extent of the whole GC system is settled as about 40 kpc. The GC population is quite poor, about 500 ± 110 members that corresponds to a low total specific frequency SN ˜ 0.8. The effective radii of a cluster sample are determined, including those of two spectroscopically confirmed young and metal-rich clusters, that are in the limit between GC and UCD sizes and brightness. The large-scale galaxy surface-brightness profile can be decomposed as an inner embedded disc and an outer spheroid, determining for both larger extents than earlier research (10 and 30 kpc, respectively). We detect boxy isophotes, expected in merger remnants, and show a wealth of fine-structure in the surface-brightness distribution with unprecedented detail, coincident with the outer spheroid. The lack of symmetry in the galaxy colour map adds a new piece of evidence to the recent merger scenario of NGC 3610.

Measurement of kT splitting scales in W→ℓν events at [Formula: see text] with the ATLAS detector.

PubMed

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Düren, M; Duxfield, R; Dwuznik, M; Ebenstein, W L; Ebke, J; Eckweiler, S; Edson, W; Edwards, C A; Edwards, N C; Ehrenfeld, W; Eifert, T; Eigen, G; Einsweiler, K; Eisenhandler, E; Ekelof, T; El Kacimi, M; Ellert, M; Elles, S; Ellinghaus, F; Ellis, K; Ellis, N; Elmsheuser, J; Elsing, M; Emeliyanov, D; Enari, Y; Engelmann, R; Engl, A; Epp, B; Erdmann, J; Ereditato, A; Eriksson, D; Ernst, J; Ernst, M; Ernwein, J; Errede, D; Errede, S; Ertel, E; Escalier, M; Esch, H; Escobar, C; Espinal Curull, X; Esposito, B; Etienne, F; Etienvre, A I; Etzion, E; Evangelakou, D; Evans, H; Fabbri, L; Fabre, C; Facini, G; Fakhrutdinov, R M; Falciano, S; Fang, Y; Fanti, M; Farbin, A; Farilla, A; Farley, J; Farooque, T; Farrell, S; Farrington, S M; Farthouat, P; Fassi, F; Fassnacht, P; Fassouliotis, D; Fatholahzadeh, B; Favareto, A; Fayard, L; Federic, P; Fedin, O L; Fedorko, W; Fehling-Kaschek, M; Feligioni, L; Feng, C; Feng, E J; Fenyuk, A B; Ferencei, J; Fernando, W; Ferrag, S; Ferrando, J; Ferrara, V; Ferrari, A; 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Sánchez, J; Sanchez Martinez, V; Sandaker, H; Sander, H G; Sanders, M P; Sandhoff, M; Sandoval, T; Sandoval, C; Sandstroem, R; Sankey, D P C; Sansoni, A; Santamarina Rios, C; Santoni, C; Santonico, R; Santos, H; Santoyo Castillo, I; Sapp, K; Saraiva, J G; Sarangi, T; Sarkisyan-Grinbaum, E; Sarrazin, B; Sarri, F; Sartisohn, G; Sasaki, O; Sasaki, Y; Sasao, N; Satsounkevitch, I; Sauvage, G; Sauvan, E; Sauvan, J B; Savard, P; Savinov, V; Savu, D O; Sawyer, L; Saxon, D H; Saxon, J; Sbarra, C; Sbrizzi, A; Scannicchio, D A; Scarcella, M; Schaarschmidt, J; Schacht, P; Schaefer, D; Schaelicke, A; Schaepe, S; Schaetzel, S; Schäfer, U; Schaffer, A C; Schaile, D; Schamberger, R D; Scharf, V; Schegelsky, V A; Scheirich, D; Schernau, M; Scherzer, M I; Schiavi, C; Schieck, J; Schillo, C; Schioppa, M; Schlenker, S; Schmidt, E; Schmieden, K; Schmitt, C; Schmitt, C; Schmitt, S; Schneider, B; Schnellbach, Y J; Schnoor, U; Schoeffel, L; Schoening, A; Schorlemmer, A L S; Schott, M; Schouten, D; Schovancova, J; Schram, M; Schroeder, C; Schroer, N; Schultens, M J; Schultes, J; Schultz-Coulon, H-C; Schulz, H; Schumacher, M; Schumm, B A; Schune, Ph; Schwartzman, A; Schwegler, Ph; Schwemling, Ph; Schwienhorst, R; Schwindling, J; Schwindt, T; Schwoerer, M; Sciacca, F G; Scifo, E; Sciolla, G; Scott, W G; Searcy, J; Sedov, G; Sedykh, E; Seidel, S C; Seiden, A; Seifert, F; Seixas, J M; Sekhniaidze, G; Sekula, S J; Selbach, K E; Seliverstov, D M; Sellden, B; Sellers, G; Seman, M; Semprini-Cesari, N; Serfon, C; Serin, L; Serkin, L; Serre, T; Seuster, R; Severini, H; Sfyrla, A; Shabalina, E; Shamim, M; Shan, L Y; Shank, J T; Shao, Q T; Shapiro, M; Shatalov, P B; Shaw, K; Sherwood, P; Shimizu, S; Shimojima, M; Shin, T; Shiyakova, M; Shmeleva, A; Shochet, M J; Short, D; Shrestha, S; Shulga, E; Shupe, M A; Sicho, P; Sidoti, A; Siegert, F; Sijacki, Dj; Silbert, O; Silva, J; Silver, Y; Silverstein, D; Silverstein, S B; Simak, V; Simard, O; Simic, Lj; Simion, S; Simioni, E; Simmons, B; Simoniello, R; Simonyan, M; Sinervo, P; Sinev, N B; Sipica, V; Siragusa, G; Sircar, A; Sisakyan, A N; Sivoklokov, S Yu; Sjölin, J; Sjursen, T B; Skinnari, L A; Skottowe, H P; Skovpen, K; Skubic, P; Slater, M; Slavicek, T; Sliwa, K; Smakhtin, V; Smart, B H; Smestad, L; Smirnov, S Yu; Smirnov, Y; Smirnova, L N; Smirnova, O; Smith, B C; Smith, K M; Smizanska, M; Smolek, K; Snesarev, A A; Snidero, G; Snow, S W; Snow, J; Snyder, S; Sobie, R; Sodomka, J; Soffer, A; Soh, D A; Solans, C A; Solar, M; Solc, J; Soldatov, E Yu; Soldevila, U; Solfaroli Camillocci, E; Solodkov, A A; Solovyanov, O V; Solovyev, V; Soni, N; Sood, A; Sopko, V; Sopko, B; Sosebee, M; Soualah, R; Soueid, P; Soukharev, A; South, D; Spagnolo, S; Spanò, F; Spighi, R; Spigo, G; Spiwoks, R; Spousta, M; Spreitzer, T; Spurlock, B; St Denis, R D; Stahlman, J; Stamen, R; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stanitzki, M M; Stapnes, S; Starchenko, E A; Stark, J; Staroba, P; Starovoitov, P; Staszewski, R; Staude, A; Stavina, P; Steele, G; Steinbach, P; Steinberg, P; Stekl, I; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stern, S; Stewart, G A; Stillings, J A; Stockton, M C; Stoebe, M; Stoerig, K; Stoicea, G; Stonjek, S; Strachota, P; Stradling, A R; Straessner, A; Strandberg, J; Strandberg, S; Strandlie, A; Strang, M; Strauss, E; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Strong, J A; Stroynowski, R; Stugu, B; Stumer, I; Stupak, J; Sturm, P; Styles, N A; Su, D; Subramania, Hs; Subramaniam, R; Succurro, A; Sugaya, Y; Suhr, C; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, X; Sundermann, J E; Suruliz, K; Susinno, G; Sutton, M R; Suzuki, Y; Suzuki, Y; Svatos, M; Swedish, S; Swiatlowski, M; Sykora, I; Sykora, T; Ta, D; Tackmann, K; Taffard, A; Tafirout, R; Taiblum, N; Takahashi, Y; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A; Tam, J Y C; Tamsett, M C; Tan, K G; Tanaka, J; Tanaka, R; Tanaka, S; Tanaka, S; Tanasijczuk, A J; Tani, K; Tannoury, N; Tapprogge, S; Tardif, D; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tassi, E; Tayalati, Y; Taylor, C; Taylor, F E; Taylor, G N; Taylor, W; Teinturier, M; Teischinger, F A; Teixeira Dias Castanheira, M; Teixeira-Dias, P; Temming, K K; Ten Kate, H; Teng, P K; Terada, S; Terashi, K; Terron, J; Testa, M; Teuscher, R J; Therhaag, J; Theveneaux-Pelzer, T; Thoma, S; Thomas, J P; Thompson, E N; Thompson, P D; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thong, W M; Thun, R P; Tian, F; Tibbetts, M J; Tic, T; Tikhomirov, V O; Tikhonov, Y A; Timoshenko, S; Tiouchichine, E; Tipton, P; Tisserant, S; Todorov, T; Todorova-Nova, S; Toggerson, B; Tojo, J; Tokár, S; Tokushuku, K; Tollefson, K; Tomlinson, L; Tomoto, M; Tompkins, L; Toms, K; Tonoyan, A; Topfel, C; Topilin, N D; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Tran, H L; Trefzger, T; Tremblet, L; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Triplett, N; Trischuk, W; Trocmé, B; Troncon, C; Trottier-McDonald, M; Trovatelli, M; True, P; Trzebinski, M; Trzupek, A; Tsarouchas, C; Tseng, J C-L; Tsiakiris, M; Tsiareshka, P V; Tsionou, D; Tsipolitis, G; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsukerman, I I; Tsulaia, V; Tsung, J-W; Tsuno, S; Tsybychev, D; Tua, A; Tudorache, A; Tudorache, V; Tuggle, J M; Turala, M; Turecek, D; Turk Cakir, I; Turra, R; Tuts, P M; Tykhonov, A; Tylmad, M; Tyndel, M; Tzanakos, G; Uchida, K; Ueda, I; Ueno, R; Ughetto, M; Ugland, M; Uhlenbrock, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Ungaro, F C; Unno, Y; Urbaniec, D; Urquijo, P; Usai, G; Vacavant, L; Vacek, V; Vachon, B; Vahsen, S; Valencic, N; Valentinetti, S; Valero, A; Valery, L; Valkar, S; Valladolid Gallego, E; Vallecorsa, S; Valls Ferrer, J A; Van Berg, R; Van Der Deijl, P C; van der Geer, R; van der Graaf, H; Van Der Leeuw, R; van der Poel, E; van der Ster, D; van Eldik, N; van Gemmeren, P; Van Nieuwkoop, J; van Vulpen, I; Vanadia, M; Vandelli, W; Vaniachine, A; Vankov, P; Vannucci, F; Vari, R; Varnes, E W; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vassilakopoulos, V I; Vazeille, F; Vazquez Schroeder, T; Veloso, F; Veneziano, S; Ventura, A; Ventura, D; Venturi, M; Venturi, N; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinek, E; Vinogradov, V B; Virzi, J; Vitells, O; Viti, M; Vivarelli, I; Vives Vaque, F; Vlachos, S; Vladoiu, D; Vlasak, M; Vogel, A; Vokac, P; Volpi, G; Volpi, M; Volpini, G; von der Schmitt, H; von Radziewski, H; von Toerne, E; Vorobel, V; Vorwerk, V; Vos, M; Voss, R; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vu Anh, T; Vuillermet, R; Vukotic, I; Vykydal, Z; Wagner, W; Wagner, P; Wahlen, H; Wahrmund, S; Wakabayashi, J; Walch, S; Walder, J; Walker, R; Walkowiak, W; Wall, R; Waller, P; Walsh, B; Wang, C; Wang, H; Wang, H; Wang, J; Wang, J; Wang, K; Wang, R; Wang, S M; Wang, T; 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Ziolkowski, M; Zitoun, R; Živković, L; Zmouchko, V V; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zutshi, V; Zwalinski, L

A measurement of splitting scales, as defined by the k T clustering algorithm, is presented for final states containing a W boson produced in proton-proton collisions at a centre-of-mass energy of 7 TeV. The measurement is based on the full 2010 data sample corresponding to an integrated luminosity of 36 pb -1 which was collected using the ATLAS detector at the CERN Large Hadron Collider. Cluster splitting scales are measured in events containing W bosons decaying to electrons or muons. The measurement comprises the four hardest splitting scales in a k T cluster sequence of the hadronic activity accompanying the W boson, and ratios of these splitting scales. Backgrounds such as multi-jet and top-quark-pair production are subtracted and the results are corrected for detector effects. Predictions from various Monte Carlo event generators at particle level are compared to the data. Overall, reasonable agreement is found with all generators, but larger deviations between the predictions and the data are evident in the soft regions of the splitting scales.

Reaction dynamics analysis of a reconstituted Escherichia coli protein translation system by computational modeling

PubMed Central

Matsuura, Tomoaki; Tanimura, Naoki; Hosoda, Kazufumi; Yomo, Tetsuya; Shimizu, Yoshihiro

2017-01-01

To elucidate the dynamic features of a biologically relevant large-scale reaction network, we constructed a computational model of minimal protein synthesis consisting of 241 components and 968 reactions that synthesize the Met-Gly-Gly (MGG) peptide based on an Escherichia coli-based reconstituted in vitro protein synthesis system. We performed a simulation using parameters collected primarily from the literature and found that the rate of MGG peptide synthesis becomes nearly constant in minutes, thus achieving a steady state similar to experimental observations. In addition, concentration changes to 70% of the components, including intermediates, reached a plateau in a few minutes. However, the concentration change of each component exhibits several temporal plateaus, or a quasi-stationary state (QSS), before reaching the final plateau. To understand these complex dynamics, we focused on whether the components reached a QSS, mapped the arrangement of components in a QSS in the entire reaction network structure, and investigated time-dependent changes. We found that components in a QSS form clusters that grow over time but not in a linear fashion, and that this process involves the collapse and regrowth of clusters before the formation of a final large single cluster. These observations might commonly occur in other large-scale biological reaction networks. This developed analysis might be useful for understanding large-scale biological reactions by visualizing complex dynamics, thereby extracting the characteristics of the reaction network, including phase transitions. PMID:28167777

Large-scale Map of Millimeter-wavelength Hydrogen Radio Recombination Lines around a Young Massive Star Cluster

NASA Astrophysics Data System (ADS)

Nguyen-Luong, Q.; Anderson, L. D.; Motte, F.; Kim, Kee-Tae; Schilke, P.; Carlhoff, P.; Beuther, H.; Schneider, N.; Didelon, P.; Kramer, C.; Louvet, F.; Nony, T.; Bihr, S.; Rugel, M.; Soler, J.; Wang, Y.; Bronfman, L.; Simon, R.; Menten, K. M.; Wyrowski, F.; Walmsley, C. M.

2017-08-01

We report the first map of large-scale (10 pc in length) emission of millimeter-wavelength hydrogen recombination lines (mm-RRLs) toward the giant H II region around the W43-Main young massive star cluster (YMC). Our mm-RRL data come from the IRAM 30 m telescope and are analyzed together with radio continuum and cm-RRL data from the Karl G. Jansky Very Large Array and HCO+ 1-0 line emission data from the IRAM 30 m. The mm-RRLs reveal an expanding wind-blown ionized gas shell with an electron density ˜70-1500 cm-3 driven by the WR/OB cluster, which produces a total Lyα photon flux of 1.5× {10}50 s-1. This shell is interacting with the dense neutral molecular gas in the W43-Main dense cloud. Combining the high spectral and angular resolution mm-RRL and cm-RRL cubes, we derive the two-dimensional relative distributions of dynamical and pressure broadening of the ionized gas emission and find that the RRL line shapes are dominated by pressure broadening (4-55 {km} {{{s}}}-1) near the YMC and by dynamical broadening (8-36 {km} {{{s}}}-1) near the shell’s edge. Ionized gas clumps hosting ultra-compact H II regions found at the edge of the shell suggest that large-scale ionized gas motion triggers the formation of new star generation near the periphery of the shell.

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.

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

PubMed Central

Macropol, Kathy; Can, Tolga; Singh, Ambuj K

2009-01-01

Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW) for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL), and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters. PMID:19740439

The case for electron re-acceleration at galaxy cluster shocks

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

van Weeren, Reinout J.; Andrade-Santos, Felipe; Dawson, William A.

On the largest scales, the Universe consists of voids and filaments making up the cosmic web. Galaxy clusters are located at the knots in this web, at the intersection of filaments. Clusters grow through accretion from these large-scale filaments and by mergers with other clusters and groups. In a growing number of galaxy clusters, elongated Mpc-sized radio sources have been found. Also known as radio relics, these regions of diffuse radio emission are thought to trace relativistic electrons in the intracluster plasma accelerated by low-Mach-number shocks generated by cluster–cluster merger events. A long-standing problem is how low-Mach-number shocks can acceleratemore » electrons so efficiently to explain the observed radio relics. Here, we report the discovery of a direct connection between a radio relic and a radio galaxy in the merging galaxy cluster Abell 3411–3412 by combining radio, X-ray and optical observations. This discovery indicates that fossil relativistic electrons from active galactic nuclei are re-accelerated at cluster shocks. Lastly, it also implies that radio galaxies play an important role in governing the non-thermal component of the intracluster medium in merging clusters.« less

The case for electron re-acceleration at galaxy cluster shocks

DOE PAGES

van Weeren, Reinout J.; Andrade-Santos, Felipe; Dawson, William A.; ...

2017-01-04

On the largest scales, the Universe consists of voids and filaments making up the cosmic web. Galaxy clusters are located at the knots in this web, at the intersection of filaments. Clusters grow through accretion from these large-scale filaments and by mergers with other clusters and groups. In a growing number of galaxy clusters, elongated Mpc-sized radio sources have been found. Also known as radio relics, these regions of diffuse radio emission are thought to trace relativistic electrons in the intracluster plasma accelerated by low-Mach-number shocks generated by cluster–cluster merger events. A long-standing problem is how low-Mach-number shocks can acceleratemore » electrons so efficiently to explain the observed radio relics. Here, we report the discovery of a direct connection between a radio relic and a radio galaxy in the merging galaxy cluster Abell 3411–3412 by combining radio, X-ray and optical observations. This discovery indicates that fossil relativistic electrons from active galactic nuclei are re-accelerated at cluster shocks. Lastly, it also implies that radio galaxies play an important role in governing the non-thermal component of the intracluster medium in merging clusters.« less

Scale-free Graphs for General Aviation Flight Schedules

NASA Technical Reports Server (NTRS)

Alexandov, Natalia M. (Technical Monitor); Kincaid, Rex K.

2003-01-01

In the late 1990s a number of researchers noticed that networks in biology, sociology, and telecommunications exhibited similar characteristics unlike standard random networks. In particular, they found that the cummulative degree distributions of these graphs followed a power law rather than a binomial distribution and that their clustering coefficients tended to a nonzero constant as the number of nodes, n, became large rather than O(1/n). Moreover, these networks shared an important property with traditional random graphs as n becomes large the average shortest path length scales with log n. This latter property has been coined the small-world property. When taken together these three properties small-world, power law, and constant clustering coefficient describe what are now most commonly referred to as scale-free networks. Since 1997 at least six books and over 400 articles have been written about scale-free networks. In this manuscript an overview of the salient characteristics of scale-free networks. Computational experience will be provided for two mechanisms that grow (dynamic) scale-free graphs. Additional computational experience will be given for constructing (static) scale-free graphs via a tabu search optimization approach. Finally, a discussion of potential applications to general aviation networks is given.

The split in the ancient cold front in the Perseus cluster

NASA Astrophysics Data System (ADS)

Walker, Stephen A.; ZuHone, John; Fabian, Andy; Sanders, Jeremy

2018-04-01

Sloshing cold fronts in clusters, produced as the dense cluster core moves around in the cluster potential in response to in-falling subgroups, provide a powerful probe of the physics of the intracluster medium and the magnetic fields permeating it1,2. These sharp discontinuities in density and temperature rise gradually outwards with age in a characteristic spiral pattern, embedding into the intracluster medium a record of the minor merging activity of clusters: the further from the cluster centre a cold front is, the older it is. Recently, it was discovered that these cold fronts can survive out to extremely large radii in the Perseus cluster3. Here, we report on high-spatial-resolution Chandra observations of the large-scale cold front in Perseus. We find that rather than broadening through diffusion, the cold front remains extremely sharp (consistent with abrupt jumps in density) and instead is split into two sharp edges. These results show that magnetic draping can suppress diffusion for vast periods of time—around 5 Gyr—even as the cold front expands out to nearly half the cluster virial radius.

Efficiency of parallel direct optimization

NASA Technical Reports Server (NTRS)

Janies, D. A.; Wheeler, W. C.

2001-01-01

Tremendous progress has been made at the level of sequential computation in phylogenetics. However, little attention has been paid to parallel computation. Parallel computing is particularly suited to phylogenetics because of the many ways large computational problems can be broken into parts that can be analyzed concurrently. In this paper, we investigate the scaling factors and efficiency of random addition and tree refinement strategies using the direct optimization software, POY, on a small (10 slave processors) and a large (256 slave processors) cluster of networked PCs running LINUX. These algorithms were tested on several data sets composed of DNA and morphology ranging from 40 to 500 taxa. Various algorithms in POY show fundamentally different properties within and between clusters. All algorithms are efficient on the small cluster for the 40-taxon data set. On the large cluster, multibuilding exhibits excellent parallel efficiency, whereas parallel building is inefficient. These results are independent of data set size. Branch swapping in parallel shows excellent speed-up for 16 slave processors on the large cluster. However, there is no appreciable speed-up for branch swapping with the further addition of slave processors (>16). This result is independent of data set size. Ratcheting in parallel is efficient with the addition of up to 32 processors in the large cluster. This result is independent of data set size. c2001 The Willi Hennig Society.

Improving the distinguishable cluster results: spin-component scaling

NASA Astrophysics Data System (ADS)

Kats, Daniel

2018-06-01

The spin-component scaling is employed in the energy evaluation to improve the distinguishable cluster approach. SCS-DCSD reaction energies reproduce reference values with a root-mean-squared deviation well below 1 kcal/mol, the interaction energies are three to five times more accurate than DCSD, and molecular systems with a large amount of static electron correlation are still described reasonably well. SCS-DCSD represents a pragmatic approach to achieve chemical accuracy with a simple method without triples, which can also be applied to multi-configurational molecular systems.

Covalent Binding with Neutrons on the Femto-scale

NASA Astrophysics Data System (ADS)

von Oertzen, W.; Kanada-En'yo, Y.; Kimura, M.

2017-06-01

In light nuclei we have well defined clusters, nuclei with closed shells, which serve as centers for binary molecules with covalent binding by valence neutrons. Single neutron orbitals in light neutron-excess nuclei have well defined shell model quantum numbers. With the combination of two clusters and their neutron valence states, molecular two-center orbitals are defined; in the two-center shell model we can place valence neutrons in a large variety of molecular two-center states, and the formation of Dimers becomes possible. The corresponding rotational bands point with their large moments of inertia and the Coriolis decoupling effect (for K = 1/2 bands) to the internal molecular orbital structure in these states. On the basis of these the neutron rich isotopes allow the formation of a large variety molecular structures on the nuclear scale. An extended Ikeda diagram can be drawn for these cases. Molecular bands in Be and Ne-isotopes are discussed as text-book examples.

Strong collective attraction in colloidal clusters on a liquid-air interface.

PubMed

Pergamenshchik, V M

2009-01-01

It is shown that in a cluster of many colloids, trapped at a liquid-air interface, the well-known vertical-force-induced pairwise logarithmic attraction changes to a strongly enhanced power-law attraction. In large two-dimensional clusters, the attraction energy scales as the inverse square of the distance between colloids. The enhancement is given by the ratio eta = (square of the capillary length) / (interface surface area per colloid) and can be as large as 10;{5} . This explains why a very small vertical force on colloids, which is too weak to bring two of them together, can stabilize many-body structures on a liquid-air interface. The profile of a cluster is shown to consist of a large slow collective envelope modulated by a fast low-amplitude perturbation due to individual colloids. A closed equation for the slow envelope, which incorporates an arbitrary power-law repulsion between colloids, is derived. For example, this equation is solved for a large circular cluster with the hard-core colloid repulsion. It is suggested that the predicted effect is responsible for mysterious stabilization of colloidal structures observed in experiments on a surface of isotropic liquid and nematic liquid crystal.

Not all stars form in clusters - measuring the kinematics of OB associations with Gaia

NASA Astrophysics Data System (ADS)

Ward, Jacob L.; Kruijssen, J. M. Diederik

2018-04-01

It is often stated that star clusters are the fundamental units of star formation and that most (if not all) stars form in dense stellar clusters. In this monolithic formation scenario, low-density OB associations are formed from the expansion of gravitationally bound clusters following gas expulsion due to stellar feedback. N-body simulations of this process show that OB associations formed this way retain signs of expansion and elevated radial anisotropy over tens of Myr. However, recent theoretical and observational studies suggest that star formation is a hierarchical process, following the fractal nature of natal molecular clouds and allowing the formation of large-scale associations in situ. We distinguish between these two scenarios by characterizing the kinematics of OB associations using the Tycho-Gaia Astrometric Solution catalogue. To this end, we quantify four key kinematic diagnostics: the number ratio of stars with positive radial velocities to those with negative radial velocities, the median radial velocity, the median radial velocity normalized by the tangential velocity, and the radial anisotropy parameter. Each quantity presents a useful diagnostic of whether the association was more compact in the past. We compare these diagnostics to models representing random motion and the expanding products of monolithic cluster formation. None of these diagnostics show evidence of expansion, either from a single cluster or multiple clusters, and the observed kinematics are better represented by a random velocity distribution. This result favours the hierarchical star formation model in which a minority of stars forms in bound clusters and large-scale, hierarchically structured associations are formed in situ.

Measures of large-scale structure in the CfA redshift survey slices

NASA Technical Reports Server (NTRS)

De Lapparent, Valerie; Geller, Margaret J.; Huchra, John P.

1991-01-01

Variations of the counts-in-cells with cell size are used here to define two statistical measures of large-scale clustering in three 6 deg slices of the CfA redshift survey. A percolation criterion is used to estimate the filling factor which measures the fraction of the total volume in the survey occupied by the large-scale structures. For the full 18 deg slice of the CfA redshift survey, f is about 0.25 + or - 0.05. After removing groups with more than five members from two of the slices, variations of the counts in occupied cells with cell size have a power-law behavior with a slope beta about 2.2 on scales from 1-10/h Mpc. Application of both this statistic and the percolation analysis to simulations suggests that a network of two-dimensional structures is a better description of the geometry of the clustering in the CfA slices than a network of one-dimensional structures. Counts-in-cells are also used to estimate at 0.3 galaxy h-squared/Mpc the average galaxy surface density in sheets like the Great Wall.

Large-scale clustering as a probe of the origin and the host environment of fast radio bursts

NASA Astrophysics Data System (ADS)

Shirasaki, Masato; Kashiyama, Kazumi; Yoshida, Naoki

2017-04-01

We propose to use degree-scale angular clustering of fast radio bursts (FRBs) to identify their origin and the host galaxy population. We study the information content in autocorrelation of the angular positions and dispersion measures (DM) and in cross-correlation with galaxies. We show that the cross-correlation with Sloan Digital Sky Survey (SDSS) galaxies will place stringent constraints on the mean physical quantities associated with FRBs. If ˜10 ,000 FRBs are detected with ≲deg resolution in the SDSS field, the clustering analysis with the intrinsic DM scatter of 100 pc /cm3 can constrain the global abundance of free electrons at z ≲1 and the large-scale bias of FRB host galaxies (the statistical relation between the distribution of host galaxies and cosmic matter density field) with fractional errors (with a 68% confidence level) of ˜10 % and ˜20 %, respectively. The mean near-source dispersion measure and the delay-time distribution of FRB rates relative to the global star forming rate can be also determined by combining the clustering and the probability distribution function of DM. Our approach will be complementary to high-resolution (≪deg ) event localization using e.g., VLA and VLBI for identifying the origin of FRBs and the source environment. We strongly encourage future observational programs such as CHIME, UTMOST, and HIRAX to survey FRBs in the SDSS field.

Computing Cluster for Large Scale Turbulence Simulations and Applications in Computational Aeroacoustics

NASA Astrophysics Data System (ADS)

Lele, Sanjiva K.

2002-08-01

Funds were received in April 2001 under the Department of Defense DURIP program for construction of a 48 processor high performance computing cluster. This report details the hardware which was purchased and how it has been used to enable and enhance research activities directly supported by, and of interest to, the Air Force Office of Scientific Research and the Department of Defense. The report is divided into two major sections. The first section after this summary describes the computer cluster, its setup, and some cluster performance benchmark results. The second section explains ongoing research efforts which have benefited from the cluster hardware, and presents highlights of those efforts since installation of the cluster.

“Local” Dark Energy Outflows Around Galaxy Groups and Rich Clusters

NASA Astrophysics Data System (ADS)

Byrd, Gene G.; Chernin, A. D.; Teerikorpi, P.; Dolgachev, V. P.; Kanter, A. A.; Domozhilova, L. M.; Valtonen, M.

2013-01-01

First detected at large Gpc distances, dark energy is a vacuum energy formulated as Einstein's cosmological constant, Λ. We have found its effects on “small” 1-3 Mpc scales in our Local Group. We have now found these effects in other nearby groups using member Doppler shifts and 3D distances from group centers (Cen A-M83; M81-M82; CV I). For the larger 20-30 Mpc Virgo and Fornax clusters, we now have found similar effects. Observationally, for both groups and clusters, gravity dominates a bound central system. The system gravitation and dark energy create a “zero-gravity” radius (R_{ZG}) from the center where the two balance. Smaller members bound inside R_{ZG} may be pulled out along with the less bound members which recede farther. A linear increase of recession with distance results which approaches a linear global Hubble law. These outflows are seen around groups in cosmological simulations which include galaxies as small as ~10^{-4} of the group mass. Scaled plots of asymptotic recessional velocity, V/(H(R_{ZG})), versus distance/ R_{ZG} of the outer galaxies are very similar for both the small groups and large clusters. This similarity on 1-30 Mpc scales suggests that a quasi-stationary bound central component and an expanding outflow applies to a wide range of groups and clusters due to small scale action of dark energy. Our new text book: Byrd, G., Chernin, A., Terrikorpi, P. and Valtonen, M. 2012, "Paths to Dark Energy: Theory and Observation," de Gruyter, Berlin/Boston, contains background and cosmological simulation plots. Group data and scaled plots are in our new article: A. D. Chernin, P. Teerikorpi, V. P. Dolgachev, A. A. Kanter, L. M. Domozhilova, M. J. Valtonen, and G. G. Byrd, 2012, Astronomy Reports, Vol. 56 , p. 653-669.

A Giant Warm Baryonic Halo for the Coma Cluster

NASA Technical Reports Server (NTRS)

Bonamente, Max; Lieu, Richard; Joy, Marshall K.; Six, N. Frank (Technical Monitor)

2002-01-01

Several deep PSPC observations of the Coma cluster unveil a very large-scale halo of soft X-ray emission, substantially in excess of the well know radiation from the hot intra-cluster medium. The excess emission, previously reported in the central cluster regions through lower-sensitivity EUVE and ROSAT data, is now evident out to a radius of 2.5 Mpc, demonstrating that the soft excess radiation from clusters is a phenomenon of cosmological significance. The spectrum at these large radii cannot be modeled non-thermally, but is consistent with the original scenario of thermal emission at warm temperatures. The mass of this plasma is at least on par with that of the hot X-ray emitting plasma, and significantly more massive if the plasma resides in low-density filamentary structures. Thus the data lend vital support to current theories of cosmic evolution, which predict greater than 50 percent by mass of today's baryons reside in warm-hot filaments converging at clusters of galaxies.

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

Classification of mechanisms, climatic context, areal scaling, and synchronization of floods: the hydroclimatology of floods in the Upper Paraná River basin, Brazil

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; AghaKouchak, Amir; Lall, Upmanu

2017-12-01

Floods are the main natural disaster in Brazil, causing substantial economic damage and loss of life. Studies suggest that some extreme floods result from a causal climate chain. Exceptional rain and floods are determined by large-scale anomalies and persistent patterns in the atmospheric and oceanic circulations, which influence the magnitude, extent, and duration of these extremes. Moreover, floods can result from different generating mechanisms. These factors contradict the assumptions of homogeneity, and often stationarity, in flood frequency analysis. Here we outline a methodological framework based on clustering using self-organizing maps (SOMs) that allows the linkage of large-scale processes to local-scale observations. The methodology is applied to flood data from several sites in the flood-prone Upper Paraná River basin (UPRB) in southern Brazil. The SOM clustering approach is employed to classify the 6-day rainfall field over the UPRB into four categories, which are then used to classify floods into four types based on the spatiotemporal dynamics of the rainfall field prior to the observed flood events. An analysis of the vertically integrated moisture fluxes, vorticity, and high-level atmospheric circulation revealed that these four clusters are related to known tropical and extratropical processes, including the South American low-level jet (SALLJ); extratropical cyclones; and the South Atlantic Convergence Zone (SACZ). Persistent anomalies in the sea surface temperature fields in the Pacific and Atlantic oceans are also found to be associated with these processes. Floods associated with each cluster present different patterns in terms of frequency, magnitude, spatial variability, scaling, and synchronization of events across the sites and subbasins. These insights suggest new directions for flood risk assessment, forecasting, and management.

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.

Resurrecting hot dark matter - Large-scale structure from cosmic strings and massive neutrinos

NASA Technical Reports Server (NTRS)

Scherrer, Robert J.

1988-01-01

These are the results of a numerical simulation of the formation of large-scale structure from cosmic-string loops in a universe dominated by massive neutrinos (hot dark matter). This model has several desirable features. The final matter distribution contains isolated density peaks embedded in a smooth background, producing a natural bias in the distribution of luminous matter. Because baryons can accrete onto the cosmic strings before the neutrinos, the galaxies will have baryon cores and dark neutrino halos. Galaxy formation in this model begins much earlier than in random-phase models. On large scales the distribution of clustered matter visually resembles the CfA survey, with large voids and filaments.

"A Richness Study of 14 Distant X-Ray Clusters from the 160 Square Degree Survey"

NASA Technical Reports Server (NTRS)

Jones, Christine; West, Donald (Technical Monitor)

2001-01-01

We have measured the surface density of galaxies toward 14 X-ray-selected cluster candidates at redshifts z(sub i) 0.46, and we show that they are associated with rich galaxy concentrations. These clusters, having X-ray luminosities of Lx(0.5-2 keV) approx. (0.5 - 2.6) x 10(exp 44) ergs/ sec are among the most distant and luminous in our 160 deg(exp 2) ROSAT Position Sensitive Proportional Counter cluster survey. We find that the clusters range between Abell richness classes 0 and 2 and have a most probable richness class of 1. We compare the richness distribution of our distant clusters to those for three samples of nearby clusters with similar X-ray luminosities. We find that the nearby and distant samples have similar richness distributions, which shows that clusters have apparently not evolved substantially in richness since redshift z=0.5. There is, however, a marginal tendency for the distant clusters to be slightly poorer than nearby clusters, although deeper multicolor data for a large sample would be required to confirm this trend. We compare the distribution of distant X-ray clusters in the L(sub X)-richness plane to the distribution of optically selected clusters from the Palomar Distant Cluster Survey. The optically selected clusters appear overly rich for their X-ray luminosities, when compared to X-ray-selected clusters. Apparently, X-ray and optical surveys do not necessarily sample identical mass concentrations at large redshifts. This may indicate the existence of a population of optically rich clusters with anomalously low X-ray emission, More likely, however, it reflects the tendency for optical surveys to select unvirialized mass concentrations, as might be expected when peering along large-scale filaments.

The Mass Function of Abell Clusters

NASA Astrophysics Data System (ADS)

Chen, J.; Huchra, J. P.; McNamara, B. R.; Mader, J.

1998-12-01

The velocity dispersion and mass functions for rich clusters of galaxies provide important constraints on models of the formation of Large-Scale Structure (e.g., Frenk et al. 1990). However, prior estimates of the velocity dispersion or mass function for galaxy clusters have been based on either very small samples of clusters (Bahcall and Cen 1993; Zabludoff et al. 1994) or large but incomplete samples (e.g., the Girardi et al. (1998) determination from a sample of clusters with more than 30 measured galaxy redshifts). In contrast, we approach the problem by constructing a volume-limited sample of Abell clusters. We collected individual galaxy redshifts for our sample from two major galaxy velocity databases, the NASA Extragalactic Database, NED, maintained at IPAC, and ZCAT, maintained at SAO. We assembled a database with velocity information for possible cluster members and then selected cluster members based on both spatial and velocity data. Cluster velocity dispersions and masses were calculated following the procedures of Danese, De Zotti, and di Tullio (1980) and Heisler, Tremaine, and Bahcall (1985), respectively. The final velocity dispersion and mass functions were analyzed in order to constrain cosmological parameters by comparison to the results of N-body simulations. Our data for the cluster sample as a whole and for the individual clusters (spatial maps and velocity histograms) in our sample is available on-line at http://cfa-www.harvard.edu/ huchra/clusters. This website will be updated as more data becomes available in the master redshift compilations, and will be expanded to include more clusters and large groups of galaxies.

Dynamic contact network between ribosomal subunits enables rapid large-scale rotation during spontaneous translocation

PubMed Central

Bock, Lars V.; Blau, Christian; Vaiana, Andrea C.; Grubmüller, Helmut

2015-01-01

During ribosomal translation, the two ribosomal subunits remain associated through intersubunit bridges, despite rapid large-scale intersubunit rotation. The absence of large barriers hindering rotation is a prerequisite for rapid rotation. Here, we investigate how such a flat free-energy landscape is achieved, in particular considering the large shifts the bridges undergo at the periphery. The dynamics and energetics of the intersubunit contact network are studied using molecular dynamics simulations of the prokaryotic ribosome in intermediate states of spontaneous translocation. Based on observed occupancies of intersubunit contacts, residues were grouped into clusters. In addition to the central contact clusters, peripheral clusters were found to maintain strong steady interactions by changing contacts in the course of rotation. The peripheral B1 bridges are stabilized by a changing contact pattern of charged residues that adapts to the rotational state. In contrast, steady strong interactions of the B4 bridge are ensured by the flexible helix H34 following the movement of protein S15. The tRNAs which span the subunits contribute to the intersubunit binding enthalpy to an almost constant degree, despite their different positions in the ribosome. These mechanisms keep the intersubunit interaction strong and steady during rotation, thereby preventing dissociation and enabling rapid rotation. PMID:26109353

The Morphologies and Alignments of Gas, Mass, and the Central Galaxies of CLASH Clusters of Galaxies

NASA Astrophysics Data System (ADS)

Donahue, Megan; Ettori, Stefano; Rasia, Elena; Sayers, Jack; Zitrin, Adi; Meneghetti, Massimo; Voit, G. Mark; Golwala, Sunil; Czakon, Nicole; Yepes, Gustavo; Baldi, Alessandro; Koekemoer, Anton; Postman, Marc

2016-03-01

Morphology is often used to infer the state of relaxation of galaxy clusters. The regularity, symmetry, and degree to which a cluster is centrally concentrated inform quantitative measures of cluster morphology. The Cluster Lensing and Supernova survey with Hubble Space Telescope (CLASH) used weak and strong lensing to measure the distribution of matter within a sample of 25 clusters, 20 of which were deemed to be “relaxed” based on their X-ray morphology and alignment of the X-ray emission with the Brightest Cluster Galaxy. Toward a quantitative characterization of this important sample of clusters, we present uniformly estimated X-ray morphological statistics for all 25 CLASH clusters. We compare X-ray morphologies of CLASH clusters with those identically measured for a large sample of simulated clusters from the MUSIC-2 simulations, selected by mass. We confirm a threshold in X-ray surface brightness concentration of C ≳ 0.4 for cool-core clusters, where C is the ratio of X-ray emission inside 100 h70-1 kpc compared to inside 500 {h}70-1 kpc. We report and compare morphologies of these clusters inferred from Sunyaev-Zeldovich Effect (SZE) maps of the hot gas and in from projected mass maps based on strong and weak lensing. We find a strong agreement in alignments of the orientation of major axes for the lensing, X-ray, and SZE maps of nearly all of the CLASH clusters at radii of 500 kpc (approximately 1/2 R500 for these clusters). We also find a striking alignment of clusters shapes at the 500 kpc scale, as measured with X-ray, SZE, and lensing, with that of the near-infrared stellar light at 10 kpc scales for the 20 “relaxed” clusters. This strong alignment indicates a powerful coupling between the cluster- and galaxy-scale galaxy formation processes.

The relative vertex clustering value - a new criterion for the fast discovery of functional modules in protein interaction networks

PubMed Central

2015-01-01

Background Cellular processes are known to be modular and are realized by groups of proteins implicated in common biological functions. Such groups of proteins are called functional modules, and many community detection methods have been devised for their discovery from protein interaction networks (PINs) data. In current agglomerative clustering approaches, vertices with just a very few neighbors are often classified as separate clusters, which does not make sense biologically. Also, a major limitation of agglomerative techniques is that their computational efficiency do not scale well to large PINs. Finally, PIN data obtained from large scale experiments generally contain many false positives, and this makes it hard for agglomerative clustering methods to find the correct clusters, since they are known to be sensitive to noisy data. Results We propose a local similarity premetric, the relative vertex clustering value, as a new criterion allowing to decide when a node can be added to a given node's cluster and which addresses the above three issues. Based on this criterion, we introduce a novel and very fast agglomerative clustering technique, FAC-PIN, for discovering functional modules and protein complexes from a PIN data. Conclusions Our proposed FAC-PIN algorithm is applied to nine PIN data from eight different species including the yeast PIN, and the identified functional modules are validated using Gene Ontology (GO) annotations from DAVID Bioinformatics Resources. Identified protein complexes are also validated using experimentally verified complexes. Computational results show that FAC-PIN can discover functional modules or protein complexes from PINs more accurately and more efficiently than HC-PIN and CNM, the current state-of-the-art approaches for clustering PINs in an agglomerative manner. PMID:25734691

ΛGR Centennial: Cosmic Web in Dark Energy Background

NASA Astrophysics Data System (ADS)

Chernin, A. D.

The basic building blocks of the Cosmic Web are groups and clusters of galaxies, super-clusters (pancakes) and filaments embedded in the universal dark energy background. The background produces antigravity, and the antigravity effect is strong in groups, clusters and superclusters. Antigravity is very weak in filaments where matter (dark matter and baryons) produces gravity dominating in the filament internal dynamics. Gravity-antigravity interplay on the large scales is a grandiose phenomenon predicted by ΛGR theory and seen in modern observations of the Cosmic Web.

Dark matter and cosmology

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

Schramm, D.N.

1992-03-01

The cosmological dark matter problem is reviewed. The Big Bang Nucleosynthesis constraints on the baryon density are compared with the densities implied by visible matter, dark halos, dynamics of clusters, gravitational lenses, large-scale velocity flows, and the {Omega} = 1 flatness/inflation argument. It is shown that (1) the majority of baryons are dark; and (2) non-baryonic dark matter is probably required on large scales. It is also noted that halo dark matter could be either baryonic or non-baryonic. Descrimination between ``cold`` and ``hot`` non-baryonic candidates is shown to depend on the assumed ``seeds`` that stimulate structure formation. Gaussian density fluctuations,more » such as those induced by quantum fluctuations, favor cold dark matter, whereas topological defects such as strings, textures or domain walls may work equally or better with hot dark matter. A possible connection between cold dark matter, globular cluster ages and the Hubble constant is mentioned. Recent large-scale structure measurements, coupled with microwave anisotropy limits, are shown to raise some questions for the previously favored density fluctuation picture. Accelerator and underground limits on dark matter candidates are also reviewed.« less

Dark matter and cosmology

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

Schramm, D.N.

1992-03-01

The cosmological dark matter problem is reviewed. The Big Bang Nucleosynthesis constraints on the baryon density are compared with the densities implied by visible matter, dark halos, dynamics of clusters, gravitational lenses, large-scale velocity flows, and the {Omega} = 1 flatness/inflation argument. It is shown that (1) the majority of baryons are dark; and (2) non-baryonic dark matter is probably required on large scales. It is also noted that halo dark matter could be either baryonic or non-baryonic. Descrimination between cold'' and hot'' non-baryonic candidates is shown to depend on the assumed seeds'' that stimulate structure formation. Gaussian density fluctuations,more » such as those induced by quantum fluctuations, favor cold dark matter, whereas topological defects such as strings, textures or domain walls may work equally or better with hot dark matter. A possible connection between cold dark matter, globular cluster ages and the Hubble constant is mentioned. Recent large-scale structure measurements, coupled with microwave anisotropy limits, are shown to raise some questions for the previously favored density fluctuation picture. Accelerator and underground limits on dark matter candidates are also reviewed.« less

Dark matter and cosmology

NASA Astrophysics Data System (ADS)

Schramm, David N.

1992-07-01

The cosmological dark matter problem is reviewed. The Big Bang Nucleosynthesis constraints on the baryon density are compared with the densities implied by visible matter, dark halos, dynamics of clusters, gravitational lenses, large-scale velocity flows, and the Ω = 1 flatness/inflation argument. It is shown that (1) the majority of baryons are dark; and (2) non-baryonic dark matter is probably required on large scales. It is also noted that halo dark matter could be either baryonic or non-baryonic. Descrimination between ``cold'' and ``hot'' non-baryonic candidates is shown to depend on the assumed ``seeds'' that stimulate structure formation. Gaussian density fluctuations, such as those induced by quantum fluctuations, favor cold dark matter, whereas topological defects such as strings, textures or domain walls may work equally or better with hot dark matter. A possible connection between cold dark matter, globular cluster ages and the Hubble constant is mentioned. Recent large-scale structure measurements, coupled with microwave anisotropy limits, are shown to raise some questions for the previously favored density fluctuation picture. Accelerator and underground limits on dark matter candidates are also reviewed.

Dark matter and cosmology

NASA Astrophysics Data System (ADS)

Schramm, D. N.

1992-03-01

The cosmological dark matter problem is reviewed. The Big Bang nucleosynthesis constraints on the baryon density are compared with the densities implied by visible matter, dark halos, dynamics of clusters, gravitational lenses, large-scale velocity flows, and the omega = 1 flatness/inflation argument. It is shown that (1) the majority of baryons are dark; and (2) non-baryonic dark matter is probably required on large scales. It is also noted that halo dark matter could be either baryonic or non-baryonic. Descrimination between 'cold' and 'hot' non-baryonic candidates is shown to depend on the assumed 'seeds' that stimulate structure formation. Gaussian density fluctuations, such as those induced by quantum fluctuations, favor cold dark matter, whereas topological defects such as strings, textures or domain walls may work equally or better with hot dark matter. A possible connection between cold dark matter, globular cluster ages, and the Hubble constant is mentioned. Recent large-scale structure measurements, coupled with microwave anisotropy limits, are shown to raise some questions for the previously favored density fluctuation picture. Accelerator and underground limits on dark matter candidates are also reviewed.

Discovery of a large-scale clumpy structure around the Lynx supercluster at z~ 1.27

NASA Astrophysics Data System (ADS)

Nakata, Fumiaki; Kodama, Tadayuki; Shimasaku, Kazuhiro; Doi, Mamoru; Furusawa, Hisanori; Hamabe, Masaru; Kimura, Masahiko; Komiyama, Yutaka; Miyazaki, Satoshi; Okamura, Sadanori; Ouchi, Masami; Sekiguchi, Maki; Ueda, Yoshihiro; Yagi, Masafumi; Yasuda, Naoki

2005-03-01

We report the discovery of a probable large-scale structure composed of many galaxy clumps around the known twin clusters at z= 1.26 and 1.27 in the Lynx region. Our analysis is based on deep, panoramic, and multicolour imaging, 26.4 × 24.1 arcmin2 in VRi'z' bands with the Suprime-Cam on the 8.2-m Subaru telescope. This unique, deep and wide-field imaging data set allows us for the first time to map out the galaxy distribution in the highest-redshift supercluster known. We apply a photometric redshift technique to extract plausible cluster members at z~ 1.27 down to i'= 26.15 (5σ) corresponding to ~M*+ 2.5 at this redshift. From the two-dimensional distribution of these photometrically selected galaxies, we newly identify seven candidates of galaxy groups or clusters where the surface density of red galaxies is significantly high (>5σ), in addition to the two known clusters. These candidates show clear red colour-magnitude sequences consistent with a passive evolution model, which suggests the existence of additional high-density regions around the Lynx superclusters.

Galaxy And Mass Assembly (GAMA): the signatures of galaxy interactions as viewed from small scale galaxy clustering

NASA Astrophysics Data System (ADS)

Gunawardhana, M. L. P.; Norberg, P.; Zehavi, I.; Farrow, D. J.; Loveday, J.; Hopkins, A. M.; Davies, L. J. M.; Wang, L.; Alpaslan, M.; Bland-Hawthorn, J.; Brough, S.; Holwerda, B. W.; Owers, M. S.; Wright, A. H.

2018-06-01

Statistical studies of galaxy-galaxy interactions often utilise net change in physical properties of progenitors as a function of the separation between their nuclei to trace both the strength and the observable timescale of their interaction. In this study, we use two-point auto, cross and mark correlation functions to investigate the extent to which small-scale clustering properties of star forming galaxies can be used to gain physical insight into galaxy-galaxy interactions between galaxies of similar optical brightness and stellar mass. The Hα star formers, drawn from the highly spatially complete Galaxy And Mass Assembly (GAMA) survey, show an increase in clustering on small separations. Moreover, the clustering strength shows a strong dependence on optical brightness and stellar mass, where (1) the clustering amplitude of optically brighter galaxies at a given separation is larger than that of optically fainter systems, (2) the small scale clustering properties (e.g. the strength, the scale at which the signal relative to the fiducial power law plateaus) of star forming galaxies appear to differ as a function of increasing optical brightness of galaxies. According to cross and mark correlation analyses, the former result is largely driven by the increased dust content in optically bright star forming galaxies. The latter could be interpreted as evidence of a correlation between interaction-scale and optical brightness of galaxies, where physical evidence of interactions between optically bright star formers, likely hosted within relatively massive halos, persist over larger separations than those between optically faint star formers.

Galaxy clusters in the cosmic web

NASA Astrophysics Data System (ADS)

Acebrón, A.; Durret, F.; Martinet, N.; Adami, C.; Guennou, L.

2014-12-01

Simulations of large scale structure formation in the universe predict that matter is essentially distributed along filaments at the intersection of which lie galaxy clusters. We have analysed 9 clusters in the redshift range 0.4

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

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

Rizzi, Silvio; Hereld, Mark; Insley, Joseph

In this work we perform in-situ visualization of molecular dynamics simulations, which can help scientists to visualize simulation output on-the-fly, without incurring storage overheads. We present a case study to couple LAMMPS, the large-scale molecular dynamics simulation code with vl3, our parallel framework for large-scale visualization and analysis. Our motivation is to identify effective approaches for covisualization and exploration of large-scale atomistic simulations at interactive frame rates.We propose a system of coupled libraries and describe its architecture, with an implementation that runs on GPU-based clusters. We present the results of strong and weak scalability experiments, as well as future researchmore » avenues based on our results.« less

On the large scale structure of X-ray background sources

NASA Technical Reports Server (NTRS)

Bi, H. G.; Meszaros, A.; Meszaros, P.

1991-01-01

The large scale clustering of the sources responsible for the X-ray background is discussed, under the assumption of a discrete origin. The formalism necessary for calculating the X-ray spatial fluctuations in the most general case where the source density contrast in structures varies with redshift is developed. A comparison of this with observational limits is useful for obtaining information concerning various galaxy formation scenarios. The calculations presented show that a varying density contrast has a small impact on the expected X-ray fluctuations. This strengthens and extends previous conclusions concerning the size and comoving density of large scale structures at redshifts 0.5 between 4.0.

The large-scale distribution of galaxies

NASA Technical Reports Server (NTRS)

Geller, Margaret J.

1989-01-01

The spatial distribution of galaxies in the universe is characterized on the basis of the six completed strips of the Harvard-Smithsonian Center for Astrophysics redshift-survey extension. The design of the survey is briefly reviewed, and the results are presented graphically. Vast low-density voids similar to the void in Bootes are found, almost completely surrounded by thin sheets of galaxies. Also discussed are the implications of the results for the survey sampling problem, the two-point correlation function of the galaxy distribution, the possibility of detecting large-scale coherent flows, theoretical models of large-scale structure, and the identification of groups and clusters of galaxies.

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.

On hierarchical solutions to the BBGKY hierarchy

NASA Technical Reports Server (NTRS)

Hamilton, A. J. S.

1988-01-01

It is thought that the gravitational clustering of galaxies in the universe may approach a scale-invariant, hierarchical form in the small separation, large-clustering regime. Past attempts to solve the Born-Bogoliubov-Green-Kirkwood-Yvon (BBGKY) hierarchy in this regime have assumed a certain separable hierarchical form for the higher order correlation functions of galaxies in phase space. It is shown here that such separable solutions to the BBGKY equations must satisfy the condition that the clustered component of the solution has cluster-cluster correlations equal to galaxy-galaxy correlations to all orders. The solutions also admit the presence of an arbitrary unclustered component, which plays no dyamical role in the large-clustering regime. These results are a particular property of the specific separable model assumed for the correlation functions in phase space, not an intrinsic property of spatially hierarchical solutions to the BBGKY hierarchy. The observed distribution of galaxies does not satisfy the required conditions. The disagreement between theory and observation may be traced, at least in part, to initial conditions which, if Gaussian, already have cluster correlations greater than galaxy correlations.

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.

THERMODYNAMICS OF THE COMA CLUSTER OUTSKIRTS

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

Simionescu, A.; Werner, N.; Urban, O.

2013-09-20

We present results from a large mosaic of Suzaku observations of the Coma Cluster, the nearest and X-ray brightest hot ({approx}8 keV), dynamically active, non-cool core system, focusing on the thermodynamic properties of the intracluster medium on large scales. For azimuths not aligned with an infalling subcluster toward the southwest, our measured temperature and X-ray brightness profiles exhibit broadly consistent radial trends, with the temperature decreasing from about 8.5 keV at the cluster center to about 2 keV at a radius of 2 Mpc, which is the edge of our detection limit. The southwest merger significantly boosts the surface brightness,more » allowing us to detect X-ray emission out to {approx}2.2 Mpc along this direction. Apart from the southwestern infalling subcluster, the surface brightness profiles show multiple edges around radii of 30-40 arcmin. The azimuthally averaged temperature profile, as well as the deprojected density and pressure profiles, all show a sharp drop consistent with an outwardly-propagating shock front located at 40 arcmin, corresponding to the outermost edge of the giant radio halo observed at 352 MHz with the Westerbork Synthesis Radio Telescope. The shock front may be powering this radio emission. A clear entropy excess inside of r{sub 500} reflects the violent merging events linked with these morphological features. Beyond r{sub 500}, the entropy profiles of the Coma Cluster along the relatively relaxed directions are consistent with the power-law behavior expected from simple models of gravitational large-scale structure formation. The pressure is also in agreement at these radii with the expected values measured from Sunyaev-Zel'dovich data from the Planck satellite. However, due to the large uncertainties associated with the Coma Cluster measurements, we cannot yet exclude an entropy flattening in this system consistent with that seen in more relaxed cool core clusters.« 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.

Alternative to particle dark matter

NASA Astrophysics Data System (ADS)

Khoury, Justin

2015-01-01

We propose an alternative to particle dark matter that borrows ingredients of modified Newtonian dynamics (MOND) while adding new key components. The first new feature is a dark matter fluid, in the form of a scalar field with small equation of state and sound speed. This component is critical in reproducing the success of cold dark matter for the expansion history and the growth of linear perturbations, but does not cluster significantly on nonlinear scales. Instead, the missing mass problem on nonlinear scales is addressed by a modification of the gravitational force law. The force law approximates MOND at large and intermediate accelerations, and therefore reproduces the empirical success of MOND at fitting galactic rotation curves. At ultralow accelerations, the force law reverts to an inverse-square law, albeit with a larger Newton's constant. This latter regime is important in galaxy clusters and is consistent with their observed isothermal profiles, provided the characteristic acceleration scale of MOND is mildly varying with scale or mass, such that it is 12 times higher in clusters than in galaxies. We present an explicit relativistic theory in terms of two scalar fields. The first scalar field is governed by a Dirac-Born-Infeld action and behaves as a dark matter fluid on large scales. The second scalar field also has single-derivative interactions and mediates a fifth force that modifies gravity on nonlinear scales. Both scalars are coupled to matter via an effective metric that depends locally on the fields. The form of this effective metric implies the equality of the two scalar gravitational potentials, which ensures that lensing and dynamical mass estimates agree. Further work is needed in order to make both the acceleration scale of MOND and the fraction at which gravity reverts to an inverse-square law explicitly dynamical quantities, varying with scale or mass.

On the amplification of magnetic fields in cosmic filaments and galaxy clusters

NASA Astrophysics Data System (ADS)

Vazza, F.; Brüggen, M.; Gheller, C.; Wang, P.

2014-12-01

The amplification of primordial magnetic fields via a small-scale turbulent dynamo during structure formation might be able to explain the observed magnetic fields in galaxy clusters. The magnetization of more tenuous large-scale structures such as cosmic filaments is more uncertain, as it is challenging for numerical simulations to achieve the required dynamical range. In this work, we present magnetohydrodynamical cosmological simulations on large uniform grids to study the amplification of primordial seed fields in the intracluster medium (ICM) and in the warm-hot-intergalactic medium (WHIM). In the ICM, we confirm that turbulence caused by structure formation can produce a significant dynamo amplification, even if the amplification is smaller than what is reported in other papers. In the WHIM inside filaments, we do not observe significant dynamo amplification, even though we achieve Reynolds numbers of Re ˜ 200-300. The maximal amplification for large filaments is of the order of ˜100 for the magnetic energy, corresponding to a typical field of a few ˜nG starting from a primordial weak field of 10-10 G (comoving). In order to start a small-scale dynamo, we found that a minimum of ˜102 resolution elements across the virial radius of galaxy clusters was necessary. In filaments we could not find a minimum resolution to set off a dynamo. This stems from the inefficiency of supersonic motions in the WHIM in triggering solenoidal modes and small-scale twisting of magnetic field structures. Magnetic fields this small will make it hard to detect filaments in radio observations.

A curvature-based weighted fuzzy c-means algorithm for point clouds de-noising

NASA Astrophysics Data System (ADS)

Cui, Xin; Li, Shipeng; Yan, Xiutian; He, Xinhua

2018-04-01

In order to remove the noise of three-dimensional scattered point cloud and smooth the data without damnify the sharp geometric feature simultaneity, a novel algorithm is proposed in this paper. The feature-preserving weight is added to fuzzy c-means algorithm which invented a curvature weighted fuzzy c-means clustering algorithm. Firstly, the large-scale outliers are removed by the statistics of r radius neighboring points. Then, the algorithm estimates the curvature of the point cloud data by using conicoid parabolic fitting method and calculates the curvature feature value. Finally, the proposed clustering algorithm is adapted to calculate the weighted cluster centers. The cluster centers are regarded as the new points. The experimental results show that this approach is efficient to different scale and intensities of noise in point cloud with a high precision, and perform a feature-preserving nature at the same time. Also it is robust enough to different noise model.

Observations of cloud cluster hierarchies over the tropical western Pacific

NASA Technical Reports Server (NTRS)

Lau, K. M.; Nakazawa, T.; Sui, C. H.

1991-01-01

The structure and propagation of tropical-cloud clusters are investigated during two contrasting periods over the tropical western Pacific in order to determine possible similarities or differences and to compare with previous studies. Three fundamental periodicities are found in tropical convection in the region: 1 day, 2-3 days, and 10-15 days. It is noted that the 10-15-day time scale is closely related to the intraseasonal oscillations propagating from the Indian Ocean to the western Pacific. Large convective complexes, supercloud clusters (SSC) are found to organize in this time scale. The SCC is made up from several cloud clusters generated at 2-3-day intervals. The diurnal variation is found to be most pronounced over the maritime continent, and the amplitude of the diurnal cycle is shown to be modulated by the 2-3-day and 10-15-day oscillations.

The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales

PubMed Central

Millette, Katie L; Keyghobadi, Nusha

2015-01-01

Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (FST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent. PMID:25628865

The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales.

PubMed

Millette, Katie L; Keyghobadi, Nusha

2015-01-01

Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (F ST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent.

Clustering of Farsi sub-word images for whole-book recognition

NASA Astrophysics Data System (ADS)

Soheili, Mohammad Reza; Kabir, Ehsanollah; Stricker, Didier

2015-01-01

Redundancy of word and sub-word occurrences in large documents can be effectively utilized in an OCR system to improve recognition results. Most OCR systems employ language modeling techniques as a post-processing step; however these techniques do not use important pictorial information that exist in the text image. In case of large-scale recognition of degraded documents, this information is even more valuable. In our previous work, we proposed a subword image clustering method for the applications dealing with large printed documents. In our clustering method, the ideal case is when all equivalent sub-word images lie in one cluster. To overcome the issues of low print quality, the clustering method uses an image matching algorithm for measuring the distance between two sub-word images. The measured distance with a set of simple shape features were used to cluster all sub-word images. In this paper, we analyze the effects of adding more shape features on processing time, purity of clustering, and the final recognition rate. Previously published experiments have shown the efficiency of our method on a book. Here we present extended experimental results and evaluate our method on another book with totally different font face. Also we show that the number of the new created clusters in a page can be used as a criteria for assessing the quality of print and evaluating preprocessing phases.

A Multi-Hop Clustering Mechanism for Scalable IoT Networks.

PubMed

Sung, Yoonyoung; Lee, Sookyoung; Lee, Meejeong

2018-03-23

It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63-87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6-89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network.

A Multi-Hop Clustering Mechanism for Scalable IoT Networks

PubMed Central

2018-01-01

It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63–87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6–89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network. PMID:29570691

Cluster mass estimators from CMB temperature and polarization lensing

NASA Astrophysics Data System (ADS)

Hu, Wayne; DeDeo, Simon; Vale, Chris

2007-12-01

Upcoming Sunyaev Zel'dovich surveys are expected to return ~104 intermediate mass clusters at high redshift. Their average masses must be known to the same accuracy as desired for the dark energy properties. Internal to the surveys, the cosmic microwave background (CMB) potentially provides a source for lensing mass measurements whose distance is precisely known and behind all clusters. We develop statistical mass estimators from six quadratic combinations of CMB temperature and polarization fields that can simultaneously recover large-scale structure and cluster mass profiles. The performance of these estimators on idealized Navarro Frenk White (NFW) clusters suggests that surveys with a ~1' beam and 10\\,\\muK^{\\prime} noise in uncontaminated temperature maps can make a ~10σ detection, or equivalently a ~10% mass measurement for each 103 set of clusters. With internal or external acoustic scale E-polarization measurements, the ET cross-correlation estimator can provide a stringent test for contaminants on a first detection at ~1/3 the significance. For surveys that reach below 3\\,\\muK^{\\prime}, the EB cross-correlation estimator should provide the most precise measurements and potentially the strongest control over contaminants.

Properties and spatial distribution of galaxy superclusters

NASA Astrophysics Data System (ADS)

Liivamägi, Lauri Juhan

2017-01-01

Astronomy is a science that can offer plenty of unforgettable imagery, and the large-scale distribution of galaxies is no exception. Among the first features the viewer's eye is likely to be drawn to, are large concentrations of galaxies - galaxy superclusters, contrasting to the seemingly empty regions beside them. Superclusters can extend from tens to over hundred megaparsecs, they contain from hundreds to thousands of galaxies, and many galaxy groups and clusters. Unlike galaxy clusters, superclusters are clearly unrelaxed systems, not gravitationally bound as crossing times exceed the age of the universe, and show little to no radial symmetry. Superclusters, as part of the large-scale structure, are sensitive to the initial power spectrum and the following evolution. They are massive enough to leave an imprint on the cosmic microwave background radiation. Superclusters can also provide an unique environment for their constituent galaxies and galaxy clusters. In this study we used two different observational and one simulated galaxy samples to create several catalogues of structures that, we think, correspond to what are generally considered galaxy superclusters. Superclusters were delineated as continuous over-dense regions in galaxy luminosity density fields. When calculating density fields several corrections were applied to remove small-scale redshift distortions and distance-dependent selection effects. Resulting catalogues of objects display robust statistical properties, showing that flux-limited galaxy samples can be used to create nearly volume-limited catalogues of superstructures. Generally, large superclusters can be regarded as massive, often branching filamentary structures, that are mainly characterised by their length. Smaller superclusters, on the other hand, can display a variety of shapes. Spatial distribution of superclusters shows large-scale variations, with high-density concentrations often found in semi-regularly spaced groups. Future studies are needed to quantify the relations between superclusters and finer details of the galaxy distribution. Supercluster catalogues from this thesis have already been used in numerous other studies.

LoCuSS: comparison of observed X-ray and lensing galaxy cluster scaling relations with simulations

NASA Astrophysics Data System (ADS)

Zhang, Y.-Y.; Finoguenov, A.; Böhringer, H.; Kneib, J.-P.; Smith, G. P.; Kneissl, R.; Okabe, N.; Dahle, H.

2008-05-01

The Local Cluster Substructure Survey (LoCuSS, Smith et al.) is a systematic multi-wavelength survey of more than 100 X-ray luminous galaxy clusters in the redshift range 0.14-0.3 selected from the ROSAT All Sky Survey. We used data on 37 LoCuSS clusters from the XMM-Newton archive to investigate the global scaling relations of galaxy clusters. The scaling relations based solely on the X-ray data (S-T, S-Y_X, P-Y_X, M-T, M-Y_X, M-M_gas, M_gas-T, L-T, L-Y_X, and L-M) obey empirical self-similarity and reveal no additional evolution beyond the large-scale structure growth. They also reveal up to 17 per cent segregation between all 37 clusters and non-cool core clusters. Weak lensing mass measurements are also available in the literature for 19 of the clusters with XMM-Newton data. The average of the weak lensing mass to X-ray based mass ratio is 1.09± 0.08, setting the limit of the non-thermal pressure support to 9 ± 8 per cent. The mean of the weak lensing mass to X-ray based mass ratio of these clusters is ~1, indicating good agreement between X-ray and weak lensing masses for most clusters, although with 31-51 per cent scatter. The scatter in the mass-observable relations (M-Y_X, M-M_gas, and M-T) is smaller using X-ray based masses than using weak lensing masses by a factor of 2. With the scaled radius defined by the YX profile - r500 Y_X,X, r500YX,wl, and r500Y_X,si, we obtain lower scatter in the weak lensing mass based mass-observable relations, which means the origin of the scatter is M^wl and MX instead of Y_X. The normalization of the M-YX relation using X-ray mass estimates is lower than the one from simulations by up to 18-24 per cent at 3σ significance. This agrees with the M-YX relation based on weak lensing masses, the normalization of the latter being ~20 per cent lower than the one from simulations at ~2σ significance. This difference between observations and simulations is also indicated in the M-M_gas and M-T relations. Despite the large scatter in the comparison of X-ray to lensing, the agreement between these two completely independent observational methods is an important step towards controlling astrophysical and measurement systematics in cosmological scaling relations. This work is based on observations made with the XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA member states and the USA (NASA). Appendices A-C are only available in electronic form at http://www.aanda.org

Internal velocity and mass distributions in simulated clusters of galaxies for a variety of cosmogonic models

NASA Technical Reports Server (NTRS)

Cen, Renyue

1994-01-01

The mass and velocity distributions in the outskirts (0.5-3.0/h Mpc) of simulated clusters of galaxies are examined for a suite of cosmogonic models (two Omega(sub 0) = 1 and two Omega(sub 0) = 0.2 models) utilizing large-scale particle-mesh (PM) simulations. Through a series of model computations, designed to isolate the different effects, we find that both Omega(sub 0) and P(sub k) (lambda less than or = 16/h Mpc) are important to the mass distributions in clusters of galaxies. There is a correlation between power, P(sub k), and density profiles of massive clusters; more power tends to point to the direction of a stronger correlation between alpha and M(r less than 1.5/h Mpc); i.e., massive clusters being relatively extended and small mass clusters being relatively concentrated. A lower Omega(sub 0) universe tends to produce relatively concentrated massive clusters and relatively extended small mass clusters compared to their counterparts in a higher Omega(sub 0) model with the same power. Models with little (initial) small-scale power, such as the hot dark matter (HDM) model, produce more extended mass distributions than the isothermal distribution for most of the mass clusters. But the cold dark matter (CDM) models show mass distributions of most of the clusters more concentrated than the isothermal distribution. X-ray and gravitational lensing observations are beginning providing useful information on the mass distribution in and around clusters; some interesting constraints on Omega(sub 0) and/or the (initial) power of the density fluctuations on scales lambda less than or = 16/h Mpc (where linear extrapolation is invalid) can be obtained when larger observational data sets, such as the Sloan Digital Sky Survey, become available.

Evaluating Tests of Virialization and Substructure Using Galaxy Clusters in the ORELSE Survey

NASA Astrophysics Data System (ADS)

Rumbaugh, N.; Lemaux, B. C.; Tomczak, A. R.; Shen, L.; Pelliccia, D.; Lubin, L. M.; Kocevski, D. D.; Wu, P.-F.; Gal, R. R.; Mei, S.; Fassnacht, C. D.; Squires, G. K.

2018-05-01

We evaluated the effectiveness of different indicators of cluster virialization using 12 large-scale structures in the ORELSE survey spanning from 0.7 < z < 1.3. We located diffuse X-ray emission from 16 galaxy clusters using Chandra observations. We studied the properties of these clusters and their members, using Chandra data in conjunction with optical and near-IR imaging and spectroscopy. We measured X-ray luminosities and gas temperatures of each cluster, as well as velocity dispersions of their member galaxies. We compared these results to scaling relations derived from virialized clusters, finding significant offsets of up to 3-4σ for some clusters, which could indicate they are disturbed or still forming. We explored if other properties of the clusters correlated with these offsets by performing a set of tests of virialization and substructure on our sample, including Dressler-Schectman tests, power ratios, analyses of the velocity distributions of galaxy populations, and centroiding differences. For comparison to a wide range of studies, we used two sets of tests: ones that did and did not use spectral energy distribution fitting to obtain rest-frame colours, stellar masses, and photometric redshifts of galaxies. Our results indicated that the difference between the stellar mass or light mean-weighted center and the X-ray center, as well as the projected offset of the most-massive/brightest cluster galaxy from other cluster centroids had the strongest correlations with scaling relation offsets, implying they are the most robust indicators of cluster virialization and can be used for this purpose when X-ray data is insufficiently deep for reliable LX and TX measurements.

A large-scale cluster randomized trial to determine the effects of community-based dietary sodium reduction--the China Rural Health Initiative Sodium Reduction Study.

PubMed

Li, Nicole; Yan, Lijing L; Niu, Wenyi; Labarthe, Darwin; Feng, Xiangxian; Shi, Jingpu; Zhang, Jianxin; Zhang, Ruijuan; Zhang, Yuhong; Chu, Hongling; Neiman, Andrea; Engelgau, Michael; Elliott, Paul; Wu, Yangfeng; Neal, Bruce

2013-11-01

Cardiovascular diseases are the leading cause of death and disability in China. High blood pressure caused by excess intake of dietary sodium is widespread and an effective sodium reduction program has potential to improve cardiovascular health. This study is a large-scale, cluster-randomized, trial done in five Northern Chinese provinces. Two counties have been selected from each province and 12 townships in each county making a total of 120 clusters. Within each township one village has been selected for participation with 1:1 randomization stratified by county. The sodium reduction intervention comprises community health education and a food supply strategy based upon providing access to salt substitute. Subsidization of the price of salt substitute was done in 30 intervention villages selected at random. Control villages continued usual practices. The primary outcome for the study is dietary sodium intake level estimated from assays of 24-hour urine. The trial recruited and randomized 120 townships in April 2011. The sodium reduction program was commenced in the 60 intervention villages between May and June of that year with outcome surveys scheduled for October to December 2012. Baseline data collection shows that randomisation achieved good balance across groups. The establishment of the China Rural Health Initiative has enabled the launch of this large-scale trial designed to identify a novel, scalable strategy for reduction of dietary sodium and control of blood pressure. If proved effective, the intervention could plausibly be implemented at low cost in large parts of China and other countries worldwide. © 2013.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states.

PubMed

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states

NASA Astrophysics Data System (ADS)

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

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.

Weak lensing study of 16 DAFT/FADA clusters: Substructures and filaments

NASA Astrophysics Data System (ADS)

Martinet, Nicolas; Clowe, Douglas; Durret, Florence; Adami, Christophe; Acebrón, Ana; Hernandez-García, Lorena; Márquez, Isabel; Guennou, Loic; Sarron, Florian; Ulmer, Mel

2016-05-01

While our current cosmological model places galaxy clusters at the nodes of a filament network (the cosmic web), we still struggle to detect these filaments at high redshifts. We perform a weak lensing study for a sample of 16 massive, medium-high redshift (0.4

Accurate Modeling of Galaxy Clustering on Small Scales: Testing the Standard ΛCDM + Halo Model

NASA Astrophysics Data System (ADS)

Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron; Scoccimarro, Roman

2015-01-01

The large-scale distribution of galaxies can be explained fairly simply by assuming (i) a cosmological model, which determines the dark matter halo distribution, and (ii) a simple connection between galaxies and the halos they inhabit. This conceptually simple framework, called the halo model, has been remarkably successful at reproducing the clustering of galaxies on all scales, as observed in various galaxy redshift surveys. However, none of these previous studies have carefully modeled the systematics and thus truly tested the halo model in a statistically rigorous sense. We present a new accurate and fully numerical halo model framework and test it against clustering measurements from two luminosity samples of galaxies drawn from the SDSS DR7. We show that the simple ΛCDM cosmology + halo model is not able to simultaneously reproduce the galaxy projected correlation function and the group multiplicity function. In particular, the more luminous sample shows significant tension with theory. We discuss the implications of our findings and how this work paves the way for constraining galaxy formation by accurate simultaneous modeling of multiple galaxy clustering statistics.

Final Report for "Non-Accelerator Physics – Research in High Energy Physics: Dark Energy Research on DES"

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

Ritz, Steve; Jeltema, Tesla

One of the greatest mysteries in modern cosmology is the fact that the expansion of the universe is observed to be accelerating. This acceleration may stem from dark energy, an additional energy component of the universe, or may indicate that the theory of general relativity is incomplete on cosmological scales. The growth rate of large-scale structure in the universe and particularly the largest collapsed structures, clusters of galaxies, is highly sensitive to the underlying cosmology. Clusters will provide one of the single most precise methods of constraining dark energy with the ongoing Dark Energy Survey (DES). The accuracy of themore » cosmological constraints derived from DES clusters necessarily depends on having an optimized and well-calibrated algorithm for selecting clusters as well as an optical richness estimator whose mean relation and scatter compared to cluster mass are precisely known. Calibrating the galaxy cluster richness-mass relation and its scatter was the focus of the funded work. Specifically, we employ X-ray observations and optical spectroscopy with the Keck telescopes of optically-selected clusters to calibrate the relationship between optical richness (the number of galaxies in a cluster) and underlying mass. This work also probes aspects of cluster selection like the accuracy of cluster centering which are critical to weak lensing cluster studies.« less

paraGSEA: a scalable approach for large-scale gene expression profiling

PubMed Central

Peng, Shaoliang; Yang, Shunyun

2017-01-01

Abstract More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA. PMID:28973463

Measurement of k T splitting scales in W→ℓν events at $$\\sqrt{s} = 7\\ \\mathrm{TeV}$$ with the ATLAS detector

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

Aad, G.; Abajyan, T.; Abbott, B.

2013-05-15

A measurement of splitting scales, as defined by the k T clustering algorithm, is presented for final states containing a W boson produced in proton–proton collisions at a centre-of-mass energy of 7 TeV. The measurement is based on the full 2010 data sample corresponding to an integrated luminosity of 36 pb -1 which was collected using the ATLAS detector at the CERN Large Hadron Collider. Cluster splitting scales are measured in events containing W bosons decaying to electrons or muons. The measurement comprises the four hardest splitting scales in a k T cluster sequence of the hadronic activity accompanying themore » W boson, and ratios of these splitting scales. Backgrounds such as multi-jet and top-quark-pair production are subtracted and the results are corrected for detector effects. Predictions from various Monte Carlo event generators at particle level are compared to the data. Overall, reasonable agreement is found with all generators, but larger deviations between the predictions and the data are evident in the soft regions of the splitting scales.« less

The Angular Power Spectrum of BATSE 3B Gamma-Ray Bursts

NASA Technical Reports Server (NTRS)

Tegmark, Max; Hartmann, Dieter H.; Briggs, Michael S.; Meegan, Charles A.

1996-01-01

We compute the angular power spectrum C(sub l) from the BATSE 3B catalog of 1122 gamma-ray bursts and find no evidence for clustering on any scale. These constraints bridge the entire range from small scales (which probe source clustering and burst repetition) to the largest scales (which constrain possible anisotropics from the Galactic halo or from nearby cosmological large-scale structures). We develop an analysis technique that takes the angular position errors into account. For specific clustering or repetition models, strong upper limits can be obtained down to scales l approx. equal to 30, corresponding to a couple of degrees on the sky. The minimum-variance burst weighting that we employ is visualized graphically as an all-sky map in which each burst is smeared out by an amount corresponding to its position uncertainty. We also present separate bandpass-filtered sky maps for the quadrupole term and for the multipole ranges l = 3-10 and l = 11-30, so that the fluctuations on different angular scales can be inspected separately for visual features such as localized 'hot spots' or structures aligned with the Galactic plane. These filtered maps reveal no apparent deviations from isotropy.

Centre-excised X-ray luminosity as an efficient mass proxy for future galaxy cluster surveys

DOE PAGES

Mantz, Adam B.; Allen, Steven W.; Morris, R. Glenn; ...

2017-10-02

The cosmological constraining power of modern galaxy cluster catalogues can be improved by obtaining low-scatter mass proxy measurements for even a small fraction of sources. In the context of large upcoming surveys that will reveal the cluster population down to the group scale and out to high redshifts, efficient strategies for obtaining such mass proxies will be valuable. Here in this work, we use high-quality weak-lensing and X-ray mass estimates for massive clusters in current X-ray-selected catalogues to revisit the scaling relations of the projected, centre-excised X-ray luminosity (L ce), which previous work suggests correlates tightly with total mass. Ourmore » data confirm that this is the case with Lce having an intrinsic scatter at fixed mass comparable to that of gas mass, temperature or YX. Compared to the other proxies, however, Lce is less susceptible to systematic uncertainties due to background modelling, and can be measured precisely with shorter exposures. This opens up the possibility of using L ce to estimate masses for large numbers of clusters discovered by new X-ray surveys (e.g. eROSITA) directly from the survey data, as well as for clusters discovered at other wavelengths with relatively short follow-up observations. We describe a simple procedure for making such estimates from X-ray surface brightness data, and comment on the spatial resolution required to apply this method as a function of cluster mass and redshift. Lastly, we also explore the potential impact of Chandra and XMM–Newton follow-up observations over the next decade on dark energy constraints from new cluster surveys.« less

Centre-excised X-ray luminosity as an efficient mass proxy for future galaxy cluster surveys

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

Mantz, Adam B.; Allen, Steven W.; Morris, R. Glenn

The cosmological constraining power of modern galaxy cluster catalogues can be improved by obtaining low-scatter mass proxy measurements for even a small fraction of sources. In the context of large upcoming surveys that will reveal the cluster population down to the group scale and out to high redshifts, efficient strategies for obtaining such mass proxies will be valuable. Here in this work, we use high-quality weak-lensing and X-ray mass estimates for massive clusters in current X-ray-selected catalogues to revisit the scaling relations of the projected, centre-excised X-ray luminosity (L ce), which previous work suggests correlates tightly with total mass. Ourmore » data confirm that this is the case with Lce having an intrinsic scatter at fixed mass comparable to that of gas mass, temperature or YX. Compared to the other proxies, however, Lce is less susceptible to systematic uncertainties due to background modelling, and can be measured precisely with shorter exposures. This opens up the possibility of using L ce to estimate masses for large numbers of clusters discovered by new X-ray surveys (e.g. eROSITA) directly from the survey data, as well as for clusters discovered at other wavelengths with relatively short follow-up observations. We describe a simple procedure for making such estimates from X-ray surface brightness data, and comment on the spatial resolution required to apply this method as a function of cluster mass and redshift. Lastly, we also explore the potential impact of Chandra and XMM–Newton follow-up observations over the next decade on dark energy constraints from new cluster surveys.« less

Reference Values of Within-District Intraclass Correlations of Academic Achievement by District Characteristics: Results from a Meta-Analysis of District-Specific Values

ERIC Educational Resources Information Center

Hedberg, E. C.; Hedges, Larry V.

2014-01-01

Randomized experiments are often considered the strongest designs to study the impact of educational interventions. Perhaps the most prevalent class of designs used in large scale education experiments is the cluster randomized design in which entire schools are assigned to treatments. In cluster randomized trials (CRTs) that assign schools to…

Cognitive Model Exploration and Optimization: A New Challenge for Computational Science

DTIC Science & Technology

2010-01-01

Introduction Research in cognitive science often involves the generation and analysis of computational cognitive models to explain various...HPC) clusters and volunteer computing for large-scale computational resources. The majority of applications on the Department of Defense HPC... clusters focus on solving partial differential equations (Post, 2009). These tend to be lean, fast models with little noise. While we lack specific

Weighted graph cuts without eigenvectors a multilevel approach.

PubMed

Dhillon, Inderjit S; Guan, Yuqiang; Kulis, Brian

2007-11-01

A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods. In this paper, we discuss an equivalence between the objective functions used in these seemingly different methods--in particular, a general weighted kernel k-means objective is mathematically equivalent to a weighted graph clustering objective. We exploit this equivalence to develop a fast, high-quality multilevel algorithm that directly optimizes various weighted graph clustering objectives, such as the popular ratio cut, normalized cut, and ratio association criteria. This eliminates the need for any eigenvector computation for graph clustering problems, which can be prohibitive for very large graphs. Previous multilevel graph partitioning methods, such as Metis, have suffered from the restriction of equal-sized clusters; our multilevel algorithm removes this restriction by using kernel k-means to optimize weighted graph cuts. Experimental results show that our multilevel algorithm outperforms a state-of-the-art spectral clustering algorithm in terms of speed, memory usage, and quality. We demonstrate that our algorithm is applicable to large-scale clustering tasks such as image segmentation, social network analysis and gene network analysis.

Scales of Star Formation: Does Local Environment Matter?

NASA Astrophysics Data System (ADS)

Bittle, Lauren

2018-01-01

I will present my work on measuring molecular gas properties in local universe galaxies to assess the impact of local environment on the gas and thus star formation. I will also discuss the gas properties on spatial scales that span an order of magnitude to best understand the layers of star formation processes. Local environments within these galaxies include external mechanisms from starburst supernova shells, spiral arm structure, and superstar cluster radiation. Observations of CO giant molecular clouds (GMC) of ~150pc resolution in IC 10, the Local Group dwarf starburst, probe the large-scale diffuse gas, some of which are near supernova bubble ridges. We mapped CO clouds across the spiral NGC 7793 at intermediate scales of ~20pc resolution with ALMA. With the clouds, we can test theories of cloud formation and destruction in relation to the spiral arm pattern and cluster population from the HST LEGUS analysis. Addressing the smallest scales, I will show results of 30 Doradus ALMA observations of sub-parsec dense molecular gas clumps only 15pc away from a superstar cluster R136. Though star formation occurs directly from the collapse of densest molecular gas, we test theories of scale-free star formation, which suggests a constant slope of the mass function from ~150pc GMCs to sub-parsec clumps. Probing environments including starburst supernova shells, spiral arm structure, and superstar cluster radiation shed light on how these local external mechanisms affect the molecular gas at various scales of star formation.

Large Data at Small Universities: Astronomical processing using a computer classroom

NASA Astrophysics Data System (ADS)

Fuller, Nathaniel James; Clarkson, William I.; Fluharty, Bill; Belanger, Zach; Dage, Kristen

2016-06-01

The use of large computing clusters for astronomy research is becoming more commonplace as datasets expand, but access to these required resources is sometimes difficult for research groups working at smaller Universities. As an alternative to purchasing processing time on an off-site computing cluster, or purchasing dedicated hardware, we show how one can easily build a crude on-site cluster by utilizing idle cycles on instructional computers in computer-lab classrooms. Since these computers are maintained as part of the educational mission of the University, the resource impact on the investigator is generally low.By using open source Python routines, it is possible to have a large number of desktop computers working together via a local network to sort through large data sets. By running traditional analysis routines in an “embarrassingly parallel” manner, gains in speed are accomplished without requiring the investigator to learn how to write routines using highly specialized methodology. We demonstrate this concept here applied to 1. photometry of large-format images and 2. Statistical significance-tests for X-ray lightcurve analysis. In these scenarios, we see a speed-up factor which scales almost linearly with the number of cores in the cluster. Additionally, we show that the usage of the cluster does not severely limit performance for a local user, and indeed the processing can be performed while the computers are in use for classroom purposes.

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.

MEASURING LENSING MAGNIFICATION OF QUASARS BY LARGE SCALE STRUCTURE USING THE VARIABILITY-LUMINOSITY RELATION

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

Bauer, Anne H.; Seitz, Stella; Jerke, Jonathan

2011-05-10

We introduce a technique to measure gravitational lensing magnification using the variability of type I quasars. Quasars' variability amplitudes and luminosities are tightly correlated, on average. Magnification due to gravitational lensing increases the quasars' apparent luminosity, while leaving the variability amplitude unchanged. Therefore, the mean magnification of an ensemble of quasars can be measured through the mean shift in the variability-luminosity relation. As a proof of principle, we use this technique to measure the magnification of quasars spectroscopically identified in the Sloan Digital Sky Survey (SDSS), due to gravitational lensing by galaxy clusters in the SDSS MaxBCG catalog. The Palomar-QUESTmore » Variability Survey, reduced using the DeepSky pipeline, provides variability data for the sources. We measure the average quasar magnification as a function of scaled distance (r/R{sub 200}) from the nearest cluster; our measurements are consistent with expectations assuming Navarro-Frenk-White cluster profiles, particularly after accounting for the known uncertainty in the clusters' centers. Variability-based lensing measurements are a valuable complement to shape-based techniques because their systematic errors are very different, and also because the variability measurements are amenable to photometric errors of a few percent and to depths seen in current wide-field surveys. Given the volume data of the expected from current and upcoming surveys, this new technique has the potential to be competitive with weak lensing shear measurements of large-scale structure.« less

The stellar populations of M 33

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

Van den bergh, S.

1991-07-01

A review is given of present ideas on the evolution and stellar content of the Triangulum nebula = M 33 = NGC 598. The disk of M 33 is embedded in a halo of globular clusters, metal-poor red giants, and RR Lyrae stars. Its nuclear bulge component is weak, suggesting that the halos of galaxies are not extensions of their bulges to large radii. The ages of M 33 clusters do not appear to exhibit a hiatus in their star-forming history like that which is observed in the Large Magellanic Cloud (LMC). Young and intermediate-age clusters with luminosities rivaling themore » populous clusters in the LMC are rare in M 33. The integrated light of the semistellar nucleus of M 33, which contains the strongest X-ray source in the Local Group, is dominated by a young metal-rich population. At optical wavelengths the disk scale length of M 33 is 9.6 arcmin, which is similar to the 9.9 arcmin scale length of OB associations. The ratio of the nova rate in M 33 to that in M 31 is approximately equal to the ratio of their luminosities. This suggests that the nova rate in a galaxy is not determined entirely by the integrated luminosity of old bulge stars. The gas-depletion time scale in the central region of M 33 is found to be about 1.7 {times} 10 to the 9th yr, which is significantly shorter than a Hubble time. 141 refs.« less

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.

Searching for Constraints on Starobinsky's Model with a Disappearing Cosmological Constant on Galaxy Cluster Scales

NASA Astrophysics Data System (ADS)

Alexeyev, S. O.; Latosh, B. N.; Echeistov, V. A.

2017-12-01

Predictions of the f( R)-gravity model with a disappearing cosmological constant (Starobinsky's model) on scales characteristic of galaxies and their clusters are considered. The absence of a difference in the mass dependence of the turnaround radius between Starobinsky's model and General Relativity accessible to observation at the current accuracy of measurements has been established. This is true both for small masses (from 109 M Sun) corresponding to an individual galaxy and for masses corresponding to large galaxy clusters (up to 1015 M Sun). The turnaround radius increases with parameter n for all masses. Despite the fact that some models give a considerably smaller turnaround radius than does General Relativity, none of the models goes beyond the bounds specified by the observational data.

Testing the Large-scale Environments of Cool-core and Non-cool-core Clusters with Clustering Bias

NASA Astrophysics Data System (ADS)

Medezinski, Elinor; Battaglia, Nicholas; Coupon, Jean; Cen, Renyue; Gaspari, Massimo; Strauss, Michael A.; Spergel, David N.

2017-02-01

There are well-observed differences between cool-core (CC) and non-cool-core (NCC) clusters, but the origin of this distinction is still largely unknown. Competing theories can be divided into internal (inside-out), in which internal physical processes transform or maintain the NCC phase, and external (outside-in), in which the cluster type is determined by its initial conditions, which in turn leads to different formation histories (I.e., assembly bias). We propose a new method that uses the relative assembly bias of CC to NCC clusters, as determined via the two-point cluster-galaxy cross-correlation function (CCF), to test whether formation history plays a role in determining their nature. We apply our method to 48 ACCEPT clusters, which have well resolved central entropies, and cross-correlate with the SDSS-III/BOSS LOWZ galaxy catalog. We find that the relative bias of NCC over CC clusters is b = 1.42 ± 0.35 (1.6σ different from unity). Our measurement is limited by the small number of clusters with core entropy information within the BOSS footprint, 14 CC and 34 NCC clusters. Future compilations of X-ray cluster samples, combined with deep all-sky redshift surveys, will be able to better constrain the relative assembly bias of CC and NCC clusters and determine the origin of the bimodality.

Testing the Large-scale Environments of Cool-core and Non-cool-core Clusters with Clustering Bias

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

Medezinski, Elinor; Battaglia, Nicholas; Cen, Renyue

2017-02-10

There are well-observed differences between cool-core (CC) and non-cool-core (NCC) clusters, but the origin of this distinction is still largely unknown. Competing theories can be divided into internal (inside-out), in which internal physical processes transform or maintain the NCC phase, and external (outside-in), in which the cluster type is determined by its initial conditions, which in turn leads to different formation histories (i.e., assembly bias). We propose a new method that uses the relative assembly bias of CC to NCC clusters, as determined via the two-point cluster-galaxy cross-correlation function (CCF), to test whether formation history plays a role in determiningmore » their nature. We apply our method to 48 ACCEPT clusters, which have well resolved central entropies, and cross-correlate with the SDSS-III/BOSS LOWZ galaxy catalog. We find that the relative bias of NCC over CC clusters is b = 1.42 ± 0.35 (1.6 σ different from unity). Our measurement is limited by the small number of clusters with core entropy information within the BOSS footprint, 14 CC and 34 NCC clusters. Future compilations of X-ray cluster samples, combined with deep all-sky redshift surveys, will be able to better constrain the relative assembly bias of CC and NCC clusters and determine the origin of the bimodality.« less

Fast large-scale clustering of protein structures using Gauss integrals.

PubMed

Harder, Tim; Borg, Mikael; Boomsma, Wouter; Røgen, Peter; Hamelryck, Thomas

2012-02-15

Clustering protein structures is an important task in structural bioinformatics. De novo structure prediction, for example, often involves a clustering step for finding the best prediction. Other applications include assigning proteins to fold families and analyzing molecular dynamics trajectories. We present Pleiades, a novel approach to clustering protein structures with a rigorous mathematical underpinning. The method approximates clustering based on the root mean square deviation by first mapping structures to Gauss integral vectors--which were introduced by Røgen and co-workers--and subsequently performing K-means clustering. Compared to current methods, Pleiades dramatically improves on the time needed to perform clustering, and can cluster a significantly larger number of structures, while providing state-of-the-art results. The number of low energy structures generated in a typical folding study, which is in the order of 50,000 structures, can be clustered within seconds to minutes.

Small vs. Large Convective Cloud Objects from CERES Aqua Observations: Where are the Intraseasonal Variation Signals?

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2016-01-01

During inactive phases of Madden-Julian oscillation (MJO), there are plenty of deep but small convective systems and far fewer deep and large ones. During active phases of MJO, a manifestation of an increase in the occurrence of large and deep cloud clusters results from an amplification of large-scale motions by stronger convective heating. This study is designed to quantitatively examine the roles of small and large cloud clusters during the MJO life cycle. We analyze the cloud object data from Aqua CERES observations for tropical deep convective (DC) and cirrostratus (CS) cloud object types according to the real-time multivariate MJO index. The cloud object is a contiguous region of the earth with a single dominant cloud-system type. The size distributions, defined as the footprint numbers as a function of cloud object diameters, for particular MJO phases depart greatly from the combined (8-phase) distribution at large cloud-object diameters due to the reduced/increased numbers of cloud objects related to changes in the large-scale environments. The medium diameter corresponding to the combined distribution is determined and used to partition all cloud objects into "small" and "large" groups of a particular phase. The two groups corresponding to the combined distribution have nearly equal numbers of footprints. The medium diameters are 502 km for DC and 310 km for cirrostratus. The range of the variation between two extreme phases (typically, the most active and depressed phases) for the small group is 6-11% in terms of the numbers of cloud objects and the total footprint numbers. The corresponding range for the large group is 19-44%. In terms of the probability density functions of radiative and cloud physical properties, there are virtually no differences between the MJO phases for the small group, but there are significant differences for the large groups for both DC and CS types. These results suggest that the intreseasonal variation signals reside at the large cloud clusters while the small cloud clusters represent the background noises resulting from various types of the tropical waves with different wavenumbers and propagation directions/speeds.

The peculiar velocities of rich clusters in the hot and cold dark matter scenarios

NASA Technical Reports Server (NTRS)

Rhee, George F.; West, Michael J.; Villumsen, Jens V.

1993-01-01

We present the results of a study of the peculiar velocities of rich clusters of galaxies. The peculiar motion of rich clusters in various cosmological scenarios is of interest for a number of reasons. Observationally, one can measure the peculiar motion of clusters to greater distances than galaxies because cluster peculiar motions can be determined to greater accuracy. One can also test the slope of distance indicator relations using clusters to see if galaxy properties vary with environment. We have used N-body simulations to measure the amplitude and rms cluster peculiar velocity as a function of bias parameter in the hot and cold dark matter scenarios. In addition to measuring the mean and rms peculiar velocity of clusters in the two models, we determined whether the peculiar velocity vector of a given cluster is well aligned with the gravity vector due to all the particles in the simulation and the gravity vector due to the particles present only in the clusters. We have investigated the peculiar velocities of rich clusters of galaxies in the cold dark matter and hot dark matter galaxy formation scenarios. We have derived peculiar velocities and associated errors for the scenarios using four values of the bias parameter ranging from b = 1 to b = 2.5. The growth of the mean peculiar velocity with scale factor has been determined and compared to that predicted by linear theory. In addition, we have compared the orientation of force and velocity in these simulations to see if a program such as that proposed by Bertschinger and Dekel (1989) for elliptical galaxy peculiar motions can be applied to clusters. The method they describe enables one to recover the density field from large scale redshift distance samples. The method makes it possible to do this when only radial velocities are known by assuming that the velocity field is curl free. Our analysis suggests that this program if applied to clusters is only realizable for models with a low value of the bias parameter, i.e., models in which the peculiar velocities of clusters are large enough that the errors do not render the analysis impracticable.

Ontology-based topic clustering for online discussion data

NASA Astrophysics Data System (ADS)

Wang, Yongheng; Cao, Kening; Zhang, Xiaoming

2013-03-01

With the rapid development of online communities, mining and extracting quality knowledge from online discussions becomes very important for the industrial and marketing sector, as well as for e-commerce applications and government. Most of the existing techniques model a discussion as a social network of users represented by a user-based graph without considering the content of the discussion. In this paper we propose a new multilayered mode to analysis online discussions. The user-based and message-based representation is combined in this model. A novel frequent concept sets based clustering method is used to cluster the original online discussion network into topic space. Domain ontology is used to improve the clustering accuracy. Parallel methods are also used to make the algorithms scalable to very large data sets. Our experimental study shows that the model and algorithms are effective when analyzing large scale online discussion data.

EarthShape: A Strategy for Investigating the Role of Biota on Surface Processes

NASA Astrophysics Data System (ADS)

Ehlers, T. A.; von Blanckenburg, F.; Übernickel, K.; Paulino, L.

2016-12-01

EarthShape - "Earth surface shaping by biota" is a 6-year priority research program funded by the German science foundation (DFG-SPP 1803) that performs soil- and landscape-scale critical zone research at 4 locations along a climate gradient in the Chilean Coastal Cordillera. This region was selected because of its north-south orientation such that it captures a large ecological and climate gradient ranging from hyper-arid to temperate to humid conditions. The sites comprise granitic, previously unglaciated mountain ranges. EarthShape involves an interdisciplinary collaboration between geologists, geomorphologists, ecologists, soil scientists, microbiologists, geophysicists, geochemists, and hydrogeologists including 18 German and 8 Chilean institutions. EarthShape is composed of 4 research clusters representing the process chain from weathering of substrate to deposition of eroded material. Cluster 1 explores micro-biota as the "weathering engine". Investigations in this cluster quantify different mechanisms of biogenic weathering whereby plants, fungi, and bacteria interact with rock in the production of soil. Cluster 2 explores bio-mediated redistribution of material within the weathering zone. Studies in this cluster focus on soil catenas along hill slope profiles to investigate the modification of matter along its transport path. Cluster 3 explores biotic modulation of erosion and sediment routing at the catchment scale. Investigations in this cluster explore the effects of vegetation cover on solute and sediment transport from hill slopes to the channel network. Cluster 4 explores the depositional legacy of coupled biogenic and Earth surface systems. This cluster investigates records of vegetation-land surface interactions in different depositional settings. A final component of EarthShape lies in the integration of results from these 4 clusters using numerical models to bridging between the diverse times scales used by different disciplines.

Confirmation of general relativity on large scales from weak lensing and galaxy velocities.

PubMed

Reyes, Reinabelle; Mandelbaum, Rachel; Seljak, Uros; Baldauf, Tobias; Gunn, James E; Lombriser, Lucas; Smith, Robert E

2010-03-11

Although general relativity underlies modern cosmology, its applicability on cosmological length scales has yet to be stringently tested. Such a test has recently been proposed, using a quantity, E(G), that combines measures of large-scale gravitational lensing, galaxy clustering and structure growth rate. The combination is insensitive to 'galaxy bias' (the difference between the clustering of visible galaxies and invisible dark matter) and is thus robust to the uncertainty in this parameter. Modified theories of gravity generally predict values of E(G) different from the general relativistic prediction because, in these theories, the 'gravitational slip' (the difference between the two potentials that describe perturbations in the gravitational metric) is non-zero, which leads to changes in the growth of structure and the strength of the gravitational lensing effect. Here we report that E(G) = 0.39 +/- 0.06 on length scales of tens of megaparsecs, in agreement with the general relativistic prediction of E(G) approximately 0.4. The measured value excludes a model within the tensor-vector-scalar gravity theory, which modifies both Newtonian and Einstein gravity. However, the relatively large uncertainty still permits models within f(R) theory, which is an extension of general relativity. A fivefold decrease in uncertainty is needed to rule out these models.

Confirmation of general relativity on large scales from weak lensing and galaxy velocities

NASA Astrophysics Data System (ADS)

Reyes, Reinabelle; Mandelbaum, Rachel; Seljak, Uros; Baldauf, Tobias; Gunn, James E.; Lombriser, Lucas; Smith, Robert E.

2010-03-01

Although general relativity underlies modern cosmology, its applicability on cosmological length scales has yet to be stringently tested. Such a test has recently been proposed, using a quantity, EG, that combines measures of large-scale gravitational lensing, galaxy clustering and structure growth rate. The combination is insensitive to `galaxy bias' (the difference between the clustering of visible galaxies and invisible dark matter) and is thus robust to the uncertainty in this parameter. Modified theories of gravity generally predict values of EG different from the general relativistic prediction because, in these theories, the `gravitational slip' (the difference between the two potentials that describe perturbations in the gravitational metric) is non-zero, which leads to changes in the growth of structure and the strength of the gravitational lensing effect. Here we report that EG = 0.39+/-0.06 on length scales of tens of megaparsecs, in agreement with the general relativistic prediction of EG~0.4. The measured value excludes a model within the tensor-vector-scalar gravity theory, which modifies both Newtonian and Einstein gravity. However, the relatively large uncertainty still permits models within f() theory, which is an extension of general relativity. A fivefold decrease in uncertainty is needed to rule out these models.

Large-scale parallel genome assembler over cloud computing environment.

PubMed

Das, Arghya Kusum; Koppa, Praveen Kumar; Goswami, Sayan; Platania, Richard; Park, Seung-Jong

2017-06-01

The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research. In this paper, we present a de Bruijn graph oriented Parallel Giraph-based Genome Assembler (GiGA), as well as the hardware platform required for its optimal performance. GiGA uses the power of Hadoop (MapReduce) and Giraph (large-scale graph analysis) to achieve high scalability over hundreds of compute nodes by collocating the computation and data. GiGA achieves significantly higher scalability with competitive assembly quality compared to contemporary parallel assemblers (e.g. ABySS and Contrail) over traditional HPC cluster. Moreover, we show that the performance of GiGA is significantly improved by using an SSD-based private cloud infrastructure over traditional HPC cluster. We observe that the performance of GiGA on 256 cores of this SSD-based cloud infrastructure closely matches that of 512 cores of traditional HPC cluster.

The XMM Cluster Outskirts Project (X-COP)

NASA Astrophysics Data System (ADS)

Eckert, D.

2017-10-01

The outskirts of galaxy clusters (typically the regions located beyond R500) are the regions where the transition between the virialized ICM and the infalling material from the large-scale structure takes place. As such, they play a central role in our understanding of the processes leading to the virialization of the accreting gas within the central dark-matter halo. I will give an overview of the XMM cluster outskirts project (X-COP), a very large program on XMM to study the virial region of galaxy clusters with unprecedented details. I will show how X-ray observations can be combined with the Sunyaev-Zeldovich signal to recover the thermodynamic properties and hydrostatic mass of the ICM, bypassing the need for expensive X-ray spectroscopic observations. I will discuss the results obtained using this technique on Abell 2142 and Abell 2319 and give prospects for the results expected using the full X-COP sample. I will also present recent results on the search for warm-hot baryons in the filaments connected to clusters, emphasizing on the discovery of 3 filaments of 10-million-degree gas connected to the massive cluster Abell 2744.

Route to the Smallest Doped Semiconductor: Mn(2+)-Doped (CdSe)13 Clusters.

PubMed

Yang, Jiwoong; Fainblat, Rachel; Kwon, Soon Gu; Muckel, Franziska; Yu, Jung Ho; Terlinden, Hendrik; Kim, Byung Hyo; Iavarone, Dino; Choi, Moon Kee; Kim, In Young; Park, Inchul; Hong, Hyo-Ki; Lee, Jihwa; Son, Jae Sung; Lee, Zonghoon; Kang, Kisuk; Hwang, Seong-Ju; Bacher, Gerd; Hyeon, Taeghwan

2015-10-14

Doping semiconductor nanocrystals with magnetic transition-metal ions has attracted fundamental interest to obtain a nanoscale dilute magnetic semiconductor, which has unique spin exchange interaction between magnetic spin and exciton. So far, the study on the doped semiconductor NCs has usually been conducted with NCs with larger than 2 nm because of synthetic challenges. Herein, we report the synthesis and characterization of Mn(2+)-doped (CdSe)13 clusters, the smallest doped semiconductors. In this study, single-sized doped clusters are produced in large scale. Despite their small size, these clusters have semiconductor band structure instead of that of molecules. Surprisingly, the clusters show multiple excitonic transitions with different magneto-optical activities, which can be attributed to the fine structure splitting. Magneto-optically active states exhibit giant Zeeman splittings up to elevated temperatures (128 K) with large g-factors of 81(±8) at 4 K. Our results present a new synthetic method for doped clusters and facilitate the understanding of doped semiconductor at the boundary of molecules and quantum nanostructure.

Image Patch Analysis of Sunspots and Active Regions

NASA Astrophysics Data System (ADS)

Moon, K.; Delouille, V.; Hero, A.

2017-12-01

The flare productivity of an active region has been observed to be related to its spatial complexity. Separating active regions that are quiet from potentially eruptive ones is a key issue in space weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. However, their qualitative nature does not use all of the information present in the observations. In our work, we present an image patch analysis for characterizing sunspots and active regions. We first propose fine-scale quantitative descriptors for an active region's complexity such as intrinsic dimension, and we relate them to the Mount Wilson classification. Second, we introduce a new clustering of active regions that is based on the local geometry observed in Line of Sight magnetogram and continuum images. To obtain this local geometry, we use a reduced-dimension representation of an active region that is obtained by factoring the corresponding data matrix comprised of local image patches using the singular value decomposition. The resulting factorizations of active regions can be compared via the definition of appropriate metrics on the factors. The distances obtained from these metrics are then used to cluster the active regions. Results. We find that these metrics result in natural clusterings of active regions. The clusterings are related to large scale descriptors of an active region such as its size, its local magnetic field distribution, and its complexity as measured by the Mount Wilson classification scheme. We also find that including data focused on the neutral line of an active region can result in an increased correspondence between our clustering results and other active region descriptors such as the Mount Wilson classifications and the R-value.

Suppression of AGN-Driven G-Mode Turbulence by Magnetic Fields in a Magnetohydrodynamic Model of the Intracluster Medium

NASA Astrophysics Data System (ADS)

Bambic, Christopher J.; Morsony, Brian J.; Reynolds, Christopher S.

2017-08-01

We investigate the role of AGN feedback in turbulent heating of galaxy clusters. X-ray measurements of the Perseus Cluster intracluster medium (ICM) by the Hitomi Mission found a velocity dispersion measure of σ ˜ 164 km/s, indicating a large-scale turbulent energy of approximately 4% of the thermal energy. If this energy is transferred to small scales via a turbulent cascade and dissipated as heat, radiative cooling can be offset and the cluster can remain in the observed thermal equilibrium. Using 3D ideal MHD simulations and a plane-parallel model of the ICM, we analyze the production of turbulence by g-modes generated by the supersonic expansion and buoyant rise of AGN-driven bubbles. Previous work has shown that this process is inefficient, with less than 1% of the injected energy ending up in turbulence. Hydrodynamic instabilities shred the bubbles apart before they can excite sufficiently strong g-modes. We examine the role of a large-scale magnetic field which is able to drape around these rising bubbles, preserving them from instabilities. We show that a helical magnetic field geometry is able to better preserve bubbles, driving stronger g-modes; however, the production of turbulence is still inefficient. Magnetic tension acts to stabilize g-modes, preventing the nonlinear transition to turbulence. In addition, the magnetic tension force acts along the field lines to suppress the formation of small-scale vortices. These two effects halt the turbulent cascade. Our work shows that ideal MHD is an insufficient description for the cluster feedback process, and we discuss future work such as the inclusion of anisotropic viscosity as a means of simulating high β plasma kinetic effects. In addition, other mechanisms of heating the ICM plasma such as sound waves or cosmic rays may be responsible to account for observed feedback in galaxy clusters.

Diffusion of two-dimensional epitaxial clusters on metal (100) surfaces: Facile versus nucleation-mediated behavior and their merging for larger sizes

NASA Astrophysics Data System (ADS)

Lai, King C.; Liu, Da-Jiang; Evans, James W.

2017-12-01

For diffusion of two-dimensional homoepitaxial clusters of N atoms on metal (100) surfaces mediated by edge atom hopping, macroscale continuum theory suggests that the diffusion coefficient scales like DN˜ N-β with β =3 /2 . However, we find quite different and diverse behavior in multiple size regimes. These include: (i) facile diffusion for small sizes N <9 ; (ii) slow nucleation-mediated diffusion with small β <1 for "perfect" sizes N = Np= L2 or L (L +1 ) , for L =3 ,4 , ... having unique ground-state shapes, for moderate sizes 9 ≤N ≤O (102) ; the same also applies for N =Np+3 , Np+ 4 , ... (iii) facile diffusion but with large β >2 for N =Np+1 and Np+2 also for moderate sizes 9 ≤N ≤O (102) ; (iv) merging of the above distinct branches and subsequent anomalous scaling with 1 ≲β <3 /2 , reflecting the quasifacetted structure of clusters, for larger N =O (102) to N =O (103) ; (v) classic scaling with β =3 /2 for very large N =O (103) and above. The specified size ranges apply for typical model parameters. We focus on the moderate size regime where we show that diffusivity cycles quasiperiodically from the slowest branch for Np+3 (not Np) to the fastest branch for Np+1 . Behavior is quantified by kinetic Monte Carlo simulation of an appropriate stochastic lattice-gas model. However, precise analysis must account for a strong enhancement of diffusivity for short time increments due to back correlation in the cluster motion. Further understanding of this enhancement, of anomalous size scaling behavior, and of the merging of various branches, is facilitated by combinatorial analysis of the number of the ground-state and low-lying excited state cluster configurations, and also of kink populations.

Diffusion of two-dimensional epitaxial clusters on metal (100) surfaces: Facile versus nucleation-mediated behavior and their merging for larger sizes

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

Lai, King C.; Liu, Da -Jiang; Evans, James W.

For diffusion of two-dimensional homoepitaxial clusters of N atoms on metal(100) surfaces mediated by edge atom hopping, macroscale continuum theory suggests that the diffusion coefficient scales like DN ~ N -β with β = 3/2. However, we find quite different and diverse behavior in multiple size regimes. These include: (i) facile diffusion for small sizes N < 9; (ii) slow nucleation-mediated diffusion with small β < 1 for “perfect” sizes N = N p = L 2 or L(L+1), for L = 3, 4,… having unique ground state shapes, for moderate sizes 9 ≤ N ≤ O(10 2); the samemore » also applies for N = N p +3, N p + 4,… (iii) facile diffusion but with large β > 2 for N = Np + 1 and N p + 2 also for moderate sizes 9 ≤ N ≤ O(10 2); (iv) merging of the above distinct branches and subsequent anomalous scaling with 1 ≲ β < 3/2, reflecting the quasi-facetted structure of clusters, for larger N = O(10 2) to N = O(10 3); and (v) classic scaling with β = 3/2 for very large N = O(103) and above. The specified size ranges apply for typical model parameters. We focus on the moderate size regime where show that diffusivity cycles quasi-periodically from the slowest branch for N p + 3 (not Np) to the fastest branch for Np + 1. Behavior is quantified by Kinetic Monte Carlo simulation of an appropriate stochastic lattice-gas model. However, precise analysis must account for a strong enhancement of diffusivity for short time increments due to back-correlation in the cluster motion. Further understanding of this enhancement, of anomalous size scaling behavior, and of the merging of various branches, is facilitated by combinatorial analysis of the number of the ground state and low-lying excited state cluster configurations, and also of kink populations.« less

Diffusion of two-dimensional epitaxial clusters on metal (100) surfaces: Facile versus nucleation-mediated behavior and their merging for larger sizes

DOE PAGES

Lai, King C.; Liu, Da -Jiang; Evans, James W.

2017-12-05

For diffusion of two-dimensional homoepitaxial clusters of N atoms on metal(100) surfaces mediated by edge atom hopping, macroscale continuum theory suggests that the diffusion coefficient scales like DN ~ N -β with β = 3/2. However, we find quite different and diverse behavior in multiple size regimes. These include: (i) facile diffusion for small sizes N < 9; (ii) slow nucleation-mediated diffusion with small β < 1 for “perfect” sizes N = N p = L 2 or L(L+1), for L = 3, 4,… having unique ground state shapes, for moderate sizes 9 ≤ N ≤ O(10 2); the samemore » also applies for N = N p +3, N p + 4,… (iii) facile diffusion but with large β > 2 for N = Np + 1 and N p + 2 also for moderate sizes 9 ≤ N ≤ O(10 2); (iv) merging of the above distinct branches and subsequent anomalous scaling with 1 ≲ β < 3/2, reflecting the quasi-facetted structure of clusters, for larger N = O(10 2) to N = O(10 3); and (v) classic scaling with β = 3/2 for very large N = O(103) and above. The specified size ranges apply for typical model parameters. We focus on the moderate size regime where show that diffusivity cycles quasi-periodically from the slowest branch for N p + 3 (not Np) to the fastest branch for Np + 1. Behavior is quantified by Kinetic Monte Carlo simulation of an appropriate stochastic lattice-gas model. However, precise analysis must account for a strong enhancement of diffusivity for short time increments due to back-correlation in the cluster motion. Further understanding of this enhancement, of anomalous size scaling behavior, and of the merging of various branches, is facilitated by combinatorial analysis of the number of the ground state and low-lying excited state cluster configurations, and also of kink populations.« less

Stochastic theory of log-periodic patterns

NASA Astrophysics Data System (ADS)

Canessa, Enrique

2000-12-01

We introduce an analytical model based on birth-death clustering processes to help in understanding the empirical log-periodic corrections to power law scaling and the finite-time singularity as reported in several domains including rupture, earthquakes, world population and financial systems. In our stochastic theory log-periodicities are a consequence of transient clusters induced by an entropy-like term that may reflect the amount of co-operative information carried by the state of a large system of different species. The clustering completion rates for the system are assumed to be given by a simple linear death process. The singularity at t0 is derived in terms of birth-death clustering coefficients.

RR Lyrae stars and the horizontal branch of NGC 5904 (M5)

NASA Astrophysics Data System (ADS)

Arellano Ferro, A.; Luna, A.; Bramich, D. M.; Giridhar, Sunetra; Ahumada, J. A.; Muneer, S.

2016-05-01

We report the distance and [Fe/H] value for the globular cluster NGC 5904 (M5) derived from the Fourier decomposition of the light curves of selected RRab and RRc stars. The aim in doing this was to bring these parameters into the homogeneous scales established by our previous work on numerous other globular clusters, allowing a direct comparison of the horizontal branch luminosity in clusters with a wide range of metallicities. Our CCD photometry of the large variable star population of this cluster is used to discuss light curve peculiarities, like Blazhko modulations, on an individual basis. New Blazhko variables are reported.

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

Large-Scale Genomic Analysis of Codon Usage in Dengue Virus and Evaluation of Its Phylogenetic Dependence

PubMed Central

Lara-Ramírez, Edgar E.; Salazar, Ma Isabel; López-López, María de Jesús; Salas-Benito, Juan Santiago; Sánchez-Varela, Alejandro

2014-01-01

The increasing number of dengue virus (DENV) genome sequences available allows identifying the contributing factors to DENV evolution. In the present study, the codon usage in serotypes 1–4 (DENV1–4) has been explored for 3047 sequenced genomes using different statistics methods. The correlation analysis of total GC content (GC) with GC content at the three nucleotide positions of codons (GC1, GC2, and GC3) as well as the effective number of codons (ENC, ENCp) versus GC3 plots revealed mutational bias and purifying selection pressures as the major forces influencing the codon usage, but with distinct pressure on specific nucleotide position in the codon. The correspondence analysis (CA) and clustering analysis on relative synonymous codon usage (RSCU) within each serotype showed similar clustering patterns to the phylogenetic analysis of nucleotide sequences for DENV1–4. These clustering patterns are strongly related to the virus geographic origin. The phylogenetic dependence analysis also suggests that stabilizing selection acts on the codon usage bias. Our analysis of a large scale reveals new feature on DENV genomic evolution. PMID:25136631

Topology of Large-Scale Structure by Galaxy Type: Hydrodynamic Simulations

NASA Astrophysics Data System (ADS)

Gott, J. Richard, III; Cen, Renyue; Ostriker, Jeremiah P.

1996-07-01

The topology of large-scale structure is studied as a function of galaxy type using the genus statistic. In hydrodynamical cosmological cold dark matter simulations, galaxies form on caustic surfaces (Zeldovich pancakes) and then slowly drain onto filaments and clusters. The earliest forming galaxies in the simulations (defined as "ellipticals") are thus seen at the present epoch preferentially in clusters (tending toward a meatball topology), while the latest forming galaxies (defined as "spirals") are seen currently in a spongelike topology. The topology is measured by the genus (number of "doughnut" holes minus number of isolated regions) of the smoothed density-contour surfaces. The measured genus curve for all galaxies as a function of density obeys approximately the theoretical curve expected for random- phase initial conditions, but the early-forming elliptical galaxies show a shift toward a meatball topology relative to the late-forming spirals. Simulations using standard biasing schemes fail to show such an effect. Large observational samples separated by galaxy type could be used to test for this effect.

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.

Mass propagation of shoots of Stevia rebaudiana using a large scale bioreactor.

PubMed

Akita, M; Shigeoka, T; Koizumi, Y; Kawamura, M

1994-01-01

A procedure for the mass propagation of multiple shoots of Stevia rebaudiana is described. Isolated shoot primordia were used as the inoculum to obtain clusters of shoot primordia. Such clusters were grown in a 500 liter bioreactor to obtain shoots. A total of 64.6 Kg of shoots were propagated from 460 g of the inoculated shoot primordia. These shoots were easily acclimatized in soil.

Chemical Abundances of Giants in Globular Clusters

NASA Astrophysics Data System (ADS)

Gratton, Raffaele G.; Bragaglia, Angela; Carretta, Eugenio; D'Orazi, Valentina; Lucatello, Sara

A large fraction of stars form in clusters. According to a widespread paradigma, stellar clusters are prototypes of single stellar populations. According to this concept, they formed on a very short time scale, and all their stars share the same chemical composition. Recently it has been understood that massive stellar clusters (the globular clusters) rather host various stellar populations, characterized by different chemical composition: these stellar populations have also slightly different ages, stars of the second generations being formed from the ejecta of part of those of an earlier one. Furthermore, it is becoming clear that the efficiency of the process is quite low: many more stars formed within this process than currently present in the clusters. This implies that a significant, perhaps even dominant fraction of the ancient population of galaxies formed within the episodes that lead to formation the globular clusters.

Clustering and heterogeneous dynamics in a kinetic Monte Carlo model of self-propelled hard disks

NASA Astrophysics Data System (ADS)

Levis, Demian; Berthier, Ludovic

2014-06-01

We introduce a kinetic Monte Carlo model for self-propelled hard disks to capture with minimal ingredients the interplay between thermal fluctuations, excluded volume, and self-propulsion in large assemblies of active particles. We analyze in detail the resulting (density, self-propulsion) nonequilibrium phase diagram over a broad range of parameters. We find that purely repulsive hard disks spontaneously aggregate into fractal clusters as self-propulsion is increased and rationalize the evolution of the average cluster size by developing a kinetic model of reversible aggregation. As density is increased, the nonequilibrium clusters percolate to form a ramified structure reminiscent of a physical gel. We show that the addition of a finite amount of noise is needed to trigger a nonequilibrium phase separation, showing that demixing in active Brownian particles results from a delicate balance between noise, interparticle interactions, and self-propulsion. We show that self-propulsion has a profound influence on the dynamics of the active fluid. We find that the diffusion constant has a nonmonotonic behavior as self-propulsion is increased at finite density and that activity produces strong deviations from Fickian diffusion that persist over large time scales and length scales, suggesting that systems of active particles generically behave as dynamically heterogeneous systems.

Using DOUBLE STAR and CLUSTER Synoptic Observations to Test Global MHD Simulations of the Large-scale Topology of the Dayside Merging Region

NASA Astrophysics Data System (ADS)

Berchem, J.; Marchaudon, A.; Bosqued, J.; Escoubet, C. P.; Dunlop, M.; Owen, C. J.; Reme, H.; Balogh, A.; Carr, C.; Fazakerley, A. N.; Cao, J. B.

2005-12-01

Synoptic measurements from the DOUBLE STAR and CLUSTER spacecraft offer a unique opportunity to evaluate global models in simulating the complex topology and dynamics of the dayside merging region. We compare observations from the DOUBLE STAR TC-1 and CLUSTER spacecraft on May 8, 2004 with the predictions from a three-dimensional magnetohydrodynamic (MHD) simulation that uses plasma and magnetic field parameters measured upstream of the bow shock by the WIND spacecraft. Results from the global simulation are consistent with the large-scale features observed by CLUSTER and TC-1. We discuss topological changes and plasma flows at the dayside magnetospheric boundary inferred from the simulation results. The simulation shows that the DOUBLE STAR spacecraft passed through the dawn side merging region as the IMF rotated. In particular, the simulation indicates that at times TC-1 was very close to the merging region. In addition, we found that the bifurcation of the merging region in the simulation results is consistent with predictions by the antiparallel merging model. However, because of the draping of the magnetosheath field lines over the magnetopause, the positions and shape of the merging region differ significantly from those predicted by the model.

Halo Intrinsic Alignment: Dependence on Mass, Formation Time, and Environment

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

Xia, Qianli; Kang, Xi; Wang, Peng

In this paper we use high-resolution cosmological simulations to study halo intrinsic alignment and its dependence on mass, formation time, and large-scale environment. In agreement with previous studies using N -body simulations, it is found that massive halos have stronger alignment. For the first time, we find that for a given halo mass older halos have stronger alignment and halos in cluster regions also have stronger alignment than those in filaments. To model these dependencies, we extend the linear alignment model with inclusion of halo bias and find that the halo alignment with its mass and formation time dependence canmore » be explained by halo bias. However, the model cannot account for the environment dependence, as it is found that halo bias is lower in clusters and higher in filaments. Our results suggest that halo bias and environment are independent factors in determining halo alignment. We also study the halo alignment correlation function and find that halos are strongly clustered along their major axes and less clustered along the minor axes. The correlated halo alignment can extend to scales as large as 100 h {sup −1} Mpc, where its feature is mainly driven by the baryon acoustic oscillation effect.« less

Performance of an MPI-only semiconductor device simulator on a quad socket/quad core InfiniBand platform.

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

Shadid, John Nicolas; Lin, Paul Tinphone

2009-01-01

This preliminary study considers the scaling and performance of a finite element (FE) semiconductor device simulator on a capacity cluster with 272 compute nodes based on a homogeneous multicore node architecture utilizing 16 cores. The inter-node communication backbone for this Tri-Lab Linux Capacity Cluster (TLCC) machine is comprised of an InfiniBand interconnect. The nonuniform memory access (NUMA) nodes consist of 2.2 GHz quad socket/quad core AMD Opteron processors. The performance results for this study are obtained with a FE semiconductor device simulation code (Charon) that is based on a fully-coupled Newton-Krylov solver with domain decomposition and multilevel preconditioners. Scaling andmore » multicore performance results are presented for large-scale problems of 100+ million unknowns on up to 4096 cores. A parallel scaling comparison is also presented with the Cray XT3/4 Red Storm capability platform. The results indicate that an MPI-only programming model for utilizing the multicore nodes is reasonably efficient on all 16 cores per compute node. However, the results also indicated that the multilevel preconditioner, which is critical for large-scale capability type simulations, scales better on the Red Storm machine than the TLCC machine.« less

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

Gallarno, George; Rogers, James H; Maxwell, Don E

The high computational capability of graphics processing units (GPUs) is enabling and driving the scientific discovery process at large-scale. The world s second fastest supercomputer for open science, Titan, has more than 18,000 GPUs that computational scientists use to perform scientific simu- lations and data analysis. Understanding of GPU reliability characteristics, however, is still in its nascent stage since GPUs have only recently been deployed at large-scale. This paper presents a detailed study of GPU errors and their impact on system operations and applications, describing experiences with the 18,688 GPUs on the Titan supercom- puter as well as lessons learnedmore » in the process of efficient operation of GPUs at scale. These experiences are helpful to HPC sites which already have large-scale GPU clusters or plan to deploy GPUs in the future.« less

REVIEWS OF TOPICAL PROBLEMS: The large-scale structure of the universe

NASA Astrophysics Data System (ADS)

Shandarin, S. F.; Doroshkevich, A. G.; Zel'dovich, Ya B.

1983-01-01

A survey is given of theories for the origin of large-scale structure in the universe: clusters and superclusters of galaxies, and vast black regions practically devoid of galaxies. Special attention is paid to the theory of a neutrino-dominated universe—a cosmology in which electron neutrinos with a rest mass of a few tens of electron volts would contribute the bulk of the mean density. The evolution of small perturbations is discussed, and estimates are made for the temperature anisotropy of the microwave background radiation on various angular scales. The nonlinear stage in the evolution of smooth irrotational perturbations in a lowpressure medium is described in detail. Numerical experiments simulating large-scale structure formation processes are discussed, as well as their interpretation in the context of catastrophe theory.

Multiscale Embedded Gene Co-expression Network Analysis

PubMed Central

Song, Won-Min; Zhang, Bin

2015-01-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma. PMID:26618778

Multiscale Embedded Gene Co-expression Network Analysis.

PubMed

Song, Won-Min; Zhang, Bin

2015-11-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

Decomposition method for fast computation of gigapixel-sized Fresnel holograms on a graphics processing unit cluster.

PubMed

Jackin, Boaz Jessie; Watanabe, Shinpei; Ootsu, Kanemitsu; Ohkawa, Takeshi; Yokota, Takashi; Hayasaki, Yoshio; Yatagai, Toyohiko; Baba, Takanobu

2018-04-20

A parallel computation method for large-size Fresnel computer-generated hologram (CGH) is reported. The method was introduced by us in an earlier report as a technique for calculating Fourier CGH from 2D object data. In this paper we extend the method to compute Fresnel CGH from 3D object data. The scale of the computation problem is also expanded to 2 gigapixels, making it closer to real application requirements. The significant feature of the reported method is its ability to avoid communication overhead and thereby fully utilize the computing power of parallel devices. The method exhibits three layers of parallelism that favor small to large scale parallel computing machines. Simulation and optical experiments were conducted to demonstrate the workability and to evaluate the efficiency of the proposed technique. A two-times improvement in computation speed has been achieved compared to the conventional method, on a 16-node cluster (one GPU per node) utilizing only one layer of parallelism. A 20-times improvement in computation speed has been estimated utilizing two layers of parallelism on a very large-scale parallel machine with 16 nodes, where each node has 16 GPUs.

Non Thermal Emission from Clusters of Galaxies: the Importance of a Joint LOFAR/Simbol-X View

NASA Astrophysics Data System (ADS)

Ferrari, C.

2009-05-01

Deep radio observations of galaxy clusters have revealed the existence of diffuse radio sources (``halos'' and ``relics'') related to the presence of relativistic electrons and weak magnetic fields in the intracluster volume. I will outline our current knowledge about the presence and properties of this non-thermal cluster component. Despite the recent progress made in observational and theoretical studies of the non-thermal emission in galaxy clusters, a number of open questions about its origin and its effects on the thermo-dynamical evolution of galaxy clusters need to be answered. I will show the importance of combining galaxy cluster observations by new-generation instruments such as LOFAR and Simbol-X. A deeper knowledge of the non-thermal cluster component, together with statistical studies of radio halos and relics, will allow to test the current cluster formation scenario and to better constrain the physics of large scale structure evolution.

A Simple but Powerful Heuristic Method for Accelerating k-Means Clustering of Large-Scale Data in Life Science.

PubMed

Ichikawa, Kazuki; Morishita, Shinichi

2014-01-01

K-means clustering has been widely used to gain insight into biological systems from large-scale life science data. To quantify the similarities among biological data sets, Pearson correlation distance and standardized Euclidean distance are used most frequently; however, optimization methods have been largely unexplored. These two distance measurements are equivalent in the sense that they yield the same k-means clustering result for identical sets of k initial centroids. Thus, an efficient algorithm used for one is applicable to the other. Several optimization methods are available for the Euclidean distance and can be used for processing the standardized Euclidean distance; however, they are not customized for this context. We instead approached the problem by studying the properties of the Pearson correlation distance, and we invented a simple but powerful heuristic method for markedly pruning unnecessary computation while retaining the final solution. Tests using real biological data sets with 50-60K vectors of dimensions 10-2001 (~400 MB in size) demonstrated marked reduction in computation time for k = 10-500 in comparison with other state-of-the-art pruning methods such as Elkan's and Hamerly's algorithms. The BoostKCP software is available at http://mlab.cb.k.u-tokyo.ac.jp/~ichikawa/boostKCP/.

Light Scattering by Fractal Dust Aggregates. I. Angular Dependence of Scattering

NASA Astrophysics Data System (ADS)

Tazaki, Ryo; Tanaka, Hidekazu; Okuzumi, Satoshi; Kataoka, Akimasa; Nomura, Hideko

2016-06-01

In protoplanetary disks, micron-sized dust grains coagulate to form highly porous dust aggregates. Because the optical properties of these aggregates are not completely understood, it is important to investigate how porous dust aggregates scatter light. In this study, the light scattering properties of porous dust aggregates were calculated using a rigorous method, the T-matrix method, and the results were then compared with those obtained using the Rayleigh-Gans-Debye (RGD) theory and Mie theory with the effective medium approximation (EMT). The RGD theory is applicable to moderately large aggregates made of nearly transparent monomers. This study considered two types of porous dust aggregates—ballistic cluster-cluster agglomerates (BCCAs) and ballistic particle-cluster agglomerates. First, the angular dependence of the scattered intensity was shown to reflect the hierarchical structure of dust aggregates; the large-scale structure of the aggregates is responsible for the intensity at small scattering angles, and their small-scale structure determines the intensity at large scattering angles. Second, it was determined that the EMT underestimates the backward scattering intensity by multiple orders of magnitude, especially in BCCAs, because the EMT averages the structure within the size of the aggregates. It was concluded that the RGD theory is a very useful method for calculating the optical properties of BCCAs.

A VLT/MUSE galaxy survey towards QSO Q1410: looking for a WHIM traced by BLAs in inter-cluster filaments

NASA Astrophysics Data System (ADS)

Pessa, Ismael; Tejos, Nicolas; Barrientos, L. Felipe; Werk, Jessica; Bielby, Richard; Padilla, Nelson; Morris, Simon L.; Prochaska, J. Xavier; Lopez, Sebastian; Hummels, Cameron

2018-07-01

Cosmological simulations predict that a significant fraction of the low-z baryon budget resides in large-scale filaments in the form of a diffuse plasma at temperatures T ˜ 105 - 107 K. However, direct observation of this so-called warm-hot intergalactic medium (WHIM) has been elusive. In the Λcold dark matter paradigm, galaxy clusters correspond to the nodes of the cosmic web at the intersection of several large-scale filamentary threads. In previous work, we used HST/COS data to conduct the first survey of broad H I Lyα absorbers (BLAs) potentially produced by WHIM in inter-cluster filaments. We targeted a single QSO, namely Q1410, whose sightline intersects seven independent inter-cluster axes at impact parameters <3 Mpc (comoving), and found a tentative excess of a factor of ˜4 with respect to the field. Here, we further investigate the origin of these BLAs by performing a blind galaxy survey within the Q1410 field using VLT/MUSE. We identified 77 sources and obtained the redshifts for 52 of them. Out of the total sample of seven BLAs in inter-cluster axes, we found three without any galaxy counterpart to stringent luminosity limits (˜4 × 108 L⊙ ˜0.01 L*), providing further evidence that these BLAs may represent genuine WHIM detections. We combined this sample with other suitable BLAs from the literature and inferred the corresponding baryon mean density for these filaments in the range Ω ^fil_bar= 0.02-0.04. Our rough estimates are consistent with the predictions from numerical simulations but still subject to large systematic uncertainties, mostly from the adopted geometry, ionization corrections, and density profile.

Sloan Digital Sky Survey III photometric quasar clustering: probing the initial conditions of the Universe

NASA Astrophysics Data System (ADS)

Ho, Shirley; Agarwal, Nishant; Myers, Adam D.; Lyons, Richard; Disbrow, Ashley; Seo, Hee-Jong; Ross, Ashley; Hirata, Christopher; Padmanabhan, Nikhil; O'Connell, Ross; Huff, Eric; Schlegel, David; Slosar, Anže; Weinberg, David; Strauss, Michael; Ross, Nicholas P.; Schneider, Donald P.; Bahcall, Neta; Brinkmann, J.; Palanque-Delabrouille, Nathalie; Yèche, Christophe

2015-05-01

The Sloan Digital Sky Survey has surveyed 14,555 square degrees of the sky, and delivered over a trillion pixels of imaging data. We present the large-scale clustering of 1.6 million quasars between z=0.5 and z=2.5 that have been classified from this imaging, representing the highest density of quasars ever studied for clustering measurements. This data set spans 0~ 11,00 square degrees and probes a volume of 80 h-3 Gpc3. In principle, such a large volume and medium density of tracers should facilitate high-precision cosmological constraints. We measure the angular clustering of photometrically classified quasars using an optimal quadratic estimator in four redshift slices with an accuracy of ~ 25% over a bin width of δl ~ 10-15 on scales corresponding to matter-radiation equality and larger (0l ~ 2-3). Observational systematics can strongly bias clustering measurements on large scales, which can mimic cosmologically relevant signals such as deviations from Gaussianity in the spectrum of primordial perturbations. We account for systematics by employing a new method recently proposed by Agarwal et al. (2014) to the clustering of photometrically classified quasars. We carefully apply our methodology to mitigate known observational systematics and further remove angular bins that are contaminated by unknown systematics. Combining quasar data with the photometric luminous red galaxy (LRG) sample of Ross et al. (2011) and Ho et al. (2012), and marginalizing over all bias and shot noise-like parameters, we obtain a constraint on local primordial non-Gaussianity of fNL = -113+154-154 (1σ error). We next assume that the bias of quasar and galaxy distributions can be obtained independently from quasar/galaxy-CMB lensing cross-correlation measurements (such as those in Sherwin et al. (2013)). This can be facilitated by spectroscopic observations of the sources, enabling the redshift distribution to be completely determined, and allowing precise estimates of the bias parameters. In this paper, if the bias and shot noise parameters are fixed to their known values (which we model by fixing them to their best-fit Gaussian values), we find that the error bar reduces to 1σ simeq 65. We expect this error bar to reduce further by at least another factor of five if the data is free of any observational systematics. We therefore emphasize that in order to make best use of large scale structure data we need an accurate modeling of known systematics, a method to mitigate unknown systematics, and additionally independent theoretical models or observations to probe the bias of dark matter halos.

Phylogenetic investigation of a statewide HIV-1 epidemic reveals ongoing and active transmission networks among men who have sex with men

PubMed Central

Chan, Philip A.; Hogan, Joseph W.; Huang, Austin; DeLong, Allison; Salemi, Marco; Mayer, Kenneth H.; Kantor, Rami

2015-01-01

Background Molecular epidemiologic evaluation of HIV-1 transmission networks can elucidate behavioral components of transmission that can be targets for intervention. Methods We combined phylogenetic and statistical approaches using pol sequences from patients diagnosed 2004-2011 at a large HIV center in Rhode Island, following 75% of the state’s HIV population. Phylogenetic trees were constructed using maximum likelihood and putative transmission clusters were evaluated using latent class analyses (LCA) to determine association of cluster size with underlying demographic/behavioral characteristics. A logistic growth model was used to assess intra-cluster dynamics over time and predict “active” clusters that were more likely to harbor undiagnosed infections. Results Of 1,166 HIV-1 subtype B sequences, 31% were distributed among 114 statistically-supported, monophyletic clusters (range: 2-15 sequences/cluster). Sequences from men who have sex with men (MSM) formed 52% of clusters. LCA demonstrated that sequences from recently diagnosed (2008-2011) MSM with primary HIV infection (PHI) and other sexually transmitted infections (STIs) were more likely to form larger clusters (Odds Ratio 1.62-11.25, p<0.01). MSM in clusters were more likely to have anonymous partners and meet partners at sex clubs and pornographic stores. Four large clusters with 38 sequences (100% male, 89% MSM) had a high-probability of harboring undiagnosed infections and included younger MSM with PHI and STIs. Conclusions In this first large-scale molecular epidemiologic investigation of HIV-1 transmission in New England, sexual networks among recently diagnosed MSM with PHI and concomitant STIs contributed to ongoing transmission. Characterization of transmission dynamics revealed actively growing clusters which may be targets for intervention. PMID:26258569

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states

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

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field ismore » chaotic. We argue that this second type of behavior is “extensive” in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.« less

On the statistics of proto-cluster candidates detected in the Planck all-sky survey

NASA Astrophysics Data System (ADS)

Negrello, M.; Gonzalez-Nuevo, J.; De Zotti, G.; Bonato, M.; Cai, Z.-Y.; Clements, D.; Danese, L.; Dole, H.; Greenslade, J.; Lapi, A.; Montier, L.

2017-09-01

Observational investigations of the abundance of massive precursors of local galaxy clusters ('proto-clusters') allow us to test the growth of density perturbations, to constrain cosmological parameters that control it, to test the theory of non-linear collapse and how the galaxy formation takes place in dense environments. The Planck collaboration has recently published a catalogue of ≳2000 cold extragalactic sub-millimeter sources, I.e. with colours indicative of z ≳ 2, almost all of which appear to be overdensities of star-forming galaxies. They are thus considered as proto-cluster candidates. Their number densities (or their flux densities) are far in excess of expectations from the standard scenario for the evolution of large-scale structure. Simulations based on a physically motivated galaxy evolution model show that essentially all cold peaks brighter than S545GHz = 500 mJy found in Planck maps after having removed the Galactic dust emission can be interpreted as positive Poisson fluctuations of the number of high-z dusty proto-clusters within the same Planck beam, rather then being individual clumps of physically bound galaxies. This conclusion does not change if an empirical fit to the luminosity function of dusty galaxies is used instead of the physical model. The simulations accurately reproduce the statistic of the Planck detections and yield distributions of sizes and ellipticities in qualitative agreement with observations. The redshift distribution of the brightest proto-clusters contributing to the cold peaks has a broad maximum at 1.5 ≤ z ≤ 3. Therefore follow-up of Planck proto-cluster candidates will provide key information on the high-z evolution of large scale structure.

Large scale structural optimization of trimetallic Cu-Au-Pt clusters up to 147 atoms

NASA Astrophysics Data System (ADS)

Wu, Genhua; Sun, Yan; Wu, Xia; Chen, Run; Wang, Yan

2017-10-01

The stable structures of Cu-Au-Pt clusters up to 147 atoms are optimized by using an improved adaptive immune optimization algorithm (AIOA-IC method), in which several motifs, such as decahedron, icosahedron, face centered cubic, sixfold pancake, and Leary tetrahedron, are randomly selected as the inner cores of the starting structures. The structures of Cu8AunPt30-n (n = 1-29), Cu8AunPt47-n (n = 1-46), and partial 75-, 79-, 100-, and 147-atom clusters are analyzed. Cu12Au93Pt42 cluster has onion-like Mackay icosahedral motif. The segregation phenomena of Cu, Au and Pt in clusters are explained by the atomic radius, surface energy, and cohesive energy.

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

A LARGE-SCALE CLUSTER RANDOMIZED TRIAL TO DETERMINE THE EFFECTS OF COMMUNITY-BASED DIETARY SODIUM REDUCTION – THE CHINA RURAL HEALTH INITIATIVE SODIUM REDUCTION STUDY

PubMed Central

Li, Nicole; Yan, Lijing L.; Niu, Wenyi; Labarthe, Darwin; Feng, Xiangxian; Shi, Jingpu; Zhang, Jianxin; Zhang, Ruijuan; Zhang, Yuhong; Chu, Hongling; Neiman, Andrea; Engelgau, Michael; Elliott, Paul; Wu, Yangfeng; Neal, Bruce

2013-01-01

Background Cardiovascular diseases are the leading cause of death and disability in China. High blood pressure caused by excess intake of dietary sodium is widespread and an effective sodium reduction program has potential to improve cardiovascular health. Design This study is a large-scale, cluster-randomized, trial done in five Northern Chinese provinces. Two counties have been selected from each province and 12 townships in each county making a total of 120 clusters. Within each township one village has been selected for participation with 1:1 randomization stratified by county. The sodium reduction intervention comprises community health education and a food supply strategy based upon providing access to salt substitute. Subsidization of the price of salt substitute was done in 30 intervention villages selected at random. Control villages continued usual practices. The primary outcome for the study is dietary sodium intake level estimated from assays of 24 hour urine. Trial status The trial recruited and randomized 120 townships in April 2011. The sodium reduction program was commenced in the 60 intervention villages between May and June of that year with outcome surveys scheduled for October to December 2012. Baseline data collection shows that randomisation achieved good balance across groups. Discussion The establishment of the China Rural Health Initiative has enabled the launch of this large-scale trial designed to identify a novel, scalable strategy for reduction of dietary sodium and control of blood pressure. If proved effective, the intervention could plausibly be implemented at low cost in large parts of China and other countries worldwide. PMID:24176436

Constraining AGN triggering mechanisms through the clustering analysis of active black holes

NASA Astrophysics Data System (ADS)

Gatti, M.; Shankar, F.; Bouillot, V.; Menci, N.; Lamastra, A.; Hirschmann, M.; Fiore, F.

2016-02-01

The triggering mechanisms for active galactic nuclei (AGN) are still debated. Some of the most popular ones include galaxy interactions (IT) and disc instabilities (DIs). Using an advanced semi-analytic model (SAM) of galaxy formation, coupled to accurate halo occupation distribution modelling, we investigate the imprint left by each separate triggering process on the clustering strength of AGN at small and large scales. Our main results are as follows: (I) DIs, irrespective of their exact implementation in the SAM, tend to fall short in triggering AGN activity in galaxies at the centre of haloes with Mh > 1013.5 h-1 M⊙. On the contrary, the IT scenario predicts abundance of active central galaxies that generally agrees well with observations at every halo mass. (II) The relative number of satellite AGN in DIs at intermediate-to-low luminosities is always significantly higher than in IT models, especially in groups and clusters. The low AGN satellite fraction predicted for the IT scenario might suggest that different feeding modes could simultaneously contribute to the triggering of satellite AGN. (III) Both scenarios are quite degenerate in matching large-scale clustering measurements, suggesting that the sole average bias might not be an effective observational constraint. (IV) Our analysis suggests the presence of both a mild luminosity and a more consistent redshift dependence in the AGN clustering, with AGN inhabiting progressively less massive dark matter haloes as the redshift increases. We also discuss the impact of different observational selection cuts in measuring AGN clustering, including possible discrepancies between optical and X-ray surveys.

RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections

PubMed Central

Jaeger, Sébastien; Thieffry, Denis

2017-01-01

Abstract Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines. PMID:28591841

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.

Measuring the topology of large-scale structure in the universe

NASA Technical Reports Server (NTRS)

Gott, J. Richard, III

1988-01-01

An algorithm for quantitatively measuring the topology of large-scale structure has now been applied to a large number of observational data sets. The present paper summarizes and provides an overview of some of these observational results. On scales significantly larger than the correlation length, larger than about 1200 km/s, the cluster and galaxy data are fully consistent with a sponge-like random phase topology. At a smoothing length of about 600 km/s, however, the observed genus curves show a small shift in the direction of a meatball topology. Cold dark matter (CDM) models show similar shifts at these scales but not generally as large as those seen in the data. Bubble models, with voids completely surrounded on all sides by wall of galaxies, show shifts in the opposite direction. The CDM model is overall the most successful in explaining the data.

Measuring the topology of large-scale structure in the universe

NASA Astrophysics Data System (ADS)

Gott, J. Richard, III

1988-11-01

An algorithm for quantitatively measuring the topology of large-scale structure has now been applied to a large number of observational data sets. The present paper summarizes and provides an overview of some of these observational results. On scales significantly larger than the correlation length, larger than about 1200 km/s, the cluster and galaxy data are fully consistent with a sponge-like random phase topology. At a smoothing length of about 600 km/s, however, the observed genus curves show a small shift in the direction of a meatball topology. Cold dark matter (CDM) models show similar shifts at these scales but not generally as large as those seen in the data. Bubble models, with voids completely surrounded on all sides by wall of galaxies, show shifts in the opposite direction. The CDM model is overall the most successful in explaining the data.

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.

The effect of AGN feedback on the X-ray morphologies of clusters: Simulations vs. observations

NASA Astrophysics Data System (ADS)

Chon, Gayoung; Puchwein, Ewald; Böhringer, Hans

2016-07-01

Clusters of galaxies probe the large-scale distribution of matter and are a useful tool to test the cosmological models by constraining cosmic structure growth and the expansion of the Universe. It is the scaling relations between mass observables and the true mass of a cluster through which we obtain the cosmological constraints by comparing to theoretical cluster mass functions. These scaling relations are, however, heavily influenced by cluster morphology. The presence of the slight tension in recent cosmological constraints on Ωm and σ8 based on the CMB and clusters has boosted the interests in looking for possible sources for the discrepancy. Therefore we study here the effect of active galactic nucleus (AGN) feedback as one of the major mechanisms modifying the cluster morphology influencing scaling relations. It is known that AGN feedback injects energies up to 1062 erg into the intracluster medium, controls the heating and cooling of a cluster, and re-distributes cold gas from the centre to outer radii. We have also learned that cluster simulations with AGN feedback can reproduce observed cluster properties, for example, the X-ray luminosity, temperature, and cooling rate at the centre better than without the AGN feedback. In this paper using cosmological hydrodynamical simulations we investigate how the AGN feedback changes the X-ray morphology of the simulated systems, and compare this to the observed Representative XMM-Newton Cluster Structure Survey (REXCESS) clusters. We apply two substructure measures, centre shifts (w) and power ratios (e.g. P3/P0), to characterise the cluster morphology, and find that our simulated clusters are more substructured than the observed clusters based on the values of w and P3/P0. We also show that the degree of this discrepancy is affected by the inclusion of AGN feedback. While the clusters simulated with the AGN feedback are in much better agreement with the REXCESS LX-T relation, they are also more substructured, which increases the tension with observations. When classified as non-relaxed or relaxed according to their w and P3/P0 values, we find that there are no relaxed clusters in the simulations with the AGN feedback. This suggests that not only global cluster properties, like LX and T, and radial profiles should be used to compare and to calibrate simulations with observations, but also substructure measures like centre shifts and power ratios. Finally, we discuss what changes in the simulations might ease the tension with observational constraints on these quantities.

Simulations of the Formation and Evolution of X-ray Clusters

NASA Astrophysics Data System (ADS)

Bryan, G. L.; Klypin, A.; Norman, M. L.

1994-05-01

We describe results from a set of Omega = 1 Cold plus Hot Dark Matter (CHDM) and Cold Dark Matter (CDM) simulations. We examine the formation and evolution of X-ray clusters in a cosmological setting with sufficient numbers to perform statistical analysis. We find that CDM, normalized to COBE, seems to produce too many large clusters, both in terms of the luminosity (dn/dL) and temperature (dn/dT) functions. The CHDM simulation produces fewer clusters and the temperature distribution (our numerically most secure result) matches observations where they overlap. The computed cluster luminosity function drops below observations, but we are almost surely underestimating the X-ray luminosity. Because of the lower fluctuations in CHDM, there are only a small number of bright clusters in our simulation volume; however we can use the simulated clusters to fix the relation between temperature and velocity dispersion, allowing us to use collisionless N-body codes to probe larger length scales with correspondingly brighter clusters. The hydrodynamic simulations have been performed with a hybrid particle-mesh scheme for the dark matter and a high resolution grid-based piecewise parabolic method for the adiabatic gas dynamics. This combination has been implemented for massively parallel computers, allowing us to achive grids as large as 512(3) .

Gentle reenergization of electrons in merging galaxy clusters

PubMed Central

de Gasperin, Francesco; Intema, Huib T.; Shimwell, Timothy W.; Brunetti, Gianfranco; Brüggen, Marcus; Enßlin, Torsten A.; van Weeren, Reinout J.; Bonafede, Annalisa; Röttgering, Huub J. A.

2017-01-01

Galaxy clusters are the most massive constituents of the large-scale structure of the universe. Although the hot thermal gas that pervades galaxy clusters is relatively well understood through observations with x-ray satellites, our understanding of the nonthermal part of the intracluster medium (ICM) remains incomplete. With Low-Frequency Array (LOFAR) and Giant Metrewave Radio Telescope (GMRT) observations, we have identified a phenomenon that can be unveiled only at extremely low radio frequencies and offers new insights into the nonthermal component. We propose that the interplay between radio-emitting plasma and the perturbed intracluster medium can gently reenergize relativistic particles initially injected by active galactic nuclei. Sources powered through this mechanism can maintain electrons at higher energies than radiative aging would allow. If this mechanism is common for aged plasma, a population of mildly relativistic electrons can be accumulated inside galaxy clusters providing the seed population for merger-induced reacceleration mechanisms on larger scales such as turbulence and shock waves. PMID:28983512

Unconventional Current Scaling and Edge Effects for Charge Transport through Molecular Clusters

PubMed Central

2017-01-01

Metal–molecule–metal junctions are the key components of molecular electronics circuits. Gaining a microscopic understanding of their conducting properties is central to advancing the field. In the present contribution, we highlight the fundamental differences between single-molecule and ensemble junctions focusing on the fundamentals of transport through molecular clusters. In this way, we elucidate the collective behavior of parallel molecular wires, bridging the gap between single molecule and large-area monolayer electronics, where even in the latter case transport is usually dominated by finite-size islands. On the basis of first-principles charge-transport simulations, we explain why the scaling of the conductivity of a junction has to be distinctly nonlinear in the number of molecules it contains. Moreover, transport through molecular clusters is found to be highly inhomogeneous with pronounced edge effects determined by molecules in locally different electrostatic environments. These effects are most pronounced for comparably small clusters, but electrostatic considerations show that they prevail also for more extended systems. PMID:29043825

Gentle reenergization of electrons in merging galaxy clusters.

PubMed

de Gasperin, Francesco; Intema, Huib T; Shimwell, Timothy W; Brunetti, Gianfranco; Brüggen, Marcus; Enßlin, Torsten A; van Weeren, Reinout J; Bonafede, Annalisa; Röttgering, Huub J A

2017-10-01

Galaxy clusters are the most massive constituents of the large-scale structure of the universe. Although the hot thermal gas that pervades galaxy clusters is relatively well understood through observations with x-ray satellites, our understanding of the nonthermal part of the intracluster medium (ICM) remains incomplete. With Low-Frequency Array (LOFAR) and Giant Metrewave Radio Telescope (GMRT) observations, we have identified a phenomenon that can be unveiled only at extremely low radio frequencies and offers new insights into the nonthermal component. We propose that the interplay between radio-emitting plasma and the perturbed intracluster medium can gently reenergize relativistic particles initially injected by active galactic nuclei. Sources powered through this mechanism can maintain electrons at higher energies than radiative aging would allow. If this mechanism is common for aged plasma, a population of mildly relativistic electrons can be accumulated inside galaxy clusters providing the seed population for merger-induced reacceleration mechanisms on larger scales such as turbulence and shock waves.

High-resolution simulation of deep pencil beam surveys - analysis of quasi-periodicity

NASA Astrophysics Data System (ADS)

Weiss, A. G.; Buchert, T.

1993-07-01

We carry out pencil beam constructions in a high-resolution simulation of the large-scale structure of galaxies. The initial density fluctuations are taken to have a truncated power spectrum. All the models have {OMEGA} = 1. As an example we present the results for the case of "Hot-Dark-Matter" (HDM) initial conditions with scale-free n = 1 power index on large scales as a representative of models with sufficient large-scale power. We use an analytic approximation for particle trajectories of a self-gravitating dust continuum and apply a local dynamical biasing of volume elements to identify luminous matter in the model. Using this method, we are able to resolve formally a simulation box of 1200h^-1^ Mpc (e.g. for HDM initial conditions) down to the scale of galactic halos using 2160^3^ particles. We consider this as the minimal resolution necessary for a sensible simulation of deep pencil beam data. Pencil beam probes are taken for a given epoch using the parameters of observed beams. In particular, our analysis concentrates on the detection of a quasi-periodicity in the beam probes using several different methods. The resulting beam ensembles are analyzed statistically using number distributions, pair-count histograms, unnormalized pair-counts, power spectrum analysis and trial-period folding. Periodicities are classified according to their significance level in the power spectrum of the beams. The simulation is designed for application to parameter studies which prepare future observational projects. We find that a large percentage of the beams show quasi- periodicities with periods which cluster at a certain length scale. The periods found range between one and eight times the cutoff length in the initial fluctuation spectrum. At significance levels similar to those of the data of Broadhurst et al. (1990), we find about 15% of the pencil beams to show periodicities, about 30% of which are around the mean separation of rich clusters, while the distribution of scales reaches values of more than 200h^-1^ Mpc. The detection of periodicities larger than the typical void size must not be due to missing of "walls" (like the so called "Great Wall" seen in the CfA catalogue of galaxies), but can be due to different clustering properties of galaxies along the beams.

University of Hawaii Institute for Astronomy

DTIC Science & Technology

2001-01-01

sample is being used to investigate the nature of cluster evolution and explore potential implica- tions for large-scale structure. Four papers were...ping in the Virgo Cluster Galaxy NGC 4388. ApJ, 520, 111–123 (1999) Veilleux, S.; Kim, D.-C.; Sanders, D. B. Optical Spectroscopy of the IRAS 1 Jy...was compiled in October 2000. 1 Introduction The Institute for Astronomy (IfA) is the astronomical research organization of the University of Hawaii

Probing the largest cosmological scales with the correlation between the cosmic microwave background and peculiar velocities

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

Fosalba, Pablo; Dore, Olivier

2007-11-15

Cross correlation between the cosmic microwave background (CMB) and large-scale structure is a powerful probe of dark energy and gravity on the largest physical scales. We introduce a novel estimator, the CMB-velocity correlation, that has most of its power on large scales and that, at low redshift, delivers up to a factor of 2 higher signal-to-noise ratio than the recently detected CMB-dark matter density correlation expected from the integrated Sachs-Wolfe effect. We propose to use a combination of peculiar velocities measured from supernovae type Ia and kinetic Sunyaev-Zeldovich cluster surveys to reveal this signal and forecast dark energy constraints thatmore » can be achieved with future surveys. We stress that low redshift peculiar velocity measurements should be exploited with complementary deeper large-scale structure surveys for precision cosmology.« less

The formation of cosmic structure in a texture-seeded cold dark matter cosmogony

NASA Technical Reports Server (NTRS)

Gooding, Andrew K.; Park, Changbom; Spergel, David N.; Turok, Neil; Gott, Richard, III

1992-01-01

The growth of density fluctuations induced by global texture in an Omega = 1 cold dark matter (CDM) cosmogony is calculated. The resulting power spectra are in good agreement with each other, with more power on large scales than in the standard inflation plus CDM model. Calculation of related statistics (two-point correlation functions, mass variances, cosmic Mach number) indicates that the texture plus CDM model compares more favorably than standard CDM with observations of large-scale structure. Texture produces coherent velocity fields on large scales, as observed. Excessive small-scale velocity dispersions, and voids less empty than those observed may be remedied by including baryonic physics. The topology of the cosmic structure agrees well with observation. The non-Gaussian texture induced density fluctuations lead to earlier nonlinear object formation than in Gaussian models and may also be more compatible with recent evidence that the galaxy density field is non-Gaussian on large scales. On smaller scales the density field is strongly non-Gaussian, but this appears to be primarily due to nonlinear gravitational clustering. The velocity field on smaller scales is surprisingly Gaussian.

Dynamic Cluster Size Effects on the Glass Transition of Thin Films

NASA Astrophysics Data System (ADS)

Wool, Richard

2013-03-01

During cooling from the melt of amorphous materials, it has been shown experimentally that dynamic rigid clusters form in equilibrium with the liquid and their relaxation behavior determines the kinetic nature of Tg [Stanzione et al, J. Non Cryst Solids 357(2): 311-319 2011]. The fractal clusters of size R ~ 5-60 nm (polystyrene) have relaxation times τ ~ R1.8 (solid-to-liquid). They are analogous to sub critical size embryos during crystallization as the amorphous material tries to crystallize due to the strong intermolecular forces at T < Tm ; they are not related to density fluctuations or surface capillary waves. In free-standing thin films of thickness h, several important events occur: (a) The large clusters with R > h are excluded and the thin films have an average faster relaxation time compared to the bulk; consequently Tg decreases as h decreases. (b) The segmental dynamics at the 1 nm scale are largely not affected by nanoconfinement since Tg is determined only by the cluster dynamics with R >> 1 nm. (c) The mobile layer on the surface of free standing films is due to the presence of smaller clusters on the surface which will disappear with increasing rate of testing. (d) With adhesion to a solid substrate, the surface mobile layer disappears as the surface clusters size grow and the change in Tg is suppressed. (e) Physical aging is controlled by the relaxation of the rigid fractal clusters and in thin films, physical aging will occur more rapidly compared to the bulk. (f) The large effect of molecular weight M on Tg appears to be related to the effect on the cluster size distribution giving smaller clusters and faster relation times with increasing M. These results are in accord with the Twinkling Fractal theory of the glass transition.

Deep X-ray Observations of an Ongoing Merger and 400 Myr of AGN Activity in Cygnus A

NASA Astrophysics Data System (ADS)

Wise, Michael W.; De Vries, Martijn; Nulsen, Paul; Snios, Bradford; Birkinshaw, Mark; Worrall, Diana; Duffy, Ryan; Halbesma, Timo; Donnert, Julius; Hardcastle, Martin

2017-08-01

We present a detailed spatial and spectral analysis of the large-scale X-ray emission associated with the merging cluster of galaxies containing the powerful Cygnus A radio galaxy. Using a new 1 Msec exposure from the ongoing Chandra XVP project, we have mapped the large-scale structure, temperature and abundance of the ICM in a 1 Mpc x 1 Mpc region surrounding Cygnus A. This new, deep exposure resolves unprecedented detail in the jets, lobes, and cocoon shock associated with Cygnus A, and provides new insights into the emission mechanisms that produce these features as well as implications for the ongoing activity of the central AGN. On larger scales, these new data reveal complex and dramatic temperature, pressure, entropy and metallicity structure in the ICM surrounding Cygnus A. We confirm the presence of large-scale X-ray emission associated with the two merging cluster components seen previously in lower resolution data. The temperature structure on the scale of the merger exhibits an asymmetric enhancement to the NW consistent with projected hotter gas from the merger shock. Using the derived density and temperature profiles in the two merging sub-cluster components as inputs, we have constructed a grid of hydro-dynamical simulations to constrain the geometry of the merger system. These models imply a pre-merger system with a 1:1 mass ratio at the virial radius with an inclination toward the line of sight of 35-45 deg. In addition to the merger-induced temperature asymmetry, we find evidence for additional surface brightness and temperature features indicative of previous outburst activity in Cygnus A over the past 400 Myr. Based on the location and strength of these features, we derive the energy associated with these previous outbursts and place constraints on the growth of the black hole in Cygnus A over that timescale.

Galaxy Transformations In The Cosmic Web

NASA Astrophysics Data System (ADS)

Jablonka, Pascale

2017-06-01

In this talk, I present a new survey, the Spatial Extended EDisCS Survey (SEEDisCS), that aims at understanding how clusters assemble and the level at which galaxies are preprocessed before falling on the cluster cores. SEEDisCS therefore focusses on the changes in galaxy properties along the large scale structures surrounding a couple of z 0.5 medium mass clusters, I first describe how spiral disc stellar populations are affected by the environment,and how we can get constraints on the timescale of star formation quenching. I then present new NOEMA and ALMA CO observations that trace the fate of the galaxy cold gas content along the infalling paths towards the cluster cores.

Coevolutionary dynamics with clustering behaviors on cyclic competition

NASA Astrophysics Data System (ADS)

Dong, Linrong; Yang, Guangcan

2012-05-01

We propose a dynamic model for describing clustering behaviors on a cyclic game, in which the same species form a cluster to compete. The rates of consuming the prey depend not only on the individual competing ability v, but also on the two interacting cluster’s sizes. The fragmentation and coagulation rates of the clusters are related to the cohesive strength among the individuals. A new parameter u is introduced to indicate the uniting degree. We find that the probability distribution of the clustering sizes is almost a power law in a large regime specified by the two parameters, which reflects the scale-free behavior in complex systems. In addition, the exponential magnitudes are mostly in the range of real social systems. Our simulation shows that clustering promotes biodiversity. At steady state, the amounts about the three species evolve tempestuously with asymmetric period; the aggregations about big size’s clusters to compete are obvious and on-off intermittence.

Clustering impact regime with shocks in freely evolving granular gas

NASA Astrophysics Data System (ADS)

Isobe, Masaharu

2017-06-01

A freely cooling granular gas without any external force evolves from the initial homogeneous state to the inhomogeneous clustering state, at which the energy decay deviates from the Haff's law. The asymptotic behavior of energy in the inelastic hard sphere model have been predicted by several theories, which are based on the mode coupling theory or extension of inelastic hard rods gas. In this study, we revisited the clustering regime of freely evolving granular gas via large-scale molecular dynamics simulation with up to 16.7 million inelastic hard disks. We found novel regime regarding on collisions between "clusters" spontaneously appearing after clustering regime, which can only be identified more than a few million particles system. The volumetric dilatation pattern of semicircular shape originated from density shock propagation are well characterized on the appearing of "cluster impact" during the aggregation process of clusters.

Constraints on the gamma-ray emission from the cluster-scale AGN outburst in the Hydra A galaxy cluster

NASA Astrophysics Data System (ADS)

HESS Collaboration; Abramowski, A.; Acero, F.; Aharonian, F.; Akhperjanian, A. G.; Anton, G.; Balenderan, S.; Balzer, A.; Barnacka, A.; Becherini, Y.; Becker, J.; Bernlöhr, K.; Birsin, E.; Biteau, J.; Bochow, A.; Boisson, C.; Bolmont, J.; Bordas, P.; Brucker, J.; Brun, F.; Brun, P.; Bulik, T.; Büsching, I.; Carrigan, S.; Casanova, S.; Cerruti, M.; Chadwick, P. M.; Charbonnier, A.; Chaves, R. C. G.; Cheesebrough, A.; Cologna, G.; Conrad, J.; Couturier, C.; Daniel, M. K.; Davids, I. D.; Degrange, B.; Deil, C.; Dickinson, H. J.; Djannati-Ataï, A.; Domainko, W.; O'C. Drury, L.; Dubus, G.; Dutson, K.; Dyks, J.; Dyrda, M.; Egberts, K.; Eger, P.; Espigat, P.; Fallon, L.; Fegan, S.; Feinstein, F.; Fernandes, M. V.; Fiasson, A.; Fontaine, G.; Förster, A.; Füßling, M.; Gajdus, M.; Gallant, Y. A.; Garrigoux, T.; Gast, H.; Gérard, L.; Giebels, B.; Glicenstein, J. F.; Glück, B.; Göring, D.; Grondin, M.-H.; Häffner, S.; Hague, J. D.; Hahn, J.; Hampf, D.; Harris, J.; Hauser, M.; Heinz, S.; Heinzelmann, G.; Henri, G.; Hermann, G.; Hillert, A.; Hinton, J. A.; Hofmann, W.; Hofverberg, P.; Holler, M.; Horns, D.; Jacholkowska, A.; Jahn, C.; Jamrozy, M.; Jung, I.; Kastendieck, M. A.; Katarzyński, K.; Katz, U.; Kaufmann, S.; Khélifi, B.; Klochkov, D.; Kluźniak, W.; Kneiske, T.; Komin, Nu.; Kosack, K.; Kossakowski, R.; Krayzel, F.; Laffon, H.; Lamanna, G.; Lenain, J.-P.; Lennarz, D.; Lohse, T.; Lopatin, A.; Lu, C.-C.; Marandon, V.; Marcowith, A.; Masbou, J.; Maurin, G.; Maxted, N.; Mayer, M.; McComb, T. J. L.; Medina, M. C.; Méhault, J.; Moderski, R.; Mohamed, M.; Moulin, E.; Naumann, C. L.; Naumann-Godo, M.; de Naurois, M.; Nedbal, D.; Nekrassov, D.; Nguyen, N.; Nicholas, B.; Niemiec, J.; Nolan, S. J.; Ohm, S.; de Oña Wilhelmi, E.; Opitz, B.; Ostrowski, M.; Oya, I.; Panter, M.; Paz Arribas, M.; Pekeur, N. W.; Pelletier, G.; Perez, J.; Petrucci, P.-O.; Peyaud, B.; Pita, S.; Pühlhofer, G.; Punch, M.; Quirrenbach, A.; Raue, M.; Reimer, A.; Reimer, O.; Renaud, M.; de los Reyes, R.; Rieger, F.; Ripken, J.; Rob, L.; Rosier-Lees, S.; Rowell, G.; Rudak, B.; Rulten, C. B.; Sahakian, V.; Sanchez, D. A.; Santangelo, A.; Schlickeiser, R.; Schulz, A.; Schwanke, U.; Schwarzburg, S.; Schwemmer, S.; Sheidaei, F.; Skilton, J. L.; Sol, H.; Spengler, G.; Stawarz, Ł.; Steenkamp, R.; Stegmann, C.; Stinzing, F.; Stycz, K.; Sushch, I.; Szostek, A.; Tavernet, J.-P.; Terrier, R.; Tluczykont, M.; Valerius, K.; van Eldik, C.; Vasileiadis, G.; Venter, C.; Viana, A.; Vincent, P.; Völk, H. J.; Volpe, F.; Vorobiov, S.; Vorster, M.; Wagner, S. J.; Ward, M.; White, R.; Wierzcholska, A.; Zacharias, M.; Zajczyk, A.; Zdziarski, A. A.; Zech, A.; Zechlin, H.-S.; Ali, M. O.

2012-09-01

Context. In some galaxy clusters, powerful active galactic nuclei (AGN) have blown bubbles with cluster scale extent into the ambient medium. The main pressure support of these bubbles is not known to date, but cosmic rays are a viable possibility. For such a scenario copious gamma-ray emission is expected as a tracer of cosmic rays from these systems. Aims: Hydra A, the closest galaxy cluster hosting a cluster scale AGN outburst, located at a redshift of 0.0538, is investigated for being a gamma-ray emitter with the High Energy Stereoscopic System (H.E.S.S.) array and the Fermi Large Area Telescope (Fermi-LAT). Methods: Data obtained in 20.2 h of dedicated H.E.S.S. observations and 38 months of Fermi-LAT data, gathered by its usual all-sky scanning mode, have been analyzed to search for a gamma-ray signal. Results: No signal has been found in either data set. Upper limits on the gamma-ray flux are derived and are compared to models. These are the first limits on gamma-ray emission ever presented for galaxy clusters hosting cluster scale AGN outbursts. Conclusions: The non-detection of Hydra A in gamma-rays has important implications on the particle populations and physical conditions inside the bubbles in this system. For the case of bubbles mainly supported by hadronic cosmic rays, the most favorable scenario, which involves full mixing between cosmic rays and embedding medium, can be excluded. However, hadronic cosmic rays still remain a viable pressure support agent to sustain the bubbles against the thermal pressure of the ambient medium. The largest population of highly-energetic electrons, which are relevant for inverse-Compton gamma-ray production is found in the youngest inner lobes of Hydra A. The limit on the inverse-Compton gamma-ray flux excludes a magnetic field below half of the equipartition value of 16 μG in the inner lobes.

The XXL Survey. II. The bright cluster sample: catalogue and luminosity function

NASA Astrophysics Data System (ADS)

Pacaud, F.; Clerc, N.; Giles, P. A.; Adami, C.; Sadibekova, T.; Pierre, M.; Maughan, B. J.; Lieu, M.; Le Fèvre, J. P.; Alis, S.; Altieri, B.; Ardila, F.; Baldry, I.; Benoist, C.; Birkinshaw, M.; Chiappetti, L.; Démoclès, J.; Eckert, D.; Evrard, A. E.; Faccioli, L.; Gastaldello, F.; Guennou, L.; Horellou, C.; Iovino, A.; Koulouridis, E.; Le Brun, V.; Lidman, C.; Liske, J.; Maurogordato, S.; Menanteau, F.; Owers, M.; Poggianti, B.; Pomarède, D.; Pompei, E.; Ponman, T. J.; Rapetti, D.; Reiprich, T. H.; Smith, G. P.; Tuffs, R.; Valageas, P.; Valtchanov, I.; Willis, J. P.; Ziparo, F.

2016-06-01

Context. The XXL Survey is the largest survey carried out by the XMM-Newton satellite and covers a total area of 50 square degrees distributed over two fields. It primarily aims at investigating the large-scale structures of the Universe using the distribution of galaxy clusters and active galactic nuclei as tracers of the matter distribution. The survey will ultimately uncover several hundreds of galaxy clusters out to a redshift of ~2 at a sensitivity of ~10-14 erg s-1 cm-2 in the [0.5-2] keV band. Aims: This article presents the XXL bright cluster sample, a subsample of 100 galaxy clusters selected from the full XXL catalogue by setting a lower limit of 3 × 10-14 erg s-1 cm-2 on the source flux within a 1' aperture. Methods: The selection function was estimated using a mixture of Monte Carlo simulations and analytical recipes that closely reproduce the source selection process. An extensive spectroscopic follow-up provided redshifts for 97 of the 100 clusters. We derived accurate X-ray parameters for all the sources. Scaling relations were self-consistently derived from the same sample in other publications of the series. On this basis, we study the number density, luminosity function, and spatial distribution of the sample. Results: The bright cluster sample consists of systems with masses between M500 = 7 × 1013 and 3 × 1014 M⊙, mostly located between z = 0.1 and 0.5. The observed sky density of clusters is slightly below the predictions from the WMAP9 model, and significantly below the prediction from the Planck 2015 cosmology. In general, within the current uncertainties of the cluster mass calibration, models with higher values of σ8 and/or ΩM appear more difficult to accommodate. We provide tight constraints on the cluster differential luminosity function and find no hint of evolution out to z ~ 1. We also find strong evidence for the presence of large-scale structures in the XXL bright cluster sample and identify five new superclusters. Based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA. Based on observations made with ESO Telescopes at the La Silla and Paranal Observatories under programme ID 089.A-0666 and LP191.A-0268.The Master Catalogue is available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/592/A2

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.

Topology in two dimensions. II - The Abell and ACO cluster catalogues

NASA Astrophysics Data System (ADS)

Plionis, Manolis; Valdarnini, Riccardo; Coles, Peter

1992-09-01

We apply a method for quantifying the topology of projected galaxy clustering to the Abell and ACO catalogues of rich clusters. We use numerical simulations to quantify the statistical bias involved in using high peaks to define the large-scale structure, and we use the results obtained to correct our observational determinations for this known selection effect and also for possible errors introduced by boundary effects. We find that the Abell cluster sample is consistent with clusters being identified with high peaks of a Gaussian random field, but that the ACO shows a slight meatball shift away from the Gaussian behavior over and above that expected purely from the high-peak selection. The most conservative explanation of this effect is that it is caused by some artefact of the procedure used to select the clusters in the two samples.

Electronic and molecular structure of carbon grains

NASA Technical Reports Server (NTRS)

Almloef, Jan; Luethi, Hans-Peter

1990-01-01

Clusters of carbon atoms have been studied with large-scale ab initio calculations. Planar, single-sheet graphite fragments with 6 to 54 atoms were investigated, as well as the spherical C(sub 60) Buckminsterfullerene molecule. Polycyclic aromatic hydrocarbons (PAHs) have also been considered. Thermodynamic differences between diamond- and graphite-like grains have been studied in particular. Saturation of the peripheral bonds with hydrogen is found to provide a smooth and uniform convergence of the properties with increasing cluster size. For the graphite-like clusters the convergence to bulk values is much slower than for the three-dimensional complexes.

Characterizing Temperature Variability and Associated Large Scale Meteorological Patterns Across South America

NASA Astrophysics Data System (ADS)

Detzer, J.; Loikith, P. C.; Mechoso, C. R.; Barkhordarian, A.; Lee, H.

2017-12-01

South America's climate varies considerably owing to its large geographic range and diverse topographical features. Spanning the tropics to the mid-latitudes and from high peaks to tropical rainforest, the continent experiences an array of climate and weather patterns. Due to this considerable spatial extent, assessing temperature variability at the continent scale is particularly challenging. It is well documented in the literature that temperatures have been increasing across portions of South America in recent decades, and while there have been many studies that have focused on precipitation variability and change, temperature has received less scientific attention. Therefore, a more thorough understanding of the drivers of temperature variability is critical for interpreting future change. First, k-means cluster analysis is used to identify four primary modes of temperature variability across the continent, stratified by season. Next, composites of large scale meteorological patterns (LSMPs) are calculated for months assigned to each cluster. Initial results suggest that LSMPs, defined using meteorological variables such as sea level pressure (SLP), geopotential height, and wind, are able to identify synoptic scale mechanisms important for driving temperature variability at the monthly scale. Some LSMPs indicate a relationship with known recurrent modes of climate variability. For example, composites of geopotential height suggest that the Southern Annular Mode is an important, but not necessarily dominant, component of temperature variability over southern South America. This work will be extended to assess the drivers of temperature extremes across South America.

Strong orientation dependence of surface mass density profiles of dark haloes at large scales

NASA Astrophysics Data System (ADS)

Osato, Ken; Nishimichi, Takahiro; Oguri, Masamune; Takada, Masahiro; Okumura, Teppei

2018-06-01

We study the dependence of surface mass density profiles, which can be directly measured by weak gravitational lensing, on the orientation of haloes with respect to the line-of-sight direction, using a suite of N-body simulations. We find that, when major axes of haloes are aligned with the line-of-sight direction, surface mass density profiles have higher amplitudes than those averaged over all halo orientations, over all scales from 0.1 to 100 Mpc h-1 we studied. While the orientation dependence at small scales is ascribed to the halo triaxiality, our results indicate even stronger orientation dependence in the so-called two-halo regime, up to 100 Mpc h-1. The orientation dependence for the two-halo term is well approximated by a multiplicative shift of the amplitude and therefore a shift in the halo bias parameter value. The halo bias from the two-halo term can be overestimated or underestimated by up to ˜ 30 per cent depending on the viewing angle, which translates into the bias in estimated halo masses by up to a factor of 2 from halo bias measurements. The orientation dependence at large scales originates from the anisotropic halo-matter correlation function, which has an elliptical shape with the axis ratio of ˜0.55 up to 100 Mpc h-1. We discuss potential impacts of halo orientation bias on other observables such as optically selected cluster samples and a clustering analysis of large-scale structure tracers such as quasars.

Theoretical and Empirical Comparison of Big Data Image Processing with Apache Hadoop and Sun Grid Engine.

PubMed

Bao, Shunxing; Weitendorf, Frederick D; Plassard, Andrew J; Huo, Yuankai; Gokhale, Aniruddha; Landman, Bennett A

2017-02-11

The field of big data is generally concerned with the scale of processing at which traditional computational paradigms break down. In medical imaging, traditional large scale processing uses a cluster computer that combines a group of workstation nodes into a functional unit that is controlled by a job scheduler. Typically, a shared-storage network file system (NFS) is used to host imaging data. However, data transfer from storage to processing nodes can saturate network bandwidth when data is frequently uploaded/retrieved from the NFS, e.g., "short" processing times and/or "large" datasets. Recently, an alternative approach using Hadoop and HBase was presented for medical imaging to enable co-location of data storage and computation while minimizing data transfer. The benefits of using such a framework must be formally evaluated against a traditional approach to characterize the point at which simply "large scale" processing transitions into "big data" and necessitates alternative computational frameworks. The proposed Hadoop system was implemented on a production lab-cluster alongside a standard Sun Grid Engine (SGE). Theoretical models for wall-clock time and resource time for both approaches are introduced and validated. To provide real example data, three T1 image archives were retrieved from a university secure, shared web database and used to empirically assess computational performance under three configurations of cluster hardware (using 72, 109, or 209 CPU cores) with differing job lengths. Empirical results match the theoretical models. Based on these data, a comparative analysis is presented for when the Hadoop framework will be relevant and non-relevant for medical imaging.

Theoretical and empirical comparison of big data image processing with Apache Hadoop and Sun Grid Engine

NASA Astrophysics Data System (ADS)

Bao, Shunxing; Weitendorf, Frederick D.; Plassard, Andrew J.; Huo, Yuankai; Gokhale, Aniruddha; Landman, Bennett A.

2017-03-01

The field of big data is generally concerned with the scale of processing at which traditional computational paradigms break down. In medical imaging, traditional large scale processing uses a cluster computer that combines a group of workstation nodes into a functional unit that is controlled by a job scheduler. Typically, a shared-storage network file system (NFS) is used to host imaging data. However, data transfer from storage to processing nodes can saturate network bandwidth when data is frequently uploaded/retrieved from the NFS, e.g., "short" processing times and/or "large" datasets. Recently, an alternative approach using Hadoop and HBase was presented for medical imaging to enable co-location of data storage and computation while minimizing data transfer. The benefits of using such a framework must be formally evaluated against a traditional approach to characterize the point at which simply "large scale" processing transitions into "big data" and necessitates alternative computational frameworks. The proposed Hadoop system was implemented on a production lab-cluster alongside a standard Sun Grid Engine (SGE). Theoretical models for wall-clock time and resource time for both approaches are introduced and validated. To provide real example data, three T1 image archives were retrieved from a university secure, shared web database and used to empirically assess computational performance under three configurations of cluster hardware (using 72, 109, or 209 CPU cores) with differing job lengths. Empirical results match the theoretical models. Based on these data, a comparative analysis is presented for when the Hadoop framework will be relevant and nonrelevant for medical imaging.

Formation of globular cluster candidates in merging proto-galaxies at high redshift: a view from the FIRE cosmological simulations

DOE PAGES

Kim, Ji-hoon; Ma, Xiangcheng; Grudić, Michael Y.; ...

2017-11-23

Using a state-of-the-art cosmological simulation of merging proto-galaxies at high redshift from the FIRE project, with explicit treatments of star formation and stellar feedback in the interstellar medium, we investigate the formation of star clusters and examine one of the formation hypotheses of present-day metal-poor globular clusters. Here, we find that frequent mergers in high-redshift proto-galaxies could provide a fertile environment to produce long-lasting bound star clusters. The violent merger event disturbs the gravitational potential and pushes a large gas mass of ≳ 10 5–6 M ⊙ collectively to high density, at which point it rapidly turns into stars beforemore » stellar feedback can stop star formation. The high dynamic range of the reported simulation is critical in realizing such dense star-forming clouds with a small dynamical time-scale, tff ≲ 3 Myr, shorter than most stellar feedback time-scales. Our simulation then allows us to trace how clusters could become virialized and tightly bound to survive for up to ~420 Myr till the end of the simulation. Finally, because the cluster's tightly bound core was formed in one short burst, and the nearby older stars originally grouped with the cluster tend to be preferentially removed, at the end of the simulation the cluster has a small age spread.« less

Formation of globular cluster candidates in merging proto-galaxies at high redshift: a view from the FIRE cosmological simulations

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

Kim, Ji-hoon; Ma, Xiangcheng; Grudić, Michael Y.

Using a state-of-the-art cosmological simulation of merging proto-galaxies at high redshift from the FIRE project, with explicit treatments of star formation and stellar feedback in the interstellar medium, we investigate the formation of star clusters and examine one of the formation hypotheses of present-day metal-poor globular clusters. Here, we find that frequent mergers in high-redshift proto-galaxies could provide a fertile environment to produce long-lasting bound star clusters. The violent merger event disturbs the gravitational potential and pushes a large gas mass of ≳ 10 5–6 M ⊙ collectively to high density, at which point it rapidly turns into stars beforemore » stellar feedback can stop star formation. The high dynamic range of the reported simulation is critical in realizing such dense star-forming clouds with a small dynamical time-scale, tff ≲ 3 Myr, shorter than most stellar feedback time-scales. Our simulation then allows us to trace how clusters could become virialized and tightly bound to survive for up to ~420 Myr till the end of the simulation. Finally, because the cluster's tightly bound core was formed in one short burst, and the nearby older stars originally grouped with the cluster tend to be preferentially removed, at the end of the simulation the cluster has a small age spread.« less

Formation of globular cluster candidates in merging proto-galaxies at high redshift: a view from the FIRE cosmological simulations

NASA Astrophysics Data System (ADS)

Kim, Ji-hoon; Ma, Xiangcheng; Grudić, Michael Y.; Hopkins, Philip F.; Hayward, Christopher C.; Wetzel, Andrew; Faucher-Giguère, Claude-André; Kereš, Dušan; Garrison-Kimmel, Shea; Murray, Norman

2018-03-01

Using a state-of-the-art cosmological simulation of merging proto-galaxies at high redshift from the FIRE project, with explicit treatments of star formation and stellar feedback in the interstellar medium, we investigate the formation of star clusters and examine one of the formation hypotheses of present-day metal-poor globular clusters. We find that frequent mergers in high-redshift proto-galaxies could provide a fertile environment to produce long-lasting bound star clusters. The violent merger event disturbs the gravitational potential and pushes a large gas mass of ≳ 105-6 M⊙ collectively to high density, at which point it rapidly turns into stars before stellar feedback can stop star formation. The high dynamic range of the reported simulation is critical in realizing such dense star-forming clouds with a small dynamical time-scale, tff ≲ 3 Myr, shorter than most stellar feedback time-scales. Our simulation then allows us to trace how clusters could become virialized and tightly bound to survive for up to ˜420 Myr till the end of the simulation. Because the cluster's tightly bound core was formed in one short burst, and the nearby older stars originally grouped with the cluster tend to be preferentially removed, at the end of the simulation the cluster has a small age spread.

Large-scale seismic waveform quality metric calculation using Hadoop

NASA Astrophysics Data System (ADS)

Magana-Zook, S.; Gaylord, J. M.; Knapp, D. R.; Dodge, D. A.; Ruppert, S. D.

2016-09-01

In this work we investigated the suitability of Hadoop MapReduce and Apache Spark for large-scale computation of seismic waveform quality metrics by comparing their performance with that of a traditional distributed implementation. The Incorporated Research Institutions for Seismology (IRIS) Data Management Center (DMC) provided 43 terabytes of broadband waveform data of which 5.1 TB of data were processed with the traditional architecture, and the full 43 TB were processed using MapReduce and Spark. Maximum performance of 0.56 terabytes per hour was achieved using all 5 nodes of the traditional implementation. We noted that I/O dominated processing, and that I/O performance was deteriorating with the addition of the 5th node. Data collected from this experiment provided the baseline against which the Hadoop results were compared. Next, we processed the full 43 TB dataset using both MapReduce and Apache Spark on our 18-node Hadoop cluster. These experiments were conducted multiple times with various subsets of the data so that we could build models to predict performance as a function of dataset size. We found that both MapReduce and Spark significantly outperformed the traditional reference implementation. At a dataset size of 5.1 terabytes, both Spark and MapReduce were about 15 times faster than the reference implementation. Furthermore, our performance models predict that for a dataset of 350 terabytes, Spark running on a 100-node cluster would be about 265 times faster than the reference implementation. We do not expect that the reference implementation deployed on a 100-node cluster would perform significantly better than on the 5-node cluster because the I/O performance cannot be made to scale. Finally, we note that although Big Data technologies clearly provide a way to process seismic waveform datasets in a high-performance and scalable manner, the technology is still rapidly changing, requires a high degree of investment in personnel, and will likely require significant changes in other parts of our infrastructure. Nevertheless, we anticipate that as the technology matures and third-party tool vendors make it easier to manage and operate clusters, Hadoop (or a successor) will play a large role in our seismic data processing.

Comparing selected morphological models of hydrated Nafion using large scale molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Knox, Craig K.

Experimental elucidation of the nanoscale structure of hydrated Nafion, the most popular polymer electrolyte or proton exchange membrane (PEM) to date, and its influence on macroscopic proton conductance is particularly challenging. While it is generally agreed that hydrated Nafion is organized into distinct hydrophilic domains or clusters within a hydrophobic matrix, the geometry and length scale of these domains continues to be debated. For example, at least half a dozen different domain shapes, ranging from spheres to cylinders, have been proposed based on experimental SAXS and SANS studies. Since the characteristic length scale of these domains is believed to be ˜2 to 5 nm, very large molecular dynamics (MD) simulations are needed to accurately probe the structure and morphology of these domains, especially their connectivity and percolation phenomena at varying water content. Using classical, all-atom MD with explicit hydronium ions, simulations have been performed to study the first-ever hydrated Nafion systems that are large enough (~2 million atoms in a ˜30 nm cell) to directly observe several hydrophilic domains at the molecular level. These systems consisted of six of the most significant and relevant morphological models of Nafion to-date: (1) the cluster-channel model of Gierke, (2) the parallel cylinder model of Schmidt-Rohr, (3) the local-order model of Dreyfus, (4) the lamellar model of Litt, (5) the rod network model of Kreuer, and (6) a 'random' model, commonly used in previous simulations, that does not directly assume any particular geometry, distribution, or morphology. These simulations revealed fast intercluster bridge formation and network percolation in all of the models. Sulfonates were found inside these bridges and played a significant role in percolation. Sulfonates also strongly aggregated around and inside clusters. Cluster surfaces were analyzed to study the hydrophilic-hydrophobic interface. Interfacial area and cluster volume significantly increased during the simulations, suggesting the need for morphological model refinement and improvement. Radial distribution functions and structure factors were calculated. All nonrandom models exhibited the characteristic experimental scattering peak, underscoring the insensitivity of this measurement to hydrophilic domain structure and highlighting the need for future work to clearly distinguish morphological models of Nafion.

Close packing of rods on spherical surfaces

NASA Astrophysics Data System (ADS)

Smallenburg, Frank; Löwen, Hartmut

2016-04-01

We study the optimal packing of short, hard spherocylinders confined to lie tangential to a spherical surface, using simulated annealing and molecular dynamics simulations. For clusters of up to twelve particles, we map out the changes in the geometry of the closest-packed configuration as a function of the aspect ratio L/D, where L is the cylinder length and D the diameter of the rods. We find a rich variety of cluster structures. For larger clusters, we find that the best-packed configurations up to around 100 particles are highly dependent on the exact number of particles and aspect ratio. For even larger clusters, we find largely disordered clusters for very short rods (L/D = 0.25), while slightly longer rods (L/D = 0.5 or 1) prefer a global baseball-like geometry of smectic-like domains, similar to the behavior of large-scale nematic shells. Intriguingly, we observe that when compared to their optimal flat-plane packing, short rods adapt to the spherical geometry more efficiently than both spheres and longer rods. Our results provide predictions for experimentally realizable systems of colloidal rods trapped at the interface of emulsion droplets.

A Massive Warm Baryonic Halo in the Coma Cluster

NASA Technical Reports Server (NTRS)

Bonamente, Massimiliano; Joy, Marshall K.; Lieu, Richard

2003-01-01

Several deep PSPC observations of the Coma Cluster reveal a very large scale halo of soft X-ray emission, substantially in excess of the well-known radiation from the hot intracluster medium. The excess emission, previously reported in the central region of the cluster using lower sensitivity Extreme Ultraviolet Explorer (EUVE) and ROSAT data, is now evident out to a radius of 2.6 Mpc, demonstrating that the soft excess radiation from clusters is a phenomenon of cosmological significance. The X-ray spectrum at these large radii cannot be modeled nonthermally but is consistent with the original scenario of thermal emission from warm gas at approx. 10(exp 6) K. The mass of the warm gas is on par with that of the hot X-ray-emitting plasma and significantly more massive if the warm gas resides in low-density filamentary structures. Thus, the data lend vital support to current theories of cosmic evolution, which predict that at low redshift approx. 30%-40% of the baryons reside in warm filaments converging at clusters of galaxies.

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.

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.).

Ultraviolet and optical view of galaxies in the Coma Supercluster

NASA Astrophysics Data System (ADS)

Mahajan, Smriti; Singh, Ankit; Shobhana, Devika

2018-05-01

The Coma supercluster (100h-1Mpc) offers an unprecedented contiguous range of environments in the nearby Universe. In this paper we present a catalogue of spectroscopically confirmed galaxies in the Coma supercluster detected in the ultraviolet (UV) wavebands. We use the arsenal of UV and optical data for galaxies in the Coma supercluster covering ˜500 square degrees on the sky to study their photometric and spectroscopic properties as a function of environment at various scales. We identify the different components of the cosmic-web: large-scale filaments and voids using Discrete Persistent Structures Extractor, and groups and clusters using Hierarchical Density-based spatial clustering of applications with noise, respectively. We find that in the Coma supercluster the median emission in Hα inclines, while the g - r and FUV - NUV colours of galaxies become bluer moving further away from the spine of the filaments out to a radius of ˜1 Mpc. On the other hand, an opposite trend is observed as the distance between the galaxy and centre of the nearest cluster or group decreases. Our analysis supports the hypothesis that properties of galaxies are not just defined by its stellar mass and large-scale density, but also by the environmental processes resulting due to the intrafilament medium whose role in accelerating galaxy transformations needs to be investigated thoroughly using multi-wavelength data.

Scaling Deep Learning on GPU and Knights Landing clusters

DOE PAGES

You, Yang; Buluc, Aydin; Demmel, James

2017-09-26

The speed of deep neural networks training has become a big bottleneck of deep learning research and development. For example, training GoogleNet by ImageNet dataset on one Nvidia K20 GPU needs 21 days. To speed up the training process, the current deep learning systems heavily rely on the hardware accelerators. However, these accelerators have limited on-chip memory compared with CPUs. To handle large datasets, they need to fetch data from either CPU memory or remote processors. We use both self-hosted Intel Knights Landing (KNL) clusters and multi-GPU clusters as our target platforms. From an algorithm aspect, current distributed machine learningmore » systems are mainly designed for cloud systems. These methods are asynchronous because of the slow network and high fault-tolerance requirement on cloud systems. We focus on Elastic Averaging SGD (EASGD) to design algorithms for HPC clusters. Original EASGD used round-robin method for communication and updating. The communication is ordered by the machine rank ID, which is inefficient on HPC clusters. First, we redesign four efficient algorithms for HPC systems to improve EASGD's poor scaling on clusters. Async EASGD, Async MEASGD, and Hogwild EASGD are faster \\textcolor{black}{than} their existing counterparts (Async SGD, Async MSGD, and Hogwild SGD, resp.) in all the comparisons. Finally, we design Sync EASGD, which ties for the best performance among all the methods while being deterministic. In addition to the algorithmic improvements, we use some system-algorithm codesign techniques to scale up the algorithms. By reducing the percentage of communication from 87% to 14%, our Sync EASGD achieves 5.3x speedup over original EASGD on the same platform. We get 91.5% weak scaling efficiency on 4253 KNL cores, which is higher than the state-of-the-art implementation.« less

Scaling Deep Learning on GPU and Knights Landing clusters

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

You, Yang; Buluc, Aydin; Demmel, James

The speed of deep neural networks training has become a big bottleneck of deep learning research and development. For example, training GoogleNet by ImageNet dataset on one Nvidia K20 GPU needs 21 days. To speed up the training process, the current deep learning systems heavily rely on the hardware accelerators. However, these accelerators have limited on-chip memory compared with CPUs. To handle large datasets, they need to fetch data from either CPU memory or remote processors. We use both self-hosted Intel Knights Landing (KNL) clusters and multi-GPU clusters as our target platforms. From an algorithm aspect, current distributed machine learningmore » systems are mainly designed for cloud systems. These methods are asynchronous because of the slow network and high fault-tolerance requirement on cloud systems. We focus on Elastic Averaging SGD (EASGD) to design algorithms for HPC clusters. Original EASGD used round-robin method for communication and updating. The communication is ordered by the machine rank ID, which is inefficient on HPC clusters. First, we redesign four efficient algorithms for HPC systems to improve EASGD's poor scaling on clusters. Async EASGD, Async MEASGD, and Hogwild EASGD are faster \\textcolor{black}{than} their existing counterparts (Async SGD, Async MSGD, and Hogwild SGD, resp.) in all the comparisons. Finally, we design Sync EASGD, which ties for the best performance among all the methods while being deterministic. In addition to the algorithmic improvements, we use some system-algorithm codesign techniques to scale up the algorithms. By reducing the percentage of communication from 87% to 14%, our Sync EASGD achieves 5.3x speedup over original EASGD on the same platform. We get 91.5% weak scaling efficiency on 4253 KNL cores, which is higher than the state-of-the-art implementation.« less

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.

Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale

PubMed Central

Kobourov, Stephen; Gallant, Mike; Börner, Katy

2016-01-01

Overview Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms—Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. Cluster Quality Metrics We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Network Clustering Algorithms Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters. PMID:27391786

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.

THE RELATION BETWEEN GAS DENSITY AND VELOCITY POWER SPECTRA IN GALAXY CLUSTERS: QUALITATIVE TREATMENT AND COSMOLOGICAL SIMULATIONS

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

Zhuravleva, I.; Allen, S. W.; Churazov, E. M.

2014-06-10

We address the problem of evaluating the power spectrum of the velocity field of the intracluster medium using only information on the plasma density fluctuations, which can be measured today by Chandra and XMM-Newton observatories. We argue that for relaxed clusters there is a linear relation between the rms density and velocity fluctuations across a range of scales, from the largest ones, where motions are dominated by buoyancy, down to small, turbulent scales: (δρ{sub k}/ρ){sup 2}=η{sub 1}{sup 2}(V{sub 1,k}/c{sub s}){sup 2}, where δρ {sub k}/ρ is the spectral amplitude of the density perturbations at wavenumber k, V{sub 1,k}{sup 2}=V{sub k}{supmore » 2}/3 is the mean square component of the velocity field, c{sub s} is the sound speed, and η{sub 1} is a dimensionless constant of the order of unity. Using cosmological simulations of relaxed galaxy clusters, we calibrate this relation and find η{sub 1} ≈ 1 ± 0.3. We argue that this value is set at large scales by buoyancy physics, while at small scales the density and velocity power spectra are proportional because the former are a passive scalar advected by the latter. This opens an interesting possibility to use gas density power spectra as a proxy for the velocity power spectra in relaxed clusters across a wide range of scales.« less

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

Systematic detection and classification of earthquake clusters in Italy

NASA Astrophysics Data System (ADS)

Poli, P.; Ben-Zion, Y.; Zaliapin, I. V.

2017-12-01

We perform a systematic analysis of spatio-temporal clustering of 2007-2017 earthquakes in Italy with magnitudes m>3. The study employs the nearest-neighbor approach of Zaliapin and Ben-Zion [2013a, 2013b] with basic data-driven parameters. The results indicate that seismicity in Italy (an extensional tectonic regime) is dominated by clustered events, with smaller proportion of background events than in California. Evaluation of internal cluster properties allows separation of swarm-like from burst-like seismicity. This classification highlights a strong geographical coherence of cluster properties. Swarm-like seismicity are dominant in regions characterized by relatively slow deformation with possible elevated temperature and/or fluids (e.g. Alto Tiberina, Pollino), while burst-like seismicity are observed in crystalline tectonic regions (Alps and Calabrian Arc) and in Central Italy where moderate to large earthquakes are frequent (e.g. L'Aquila, Amatrice). To better assess the variation of seismicity style across Italy, we also perform a clustering analysis with region-specific parameters. This analysis highlights clear spatial changes of the threshold separating background and clustered seismicity, and permits better resolution of different clusters in specific geological regions. For example, a large proportion of repeaters is found in the Etna region as expected for volcanic-induced seismicity. A similar behavior is observed in the northern Apennines with high pore pressure associated with mantle degassing. The observed variations of earthquakes properties highlight shortcomings of practices using large-scale average seismic properties, and points to connections between seismicity and local properties of the lithosphere. The observations help to improve the understanding of the physics governing the occurrence of earthquakes in different regions.

Axions, neutrinos and strings: The formation of structure in an SO(10) universe

NASA Technical Reports Server (NTRS)

Stecker, F. W.

1984-01-01

In a class of grand unified theories containing SO(10), cosmologically significant axion and neutrino energy densities are obtainable naturally. To obtain large scale structure, both components of dark matter are considered to exist with comparable energy densities. To obtain large scale structure, inflationary and non-inflationary scenarios are considered, as well as scenarios with and without vacuum strings. It is shown that inflation may be compatible with recent observations of the mass density within galaxy clusters and superclusters, especially if strings are present.

Axions, neutrinos and strings - The formation of structure in an SO(10) universe

NASA Technical Reports Server (NTRS)

Stecker, F. W.

1986-01-01

In a class of grand unified theories containing SO(10), cosmologically significant axion and neutrino energy densities are obtainable naturally. To obtain large scale structure, both components of dark matter are considered to exist with comparable energy densities. To obtain large scale structure, inflationary and non-inflationary scenarios are considered, as well as scenarios with and without vacuum strings. It is shown that inflation may be compatible with recent observations of the mass density within galaxy clusters and superclusters, especially if strings are present.

Cosmic Infrared Background Sources Clustered Around Quasars

NASA Astrophysics Data System (ADS)

Hall, Kirsten R.; Zakamska, Nadia; Marriage, Tobias; Crichton, Devin; Gralla, Megan

2017-06-01

Powerful quasars can be seen out to large distances. As they reside in massive dark matter halos, they provide a useful tracer of large scale structure. We stack Herschel-SPIRE images at 250, 350, and 500 microns at the locations of 13,000 quasars in redshift bins spanning 0.5 < z < 3.5. While the detected signal is dominated on instrumental beam scales by the unresolved dust emission of the quasar and its host galaxy, at z 2 the extended emission is clearly spatially resolved on Mpc scales. This emission is due to star-forming galaxies clustered around the dark matter halos hosting quasars. We measure radial surface brightness profiles of the stacked images to compute the angular correlation function of dusty star-forming galaxies correlated with quasars. We generate a halo occupation distribution model in order to determine the masses of the dark matter halos in which dusty star forming galaxies reside. We are probing potential changes in the halo mass most efficient at hosting star forming galaxies, and assessing any evidence that this halo mass evolved with redshift in the context of "cosmic downsizing".

Measurements of the pairwise kinematic Sunyaev-Zel'dovich effect with the Atacama Cosmology Telescope and future surveys

NASA Astrophysics Data System (ADS)

Vavagiakis, Eve Marie; De Bernardis, Francesco; Aiola, Simone; Battaglia, Nicholas; Niemack, Michael D.; ACTPol Collaboration

2017-06-01

We have made improved measurements of the kinematic Sunyaev-Zel’dovich (kSZ) effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). We used a map of the Cosmic Microwave Background (CMB) from two seasons of observations each by ACT and the Atacama Cosmology Telescope Polarimeter (ACTPol) receiver. We evaluated the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog via 600 square degrees of overlapping sky area. The measurement of the kSZ signal arising from the large-scale motions of clusters was made by fitting data to an analytical model. The free parameter of the fit determined the optical depth to microwave photon scattering for the cluster sample. We estimated the covariance matrix of the mean pairwise momentum as a function of galaxy separation using CMB simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based uncertainties gave signal-to-noise estimates between 3.6 and 4.1 for various luminosity cuts. Additionally, we explored a novel approach to estimating cluster optical depths from the average thermal Sunyaev-Zel’dovich (tSZ) signal at the BOSS DR11 catalog positions. Our results were broadly consistent with those obtained from the kSZ signal. In the future, the tSZ signal may provide a valuable probe of cluster optical depths, enabling the extraction of velocities from the kSZ sourced mean pairwise momenta. New CMB maps from three seasons of ACTPol observations with multi-frequency coverage overlap with nearly four times as many DR11 sources and promise to improve statistics and systematics for SZ measurements. With these and other upcoming data, the pairwise kSZ signal is poised to become a powerful new cosmological tool, able to probe large physical scales to inform neutrino physics and test models of modified gravity and dark energy.

Filtering large-scale event collections using a combination of supervised and unsupervised learning for event trigger classification.

PubMed

Mehryary, Farrokh; Kaewphan, Suwisa; Hakala, Kai; Ginter, Filip

2016-01-01

Biomedical event extraction is one of the key tasks in biomedical text mining, supporting various applications such as database curation and hypothesis generation. Several systems, some of which have been applied at a large scale, have been introduced to solve this task. Past studies have shown that the identification of the phrases describing biological processes, also known as trigger detection, is a crucial part of event extraction, and notable overall performance gains can be obtained by solely focusing on this sub-task. In this paper we propose a novel approach for filtering falsely identified triggers from large-scale event databases, thus improving the quality of knowledge extraction. Our method relies on state-of-the-art word embeddings, event statistics gathered from the whole biomedical literature, and both supervised and unsupervised machine learning techniques. We focus on EVEX, an event database covering the whole PubMed and PubMed Central Open Access literature containing more than 40 million extracted events. The top most frequent EVEX trigger words are hierarchically clustered, and the resulting cluster tree is pruned to identify words that can never act as triggers regardless of their context. For rarely occurring trigger words we introduce a supervised approach trained on the combination of trigger word classification produced by the unsupervised clustering method and manual annotation. The method is evaluated on the official test set of BioNLP Shared Task on Event Extraction. The evaluation shows that the method can be used to improve the performance of the state-of-the-art event extraction systems. This successful effort also translates into removing 1,338,075 of potentially incorrect events from EVEX, thus greatly improving the quality of the data. The method is not solely bound to the EVEX resource and can be thus used to improve the quality of any event extraction system or database. The data and source code for this work are available at: http://bionlp-www.utu.fi/trigger-clustering/.

Solutions of Smoluchowski's coagulation equation at large cluster sizes

NASA Astrophysics Data System (ADS)

Van Dongen, P. G. J.

1987-09-01

In this paper we determine the behavior of solutions ck( t) of Smoluchowski's coagulation equation for cluster sizes much larger than the mean cluster size s( t). We consider in general the homogeneous rate constants K( i, j), behaving as K( i, j) ∼ iμjv as j → ∞, where special attention is paid to models with an exponent v = 1. The behavior of ck( t) is studied in three different limits: (i) the short-time limit ( t ↓ 0), with k ≫ 1, (ii) the limit k → ∞, with t > 0 fixed, and (iii) the scaling limit, with k ≫ s( t). The two most important conclusions of this paper are, first, that the detailed behavior of ck( t) at large cluster sizes ( k ≫ s( t)) may be drastically different for different rate constants K( i, j) and, secondly, that the results for ck( t), obtained in the limits (i), (ii) and (iii), are closely related.

Revealing the cluster of slow transients behind a large slow slip event.

PubMed

Frank, William B; Rousset, Baptiste; Lasserre, Cécile; Campillo, Michel

2018-05-01

Capable of reaching similar magnitudes to large megathrust earthquakes [ M w (moment magnitude) > 7], slow slip events play a major role in accommodating tectonic motion on plate boundaries through predominantly aseismic rupture. We demonstrate here that large slow slip events are a cluster of short-duration slow transients. Using a dense catalog of low-frequency earthquakes as a guide, we investigate the M w 7.5 slow slip event that occurred in 2006 along the subduction interface 40 km beneath Guerrero, Mexico. We show that while the long-period surface displacement, as recorded by Global Positioning System, suggests a 6-month duration, the motion in the direction of tectonic release only sporadically occurs over 55 days, and its surface signature is attenuated by rapid relocking of the plate interface. Our proposed description of slow slip as a cluster of slow transients forces us to re-evaluate our understanding of the physics and scaling of slow earthquakes.

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality

PubMed Central

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; MacEachren, Alan M

2008-01-01

Background Kulldorff's spatial scan statistic and its software implementation – SaTScan – are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. Results We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. Conclusion The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. Method We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit. PMID:18992163

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality.

PubMed

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; Maceachren, Alan M

2008-11-07

Kulldorff's spatial scan statistic and its software implementation - SaTScan - are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit.

Cosmology from large-scale galaxy clustering and galaxy–galaxy lensing with Dark Energy Survey Science Verification data

DOE PAGES

Kwan, J.; Sánchez, C.; Clampitt, J.; ...

2016-10-05

We present cosmological constraints from the Dark Energy Survey (DES) using a combined analysis of angular clustering of red galaxies and their cross-correlation with weak gravitational lensing of background galaxies. We use a 139 square degree contiguous patch of DES data from the Science Verification (SV) period of observations. Using large scale measurements, we constrain the matter density of the Universe asmore » $$\\Omega_m = 0.31 \\pm 0.09$$ and the clustering amplitude of the matter power spectrum as $$\\sigma_8 = 0.74 +\\pm 0.13$$ after marginalizing over seven nuisance parameters and three additional cosmological parameters. This translates into $$S_8$$ = $$\\sigma_8(\\Omega_m/0.3)^{0.16} = 0.74 \\pm 0.12$$ for our fiducial lens redshift bin at 0.35 < z < 0.5, while $$S_8 = 0.78 \\pm 0.09$$ using two bins over the range 0.2 < z < 0.5. We study the robustness of the results under changes in the data vectors, modelling and systematics treatment, including photometric redshift and shear calibration uncertainties, and find consistency in the derived cosmological parameters. We show that our results are consistent with previous cosmological analyses from DES and other data sets and conclude with a joint analysis of DES angular clustering and galaxy-galaxy lensing with Planck CMB data, Baryon Accoustic Oscillations and Supernova type Ia measurements.« less

Ensemble averaged structure–function relationship for nanocrystals: effective superparamagnetic Fe clusters with catalytically active Pt skin [Ensemble averaged structure-function relationship for composite nanocrystals: magnetic bcc Fe clusters with catalytically active fcc Pt skin

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

Petkov, Valeri; Prasai, Binay; Shastri, Sarvjit

Practical applications require the production and usage of metallic nanocrystals (NCs) in large ensembles. Besides, due to their cluster-bulk solid duality, metallic NCs exhibit a large degree of structural diversity. This poses the question as to what atomic-scale basis is to be used when the structure–function relationship for metallic NCs is to be quantified precisely. In this paper, we address the question by studying bi-functional Fe core-Pt skin type NCs optimized for practical applications. In particular, the cluster-like Fe core and skin-like Pt surface of the NCs exhibit superparamagnetic properties and a superb catalytic activity for the oxygen reduction reaction,more » respectively. We determine the atomic-scale structure of the NCs by non-traditional resonant high-energy X-ray diffraction coupled to atomic pair distribution function analysis. Using the experimental structure data we explain the observed magnetic and catalytic behavior of the NCs in a quantitative manner. Lastly, we demonstrate that NC ensemble-averaged 3D positions of atoms obtained by advanced X-ray scattering techniques are a very proper basis for not only establishing but also quantifying the structure–function relationship for the increasingly complex metallic NCs explored for practical applications.« less

Cosmology from large-scale galaxy clustering and galaxy–galaxy lensing with Dark Energy Survey Science Verification data

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

Kwan, J.; Sánchez, C.; Clampitt, J.

We present cosmological constraints from the Dark Energy Survey (DES) using a combined analysis of angular clustering of red galaxies and their cross-correlation with weak gravitational lensing of background galaxies. We use a 139 square degree contiguous patch of DES data from the Science Verification (SV) period of observations. Using large scale measurements, we constrain the matter density of the Universe asmore » $$\\Omega_m = 0.31 \\pm 0.09$$ and the clustering amplitude of the matter power spectrum as $$\\sigma_8 = 0.74 +\\pm 0.13$$ after marginalizing over seven nuisance parameters and three additional cosmological parameters. This translates into $$S_8$$ = $$\\sigma_8(\\Omega_m/0.3)^{0.16} = 0.74 \\pm 0.12$$ for our fiducial lens redshift bin at 0.35 < z < 0.5, while $$S_8 = 0.78 \\pm 0.09$$ using two bins over the range 0.2 < z < 0.5. We study the robustness of the results under changes in the data vectors, modelling and systematics treatment, including photometric redshift and shear calibration uncertainties, and find consistency in the derived cosmological parameters. We show that our results are consistent with previous cosmological analyses from DES and other data sets and conclude with a joint analysis of DES angular clustering and galaxy-galaxy lensing with Planck CMB data, Baryon Accoustic Oscillations and Supernova type Ia measurements.« less

Calibrating First-Order Strong Lensing Mass Estimates in Clusters of Galaxies

NASA Astrophysics Data System (ADS)

Reed, Brendan; Remolian, Juan; Sharon, Keren; Li, Nan; SPT Clusters Cooperation

2018-01-01

We investigate methods to reduce the statistical and systematic errors inherent to using the Einstein Radius as a first-order mass estimate in strong lensing galaxy clusters. By finding an empirical universal calibration function, we aim to enable a first-order mass estimate of large cluster data sets in a fraction of the time and effort of full-scale strong lensing mass modeling. We use 74 simulated cluster data from the Argonne National Laboratory in a lens redshift slice of [0.159, 0.667] with various source redshifts in the range of [1.23, 2.69]. From the simulated density maps, we calculate the exact mass enclosed within the Einstein Radius. We find that the mass inferred from the Einstein Radius alone produces an error width of ~39% with respect to the true mass. We explore an array of polynomial and exponential correction functions with dependence on cluster redshift and projected radii of the lensed images, aiming to reduce the statistical and systematic uncertainty. We find that the error on the the mass inferred from the Einstein Radius can be reduced significantly by using a universal correction function. Our study has implications for current and future large galaxy cluster surveys aiming to measure cluster mass, and the mass-concentration relation.

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.

RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections.

PubMed

Castro-Mondragon, Jaime Abraham; Jaeger, Sébastien; Thieffry, Denis; Thomas-Chollier, Morgane; van Helden, Jacques

2017-07-27

Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Exploring the Web : The Active Galaxy Population in the ORELSE Survey

NASA Astrophysics Data System (ADS)

Lubin, Lori

What are the physical processes that trigger starburst and nuclear activity in galaxies and drive galaxy evolution? Studies aimed at understanding this complex issue have largely focused on the cores of galaxy clusters or on field surveys, leaving underexplored intermediate-density regimes where rapid evolution occurs. As a result, we are conducting the ORELSE survey, a search for structure on scales > 10 Mpc around 18 clusters at 0.6 < z < 1.3. The survey covers 5 sq. deg., all targeted at high-density regions, making it comparable to field surveys such as DEEP2 and COSMOS. ORELSE is unmatched, with no other cluster survey having comparable breadth, depth, precision, and multi-band coverage. As such, ORELSE overcomes critical problems with previous high-redshift studies, including cosmic variance, restricted environmental ranges, sparse cluster samples, inconsistent star formation rate measures, and limited spectroscopy. From its initial spectral and photometric components, ORELSE already contains wellmeasured properties such as redshift, color, stellar mass, and star formation rate for a statistical sample of 7000 field+cluster galaxies. Because X-ray and mid-IR observations are crucial for a complete census of the active galaxy population, we propose to use the wealth of archival Chandra, Spitzer, and Herschel data in the ORELSE fields to map AGN and starburst galaxies over large scales. When complete, our sample will exceed by more than an order of magnitude the current samples of spectroscopically-confirmed active galaxies in high-redshift clusters and their environs. Combined with our numerical simulations plus galaxy formation models, we will provide a robust census of the active galaxy population in intermediate and high-density environments at z = 1, constrain the physical processes (e.g., merging, intracluster gas interactions, AGN feedback) responsible for triggering/quenching starburst and nuclear activity, and estimate their associated timescales.

Large-Scale Coronal Heating, Clustering of Coronal Bright Points, and Concentration of Magnetic Flux

NASA Technical Reports Server (NTRS)

Falconer, D. A.; Moore, R. L.; Porter, J. G.; Hathaway, D. H.

1998-01-01

By combining quiet-region Fe XII coronal images from SOHO/EIT with magnetograms from NSO/Kitt Peak and from SOHO/MDI, we show that on scales larger than a supergranule the population of network coronal bright points and the magnetic flux content of the network are both markedly greater under the bright half of the quiet corona than under the dim half. These results (1) support the view that the heating of the entire corona in quiet regions and coronal holes is driven by fine-scale magnetic activity (microflares, explosive events, spicules) seated low in the magnetic network, and (2) suggest that this large-scale modulation of the magnetic flux and coronal heating is a signature of giant convection cells.

Searching for Primordial Antimatter

NASA Astrophysics Data System (ADS)

2008-10-01

Scientists are on the hunt for evidence of antimatter - matter's arch nemesis - leftover from the very early Universe. New results using data from NASA's Chandra X-ray Observatory and Compton Gamma Ray Observatory suggest the search may have just become even more difficult. Antimatter is made up of elementary particles, each of which has the same mass as their corresponding matter counterparts --protons, neutrons and electrons -- but the opposite charges and magnetic properties. When matter and antimatter particles collide, they annihilate each other and produce energy according to Einstein's famous equation, E=mc2. According to the Big Bang model, the Universe was awash in particles of both matter and antimatter shortly after the Big Bang. Most of this material annihilated, but because there was slightly more matter than antimatter - less than one part per billion - only matter was left behind, at least in the local Universe. Trace amounts of antimatter are believed to be produced by powerful phenomena such as relativistic jets powered by black holes and pulsars, but no evidence has yet been found for antimatter remaining from the infant Universe. How could any primordial antimatter have survived? Just after the Big Bang there was believed to be an extraordinary period, called inflation, when the Universe expanded exponentially in just a fraction of a second. "If clumps of matter and antimatter existed next to each other before inflation, they may now be separated by more than the scale of the observable Universe, so we would never see them meet," said Gary Steigman of The Ohio State University, who conducted the study. "But, they might be separated on smaller scales, such as those of superclusters or clusters, which is a much more interesting possibility." X-rayChandra X-ray Image In that case, collisions between two galaxy clusters, the largest gravitationally-bound structures in the Universe, might show evidence for antimatter. X-ray emission shows how much hot gas is involved in such a collision. If some of the gas from either cluster has particles of antimatter, then there will be annihilation and the X-rays will be accompanied by gamma rays. Steigman used data obtained by Chandra and Compton to study the so-called Bullet Cluster, where two large clusters of galaxies have crashed into one another at extremely high velocities. At a relatively close distance and with a favorable side-on orientation as viewed from Earth, the Bullet Cluster provides an excellent test site to search for the signal for antimatter. People Who Read This Also Read... Jet Power and Black Hole Assortment Revealed in New Chandra Image Chandra Data Reveal Rapidly Whirling Black Holes Black Holes Have Simple Feeding Habits Galaxies Coming of Age in Cosmic Blobs "This is the largest scale over which this test for antimatter has ever been done," said Steigman, whose paper was published in the Journal of Cosmology and Astroparticle Physics. "I'm looking to see if there could be any clusters of galaxies which are made of large amounts of antimatter." The observed amount of X-rays from Chandra and the non-detection of gamma rays from the Compton data show that the antimatter fraction in the Bullet Cluster is less than three parts per million. Moreover, simulations of the Bullet Cluster merger show that these results rule out any significant amounts of antimatter over scales of about 65 million light years, an estimate of the original separation of the two colliding clusters. "The collision of matter and antimatter is the most efficient process for generating energy in the Universe, but it just may not happen on very large scales," said Steigman. "But, I'm not giving up yet as I'm planning to look at other colliding galaxy clusters that have recently been discovered." Finding antimatter in the Universe might tell scientists about how long the period of inflation lasted. "Success in this experiment, although a long shot, would teach us a lot about the earliest stages of the Universe," said Steigman. Tighter constraints have been placed by Steigman on the presence of antimatter on smaller scales by looking at single galaxy clusters that do not involve such large, recent collisions. The Compton Gamma Ray Observatory was in orbit from 1991 until 2000 when it was safely de-orbited. The data used in this result came from Compton's Energetic Gamma Ray Telescope, or EGRET, instrument. NASA's Marshall Space Flight Center in Huntsville, Ala., manages the Chandra program for NASA's Science Mission Directorate in Washington. The Smithsonian Astrophysical Observatory controls Chandra's science and flight operations from Cambridge, Mass.

Galaxy clusters in the context of superfluid dark matter

NASA Astrophysics Data System (ADS)

Hodson, Alistair O.; Zhao, Hongsheng; Khoury, Justin; Famaey, Benoit

2017-11-01

Context. The mass discrepancy in the Universe has not been solved by the cold dark matter (CDM) or the modified Newtonian dynamics (MOND) paradigms so far. The problems and solutions of either scenario are mutually exclusive on large and small scales. It has recently been proposed, by assuming that dark matter is a superfluid, that MOND-like effects can be achieved on small scales whilst preserving the success of ΛCDM on large scales. Detailed models within this "superfluid dark matter" (SfDM) paradigm are yet to be constructed. Aims: Here, we aim to provide the first set of spherical models of galaxy clusters in the context of SfDM. We aim to determine whether the superfluid formulation is indeed sufficient to explain the mass discrepancy in galaxy clusters. Methods: The SfDM model is defined by two parameters. Λ can be thought of as a mass scale in the Lagrangian of the scalar field that effectively describes the phonons, and it acts as a coupling constant between the phonons and baryons. m is the mass of the DM particles. Based on these parameters, we outline the theoretical structure of the superfluid core and the surrounding "normal-phase" dark halo of quasi-particles. The latter are thought to encompass the largest part of galaxy clusters. Here, we set the SfDM transition at the radius where the density and pressure of the superfluid and normal phase coincide, neglecting the effect of phonons in the superfluid core. We then apply the formalism to a sample of galaxy clusters, and directly compare the SfDM predicted mass profiles to data. Results: We find that the superfluid formulation can reproduce the X-ray dynamical mass profile of clusters reasonably well, but with a slight under-prediction of the gravity in the central regions. This might be partly related to our neglecting of the effect of phonons in these regions. Two normal-phase halo profiles are tested, and it is found that clusters are better defined by a normal-phase halo resembling an Navarro-Frenk-White-like structure than an isothermal profile. Conclusions: In this first exploratory work on the topic, we conclude that depending on the amount of baryons present in the central galaxy and on the actual effect of phonons in the inner regions, this superfluid formulation could be successful in describing galaxy clusters. In the future, our model could be made more realistic by exploring non-sphericity and a more realistic SfDM to normal phase transition. The main result of this study is an estimate of the order of magnitude of the theory parameters for the superfluid formalism to be reasonably consistent with clusters. These values will have to be compared to the true values needed in galaxies.

Discovery of megaparsec-scale, low surface brightness nonthermal emission in merging galaxy clusters using the green bank telescope

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

Farnsworth, Damon; Rudnick, Lawrence; Brown, Shea

2013-12-20

We present results from a study of 12 X-ray bright clusters at 1.4 GHz with the 100 m Green Bank Telescope. After subtraction of point sources using existing interferometer data, we reach a median (best) 1σ rms sensitivity level of 0.01 (0.006) μJy arcsec{sup –2}, and find a significant excess of diffuse, low surface brightness emission in 11 of 12 Abell clusters observed. We also present initial results at 1.4 GHz of A2319 from the Very Large Array. In particular, we find: (1) four new detections of diffuse structures tentatively classified as two halos (A2065, A2069) and two relics (A2067,more » A2073); (2) the first detection of the radio halo in A2061 at 1.4 GHz, which qualifies this as a possible ultra-steep spectrum halo source with a synchrotron spectral index of α ∼ 1.8 between 327 MHz and 1.4 GHz; (3) a ∼2 Mpc radio halo in the sloshing, minor-merger cluster A2142; (4) a >2× increase of the giant radio halo extent and luminosity in the merging cluster A2319; (5) a ∼7× increase to the integrated radio flux and >4× increase to the observed extent of the peripheral radio relic in A1367 to ∼600 kpc, which we also observe to be polarized on a similar scale; (6) significant excess emission of ambiguous nature in three clusters with embedded tailed radio galaxies (A119, A400, A3744). Our radio halo detections agree with the well-known X-ray/radio luminosity correlation, but they are larger and fainter than current radio power correlation studies would predict. The corresponding volume-averaged synchrotron emissivities are 1-2 orders of magnitude below the characteristic value found in previous studies. Some of the halo-like detections may be some type of previously unseen, low surface brightness radio halo or blend of unresolved shock structures and sub-Mpc-scale turbulent regions associated with their respective cluster merging activity. Four of the five tentative halos contain one or more X-ray cold fronts, suggesting a possible connection between gas sloshing and particle acceleration on large scales in some of these clusters. Additionally, we see evidence for a possible inter-cluster filament between A2061 and A2067. For our faintest detections, we note the possibility of residual contamination from faint radio galaxies not accounted for in our confusion subtraction procedure. We also quantify the sensitivity of the NVSS to extended emission as a function of size.« less

Rapid Increase in Ownership and Use of Long-Lasting Insecticidal Nets and Decrease in Prevalence of Malaria in Three Regional States of Ethiopia (2006-2007)

PubMed Central

Shargie, Estifanos Biru; Ngondi, Jeremiah; Graves, Patricia M.; Getachew, Asefaw; Hwang, Jimee; Gebre, Teshome; Mosher, Aryc W.; Ceccato, Pietro; Endeshaw, Tekola; Jima, Daddi; Tadesse, Zerihun; Tenaw, Eskindir; Reithinger, Richard; Emerson, Paul M.; Richards, Frank O.; Ghebreyesus, Tedros Adhanom

2010-01-01

Following recent large scale-up of malaria control interventions in Ethiopia, this study aimed to compare ownership and use of long-lasting insecticidal nets (LLIN), and the change in malaria prevalence using two population-based household surveys in three regions of the country. Each survey used multistage cluster random sampling with 25 households per cluster. Household net ownership tripled from 19.6% in 2006 to 68.4% in 2007, with mean LLIN per household increasing from 0.3 to 1.2. Net use overall more than doubled from 15.3% to 34.5%, but in households owning LLIN, use declined from 71.7% to 48.3%. Parasitemia declined from 4.1% to 0.4%. Large scale-up of net ownership over a short period of time was possible. However, a large increase in net ownership was not necessarily mirrored directly by increased net use. Better targeting of nets to malaria-risk areas and sustained behavioural change communication are needed to increase and maintain net use. PMID:20936103

Mid-Holocene cluster of large-scale landslides revealed in the Southwestern Alps by 36Cl dating. Insight on an Alpine-scale landslide activity

NASA Astrophysics Data System (ADS)

Zerathe, Swann; Lebourg, Thomas; Braucher, Régis; Bourlès, Didier

2014-04-01

Although it is generally assumed that the internal structure of a slope (e.g. lithology and rock mass properties, inherited faults and heterogeneities, etc.) is preponderant for the progressive development of large-scale landslides, the ability to identify triggering factors responsible for final slope failures such as glacial debuttressing, seismic activities or climatic changes, especially when considering landslide cluster at an orogen-scale, is still debated. Highlighting in this study the spatial and temporal concordant clustering of deep-seated slope failures in the external Southwestern Alps, we discuss and review the possible causes for such wide-spread slope instabilities at both local and larger (Alpine) scale. High resolution field mapping coupled with electrical resistivity tomography first allows establishing an inventory of large landslides in the Southwestern Alps, determining their structural model, precising their depth limit (100-200 m) as well as the involved rock volumes (>107 m3). We show that they developed in the same geostructural context of thick mudstone layers overlain by faulted limestone and followed a block-spread model of deformation that could evolve in rock-collapse events. Cosmic ray exposure dating (CRE), using both 36Cl and 10Be in coexisting limestone and chert, respectively, has been carried out from the main scarps of six Deep Seated Landslides (DSL) and leads to landslide-failure CRE ages ranging from 3.7 to 4.7 ka. They highlighted: (i) mainly single and fast ruptures and (ii) a possible concomitant initiation with a main peak of activity between 3.3 and 5.1 ka, centered at ca 4.2 ka. Because this region was not affected by historical glaciations events, landslide triggering by glacial unloading can be excluded. The presented data combined with field observations preferentially suggest that these failures were climatically driven and were most likely controlled by high pressure changes in the karstic medium. In effect, the chronicle of failure-ages is concomitant to a well-known climatic pulse, the “4.2 ka” climate event characterized by intense hydrological perturbations associated to the heaviest rainfall period of the entire Holocene. Despite requiring further investigations and discussions, the dating of numerous events across the entire Alps during the middle Holocene period suggests a potential synchronous triggering of several large-scale gravitational-failures induced by the mid-Holocene climatic transition.

Stability and minimum size of colloidal clusters on a liquid-air interface.

PubMed

Pergamenshchik, V M

2012-02-01

A vertical force applied to each of two colloids, trapped at a liquid-air interface, induces their logarithmic pairwise attraction. I recently showed [Phys. Rev. E 79, 011407 (2009)] that in clusters of size R much larger than the capillary length λ, the attraction changes to that of a power law and is much stronger due to a many-body effect, and I derived two equations that describe the equilibrium coarse-grained meniscus profile and colloid density in such clusters. In this paper, this theory is shown also to describe small clusters with R≪ λ provided the number N of colloids therein is sufficiently large. An analytical solution for a small circular cluster with an arbitrary short-range power-law pairwise repulsion is found. The energy of a cluster is obtained as a function of its radius R and colloid number N. As in large clusters, the attraction force and energy universally scale with the distance L between colloids as L(-3) and L(-2), respectively, for any repulsion forces. The states of an equilibrium cluster, predicted by the theory, are shown to be stable with respect to small perturbations of the meniscus profile and colloid density. The minimum number of colloids in a circular cluster, which sustains the thermal motion, is estimated. For standard parameters, it can be very modest, e.g., in the range 20-200, which is in line with experimental findings on reversible clusterization on a liquid-air interface. © 2012 American Physical Society

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.

Performance analysis of clustering techniques over microarray data: A case study

NASA Astrophysics Data System (ADS)

Dash, Rasmita; Misra, Bijan Bihari

2018-03-01

Handling big data is one of the major issues in the field of statistical data analysis. In such investigation cluster analysis plays a vital role to deal with the large scale data. There are many clustering techniques with different cluster analysis approach. But which approach suits a particular dataset is difficult to predict. To deal with this problem a grading approach is introduced over many clustering techniques to identify a stable technique. But the grading approach depends on the characteristic of dataset as well as on the validity indices. So a two stage grading approach is implemented. In this study the grading approach is implemented over five clustering techniques like hybrid swarm based clustering (HSC), k-means, partitioning around medoids (PAM), vector quantization (VQ) and agglomerative nesting (AGNES). The experimentation is conducted over five microarray datasets with seven validity indices. The finding of grading approach that a cluster technique is significant is also established by Nemenyi post-hoc hypothetical test.

CA II TRIPLET SPECTROSCOPY OF SMALL MAGELLANIC CLOUD RED GIANTS. III. ABUNDANCES AND VELOCITIES FOR A SAMPLE OF 14 CLUSTERS

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

Parisi, M. C.; Clariá, J. J.; Marcionni, N.

2015-05-15

We obtained spectra of red giants in 15 Small Magellanic Cloud (SMC) clusters in the region of the Ca ii lines with FORS2 on the Very Large Telescope. We determined the mean metallicity and radial velocity with mean errors of 0.05 dex and 2.6 km s{sup −1}, respectively, from a mean of 6.5 members per cluster. One cluster (B113) was too young for a reliable metallicity determination and was excluded from the sample. We combined the sample studied here with 15 clusters previously studied by us using the same technique, and with 7 clusters whose metallicities determined by other authorsmore » are on a scale similar to ours. This compilation of 36 clusters is the largest SMC cluster sample currently available with accurate and homogeneously determined metallicities. We found a high probability that the metallicity distribution is bimodal, with potential peaks at −1.1 and −0.8 dex. Our data show no strong evidence of a metallicity gradient in the SMC clusters, somewhat at odds with recent evidence from Ca ii triplet spectra of a large sample of field stars. This may be revealing possible differences in the chemical history of clusters and field stars. Our clusters show a significant dispersion of metallicities, whatever age is considered, which could be reflecting the lack of a unique age–metallicity relation in this galaxy. None of the chemical evolution models currently available in the literature satisfactorily represents the global chemical enrichment processes of SMC clusters.« less

Texture descriptions of lunar surface derived from LOLA data: Kilometer-scale roughness and entropy maps

NASA Astrophysics Data System (ADS)

Li, Bo; Ling, Zongcheng; Zhang, Jiang; Chen, Jian; Wu, Zhongchen; Ni, Yuheng; Zhao, Haowei

2015-11-01

The lunar global texture maps of roughness and entropy are derived at kilometer scales from Digital Elevation Models (DEMs) data obtained by Lunar Orbiter Laser Altimeter (LOLA) aboard on Lunar Reconnaissance Orbiter (LRO) spacecraft. We use statistical moments of a gray-level histogram of elevations in a neighborhood to compute the roughness and entropy value. Our texture descriptors measurements are shown in global maps at multi-sized square neighborhoods, whose length of side is 3, 5, 10, 20, 40 and 80 pixels, respectively. We found that large-scale topographical changes can only be displayed in maps with longer side of neighborhood, but the small scale global texture maps are more disorderly and unsystematic because of more complicated textures' details. Then, the frequency curves of texture maps are made out, whose shapes and distributions are changing as the spatial scales increases. Entropy frequency curve with minimum 3-pixel scale has large fluctuations and six peaks. According to this entropy curve we can classify lunar surface into maria, highlands, different parts of craters preliminarily. The most obvious textures in the middle-scale roughness and entropy maps are the two typical morphological units, smooth maria and rough highlands. For the impact crater, its roughness and entropy value are characterized by a multiple-ring structure obviously, and its different parts have different texture results. In the last, we made a 2D scatter plot between the two texture results of typical lunar maria and highlands. There are two clusters with largest dot density which are corresponded to the lunar highlands and maria separately. In the lunar mare regions (cluster A), there is a high correlation between roughness and entropy, but in the highlands (Cluster B), the entropy shows little change. This could be subjected to different geological processes of maria and highlands forming different landforms.

False-Positive Tuberculin Skin Test Results Among Low-Risk Healthcare Workers Following Implementation of Fifty-Dose Vials of Purified Protein Derivative.

PubMed

Collins, Jeffrey M; Hunter, Mary; Gordon, Wanda; Kempker, Russell R; Blumberg, Henry M; Ray, Susan M

2018-06-01

Following large declines in tuberculosis transmission the United States, large-scale screening programs targeting low-risk healthcare workers are increasingly a source of false-positive results. We report a large cluster of presumed false-positive tuberculin skin test results in healthcare workers following a change to 50-dose vials of Tubersol tuberculin.Infect Control Hosp Epidemiol 2018;39:750-752.

Advances in Parallelization for Large Scale Oct-Tree Mesh Generation

NASA Technical Reports Server (NTRS)

O'Connell, Matthew; Karman, Steve L.

2015-01-01

Despite great advancements in the parallelization of numerical simulation codes over the last 20 years, it is still common to perform grid generation in serial. Generating large scale grids in serial often requires using special "grid generation" compute machines that can have more than ten times the memory of average machines. While some parallel mesh generation techniques have been proposed, generating very large meshes for LES or aeroacoustic simulations is still a challenging problem. An automated method for the parallel generation of very large scale off-body hierarchical meshes is presented here. This work enables large scale parallel generation of off-body meshes by using a novel combination of parallel grid generation techniques and a hybrid "top down" and "bottom up" oct-tree method. Meshes are generated using hardware commonly found in parallel compute clusters. The capability to generate very large meshes is demonstrated by the generation of off-body meshes surrounding complex aerospace geometries. Results are shown including a one billion cell mesh generated around a Predator Unmanned Aerial Vehicle geometry, which was generated on 64 processors in under 45 minutes.

Gravitational Lensing and Microlensing in Clusters: Clusters as Dark Matter Telescopes

NASA Astrophysics Data System (ADS)

Safonova, Margarita

2018-04-01

Gravitational lensing is brightening of background objects due to deflection of light by foreground sources. Rich clusters of galaxies are very effective lenses because they are centrally concentrated. Such natural Gravitational Telescopes provide us with strongly magnified galaxies at high redshifts otherwise too faint to be detected or analyzed. With a lensing boost, we can study galaxies shining at the end of the “Dark Ages”. We propose to exploit the opportunity provided by the large field of view and depth, to search for sources magnified by foreground clusters in the vicinity of the cluster critical curves, where enhancements can be of several tens in brightness. Another aspect is microlensing (ML), where we would like to continue our survey of a number of Galactic globular clusters over time-scales of weeks to years to search for ML events from planets to hypothesized central intermediate-mass black holes (IMBH).

Time-resolved x-ray imaging of a laser-induced nanoplasma and its neutral residuals

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

Fluckiger, L.; Rupp, D.; Adolph, M.

The evolution of individual, large gas-phase xenon clusters, turned into a nanoplasma by a high power infrared laser pulse, is tracked from femtoseconds up to nanoseconds after laser excitation via coherent diffractive imaging, using ultra-short soft x-ray free electron laser pulses. A decline of scattering signal at high detection angles with increasing time delay indicates a softening of the cluster surface. Here we demonstrate, for the first time a representative speckle pattern of a new stage of cluster expansion for xenon clusters after a nanosecond irradiation. The analysis of the measured average speckle size and the envelope of the intensitymore » distribution reveals a mean cluster size and length scale of internal density fluctuations. Furthermore, the measured diffraction patterns were reproduced by scattering simulations which assumed that the cluster expands with pronounced internal density fluctuations hundreds of picoseconds after excitation.« less

Studies in the X-Ray Emission of Clusters of Galaxies and Other Topics

NASA Technical Reports Server (NTRS)

Vrtilek, Jan; Thronson, Harley (Technical Monitor)

2001-01-01

The paper discusses the following: (1) X-ray study of groups of galaxies with Chandra and XMM. (2) X-ray properties of point sources in Chandra deep fields. (3) Study of cluster substructure using wavelet techniques. (4) Combined study of galaxy clusters with X-ray and the S-Z effect. Groups of galaxies are the fundamental building blocks of large scale structure in the Universe. X-ray study of the intragroup medium offers a powerful approach to addressing some of the major questions that still remain about almost all aspects of groups: their ages, origins, importance of composition of various galaxy types, relations to clusters, and origin and enrichment of the intragroup gas. Long exposures with Chandra have opened new opportunities for the study of X-ray background. The presence of substructure within clusters of galaxies has substantial implications for our understanding of cluster evolution as well as fundamental questions in cosmology.

Time-resolved x-ray imaging of a laser-induced nanoplasma and its neutral residuals

DOE PAGES

Fluckiger, L.; Rupp, D.; Adolph, M.; ...

2016-04-13

The evolution of individual, large gas-phase xenon clusters, turned into a nanoplasma by a high power infrared laser pulse, is tracked from femtoseconds up to nanoseconds after laser excitation via coherent diffractive imaging, using ultra-short soft x-ray free electron laser pulses. A decline of scattering signal at high detection angles with increasing time delay indicates a softening of the cluster surface. Here we demonstrate, for the first time a representative speckle pattern of a new stage of cluster expansion for xenon clusters after a nanosecond irradiation. The analysis of the measured average speckle size and the envelope of the intensitymore » distribution reveals a mean cluster size and length scale of internal density fluctuations. Furthermore, the measured diffraction patterns were reproduced by scattering simulations which assumed that the cluster expands with pronounced internal density fluctuations hundreds of picoseconds after excitation.« less

The origin of low mass particles within and beyond the dust coma envelopes of Comet Halley

NASA Technical Reports Server (NTRS)

Simpson, J. A.; Rabinowitz, D.; Tuzzolino, A. J.; Ksanfomality, L. V.; Sagdeev, R. Z.

1987-01-01

Measurements from the Dust Counter and Mass Analyzer (DUCMA) instruments on VEGA-1 and -2 revealed unexpected fluxes of low mass (up to 10 to the minus 13th power g) dust particles at very great distances from the nucleus (300,000 to 600,000 km). These particles are detected in clusters (10 sec duration), preceded and followed by relatively long time intervals during which no dust is detected. This cluster phenomenon also occurs inside the envelope boundaries. Clusters of low mass particles are intermixed with the overall dust distribution throughout the coma. The clusters account for many of the short-term small-scale intensity enhancements previously ascribed to microjets in the coma. The origin of these clusters appears to be emission from the nucleus of large conglomerates which disintegrate in the coma to yield clusters of discrete, small particles continuing outward to the distant coma.

Quantifying Biomass from Point Clouds by Connecting Representations of Ecosystem Structure

NASA Astrophysics Data System (ADS)

Hendryx, S. M.; Barron-Gafford, G.

2017-12-01

Quantifying terrestrial ecosystem biomass is an essential part of monitoring carbon stocks and fluxes within the global carbon cycle and optimizing natural resource management. Point cloud data such as from lidar and structure from motion can be effective for quantifying biomass over large areas, but significant challenges remain in developing effective models that allow for such predictions. Inference models that estimate biomass from point clouds are established in many environments, yet, are often scale-dependent, needing to be fitted and applied at the same spatial scale and grid size at which they were developed. Furthermore, training such models typically requires large in situ datasets that are often prohibitively costly or time-consuming to obtain. We present here a scale- and sensor-invariant framework for efficiently estimating biomass from point clouds. Central to this framework, we present a new algorithm, assignPointsToExistingClusters, that has been developed for finding matches between in situ data and clusters in remotely-sensed point clouds. The algorithm can be used for assessing canopy segmentation accuracy and for training and validating machine learning models for predicting biophysical variables. We demonstrate the algorithm's efficacy by using it to train a random forest model of above ground biomass in a shrubland environment in Southern Arizona. We show that by learning a nonlinear function to estimate biomass from segmented canopy features we can reduce error, especially in the presence of inaccurate clusterings, when compared to a traditional, deterministic technique to estimate biomass from remotely measured canopies. Our random forest on cluster features model extends established methods of training random forest regressions to predict biomass of subplots but requires significantly less training data and is scale invariant. The random forest on cluster features model reduced mean absolute error, when evaluated on all test data in leave one out cross validation, by 40.6% from deterministic mesquite allometry and 35.9% from the inferred ecosystem-state allometric function. Our framework should allow for the inference of biomass more efficiently than common subplot methods and more accurately than individual tree segmentation methods in densely vegetated environments.

IRAS galaxies and the large-scale structure in the CfA slice

NASA Technical Reports Server (NTRS)

Babul, Arif; Postman, Marc

1990-01-01

The spatial distributions of the IRAS and the optical galaxies in the first CfA slice are compared. The IRAS galaxies are generally less clustered than optical ones, but their distribution is essentially identical to that of late-type optical galaxies. The discrepancy between the clustering properties of the IRAS and optical samples in the CfA slice region is found to be entirely due to the paucity of IRAS galaxies in the core of the Coma cluster. The spatial distributions of the IRAS and the optical galaxies, both late and early types, outside the dense core of the Coma cluster are entirely consistent with each other. This conflicts with the prediction of the linear biasing scenario.

The coma cluster after lunch: Has a galaxcy group passed through the cluster core?

NASA Technical Reports Server (NTRS)

Burns, Jack O.; Roettiger, Kurt; Ledlow, Michael; Klypin, Anatoly

1994-01-01

We propose that the Coma cluster has recently undergone a collision with the NGC 4839 galaxy group. The ROSAT X-ray morphology, the Coma radio halo, the presence of poststarburst galaxies in the bridge between Coma and NGC 4839, the usually high velocity dispersion for the NGC 4839 group, and the position of a large-scale galaxy filament to the NE of Coma are all used to argue that the NGC 4839 group passed through the core of Coma approximately 2 Gyr ago. We present a new Hydro/N-body simulation of the merger between a galaxy group and a rich cluster that reproduces many of the observed X-ray and optical properties of Coma/NGC 4839.

Baryon acoustic oscillations in 2D. II. Redshift-space halo clustering in N-body simulations

NASA Astrophysics Data System (ADS)

Nishimichi, Takahiro; Taruya, Atsushi

2011-08-01

We measure the halo power spectrum in redshift space from cosmological N-body simulations, and test the analytical models of redshift distortions particularly focusing on the scales of baryon acoustic oscillations. Remarkably, the measured halo power spectrum in redshift space exhibits a large-scale enhancement in amplitude relative to the real-space clustering, and the effect becomes significant for the massive or highly biased halo samples. These findings cannot be simply explained by the so-called streaming model frequently used in the literature. By contrast, a physically motivated perturbation theory model developed in the previous paper reproduces the halo power spectrum very well, and the model combining a simple linear scale-dependent bias can accurately characterize the clustering anisotropies of halos in two dimensions, i.e., line-of-sight and its perpendicular directions. The results highlight the significance of nonlinear coupling between density and velocity fields associated with two competing effects of redshift distortions, i.e., Kaiser and Finger-of-God effects, and a proper account of this effect would be important in accurately characterizing the baryon acoustic oscillations in two dimensions.

Scale-free correlations in the geographical spreading of obesity

NASA Astrophysics Data System (ADS)

Gallos, Lazaros; Barttfeld, Pablo; Havlin, Shlomo; Sigman, Mariano; Makse, Hernan

2012-02-01

Obesity levels have been universally increasing. A crucial problem is to determine the influence of global and local drivers behind the obesity epidemic, to properly guide effective policies. Despite the numerous factors that affect the obesity evolution, we show a remarkable regularity expressed in a predictable pattern of spatial long-range correlations in the geographical spreading of obesity. We study the spatial clustering of obesity and a number of related health and economic indicators, and we use statistical physics methods to characterize the growth of the resulting clusters. The resulting scaling exponents allow us to broadly classify these indicators into two separate universality classes, weakly or strongly correlated. Weak correlations are found in generic human activity such as population distribution and the growth of the whole economy. Strong correlations are recovered, among others, for obesity, diabetes, and the food industry sectors associated with food consumption. Obesity turns out to be a global problem where local details are of little importance. The long-range correlations suggest influence that extends to large scales, hinting that the physical model of obesity clustering can be mapped to a long-range correlated percolation process.

Herschel-ATLAS/GAMA: SDSS cross-correlation induced by weak lensing

NASA Astrophysics Data System (ADS)

González-Nuevo, J.; Lapi, A.; Negrello, M.; Danese, L.; De Zotti, G.; Amber, S.; Baes, M.; Bland-Hawthorn, J.; Bourne, N.; Brough, S.; Bussmann, R. S.; Cai, Z.-Y.; Cooray, A.; Driver, S. P.; Dunne, L.; Dye, S.; Eales, S.; Ibar, E.; Ivison, R.; Liske, J.; Loveday, J.; Maddox, S.; Michałowski, M. J.; Robotham, A. S. G.; Scott, D.; Smith, M. W. L.; Valiante, E.; Xia, J.-Q.

2014-08-01

We report a highly significant (>10σ) spatial correlation between galaxies with S350 μm ≥ 30 mJy detected in the equatorial fields of the Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS) with estimated redshifts ≳ 1.5, and Sloan Digital Sky Survey (SDSS) or Galaxy And Mass Assembly (GAMA) galaxies at 0.2 ≤ z ≤ 0.6. The significance of the cross-correlation is much higher than those reported so far for samples with non-overlapping redshift distributions selected in other wavebands. Extensive, realistic simulations of clustered sub-mm galaxies amplified by foreground structures confirm that the cross-correlation can be explained by weak gravitational lensing (μ < 2). The simulations also show that the measured amplitude and range of angular scales of the signal are larger than can be accounted for by galaxy-galaxy weak lensing. However, for scales ≲ 2 arcmin, the signal can be reproduced if SDSS/GAMA galaxies act as signposts of galaxy groups/clusters with halo masses in the range 1013.2-1014.5 M⊙. The signal detected on larger scales appears to reflect the clustering of such haloes.

Comparisons of fish species traits from small streams to large rivers

USGS Publications Warehouse

Goldstein, R.M.; Meador, M.R.

2004-01-01

To examine the relations between fish community function and stream size, we classified 429 lotic freshwater fish species based on multiple categories within six species traits: (1) substrate preference, (2) geomorphic preference, (3) trophic ecology, (4) locomotion morphology, (5) reproductive strategy, and (6) stream size preference. Stream size categories included small streams, small, medium, and large rivers, and no size preference. The frequencies of each species trait category were determined for each stream size category based on life history information from the literature. Cluster analysis revealed the presence of covarying groups of species trait categories. One cluster (RUN) included the traits of planktivore and herbivore feeding ecology, migratory reproductive behavior and broadcast spawning, preferences for main-channel habitats, and a lack of preferences for substrate type. The frequencies of classifications for the RUN cluster varied significantly across stream size categories (P = 0.009), being greater for large rivers than for small streams and rivers. Another cluster (RIFFLE) included the traits of invertivore feeding ecology, simple nester reproductive behavior, a preference for riffles, and a preference for bedrock, boulder, and cobble-rubble substrate. No significant differences in the frequency of classifications among stream size categories were detected for the RIFFLE cluster (P = 0.328). Our results suggest that fish community function is structured by large-scale differences in habitat and is different for large rivers than for small streams and rivers. Our findings support theoretical predictions of variation in species traits among stream reaches based on ecological frameworks such as landscape filters, habitat templates, and the river continuum concept. We believe that the species trait classifications presented here provide an opportunity for further examination of fish species' relations to physical, chemical, and biological factors in lotic habitats ranging from small streams to large rivers.

Clustering, randomness, and regularity in cloud fields. 4. Stratocumulus cloud fields

NASA Astrophysics Data System (ADS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-07-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (>900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale.

PubMed

Emmons, Scott; Kobourov, Stephen; Gallant, Mike; Börner, Katy

2016-01-01

Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms-Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters.

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

NASA Technical Reports Server (NTRS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-01-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Scaling NASA Applications to 1024 CPUs on Origin 3K

NASA Technical Reports Server (NTRS)

Taft, Jim

2002-01-01

The long and highly successful joint SGI-NASA research effort in ever larger SSI systems was to a large degree the result of the successful development of the MLP scalable parallel programming paradigm developed at ARC: 1) MLP scaling in real production codes justified ever larger systems at NAS; 2) MLP scaling on 256p Origin 2000 gave SGl impetus to productize 256p; 3) MLP scaling on 512 gave SGI courage to build 1024p O3K; and 4) History of MLP success resulted in IBM Star Cluster based MLP effort.

Spatial clustering and halo occupation distribution modelling of local AGN via cross-correlation measurements with 2MASS galaxies

NASA Astrophysics Data System (ADS)

Krumpe, Mirko; Miyaji, Takamitsu; Coil, Alison L.; Aceves, Hector

2018-02-01

We present the clustering properties and halo occupation distribution (HOD) modelling of very low redshift, hard X-ray-detected active galactic nuclei (AGN) using cross-correlation function measurements with Two-Micron All Sky Survey galaxies. Spanning a redshift range of 0.007 < z < 0.037, with a median z = 0.024, we present a precise AGN clustering study of the most local AGN in the Universe. The AGN sample is drawn from the SWIFT/BAT 70-month and INTEGRAL/IBIS eight year all-sky X-ray surveys and contains both type I and type II AGN. We find a large-scale bias for the full AGN sample of b=1.04^{+0.10}_{-0.11}, which corresponds to a typical host dark matter halo mass of M_h^typ=12.84^{+0.22}_{-0.30} h^{-1} M_{⊙}. When split into low and high X-ray luminosity and type I and type II AGN subsamples, we detect no statistically significant differences in the large-scale bias parameters. However, there are differences in the small-scale clustering, which are reflected in the full HOD model results. We find that low and high X-ray luminosity AGN, as well as type I and type II AGN, occupy dark matter haloes differently, with 3.4σ and 4.0σ differences in their mean halo masses, respectively, when split by luminosity and type. The latter finding contradicts a simple orientation-based AGN unification model. As a by-product of our cross-correlation approach, we also present the first HOD model of 2MASS galaxies.

Planet population synthesis driven by pebble accretion in cluster environments

NASA Astrophysics Data System (ADS)

Ndugu, N.; Bitsch, B.; Jurua, E.

2018-02-01

The evolution of protoplanetary discs embedded in stellar clusters depends on the age and the stellar density in which they are embedded. Stellar clusters of young age and high stellar surface density destroy protoplanetary discs by external photoevaporation and stellar encounters. Here, we consider the effect of background heating from newly formed stellar clusters on the structure of protoplanetary discs and how it affects the formation of planets in these discs. Our planet formation model is built on the core accretion scenario, where we take the reduction of the core growth time-scale due to pebble accretion into account. We synthesize planet populations that we compare to observations obtained by radial velocity measurements. The giant planets in our simulations migrate over large distances due to the fast type-II migration regime induced by a high disc viscosity (α = 5.4 × 10-3). Cold Jupiters (rp > 1 au) originate preferably from the outer disc, due to the large-scale planetary migration, while hot Jupiters (rp < 0.1 au) preferably form in the inner disc. We find that the formation of gas giants via pebble accretion is in agreement with the metallicity correlation, meaning that more gas giants are formed at larger metallicity. However, our synthetic population of isolated stars host a significant amount of giant planets even at low metallicity, in contradiction to observations where giant planets are preferably found around high metallicity stars, indicating that pebble accretion is very efficient in the standard pebble accretion framework. On the other hand, discs around stars embedded in cluster environments hardly form any giant planets at low metallicity in agreement with observations, where these changes originate from the increased temperature in the outer parts of the disc, which prolongs the core accretion time-scale of the planet. We therefore conclude that the outer disc structure and the planet's formation location determines the giant planet occurrence rate and the formation efficiency of cold and hot Jupiters.

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.

Cluster-void degeneracy breaking: Modified gravity in the balance

NASA Astrophysics Data System (ADS)

Sahlén, Martin; Silk, Joseph

2018-05-01

Combining galaxy cluster and void abundances is a novel, powerful way to constrain deviations from general relativity and the Λ CDM model. For a flat w CDM model with growth of large-scale structure parametrized by the redshift-dependent growth index γ (z )=γ0+γ1z /(1 +z ) of linear matter perturbations, combining void and cluster abundances in future surveys with Euclid and the four-meter multiobject spectroscopic telescope could improve the figure of merit for (w ,γ0,γ1) by a factor of 20 compared to individual abundances. In an ideal case, improvement on current cosmological data is a figure of merit factor 600 or more.

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

ATLAS and LHC computing on CRAY

NASA Astrophysics Data System (ADS)

Sciacca, F. G.; Haug, S.; ATLAS Collaboration

2017-10-01

Access and exploitation of large scale computing resources, such as those offered by general purpose HPC centres, is one important measure for ATLAS and the other Large Hadron Collider experiments in order to meet the challenge posed by the full exploitation of the future data within the constraints of flat budgets. We report on the effort of moving the Swiss WLCG T2 computing, serving ATLAS, CMS and LHCb, from a dedicated cluster to the large Cray systems at the Swiss National Supercomputing Centre CSCS. These systems do not only offer very efficient hardware, cooling and highly competent operators, but also have large backfill potentials due to size and multidisciplinary usage and potential gains due to economy at scale. Technical solutions, performance, expected return and future plans are discussed.

A clustered origin for isolated massive stars

NASA Astrophysics Data System (ADS)

Lucas, William E.; Rybak, Matus; Bonnell, Ian A.; Gieles, Mark

2018-03-01

High-mass stars are commonly found in stellar clusters promoting the idea that their formation occurs due to the physical processes linked with a young stellar cluster. It has recently been reported that isolated high-mass stars are present in the Large Magellanic Cloud. Due to their low velocities, it has been argued that these are high-mass stars which formed without a surrounding stellar cluster. In this paper, we present an alternative explanation for the origin of these stars in which they formed in a cluster environment but are subsequently dispersed into the field as their natal cluster is tidally disrupted in a merger with a higher mass cluster. They escape the merged cluster with relatively low velocities typical of the cluster interaction and thus of the larger scale velocity dispersion, similarly to the observed stars. N-body simulations of cluster mergers predict a sizeable population of low-velocity (≤20 km s-1), high-mass stars at distances of >20 pc from the cluster. High-mass clusters in which gas poor mergers are frequent would be expected to commonly have haloes of young stars, including high-mass stars, which were actually formed in a cluster environment.

Large-scale Heterogeneous Network Data Analysis

DTIC Science & Technology

2012-07-31

Mining (KDD’09), 527-535, 2009. [20] B. Long, Z. M. Zhang, X. Wu, and P. S. Yu . Spectral Clustering for Multi-type Relational Data. In Proceedings of...and Data Mining (KDD’06), 374-383, 2006. [33] Y. Sun, Y. Yu , and J. Han. Ranking-Based Clustering of Heterogeneous Information Networks with Star...publications in 2012 so far:  Yi-Kuang Ko, Jing- Kai Lou, Cheng-Te Li, Shou-de Lin, and Shyh-Kang Jeng. “A Social Network Evolution Model Based on

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.

Exchange-driven growth.

PubMed

Ben-Naim, E; Krapivsky, P L

2003-09-01

We study a class of growth processes in which clusters evolve via exchange of particles. We show that depending on the rate of exchange there are three possibilities: (I) Growth-clusters grow indefinitely, (II) gelation-all mass is transformed into an infinite gel in a finite time, and (III) instant gelation. In regimes I and II, the cluster size distribution attains a self-similar form. The large size tail of the scaling distribution is Phi(x) approximately exp(-x(2-nu)), where nu is a homogeneity degree of the rate of exchange. At the borderline case nu=2, the distribution exhibits a generic algebraic tail, Phi(x) approximately x(-5). In regime III, the gel nucleates immediately and consumes the entire system. For finite systems, the gelation time vanishes logarithmically, T approximately [lnN](-(nu-2)), in the large system size limit N--> infinity. The theory is applied to coarsening in the infinite range Ising-Kawasaki model and in electrostatically driven granular layers.

Dissecting the large-scale galactic conformity

NASA Astrophysics Data System (ADS)

Seo, Seongu

2018-01-01

Galactic conformity is an observed phenomenon that galaxies located in the same region have similar properties such as star formation rate, color, gas fraction, and so on. The conformity was first observed among galaxies within in the same halos (“one-halo conformity”). The one-halo conformity can be readily explained by mutual interactions among galaxies within a halo. Recent observations however further witnessed a puzzling connection among galaxies with no direct interaction. In particular, galaxies located within a sphere of ~5 Mpc radius tend to show similarities, even though the galaxies do not share common halos with each other ("two-halo conformity" or “large-scale conformity”). Using a cosmological hydrodynamic simulation, Illustris, we investigate the physical origin of the two-halo conformity and put forward two scenarios. First, back-splash galaxies are likely responsible for the large-scale conformity. They have evolved into red galaxies due to ram-pressure stripping in a given galaxy cluster and happen to reside now within a ~5 Mpc sphere. Second, galaxies in strong tidal field induced by large-scale structure also seem to give rise to the large-scale conformity. The strong tides suppress star formation in the galaxies. We discuss the importance of the large-scale conformity in the context of galaxy evolution.

Gray matter alterations in chronic pain: A network-oriented meta-analytic approach

PubMed Central

Cauda, Franco; Palermo, Sara; Costa, Tommaso; Torta, Riccardo; Duca, Sergio; Vercelli, Ugo; Geminiani, Giuliano; Torta, Diana M.E.

2014-01-01

Several studies have attempted to characterize morphological brain changes due to chronic pain. Although it has repeatedly been suggested that longstanding pain induces gray matter modifications, there is still some controversy surrounding the direction of the change (increase or decrease in gray matter) and the role of psychological and psychiatric comorbidities. In this study, we propose a novel, network-oriented, meta-analytic approach to characterize morphological changes in chronic pain. We used network decomposition to investigate whether different kinds of chronic pain are associated with a common or specific set of altered networks. Representational similarity techniques, network decomposition and model-based clustering were employed: i) to verify the presence of a core set of brain areas commonly modified by chronic pain; ii) to investigate the involvement of these areas in a large-scale network perspective; iii) to study the relationship between altered networks and; iv) to find out whether chronic pain targets clusters of areas. Our results showed that chronic pain causes both core and pathology-specific gray matter alterations in large-scale networks. Common alterations were observed in the prefrontal regions, in the anterior insula, cingulate cortex, basal ganglia, thalamus, periaqueductal gray, post- and pre-central gyri and inferior parietal lobule. We observed that the salience and attentional networks were targeted in a very similar way by different chronic pain pathologies. Conversely, alterations in the sensorimotor and attention circuits were differentially targeted by chronic pain pathologies. Moreover, model-based clustering revealed that chronic pain, in line with some neurodegenerative diseases, selectively targets some large-scale brain networks. Altogether these findings indicate that chronic pain can be better conceived and studied in a network perspective. PMID:24936419

Gravitationally neutral dark matter-dark antimatter universe crystal with epochs of decelerated and accelerated expansion

NASA Astrophysics Data System (ADS)

Gribov, I. A.; Trigger, S. A.

2016-11-01

A large-scale self-similar crystallized phase of finite gravitationally neutral universe (GNU)—huge GNU-ball—with spherical 2D-boundary immersed into an endless empty 3D- space is considered. The main principal assumptions of this universe model are: (1) existence of stable elementary particles-antiparticles with the opposite gravitational “charges” (M+gr and M -gr), which have the same positive inertial mass M in = |M ±gr | ≥ 0 and are equally presented in the universe during all universe evolution epochs; (2) the gravitational interaction between the masses of the opposite charges” is repulsive; (3) the unbroken baryon-antibaryon symmetry; (4) M+gr-M-gr “charges” symmetry, valid for two equally presented matter-antimatter GNU-components: (a) ordinary matter (OM)-ordinary antimatter (OAM), (b) dark matter (DM)-dark antimatter (DAM). The GNU-ball is weightless crystallized dust of equally presented, mutually repulsive (OM+DM) clusters and (OAM+DAM) anticlusters. Newtonian GNU-hydrodynamics gives the observable spatial flatness and ideal Hubble flow. The GNU in the obtained large-scale self-similar crystallized phase preserves absence of the cluster-anticluster collisions and simultaneously explains the observable large-scale universe phenomena: (1) the absence of the matter-antimatter clusters annihilation, (2) the self-similar Hubble flow stability and homogeneity, (3) flatness, (4) bubble and cosmic-net structures as 3D-2D-1D decrystallization phases with decelerative (a ≤ 0) and accelerative (a ≥ 0) expansion epochs, (5) the dark energy (DE) phenomena with Λ VACUUM = 0, (6) the DE and DM fine-tuning nature and predicts (7) evaporation into isolated huge M±gr superclusters without Big Rip.

The Dependence of Galaxy Clustering on Stellar-mass Assembly History for LRGs

NASA Astrophysics Data System (ADS)

Montero-Dorta, Antonio D.; Pérez, Enrique; Prada, Francisco; Rodríguez-Torres, Sergio; Favole, Ginevra; Klypin, Anatoly; Cid Fernandes, Roberto; González Delgado, Rosa M.; Domínguez, Alberto; Bolton, Adam S.; García-Benito, Rubén; Jullo, Eric; Niemiec, Anna

2017-10-01

We analyze the spectra of 300,000 luminous red galaxies (LRGs) with stellar masses {M}* ≳ {10}11 {M}⊙ from the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). By studying their star formation histories, we find two main evolutionary paths converging into the same quiescent galaxy population at z˜ 0.55. Fast-growing LRGs assemble 80% of their stellar mass very early on (z˜ 5), whereas slow-growing LRGs reach the same evolutionary state at z˜ 1.5. Further investigation reveals that their clustering properties on scales of ˜1-30 Mpc are, at a high level of significance, also different. Fast-growing LRGs are found to be more strongly clustered and reside in overall denser large-scale structure environments than slow-growing systems, for a given stellar-mass threshold. Our results show a dependence of clustering on a property that is directly related to the evolution of galaxies, I.e., the stellar-mass assembly history, for a homogeneous population of similar mass and color. In a forthcoming work, we will address the halo connection in the context of galaxy assembly bias.

Observing RAM Pressure Stripping and Morphological Transformation in the Coma Cluster

NASA Astrophysics Data System (ADS)

Gregg, Michael; West, Michael

2017-07-01

The two largest spirals in the Coma cluster, NGC4911 and NGC4921, are being vigorously ram-pressure stripped by the hot intracluster medium. Our HST ACS and WFC3 images have revealed galactic scale shock fronts, giant "Pillars of Creation", rivulets of dust, and spatially coherent star formation in these grand design spirals. We have now obtained HST WFC3 imaging of five additional large Coma spirals to search for and investigate the effects of ram pressure stripping across the wider cluster environment. The results are equally spectacular as the first two examples. The geometry of the interactions in some cases allows an estimation of the various time scales involved, including gas flows out of the disk leading to creation of the ICM, and the attendant triggered star formation in the galaxy disks. The global star formation patterns yield insights into the spatial and temporal ISM-ICM interactions driving cluster galaxy evolution and ultimately transforming morphologies from spiral to S0. These processes were much more common in the early Universe when the intergalactic and intracluster components were initially created from stripping and destruction of member galaxies.

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.

Serial clustering of extratropical cyclones and relationship with NAO and jet intensity based on the IMILAST cyclone database

NASA Astrophysics Data System (ADS)

Ulbrich, Sven; Pinto, Joaquim G.; Economou, Theodoros; Stephenson, David B.; Karremann, Melanie K.; Shaffrey, Len C.

2017-04-01

Cyclone families are a frequent synoptic weather feature in the Euro-Atlantic area, particularly during wintertime. Given appropriate large-scale conditions, such series (clusters) of storms may cause large socio-economic impacts and cumulative losses. Recent studies analyzing reanalysis data using single cyclone tracking methods have shown that serial clustering of cyclones occurs on both flanks and downstream regions of the North Atlantic storm track. Based on winter (DJF) cyclone counts from the IMILAST cyclone database, we explore the representation of serial clustering in the ERA-Interim period and its relationship with the NAO-phase and jet intensity. With this aim, clustering is estimated by the dispersion of winter (DJF) cyclone passages for each grid point over the Euro-Atlantic area. Results indicate that clustering over the Eastern North Atlantic and Western Europe can be identified for all methods, although the exact location and the dispersion magnitude may vary. The relationship between clustering and (i) the NAO-phase and (ii) jet intensity over the North Atlantic is statistically evaluated. Results show that the NAO-index and the jet intensity show a strong contribution to clustering, even though some spread is found between methods. We conclude that the general features of clustering of extratropical cyclones over the North Atlantic and Western Europe are robust to the choice of tracking method. The same is true for the influence of the NAO and jet intensity on cyclone dispersion.

Beyond the Young-Laplace model for cluster growth during dewetting of thin films: effective coarsening exponents and the role of long range dewetting interactions.

PubMed

Constantinescu, Adi; Golubović, Leonardo; Levandovsky, Artem

2013-09-01

Long range dewetting forces acting across thin films, such as the fundamental van der Waals interactions, may drive the formation of large clusters (tall multilayer islands) and pits, observed in thin films of diverse materials such as polymers, liquid crystals, and metals. In this study we further develop the methodology of the nonequilibrium statistical mechanics of thin films coarsening within continuum interface dynamics model incorporating long range dewetting interactions. The theoretical test bench model considered here is a generalization of the classical Mullins model for the dynamics of solid film surfaces. By analytic arguments and simulations of the model, we study the coarsening growth laws of clusters formed in thin films due to the dewetting interactions. The ultimate cluster growth scaling laws at long times are strongly universal: Short and long range dewetting interactions yield the same coarsening exponents. However, long range dewetting interactions, such as the van der Waals forces, introduce a distinct long lasting early time scaling behavior characterized by a slow growth of the cluster height/lateral size aspect ratio (i.e., a time-dependent Young angle) and by effective coarsening exponents that depend on cluster size. In this study, we develop a theory capable of analytically calculating these effective size-dependent coarsening exponents characterizing the cluster growth in the early time regime. Such a pronounced early time scaling behavior has been indeed seen in experiments; however, its physical origin has remained elusive to this date. Our theory attributes these observed phenomena to ubiquitous long range dewetting interactions acting across thin solid and liquid films. Our results are also applicable to cluster growth in initially very thin fluid films, formed by depositing a few monolayers or by a submonolayer deposition. Under this condition, the dominant coarsening mechanism is diffusive intercluster mass transport while the cluster coalescence plays a minor role, both in solid and in fluid films.

A2111: A z= 0.23 Butcher-Oemler Cluster with a Non-Isothermal Atmosphere and Normal Metallicity

NASA Technical Reports Server (NTRS)

Wang, Q. Daniel; Henriksen, Mark

1998-01-01

We report results from an x-ray spectral study of the z=0.23 Abell 2111 galaxy cluster using the Advanced Satellite for Astrophysics and Cosmology and the ROSAT Position Sensitive Proportional Counter. By correcting for the energy-dependent point-spread function of the instruments, we have examined the temperature structure of the cluster. The cluster's core within 3 is found to have a temperature of 5.4 +/- 0.5 keV, significantly higher than 2.8 +/-0.7 keV in the surrounding region of r = 3-6. This radially decreasing temperature structure can be parameterized by a polytropic index of gamma less than 1.4. Furthermore, the intracluster medium appears clumpy on scales less than 1. Early studies have revealed that the x-ray centroid of the cluster shifts with spatial scale and the overall optical and x-ray morphology is strongly elongated. These results together suggest that A2111 in undergoing a merger, which is likely responsible for the high fraction of blue galaxies observed in the cluster. We have further measured the abundance of the medium as 0.25 +/- 0.14 solar. This value is similar to those of nearby clusters which do not show a large blue galaxy function, suggesting that star formation in disk galaxies and subsequent loss to the intracluster medium do not drastically alter the average abundance of a cluster since z=0.23.

Extragalactic Astrophysics

NASA Astrophysics Data System (ADS)

Webb, James R.

2016-09-01

This book is intended to be a course about the creation and evolution of the universe at large, including the basic macroscopic building blocks (galaxies) and the overall large-scale structure. This text covers a broad range of topics for a graduate-level class in a physics department where students' available credit hours for astrophysics classes are limited. The sections cover galactic structure, external galaxies, galaxy clustering, active galaxies, general relativity and cosmology.

An integrated approach to reconstructing genome-scale transcriptional regulatory networks

DOE PAGES

Imam, Saheed; Noguera, Daniel R.; Donohue, Timothy J.; ...

2015-02-27

Transcriptional regulatory networks (TRNs) program cells to dynamically alter their gene expression in response to changing internal or environmental conditions. In this study, we develop a novel workflow for generating large-scale TRN models that integrates comparative genomics data, global gene expression analyses, and intrinsic properties of transcription factors (TFs). An assessment of this workflow using benchmark datasets for the well-studied γ-proteobacterium Escherichia coli showed that it outperforms expression-based inference approaches, having a significantly larger area under the precision-recall curve. Further analysis indicated that this integrated workflow captures different aspects of the E. coli TRN than expression-based approaches, potentially making themmore » highly complementary. We leveraged this new workflow and observations to build a large-scale TRN model for the α-Proteobacterium Rhodobacter sphaeroides that comprises 120 gene clusters, 1211 genes (including 93 TFs), 1858 predicted protein-DNA interactions and 76 DNA binding motifs. We found that ~67% of the predicted gene clusters in this TRN are enriched for functions ranging from photosynthesis or central carbon metabolism to environmental stress responses. We also found that members of many of the predicted gene clusters were consistent with prior knowledge in R. sphaeroides and/or other bacteria. Experimental validation of predictions from this R. sphaeroides TRN model showed that high precision and recall was also obtained for TFs involved in photosynthesis (PpsR), carbon metabolism (RSP_0489) and iron homeostasis (RSP_3341). In addition, this integrative approach enabled generation of TRNs with increased information content relative to R. sphaeroides TRN models built via other approaches. We also show how this approach can be used to simultaneously produce TRN models for each related organism used in the comparative genomics analysis. Our results highlight the advantages of integrating comparative genomics of closely related organisms with gene expression data to assemble large-scale TRN models with high-quality predictions.« less

Adaptive nest clustering and density-dependent nest survival in dabbling ducks

USGS Publications Warehouse

Ringelman, Kevin M.; Eadie, John M.; Ackerman, Joshua T.

2014-01-01

Density-dependent population regulation is observed in many taxa, and understanding the mechanisms that generate density dependence is especially important for the conservation of heavily-managed species. In one such system, North American waterfowl, density dependence is often observed at continental scales, and nest predation has long been implicated as a key factor driving this pattern. However, despite extensive research on this topic, it remains unclear if and how nest density influences predation rates. Part of this confusion may have arisen because previous studies have studied density-dependent predation at relatively large spatial and temporal scales. Because the spatial distribution of nests changes throughout the season, which potentially influences predator behavior, nest survival may vary through time at relatively small spatial scales. As such, density-dependent nest predation might be more detectable at a spatially- and temporally-refined scale and this may provide new insights into nest site selection and predator foraging behavior. Here, we used three years of data on nest survival of two species of waterfowl, mallards and gadwall, to more fully explore the relationship between local nest clustering and nest survival. Throughout the season, we found that the distribution of nests was consistently clustered at small spatial scales (˜50–400 m), especially for mallard nests, and that this pattern was robust to yearly variation in nest density and the intensity of predation. We demonstrated further that local nest clustering had positive fitness consequences – nests with closer nearest neighbors were more likely to be successful, a result that is counter to the general assumption that nest predation rates increase with nest density.

Optimizing BAO measurements with non-linear transformations of the Lyman-α forest

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

Wang, Xinkang; Font-Ribera, Andreu; Seljak, Uroš, E-mail: xinkang.wang@berkeley.edu, E-mail: afont@lbl.gov, E-mail: useljak@berkeley.edu

2015-04-01

We explore the effect of applying a non-linear transformation to the Lyman-α forest transmitted flux F=e{sup −τ} and the ability of analytic models to predict the resulting clustering amplitude. Both the large-scale bias of the transformed field (signal) and the amplitude of small scale fluctuations (noise) can be arbitrarily modified, but we were unable to find a transformation that increases significantly the signal-to-noise ratio on large scales using Taylor expansion up to the third order. In particular, however, we achieve a 33% improvement in signal to noise for Gaussianized field in transverse direction. On the other hand, we explore anmore » analytic model for the large-scale biasing of the Lyα forest, and present an extension of this model to describe the biasing of the transformed fields. Using hydrodynamic simulations we show that the model works best to describe the biasing with respect to velocity gradients, but is less successful in predicting the biasing with respect to large-scale density fluctuations, especially for very nonlinear transformations.« less

DO NOT FORGET THE FOREST FOR THE TREES: THE STELLAR-MASS HALO-MASS RELATION IN DIFFERENT ENVIRONMENTS

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

Tonnesen, Stephanie; Cen, Renyue, E-mail: stonnes@gmail.com, E-mail: cen@astro.princeton.edu

2015-10-20

The connection between dark matter halos and galactic baryons is often not well constrained nor well resolved in cosmological hydrodynamical simulations. Thus, halo occupation distribution models that assign galaxies to halos based on halo mass are frequently used to interpret clustering observations, even though it is well known that the assembly history of dark matter halos is related to their clustering. In this paper we use high-resolution hydrodynamical cosmological simulations to compare the halo and stellar mass growth of galaxies in a large-scale overdensity to those in a large-scale underdensity (on scales of about 20 Mpc). The simulation reproduces assemblymore » bias, in which halos have earlier formation times in overdense environments than in underdense regions. We find that the ratio of stellar mass to halo mass is larger in overdense regions in central galaxies residing in halos with masses between 10{sup 11} and 10{sup 12.9} M{sub ⊙}. When we force the local density (within 2 Mpc) at z = 0 to be the same for galaxies in the large-scale over- and underdensities, we find the same results. We posit that this difference can be explained by a combination of earlier formation times, more interactions at early times with neighbors, and more filaments feeding galaxies in overdense regions. This result puts the standard practice of assigning stellar mass to halos based only on their mass, rather than considering their larger environment, into question.« less

Rotation in young massive star clusters

NASA Astrophysics Data System (ADS)

Mapelli, Michela

2017-05-01

Hydrodynamical simulations of turbulent molecular clouds show that star clusters form from the hierarchical merger of several sub-clumps. We run smoothed-particle hydrodynamics simulations of turbulence-supported molecular clouds with mass ranging from 1700 to 43 000 M⊙. We study the kinematic evolution of the main cluster that forms in each cloud. We find that the parent gas acquires significant rotation, because of large-scale torques during the process of hierarchical assembly. The stellar component of the embedded star cluster inherits the rotation signature from the parent gas. Only star clusters with final mass < few × 100 M⊙ do not show any clear indication of rotation. Our simulated star clusters have high ellipticity (˜0.4-0.5 at t = 4 Myr) and are subvirial (Qvir ≲ 0.4). The signature of rotation is stronger than radial motions due to subvirial collapse. Our results suggest that rotation is common in embedded massive (≳1000 M⊙) star clusters. This might provide a key observational test for the hierarchical assembly scenario.

OpenCluster: A Flexible Distributed Computing Framework for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Wei, Shoulin; Wang, Feng; Deng, Hui; Liu, Cuiyin; Dai, Wei; Liang, Bo; Mei, Ying; Shi, Congming; Liu, Yingbo; Wu, Jingping

2017-02-01

The volume of data generated by modern astronomical telescopes is extremely large and rapidly growing. However, current high-performance data processing architectures/frameworks are not well suited for astronomers because of their limitations and programming difficulties. In this paper, we therefore present OpenCluster, an open-source distributed computing framework to support rapidly developing high-performance processing pipelines of astronomical big data. We first detail the OpenCluster design principles and implementations and present the APIs facilitated by the framework. We then demonstrate a case in which OpenCluster is used to resolve complex data processing problems for developing a pipeline for the Mingantu Ultrawide Spectral Radioheliograph. Finally, we present our OpenCluster performance evaluation. Overall, OpenCluster provides not only high fault tolerance and simple programming interfaces, but also a flexible means of scaling up the number of interacting entities. OpenCluster thereby provides an easily integrated distributed computing framework for quickly developing a high-performance data processing system of astronomical telescopes and for significantly reducing software development expenses.

Appplication of statistical mechanical methods to the modeling of social networks

NASA Astrophysics Data System (ADS)

Strathman, Anthony Robert

With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

Large-scale clustering measurements with photometric redshifts: comparing the dark matter haloes of X-ray AGN, star-forming and passive galaxies at z ≈ 1

NASA Astrophysics Data System (ADS)

Georgakakis, A.; Mountrichas, G.; Salvato, M.; Rosario, D.; Pérez-González, P. G.; Lutz, D.; Nandra, K.; Coil, A.; Cooper, M. C.; Newman, J. A.; Berta, S.; Magnelli, B.; Popesso, P.; Pozzi, F.

2014-10-01

We combine multi-wavelength data in the AEGIS-XD and C-COSMOS surveys to measure the typical dark matter halo mass of X-ray selected active galactic nuclei (AGN) [LX(2-10 keV) > 1042 erg s- 1] in comparison with far-infrared selected star-forming galaxies detected in the Herschel/PEP survey (PACS Evolutionary Probe; LIR > 1011 L⊙) and quiescent systems at z ≈ 1. We develop a novel method to measure the clustering of extragalactic populations that uses photometric redshift probability distribution functions in addition to any spectroscopy. This is advantageous in that all sources in the sample are used in the clustering analysis, not just the subset with secure spectroscopy. The method works best for large samples. The loss of accuracy because of the lack of spectroscopy is balanced by increasing the number of sources used to measure the clustering. We find that X-ray AGN, far-infrared selected star-forming galaxies and passive systems in the redshift interval 0.6 < z < 1.4 are found in haloes of similar mass, log MDMH/(M⊙ h-1) ≈ 13.0. We argue that this is because the galaxies in all three samples (AGN, star-forming, passive) have similar stellar mass distributions, approximated by the J-band luminosity. Therefore, all galaxies that can potentially host X-ray AGN, because they have stellar masses in the appropriate range, live in dark matter haloes of log MDMH/(M⊙ h-1) ≈ 13.0 independent of their star formation rates. This suggests that the stellar mass of X-ray AGN hosts is driving the observed clustering properties of this population. We also speculate that trends between AGN properties (e.g. luminosity, level of obscuration) and large-scale environment may be related to differences in the stellar mass of the host galaxies.

Galaxy clustering and the origin of large-scale flows

NASA Technical Reports Server (NTRS)

Juszkiewicz, R.; Yahil, A.

1989-01-01

Peebles's 'cosmic virial theorem' is extended from its original range of validity at small separations, where hydrostatic equilibrium holds, to large separations, in which linear gravitational stability theory applies. The rms pairwise velocity difference at separation r is shown to depend on the spatial galaxy correlation function xi(x) only for x less than r. Gravitational instability theory can therefore be tested by comparing the two up to the maximum separation for which both can reliably be determined, and there is no dependence on the poorly known large-scale density and velocity fields. With the expected improvement in the data over the next few years, however, this method should yield a reliable determination of omega.

A HIERARCHIAL STOCHASTIC MODEL OF LARGE SCALE ATMOSPHERIC CIRCULATION PATTERNS AND MULTIPLE STATION DAILY PRECIPITATION

EPA Science Inventory

A stochastic model of weather states and concurrent daily precipitation at multiple precipitation stations is described. our algorithms are invested for classification of daily weather states; k means, fuzzy clustering, principal components, and principal components coupled with ...

High Performance Geostatistical Modeling of Biospheric Resources

NASA Astrophysics Data System (ADS)

Pedelty, J. A.; Morisette, J. T.; Smith, J. A.; Schnase, J. L.; Crosier, C. S.; Stohlgren, T. J.

2004-12-01

We are using parallel geostatistical codes to study spatial relationships among biospheric resources in several study areas. For example, spatial statistical models based on large- and small-scale variability have been used to predict species richness of both native and exotic plants (hot spots of diversity) and patterns of exotic plant invasion. However, broader use of geostastics in natural resource modeling, especially at regional and national scales, has been limited due to the large computing requirements of these applications. To address this problem, we implemented parallel versions of the kriging spatial interpolation algorithm. The first uses the Message Passing Interface (MPI) in a master/slave paradigm on an open source Linux Beowulf cluster, while the second is implemented with the new proprietary Xgrid distributed processing system on an Xserve G5 cluster from Apple Computer, Inc. These techniques are proving effective and provide the basis for a national decision support capability for invasive species management that is being jointly developed by NASA and the US Geological Survey.

Locating inefficient links in a large-scale transportation network

NASA Astrophysics Data System (ADS)

Sun, Li; Liu, Like; Xu, Zhongzhi; Jie, Yang; Wei, Dong; Wang, Pu

2015-02-01

Based on data from geographical information system (GIS) and daily commuting origin destination (OD) matrices, we estimated the distribution of traffic flow in the San Francisco road network and studied Braess's paradox in a large-scale transportation network with realistic travel demand. We measured the variation of total travel time Δ T when a road segment is closed, and found that | Δ T | follows a power-law distribution if Δ T < 0 or Δ T > 0. This implies that most roads have a negligible effect on the efficiency of the road network, while the failure of a few crucial links would result in severe travel delays, and closure of a few inefficient links would counter-intuitively reduce travel costs considerably. Generating three theoretical networks, we discovered that the heterogeneously distributed travel demand may be the origin of the observed power-law distributions of | Δ T | . Finally, a genetic algorithm was used to pinpoint inefficient link clusters in the road network. We found that closing specific road clusters would further improve the transportation efficiency.

Limits on the fluctuating part of y-type distortion monopole from Planck and SPT results

NASA Astrophysics Data System (ADS)

Khatri, Rishi; Sunyaev, Rashid

2015-08-01

We use the published Planck and SPT cluster catalogs [1,2] and recently published y-distortion maps [3] to put strong observational limits on the contribution of the fluctuating part of the y-type distortions to the y-distortion monopole. Our bounds are 5.4× 10-8 < langle yrangle < 2.2× 10-6. Our upper bound is a factor of 6.8 stronger than the currently best upper 95% confidence limit from COBE-FIRAS of langle yrangle <15× 10-6. In the standard cosmology, large scale structure is the only source of such distortions and our limits therefore constrain the baryonic physics involved in the formation of the large scale structure. Our lower limit, from the detected clusters in the Planck and SPT catalogs, also implies that a Pixie-like experiment should detect the y-distortion monopole at >27-σ. The biggest sources of uncertainty in our upper limit are the monopole offsets between different HFI channel maps that we estimate to be <10-6.

Joint analysis of galaxy-galaxy lensing and galaxy clustering: Methodology and forecasts for Dark Energy Survey

DOE PAGES

Park, Y.; Krause, E.; Dodelson, S.; ...

2016-09-30

The joint analysis of galaxy-galaxy lensing and galaxy clustering is a promising method for inferring the growth function of large scale structure. Our analysis will be carried out on data from the Dark Energy Survey (DES), with its measurements of both the distribution of galaxies and the tangential shears of background galaxies induced by these foreground lenses. We develop a practical approach to modeling the assumptions and systematic effects affecting small scale lensing, which provides halo masses, and large scale galaxy clustering. Introducing parameters that characterize the halo occupation distribution (HOD), photometric redshift uncertainties, and shear measurement errors, we studymore » how external priors on different subsets of these parameters affect our growth constraints. Degeneracies within the HOD model, as well as between the HOD and the growth function, are identified as the dominant source of complication, with other systematic effects sub-dominant. The impact of HOD parameters and their degeneracies necessitate the detailed joint modeling of the galaxy sample that we employ. Finally, we conclude that DES data will provide powerful constraints on the evolution of structure growth in the universe, conservatively/optimistically constraining the growth function to 7.9%/4.8% with its first-year data that covered over 1000 square degrees, and to 3.9%/2.3% with its full five-year data that will survey 5000 square degrees, including both statistical and systematic uncertainties.« less

Joint analysis of galaxy-galaxy lensing and galaxy clustering: Methodology and forecasts for Dark Energy Survey

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

Park, Y.; Krause, E.; Dodelson, S.

The joint analysis of galaxy-galaxy lensing and galaxy clustering is a promising method for inferring the growth function of large scale structure. Our analysis will be carried out on data from the Dark Energy Survey (DES), with its measurements of both the distribution of galaxies and the tangential shears of background galaxies induced by these foreground lenses. We develop a practical approach to modeling the assumptions and systematic effects affecting small scale lensing, which provides halo masses, and large scale galaxy clustering. Introducing parameters that characterize the halo occupation distribution (HOD), photometric redshift uncertainties, and shear measurement errors, we studymore » how external priors on different subsets of these parameters affect our growth constraints. Degeneracies within the HOD model, as well as between the HOD and the growth function, are identified as the dominant source of complication, with other systematic effects sub-dominant. The impact of HOD parameters and their degeneracies necessitate the detailed joint modeling of the galaxy sample that we employ. Finally, we conclude that DES data will provide powerful constraints on the evolution of structure growth in the universe, conservatively/optimistically constraining the growth function to 7.9%/4.8% with its first-year data that covered over 1000 square degrees, and to 3.9%/2.3% with its full five-year data that will survey 5000 square degrees, including both statistical and systematic uncertainties.« less

Multiwavelength study of X-ray luminous clusters in the Hyper Suprime-Cam Subaru Strategic Program S16A field

NASA Astrophysics Data System (ADS)

Miyaoka, Keita; Okabe, Nobuhiro; Kitaguchi, Takao; Oguri, Masamune; Fukazawa, Yasushi; Mandelbaum, Rachel; Medezinski, Elinor; Babazaki, Yasunori; Nishizawa, Atsushi J.; Hamana, Takashi; Lin, Yen-Ting; Akamatsu, Hiroki; Chiu, I.-Non; Fujita, Yutaka; Ichinohe, Yuto; Komiyama, Yutaka; Sasaki, Toru; Takizawa, Motokazu; Ueda, Shutaro; Umetsu, Keiichi; Coupon, Jean; Hikage, Chiaki; Hoshino, Akio; Leauthaud, Alexie; Matsushita, Kyoko; Mitsuishi, Ikuyuki; Miyatake, Hironao; Miyazaki, Satoshi; More, Surhud; Nakazawa, Kazuhiro; Ota, Naomi; Sato, Kousuke; Spergel, David; Tamura, Takayuki; Tanaka, Masayuki; Tanaka, Manobu M.; Utsumi, Yousuke

2018-01-01

We present a joint X-ray, optical, and weak-lensing analysis for X-ray luminous galaxy clusters selected from the MCXC (Meta-Catalog of X-Ray Detected Clusters of Galaxies) cluster catalog in the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) survey field with S16A data. As a pilot study for a series of papers, we measure hydrostatic equilibrium (HE) masses using XMM-Newton data for four clusters in the current coverage area out of a sample of 22 MCXC clusters. We additionally analyze a non-MCXC cluster associated with one MCXC cluster. We show that HE masses for the MCXC clusters are correlated with cluster richness from the CAMIRA catalog, while that for the non-MCXC cluster deviates from the scaling relation. The mass normalization of the relationship between cluster richness and HE mass is compatible with one inferred by matching CAMIRA cluster abundance with a theoretical halo mass function. The mean gas mass fraction based on HE masses for the MCXC clusters is = 0.125 ± 0.012 at spherical overdensity Δ = 500, which is ˜80%-90% of the cosmic mean baryon fraction, Ωb/Ωm, measured by cosmic microwave background experiments. We find that the mean baryon fraction estimated from X-ray and HSC-SSP optical data is comparable to Ωb/Ωm. A weak-lensing shear catalog of background galaxies, combined with photometric redshifts, is currently available only for three clusters in our sample. Hydrostatic equilibrium masses roughly agree with weak-lensing masses, albeit with large uncertainty. This study demonstrates that further multiwavelength study for a large sample of clusters using X-ray, HSC-SSP optical, and weak-lensing data will enable us to understand cluster physics and utilize cluster-based cosmology.

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

EarthShape: A Strategy for Investigating the Role of Biota on Surface Processes

NASA Astrophysics Data System (ADS)

Übernickel, Kirstin; Ehlers, Todd Alan; von Blanckenburg, Friedhelm; Paulino, Leandro

2017-04-01

EarthShape - "Earth surface shaping by biota" is a 6-year priority research program funded by the German science foundation (DFG-SPP 1803) that performs soil- and landscape-scale critical zone research at 4 locations along a climate gradient in Chile, South America. The program is in its first year and involves an interdisciplinary collaboration between geologists, geomorphologists, ecologists, soil scientists, microbiologists, geophysicists, geochemists, hydrogeologists and climatologists including 18 German and 8 Chilean institutions. EarthShape is composed of 4 research clusters representing the process chain from weathering of substrate to deposition of eroded material. Cluster 1 explores micro-biota as the "weathering engine". Investigations in this cluster quantify different mechanisms of biogenic weathering whereby plants, fungi, and bacteria interact with rock in the production of soil. Cluster 2 explores bio-mediated redistribution of material within the weathering zone. Studies in this cluster focus on soil catenas along hill slope profiles to investigate the modification of matter along its transport path. Cluster 3 explores biotic modulation of erosion and sediment routing at the catchment scale. Investigations in this cluster explore the effects of vegetation cover on solute and sediment transport from hill slopes to the channel network. Cluster 4 explores the depositional legacy of coupled biogenic and Earth surface systems. This cluster investigates records of vegetation-land surface interactions in different depositional settings. A final component of EarthShape lies in the integration of results from these 4 clusters using numerical models to bridging between the diverse times scales used by different disciplines. The Chilean Coastal Cordillera between 25° and 40°S was selected to carry out this research because its north-south orientation captures a large ecological and climate gradient. This gradient ranges from hyper-arid (Atacama desert) to temperate to humid conditions without a dry season and pristine temperate Araucaria forest. All study sites comprise granitic, previously unglaciated mountain ranges. It is one of the very few regions on Earth with uniquely rich conditions for quantifying biotic interactions with topography. Here, we benefit from (1) similar rock type, (2) tectonic uplift providing a topographic gradient for erosion on geological time-scales, (3) glaciation free catchments, and (4) well-documented records of climate change (marine, and lacustrine sediment records available). The presentation provides an introduction to the EarthShape project and an overview of activities over the first year.

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

Cluster Differences Scaling with a Within-Clusters Loss Component and a Fuzzy Successive Approximation Strategy To Avoid Local Minima.

ERIC Educational Resources Information Center

Heiser, Willem J.; And Others

1997-01-01

The least squares loss function of cluster differences scaling, originally defined only on residuals of pairs allocated to different clusters, is extended with a loss component for pairs allocated to the same cluster. Findings show that this makes the method equivalent to multidimensional scaling with cluster constraints on the coordinates. (SLD)

The star-forming complex LMC-N79 as a future rival to 30 Doradus

NASA Astrophysics Data System (ADS)

Ochsendorf, Bram B.; Zinnecker, Hans; Nayak, Omnarayani; Bally, John; Meixner, Margaret; Jones, Olivia C.; Indebetouw, Remy; Rahman, Mubdi

2017-11-01

Within the early Universe, `extreme' star formation may have been the norm rather than the exception1,2. Super star clusters (with masses greater than 105 solar masses) are thought to be the modern-day analogues of globular clusters, relics of a cosmic time (redshift z ≳ 2) when the Universe was filled with vigorously star-forming systems3. The giant H ii region 30 Doradus in the Large Magellanic Cloud is often regarded as a benchmark for studies of extreme star formation4. Here, we report the discovery of a massive embedded star-forming complex spanning about 500 pc in the unexplored southwest region of the Large Magellanic Cloud, which manifests itself as a younger, embedded twin of 30 Doradus. Previously known as N79, this region has a star-formation efficiency greater than that of 30 Doradus, by a factor of about 2, as measured over the past 0.5 Myr. Moreover, at the heart of N79 lies the most luminous infrared compact source discovered with large-scale infrared surveys of the Large Magellanic Cloud and Milky Way, possibly a precursor to the central super star cluster of 30 Doradus, R136. The discovery of a nearby candidate super star cluster may provide invaluable information to understand how extreme star formation proceeds in the current and high-redshift Universe.

Offsets between the X-ray and the Sunyaev-Zel'Dovich-effect peaks in merging galaxy clusters and their cosmological implications

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

Zhang, Congyao; Yu, Qingjuan; Lu, Youjun, E-mail: yuqj@pku.edu.cn

2014-12-01

Observations reveal that the peaks of the X-ray map and the Sunyaev-Zel'dovich (SZ) effect map of some galaxy clusters are offset from each other. In this paper, we perform a set of hydrodynamical simulations of mergers of two galaxy clusters to investigate the spatial offset between the maxima of the X-ray and the SZ surface brightness of the merging clusters. We find that significantly large SZ-X-ray offsets (>100 kpc) can be produced during the major mergers of galaxy clusters (with mass > 1 × 10{sup 14} M {sub ☉}). The significantly large offsets are mainly caused by a 'jump effect'more » that occurs between the primary and secondary pericentric passages of the two merging clusters, during which the X-ray peak may jump to the densest gas region located near the center of the small cluster, but the SZ peak remains near the center of the large one. Our simulations show that merging systems with higher masses and larger initial relative velocities may result in larger offset sizes and longer offset time durations; and only nearly head-on mergers are likely to produce significantly large offsets. We further investigate the statistical distribution of the SZ-X-ray offset sizes and find that (1) the number distribution of the offset sizes is bimodal with one peak located at low offsets ∼0 and the other at large offsets ∼350-450 h {sup –1} kpc, but the objects with intermediate offsets are scarce; and (2) the probabilities of the clusters in the mass range higher than 2 × 10{sup 14} h {sup –1} M {sub ☉} that have offsets larger than 20, 50, 200, 300, and 500 h {sup –1} kpc are 34.0%, 11.1%, 8.0%, 6.5%, and 2.0%, respectively, at z = 0.7. The probability is sensitive to the underlying pairwise velocity distribution and the merger rate of clusters. We suggest that the SZ-X-ray offsets provide a probe to the cosmic velocity fields on the cluster scale and the cluster merger rate, and future observations on the SZ-X-ray offsets for a large number of clusters may put strong constraints on them. Our simulation results suggest that the SZ-X-ray offset in the Bullet Cluster, together with the mass ratio of the two merging clusters, requires a relative velocity larger than 3000 km s{sup –1} at an initial separation 5 Mpc. The cosmic velocity distribution at the high-velocity end is expected to be crucial in determining whether there exists an incompatibility between the existence of the Bullet Cluster and the prediction of a ΛCDM model.« less

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.

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.

Structures in magnetohydrodynamic turbulence: Detection and scaling

NASA Astrophysics Data System (ADS)

Uritsky, V. M.; Pouquet, A.; Rosenberg, D.; Mininni, P. D.; Donovan, E. F.

2010-11-01

We present a systematic analysis of statistical properties of turbulent current and vorticity structures at a given time using cluster analysis. The data stem from numerical simulations of decaying three-dimensional magnetohydrodynamic turbulence in the absence of an imposed uniform magnetic field; the magnetic Prandtl number is taken equal to unity, and we use a periodic box with grids of up to 15363 points and with Taylor Reynolds numbers up to 1100. The initial conditions are either an X -point configuration embedded in three dimensions, the so-called Orszag-Tang vortex, or an Arn’old-Beltrami-Childress configuration with a fully helical velocity and magnetic field. In each case two snapshots are analyzed, separated by one turn-over time, starting just after the peak of dissipation. We show that the algorithm is able to select a large number of structures (in excess of 8000) for each snapshot and that the statistical properties of these clusters are remarkably similar for the two snapshots as well as for the two flows under study in terms of scaling laws for the cluster characteristics, with the structures in the vorticity and in the current behaving in the same way. We also study the effect of Reynolds number on cluster statistics, and we finally analyze the properties of these clusters in terms of their velocity-magnetic-field correlation. Self-organized criticality features have been identified in the dissipative range of scales. A different scaling arises in the inertial range, which cannot be identified for the moment with a known self-organized criticality class consistent with magnetohydrodynamics. We suggest that this range can be governed by turbulence dynamics as opposed to criticality and propose an interpretation of intermittency in terms of propagation of local instabilities.

On Efficient Multigrid Methods for Materials Processing Flows with Small Particles

NASA Technical Reports Server (NTRS)

Thomas, James (Technical Monitor); Diskin, Boris; Harik, VasylMichael

2004-01-01

Multiscale modeling of materials requires simulations of multiple levels of structural hierarchy. The computational efficiency of numerical methods becomes a critical factor for simulating large physical systems with highly desperate length scales. Multigrid methods are known for their superior efficiency in representing/resolving different levels of physical details. The efficiency is achieved by employing interactively different discretizations on different scales (grids). To assist optimization of manufacturing conditions for materials processing with numerous particles (e.g., dispersion of particles, controlling flow viscosity and clusters), a new multigrid algorithm has been developed for a case of multiscale modeling of flows with small particles that have various length scales. The optimal efficiency of the algorithm is crucial for accurate predictions of the effect of processing conditions (e.g., pressure and velocity gradients) on the local flow fields that control the formation of various microstructures or clusters.

Observational evidence of predawn plasma bubble and its irregularity scales in Southeast Asia

NASA Astrophysics Data System (ADS)

Watthanasangmechai, K.; Tsunoda, R. T.; Yokoyama, T.; Ishii, M.; Tsugawa, T.

2016-12-01

This paper describes an event of deep plasma depletion simultaneously detected with GPS, GNU Radio Beacon Receiver (GRBR) and in situ satellite measurement from DMFPF15. The event is on March 7, 2012 at 4:30 LT with geomagnetic quiet condition. Such a sharp depletion at plasma bubble wall detected at predawn is interesting but apparently rare event. Only one event is found from all dataset in March 2012. The inside structure of the predawn plasma bubble was clearly captured by DMSPF15 and the ground-based GRBR. The envelop structure seen from the precessed GPS-TEC appeares as a cluster. The observed cluster is concluded as the structure at the westwall of an upwelling of the large-scale wave structure, that accompanies the fifty- and thousand-km scales. This event is consistent with the plasma bubble structure simulated from the high-resolution bubble (HIRB) model.

Radio active galactic nuclei in galaxy clusters: Feedback, merger signatures, and cluster tracers

NASA Astrophysics Data System (ADS)

Paterno-Mahler, Rachel Beth

Galaxy clusters, the largest gravitationally-bound structures in the universe, are composed of 50-1000s of galaxies, hot X-ray emitting gas, and dark matter. They grow in size over time through cluster and group mergers. The merger history of a cluster can be imprinted on the hot gas, known as the intracluster medium (ICM). Merger signatures include shocks, cold fronts, and sloshing of the ICM, which can form spiral structures. Some clusters host double-lobed radio sources driven by active galactic nuclei (AGN). First, I will present a study of the galaxy cluster Abell 2029, which is very relaxed on large scales and has one of the largest continuous sloshing spirals yet observed in the X-ray, extending outward approximately 400 kpc. The sloshing gas interacts with the southern lobe of the radio galaxy, causing it to bend. Energy injection from the AGN is insufficient to offset cooling. The sloshing spiral may be an important additional mechanism in preventing large amounts of gas from cooling to very low temperatures. Next, I will present a study of Abell 98, a triple system currently undergoing a merger. I will discuss the merger history, and show that it is causing a shock. The central subcluster hosts a double-lobed AGN, which is evacuating a cavity in the ICM. Understanding the physical processes that affect the ICM is important for determining the mass of clusters, which in turn affects our calculations of cosmological parameters. To further constrain these parameters, as well as models of galaxy evolution, it is important to use a large sample of galaxy clusters over a range of masses and redshifts. Bent, double-lobed radio sources can potentially act as tracers of galaxy clusters over wide ranges of these parameters. I examine how efficient bent radio sources are at tracing high-redshift (z>0.7) clusters. Out of 646 sources in our high-redshift Clusters Occupied by Bent Radio AGN (COBRA) sample, 282 are candidate new, distant clusters of galaxies based on measurements of excess galaxy counts surrounding the radio sources in Spitzer infrared images.

Classifying epileptic EEG signals with delay permutation entropy and Multi-Scale K-means.

PubMed

Zhu, Guohun; Li, Yan; Wen, Peng Paul; Wang, Shuaifang

2015-01-01

Most epileptic EEG classification algorithms are supervised and require large training datasets, that hinder their use in real time applications. This chapter proposes an unsupervised Multi-Scale K-means (MSK-means) MSK-means algorithm to distinguish epileptic EEG signals and identify epileptic zones. The random initialization of the K-means algorithm can lead to wrong clusters. Based on the characteristics of EEGs, the MSK-means MSK-means algorithm initializes the coarse-scale centroid of a cluster with a suitable scale factor. In this chapter, the MSK-means algorithm is proved theoretically superior to the K-means algorithm on efficiency. In addition, three classifiers: the K-means, MSK-means MSK-means and support vector machine (SVM), are used to identify seizure and localize epileptogenic zone using delay permutation entropy features. The experimental results demonstrate that identifying seizure with the MSK-means algorithm and delay permutation entropy achieves 4. 7 % higher accuracy than that of K-means, and 0. 7 % higher accuracy than that of the SVM.

Gravitational clustering in the expanding universe - Controlled high-resolution studies in two dimensions

NASA Technical Reports Server (NTRS)

Beacom, John Francis; Dominik, Kurt G.; Melott, Adrian L.; Perkins, Sam P.; Shandarin, Sergei F.

1991-01-01

Results are presented from a series of gravitational clustering simulations in two dimensions. These simulations are a significant departure from previous work, since in two dimensions one can have large dynamic range in both length scale and mass using present computer technology. Controlled experiments were conducted by varying the slope of power-law initial density fluctuation spectra and varying cutoffs at large k, while holding constant the phases of individual Fourier components and the scale of nonlinearity. Filaments are found in many different simulations, even with pure power-law initial conditions. By direct comparison, filaments, called 'second-generation pancakes' are shown to arise as a consequence of mild nonlinearity on scales much larger than the correlation length and are not relics of an initial lattice or due to sparse sampling of the Fourier components. Bumps of low amplitude in the two-point correlation are found to be generic but usually only statistical fluctuations. Power spectra are much easier to relate to initial conditions, and seem to follow a simple triangular shape (on log-log plot) in the nonlinear regime. The rms density fluctuation with Gaussian smoothing is the most stable indicator of nonlinearity.

Ensemble averaged structure–function relationship for nanocrystals: effective superparamagnetic Fe clusters with catalytically active Pt skin

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

Petkov, Valeri; Prasai, Binay; Shastri, Sarvjit

2017-09-12

Practical applications require the production and usage of metallic nanocrystals (NCs) in large ensembles. Besides, due to their cluster-bulk solid duality, metallic NCs exhibit a large degree of structural diversity. This poses the question as to what atomic-scale basis is to be used when the structure–function relationship for metallic NCs is to be quantified precisely. In this paper, we address the question by studying bi-functional Fe core-Pt skin type NCs optimized for practical applications. In particular, the cluster-like Fe core and skin-like Pt surface of the NCs exhibit superparamagnetic properties and a superb catalytic activity for the oxygen reduction reaction,more » respectively. We determine the atomic-scale structure of the NCs by non-traditional resonant high-energy X-ray diffraction coupled to atomic pair distribution function analysis. Using the experimental structure data we explain the observed magnetic and catalytic behavior of the NCs in a quantitative manner. Lastly, we demonstrate that NC ensemble-averaged 3D positions of atoms obtained by advanced X-ray scattering techniques are a very proper basis for not only establishing but also quantifying the structure–function relationship for the increasingly complex metallic NCs explored for practical applications.« 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.

Scalable NIC-based reduction on large-scale clusters

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

Moody, A.; Fernández, J. C.; Petrini, F.

2003-01-01

Many parallel algorithms require effiaent support for reduction mllectives. Over the years, researchers have developed optimal reduction algonduns by taking inm account system size, dam size, and complexities of reduction operations. However, all of these algorithm have assumed the faa that the reduction precessing takes place on the host CPU. Modem Network Interface Cards (NICs) sport programmable processors with substantial memory and thus introduce a fresh variable into the equation This raises the following intersting challenge: Can we take advantage of modern NICs to implementJost redudion operations? In this paper, we take on this challenge in the context of large-scalemore » clusters. Through experiments on the 960-node, 1920-processor or ASCI Linux Cluster (ALC) located at the Lawrence Livermore National Laboratory, we show that NIC-based reductions indeed perform with reduced latency and immed consistency over host-based aleorithms for the wmmon case and that these benefits scale as the system grows. In the largest configuration tested--1812 processors-- our NIC-based algorithm can sum a single element vector in 73 ps with 32-bi integers and in 118 with Mbit floating-point numnbers. These results represent an improvement, respeaively, of 121% and 39% with resvect w the {approx}roductionle vel MPI library« less

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.

Transport on percolation clusters with power-law distributed bond strengths.

PubMed

Alava, Mikko; Moukarzel, Cristian F

2003-05-01

The simplest transport problem, namely finding the maximum flow of current, or maxflow, is investigated on critical percolation clusters in two and three dimensions, using a combination of extremal statistics arguments and exact numerical computations, for power-law distributed bond strengths of the type P(sigma) approximately sigma(-alpha). Assuming that only cutting bonds determine the flow, the maxflow critical exponent v is found to be v(alpha)=(d-1)nu+1/(1-alpha). This prediction is confirmed with excellent accuracy using large-scale numerical simulation in two and three dimensions. However, in the region of anomalous bond capacity distributions (0< or =alpha< or =1) we demonstrate that, due to cluster-structure fluctuations, it is not the cutting bonds but the blobs that set the transport properties of the backbone. This "blob dominance" avoids a crossover to a regime where structural details, the distribution of the number of red or cutting bonds, would set the scaling. The restored scaling exponents, however, still follow the simplistic red bond estimate. This is argued to be due to the existence of a hierarchy of so-called minimum cut configurations, for which cutting bonds form the lowest level, and whose transport properties scale all in the same way. We point out the relevance of our findings to other scalar transport problems (i.e., conductivity).

Large-scale Filamentary Structures around the Virgo Cluster Revisited

NASA Astrophysics Data System (ADS)

Kim, Suk; Rey, Soo-Chang; Bureau, Martin; Yoon, Hyein; Chung, Aeree; Jerjen, Helmut; Lisker, Thorsten; Jeong, Hyunjin; Sung, Eon-Chang; Lee, Youngdae; Lee, Woong; Chung, Jiwon

2016-12-01

We revisit the filamentary structures of galaxies around the Virgo cluster, exploiting a larger data set, based on the HyperLeda database, than previous studies. In particular, this includes a large number of low-luminosity galaxies, resulting in better sampled individual structures. We confirm seven known structures in the distance range 4 h -1 Mpc < SGY < 16 h -1 Mpc, now identified as filaments, where SGY is the axis of the supergalactic coordinate system roughly along the line of sight. The Hubble diagram of the filament galaxies suggests they are infalling toward the main body of the Virgo cluster. We propose that the collinear distribution of giant elliptical galaxies along the fundamental axis of the Virgo cluster is smoothly connected to two of these filaments (Leo II A and B). Behind the Virgo cluster (16 h -1 Mpc < SGY < 27 h -1 Mpc), we also identify a new filament elongated toward the NGC 5353/4 group (“NGC 5353/4 filament”) and confirm a sheet that includes galaxies from the W and M clouds of the Virgo cluster (“W-M sheet”). In the Hubble diagram, the NGC 5353/4 filament galaxies show infall toward the NGC 5353/4 group, whereas the W-M sheet galaxies do not show hints of gravitational influence from the Virgo cluster. The filamentary structures identified can now be used to better understand the generic role of filaments in the build-up of galaxy clusters at z ≈ 0.

EClerize: A customized force-directed graph drawing algorithm for biological graphs with EC attributes.

PubMed

Danaci, Hasan Fehmi; Cetin-Atalay, Rengul; Atalay, Volkan

2018-03-26

Visualizing large-scale data produced by the high throughput experiments as a biological graph leads to better understanding and analysis. This study describes a customized force-directed layout algorithm, EClerize, for biological graphs that represent pathways in which the nodes are associated with Enzyme Commission (EC) attributes. The nodes with the same EC class numbers are treated as members of the same cluster. Positions of nodes are then determined based on both the biological similarity and the connection structure. EClerize minimizes the intra-cluster distance, that is the distance between the nodes of the same EC cluster and maximizes the inter-cluster distance, that is the distance between two distinct EC clusters. EClerize is tested on a number of biological pathways and the improvement brought in is presented with respect to the original algorithm. EClerize is available as a plug-in to cytoscape ( http://apps.cytoscape.org/apps/eclerize ).

Recombination-enhanced surface expansion of clusters in intense soft x-ray laser pulses

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

Rupp, Daniela; Flückiger, Leonie; Adolph, Marcus

Here, we studied the nanoplasma formation and explosion dynamics of single large xenon clusters in ultrashort, intense x-ray free-electron laser pulses via ion spectroscopy. The simultaneous measurement of single-shot diffraction images enabled a single-cluster analysis that is free from any averaging over the cluster size and laser intensity distributions. The measured charge state-resolved ion energy spectra show narrow distributions with peak positions that scale linearly with final ion charge state. These two distinct signatures are attributed to highly efficient recombination that eventually leads to the dominant formation of neutral atoms in the cluster. The measured mean ion energies exceed themore » value expected without recombination by more than an order of magnitude, indicating that the energy release resulting from electron-ion recombination constitutes a previously unnoticed nanoplasma heating process. This conclusion is supported by results from semiclassical molecular dynamics simulations.« less

Gaussian mixture clustering and imputation of microarray data.

PubMed

Ouyang, Ming; Welsh, William J; Georgopoulos, Panos

2004-04-12

In microarray experiments, missing entries arise from blemishes on the chips. In large-scale studies, virtually every chip contains some missing entries and more than 90% of the genes are affected. Many analysis methods require a full set of data. Either those genes with missing entries are excluded, or the missing entries are filled with estimates prior to the analyses. This study compares methods of missing value estimation. Two evaluation metrics of imputation accuracy are employed. First, the root mean squared error measures the difference between the true values and the imputed values. Second, the number of mis-clustered genes measures the difference between clustering with true values and that with imputed values; it examines the bias introduced by imputation to clustering. The Gaussian mixture clustering with model averaging imputation is superior to all other imputation methods, according to both evaluation metrics, on both time-series (correlated) and non-time series (uncorrelated) data sets.

Recombination-enhanced surface expansion of clusters in intense soft x-ray laser pulses

DOE PAGES

Rupp, Daniela; Flückiger, Leonie; Adolph, Marcus; ...

2016-10-07

Here, we studied the nanoplasma formation and explosion dynamics of single large xenon clusters in ultrashort, intense x-ray free-electron laser pulses via ion spectroscopy. The simultaneous measurement of single-shot diffraction images enabled a single-cluster analysis that is free from any averaging over the cluster size and laser intensity distributions. The measured charge state-resolved ion energy spectra show narrow distributions with peak positions that scale linearly with final ion charge state. These two distinct signatures are attributed to highly efficient recombination that eventually leads to the dominant formation of neutral atoms in the cluster. The measured mean ion energies exceed themore » value expected without recombination by more than an order of magnitude, indicating that the energy release resulting from electron-ion recombination constitutes a previously unnoticed nanoplasma heating process. This conclusion is supported by results from semiclassical molecular dynamics simulations.« less

Statistical Measures of Large-Scale Structure

NASA Astrophysics Data System (ADS)

Vogeley, Michael; Geller, Margaret; Huchra, John; Park, Changbom; Gott, J. Richard

1993-12-01

\\inv Mpc} To quantify clustering in the large-scale distribution of galaxies and to test theories for the formation of structure in the universe, we apply statistical measures to the CfA Redshift Survey. This survey is complete to m_{B(0)}=15.5 over two contiguous regions which cover one-quarter of the sky and include ~ 11,000 galaxies. The salient features of these data are voids with diameter 30-50\\hmpc and coherent dense structures with a scale ~ 100\\hmpc. Comparison with N-body simulations rules out the ``standard" CDM model (Omega =1, b=1.5, sigma_8 =1) at the 99% confidence level because this model has insufficient power on scales lambda >30\\hmpc. An unbiased open universe CDM model (Omega h =0.2) and a biased CDM model with non-zero cosmological constant (Omega h =0.24, lambda_0 =0.6) match the observed power spectrum. The amplitude of the power spectrum depends on the luminosity of galaxies in the sample; bright (L>L(*) ) galaxies are more strongly clustered than faint galaxies. The paucity of bright galaxies in low-density regions may explain this dependence. To measure the topology of large-scale structure, we compute the genus of isodensity surfaces of the smoothed density field. On scales in the ``non-linear" regime, <= 10\\hmpc, the high- and low-density regions are multiply-connected over a broad range of density threshold, as in a filamentary net. On smoothing scales >10\\hmpc, the topology is consistent with statistics of a Gaussian random field. Simulations of CDM models fail to produce the observed coherence of structure on non-linear scales (>95% confidence level). The underdensity probability (the frequency of regions with density contrast delta rho //lineρ=-0.8) depends strongly on the luminosity of galaxies; underdense regions are significantly more common (>2sigma ) in bright (L>L(*) ) galaxy samples than in samples which include fainter galaxies.

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.

Large-scale seismic waveform quality metric calculation using Hadoop

DOE PAGES

Magana-Zook, Steven; Gaylord, Jessie M.; Knapp, Douglas R.; ...

2016-05-27

Here in this work we investigated the suitability of Hadoop MapReduce and Apache Spark for large-scale computation of seismic waveform quality metrics by comparing their performance with that of a traditional distributed implementation. The Incorporated Research Institutions for Seismology (IRIS) Data Management Center (DMC) provided 43 terabytes of broadband waveform data of which 5.1 TB of data were processed with the traditional architecture, and the full 43 TB were processed using MapReduce and Spark. Maximum performance of ~0.56 terabytes per hour was achieved using all 5 nodes of the traditional implementation. We noted that I/O dominated processing, and that I/Omore » performance was deteriorating with the addition of the 5th node. Data collected from this experiment provided the baseline against which the Hadoop results were compared. Next, we processed the full 43 TB dataset using both MapReduce and Apache Spark on our 18-node Hadoop cluster. We conducted these experiments multiple times with various subsets of the data so that we could build models to predict performance as a function of dataset size. We found that both MapReduce and Spark significantly outperformed the traditional reference implementation. At a dataset size of 5.1 terabytes, both Spark and MapReduce were about 15 times faster than the reference implementation. Furthermore, our performance models predict that for a dataset of 350 terabytes, Spark running on a 100-node cluster would be about 265 times faster than the reference implementation. We do not expect that the reference implementation deployed on a 100-node cluster would perform significantly better than on the 5-node cluster because the I/O performance cannot be made to scale. Finally, we note that although Big Data technologies clearly provide a way to process seismic waveform datasets in a high-performance and scalable manner, the technology is still rapidly changing, requires a high degree of investment in personnel, and will likely require significant changes in other parts of our infrastructure. Nevertheless, we anticipate that as the technology matures and third-party tool vendors make it easier to manage and operate clusters, Hadoop (or a successor) will play a large role in our seismic data processing.« less

Large-scale seismic waveform quality metric calculation using Hadoop

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

Magana-Zook, Steven; Gaylord, Jessie M.; Knapp, Douglas R.

Here in this work we investigated the suitability of Hadoop MapReduce and Apache Spark for large-scale computation of seismic waveform quality metrics by comparing their performance with that of a traditional distributed implementation. The Incorporated Research Institutions for Seismology (IRIS) Data Management Center (DMC) provided 43 terabytes of broadband waveform data of which 5.1 TB of data were processed with the traditional architecture, and the full 43 TB were processed using MapReduce and Spark. Maximum performance of ~0.56 terabytes per hour was achieved using all 5 nodes of the traditional implementation. We noted that I/O dominated processing, and that I/Omore » performance was deteriorating with the addition of the 5th node. Data collected from this experiment provided the baseline against which the Hadoop results were compared. Next, we processed the full 43 TB dataset using both MapReduce and Apache Spark on our 18-node Hadoop cluster. We conducted these experiments multiple times with various subsets of the data so that we could build models to predict performance as a function of dataset size. We found that both MapReduce and Spark significantly outperformed the traditional reference implementation. At a dataset size of 5.1 terabytes, both Spark and MapReduce were about 15 times faster than the reference implementation. Furthermore, our performance models predict that for a dataset of 350 terabytes, Spark running on a 100-node cluster would be about 265 times faster than the reference implementation. We do not expect that the reference implementation deployed on a 100-node cluster would perform significantly better than on the 5-node cluster because the I/O performance cannot be made to scale. Finally, we note that although Big Data technologies clearly provide a way to process seismic waveform datasets in a high-performance and scalable manner, the technology is still rapidly changing, requires a high degree of investment in personnel, and will likely require significant changes in other parts of our infrastructure. Nevertheless, we anticipate that as the technology matures and third-party tool vendors make it easier to manage and operate clusters, Hadoop (or a successor) will play a large role in our seismic data processing.« less

Large-scale velocities and primordial non-Gaussianity

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

Schmidt, Fabian

2010-09-15

We study the peculiar velocities of density peaks in the presence of primordial non-Gaussianity. Rare, high-density peaks in the initial density field can be identified with tracers such as galaxies and clusters in the evolved matter distribution. The distribution of relative velocities of peaks is derived in the large-scale limit using two different approaches based on a local biasing scheme. Both approaches agree, and show that halos still stream with the dark matter locally as well as statistically, i.e. they do not acquire a velocity bias. Nonetheless, even a moderate degree of (not necessarily local) non-Gaussianity induces a significant skewnessmore » ({approx}0.1-0.2) in the relative velocity distribution, making it a potentially interesting probe of non-Gaussianity on intermediate to large scales. We also study two-point correlations in redshift space. The well-known Kaiser formula is still a good approximation on large scales, if the Gaussian halo bias is replaced with its (scale-dependent) non-Gaussian generalization. However, there are additional terms not encompassed by this simple formula which become relevant on smaller scales (k > or approx. 0.01h/Mpc). Depending on the allowed level of non-Gaussianity, these could be of relevance for future large spectroscopic surveys.« less

The LAMAR: A high throughput X-ray astronomy facility for a moderate cost mission

NASA Technical Reports Server (NTRS)

Gorenstein, P.; Schwartz, D.

1981-01-01

The performance of a large area modular array of reflectors (LAMAR) is considered in several hypothetical observations relevant to: (1) cosmology, the X-ray background, and large scale structure of the universe; (2) clusters of galaxies and their evolution; (3) quasars and other active galactic nuclei; (4) compact objects in our galaxy; (5) stellar coronae; and (6) energy input to the interstellar medium.

A cloud-based framework for large-scale traditional Chinese medical record retrieval.

PubMed

Liu, Lijun; Liu, Li; Fu, Xiaodong; Huang, Qingsong; Zhang, Xianwen; Zhang, Yin

2018-01-01

Electronic medical records are increasingly common in medical practice. The secondary use of medical records has become increasingly important. It relies on the ability to retrieve the complete information about desired patient populations. How to effectively and accurately retrieve relevant medical records from large- scale medical big data is becoming a big challenge. Therefore, we propose an efficient and robust framework based on cloud for large-scale Traditional Chinese Medical Records (TCMRs) retrieval. We propose a parallel index building method and build a distributed search cluster, the former is used to improve the performance of index building, and the latter is used to provide high concurrent online TCMRs retrieval. Then, a real-time multi-indexing model is proposed to ensure the latest relevant TCMRs are indexed and retrieved in real-time, and a semantics-based query expansion method and a multi- factor ranking model are proposed to improve retrieval quality. Third, we implement a template-based visualization method for displaying medical reports. The proposed parallel indexing method and distributed search cluster can improve the performance of index building and provide high concurrent online TCMRs retrieval. The multi-indexing model can ensure the latest relevant TCMRs are indexed and retrieved in real-time. The semantics expansion method and the multi-factor ranking model can enhance retrieval quality. The template-based visualization method can enhance the availability and universality, where the medical reports are displayed via friendly web interface. In conclusion, compared with the current medical record retrieval systems, our system provides some advantages that are useful in improving the secondary use of large-scale traditional Chinese medical records in cloud environment. The proposed system is more easily integrated with existing clinical systems and be used in various scenarios. Copyright © 2017. Published by Elsevier Inc.

Probing Inflation Using Galaxy Clustering On Ultra-Large Scales

NASA Astrophysics Data System (ADS)

Dalal, Roohi; de Putter, Roland; Dore, Olivier

2018-01-01

A detailed understanding of curvature perturbations in the universe is necessary to constrain theories of inflation. In particular, measurements of the local non-gaussianity parameter, flocNL, enable us to distinguish between two broad classes of inflationary theories, single-field and multi-field inflation. While most single-field theories predict flocNL ≈ ‑5/12 (ns -1), in multi-field theories, flocNL is not constrained to this value and is allowed to be observably large. Achieving σ(flocNL) = 1 would give us discovery potential for detecting multi-field inflation, while finding flocNL=0 would rule out a good fraction of interesting multi-field models. We study the use of galaxy clustering on ultra-large scales to achieve this level of constraint on flocNL. Upcoming surveys such as Euclid and LSST will give us galaxy catalogs from which we can construct the galaxy power spectrum and hence infer a value of flocNL. We consider two possible methods of determining the galaxy power spectrum from a catalog of galaxy positions: the traditional Feldman Kaiser Peacock (FKP) Power Spectrum Estimator, and an Optimal Quadratic Estimator (OQE). We implemented and tested each method using mock galaxy catalogs, and compared the resulting constraints on flocNL. We find that the FKP estimator can measure flocNL in an unbiased way, but there remains room for improvement in its precision. We also find that the OQE is not computationally fast, but remains a promising option due to its ability to isolate the power spectrum at large scales. We plan to extend this research to study alternative methods, such as pixel-based likelihood functions. We also plan to study the impact of general relativistic effects at these scales on our ability to measure flocNL.

Test of Gravity on Large Scales with Weak Gravitational Lensing and Clustering Measurements of SDSS Luminous Red Galaxies

NASA Astrophysics Data System (ADS)

Reyes, Reinabelle; Mandelbaum, R.; Seljak, U.; Gunn, J.; Lombriser, L.

2009-01-01

We perform a test of gravity on large scales (5-50 Mpc/h) using 70,000 luminous red galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS) DR7 with redshifts 0.16

Massive gravity wrapped in the cosmic web

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

Shim, Junsup; Lee, Jounghun; Li, Baojiu, E-mail: jsshim@astro.snu.ac.kr, E-mail: jounghun@astro.snu.ac.kr

We study how the filamentary pattern of the cosmic web changes if the true gravity deviates from general relativity (GR) on a large scale. The f(R) gravity, whose strength is controlled to satisfy the current observational constraints on the cluster scale, is adopted as our fiducial model and a large, high-resolution N-body simulation is utilized for this study. By applying the minimal spanning tree algorithm to the halo catalogs from the simulation at various epochs, we identify the main stems of the rich superclusters located in the most prominent filamentary section of the cosmic web and determine their spatial extentsmore » per member cluster to be the degree of their straightness. It is found that the f(R) gravity has the effect of significantly bending the superclusters and that the effect becomes stronger as the universe evolves. Even in the case where the deviation from GR is too small to be detectable by any other observables, the degree of the supercluster straightness exhibits a conspicuous difference between the f(R) and the GR models. Our results also imply that the supercluster straightness could be a useful discriminator of f(R) gravity from the coupled dark energy since it is shown to evolve differently between the two models. As a final conclusion, the degree of the straightness of the rich superclusters should provide a powerful cosmological test of large scale gravity.« less

Background Noises Versus Intraseasonal Variation Signals: Small vs. Large Convective Cloud Objects From CERES Aqua Observations

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2015-01-01

During inactive phases of Madden-Julian Oscillation (MJO), there are plenty of deep but small convective systems and far fewer deep and large ones. During active phases of MJO, a manifestation of an increase in the occurrence of large and deep cloud clusters results from an amplification of large-scale motions by stronger convective heating. This study is designed to quantitatively examine the roles of small and large cloud clusters during the MJO life cycle. We analyze the cloud object data from Aqua CERES (Clouds and the Earth's Radiant Energy System) observations between July 2006 and June 2010 for tropical deep convective (DC) and cirrostratus (CS) cloud object types according to the real-time multivariate MJO index, which assigns the tropics to one of the eight MJO phases each day. The cloud object is a contiguous region of the earth with a single dominant cloud-system type. The criteria for defining these cloud types are overcast footprints and cloud top pressures less than 400 hPa, but DC has higher cloud optical depths (=10) than those of CS (<10). The size distributions, defined as the footprint numbers as a function of cloud object diameters, for particular MJO phases depart greatly from the combined (8-phase) distribution at large cloud-object diameters due to the reduced/increased numbers of cloud objects related to changes in the large-scale environments. The medium diameter corresponding to the combined distribution is determined and used to partition all cloud objects into "small" and "large" groups of a particular phase. The two groups corresponding to the combined distribution have nearly equal numbers of footprints. The medium diameters are 502 km for DC and 310 km for cirrostratus. The range of the variation between two extreme phases (typically, the most active and depressed phases) for the small group is 6-11% in terms of the numbers of cloud objects and the total footprint numbers. The corresponding range for the large group is 19-44%. In terms of the probability density functions of radiative and cloud physical properties, there are virtually no differences between the MJO phases for the small group, but there are significant differences for the large groups for both DC and CS types. These results suggest that the intreseasonal variation signals reside at the large cloud clusters while the small cloud clusters represent the background noises resulting from various types of the tropical waves with different wavenumbers and propagation speeds/directions.

First evidence of diffuse ultra-steep-spectrum radio emission surrounding the cool core of a cluster

NASA Astrophysics Data System (ADS)

Savini, F.; Bonafede, A.; Brüggen, M.; van Weeren, R.; Brunetti, G.; Intema, H.; Botteon, A.; Shimwell, T.; Wilber, A.; Rafferty, D.; Giacintucci, S.; Cassano, R.; Cuciti, V.; de Gasperin, F.; Röttgering, H.; Hoeft, M.; White, G.

2018-05-01

Diffuse synchrotron radio emission from cosmic-ray electrons is observed at the center of a number of galaxy clusters. These sources can be classified either as giant radio halos, which occur in merging clusters, or as mini halos, which are found only in cool-core clusters. In this paper, we present the first discovery of a cool-core cluster with an associated mini halo that also shows ultra-steep-spectrum emission extending well beyond the core that resembles radio halo emission. The large-scale component is discovered thanks to LOFAR observations at 144 MHz. We also analyse GMRT observations at 610 MHz to characterise the spectrum of the radio emission. An X-ray analysis reveals that the cluster is slightly disturbed, and we suggest that the steep-spectrum radio emission outside the core could be produced by a minor merger that powers electron re-acceleration without disrupting the cool core. This discovery suggests that, under particular circumstances, both a mini and giant halo could co-exist in a single cluster, opening new perspectives for particle acceleration mechanisms in galaxy clusters.