Sample records for dynamic cluster models

  1. Validating clustering of molecular dynamics simulations using polymer models.

    PubMed

    Phillips, Joshua L; Colvin, Michael E; Newsam, Shawn

    2011-11-14

    Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers.

  2. Validating clustering of molecular dynamics simulations using polymer models

    PubMed Central

    2011-01-01

    Background Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers. PMID:22082218

  3. Lifetime of Major Histocompatibility Complex Class-I Membrane Clusters Is Controlled by the Actin Cytoskeleton

    PubMed Central

    Lavi, Yael; Gov, Nir; Edidin, Michael; Gheber, Levi A.

    2012-01-01

    Lateral heterogeneity of cell membranes has been demonstrated in numerous studies showing anomalous diffusion of membrane proteins; it has been explained by models and experiments suggesting dynamic barriers to free diffusion, that temporarily confine membrane proteins into microscopic patches. This picture, however, comes short of explaining a steady-state patchy distribution of proteins, in face of the transient opening of the barriers. In our previous work we directly imaged persistent clusters of MHC-I, a type I transmembrane protein, and proposed a model of a dynamic equilibrium between proteins newly delivered to the cell surface by vesicle traffic, temporary confinement by dynamic barriers to lateral diffusion, and dispersion of the clusters by diffusion over the dynamic barriers. Our model predicted that the clusters are dynamic, appearing when an exocytic vesicle fuses with the plasma membrane and dispersing with a typical lifetime that depends on lateral diffusion and the dynamics of barriers. In a subsequent work, we showed this to be the case. Here we test another prediction of the model, and show that changing the stability of actin barriers to lateral diffusion changes cluster lifetimes. We also develop a model for the distribution of cluster lifetimes, consistent with the function of barriers to lateral diffusion in maintaining MHC-I clusters. PMID:22500754

  4. Exploring the Internal Dynamics of Globular Clusters

    NASA Astrophysics Data System (ADS)

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

    2018-01-01

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

  5. Clustering promotes switching dynamics in networks of noisy neurons

    NASA Astrophysics Data System (ADS)

    Franović, Igor; Klinshov, Vladimir

    2018-02-01

    Macroscopic variability is an emergent property of neural networks, typically manifested in spontaneous switching between the episodes of elevated neuronal activity and the quiescent episodes. We investigate the conditions that facilitate switching dynamics, focusing on the interplay between the different sources of noise and heterogeneity of the network topology. We consider clustered networks of rate-based neurons subjected to external and intrinsic noise and derive an effective model where the network dynamics is described by a set of coupled second-order stochastic mean-field systems representing each of the clusters. The model provides an insight into the different contributions to effective macroscopic noise and qualitatively indicates the parameter domains where switching dynamics may occur. By analyzing the mean-field model in the thermodynamic limit, we demonstrate that clustering promotes multistability, which gives rise to switching dynamics in a considerably wider parameter region compared to the case of a non-clustered network with sparse random connection topology.

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

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

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

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

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

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

    PubMed Central

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

    2014-01-01

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

  9. Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory

    NASA Astrophysics Data System (ADS)

    Jensen, Christian H.; Nerukh, Dmitry; Glen, Robert C.

    2008-03-01

    We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.

  10. Testing modified gravity with globular clusters: the case of NGC 2419

    NASA Astrophysics Data System (ADS)

    Llinares, Claudio

    2018-05-01

    The dynamics of globular clusters has been studied in great detail in the context of general relativity as well as with modifications of gravity that strongly depart from the standard paradigm such as Modified Newtonian Dynamics. However, at present there are no studies that aim to test the impact that less extreme modifications of gravity (e.g. models constructed as alternatives to dark energy) have on the behaviour of globular clusters. This Letter presents fits to the velocity dispersion profile of the cluster NGC 2419 under the symmetron-modified gravity model. The data show an increase in the velocity dispersion towards the centre of the cluster which could be difficult to explain within general relativity. By finding the best-fitting solution associated with the symmetron model, we show that this tension does not exist in modified gravity. However, the best-fitting parameters give a model that is inconsistent with the dynamics of the Solar system. Exploration of different screening mechanisms should give us the chance to understand if it is possible to maintain the appealing properties of the symmetron model when it comes to globular clusters and at the same time recover the Solar system dynamics properly.

  11. Dynamic Evolution Model Based on Social Network Services

    NASA Astrophysics Data System (ADS)

    Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen

    2013-11-01

    Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.

  12. Dynamic Fuzzy Model Development for a Drum-type Boiler-turbine Plant Through GK Clustering

    NASA Astrophysics Data System (ADS)

    Habbi, Ahcène; Zelmat, Mimoun

    2008-10-01

    This paper discusses a TS fuzzy model identification method for an industrial drum-type boiler plant using the GK fuzzy clustering approach. The fuzzy model is constructed from a set of input-output data that covers a wide operating range of the physical plant. The reference data is generated using a complex first-principle-based mathematical model that describes the key dynamical properties of the boiler-turbine dynamics. The proposed fuzzy model is derived by means of fuzzy clustering method with particular attention on structure flexibility and model interpretability issues. This may provide a basement of a new way to design model based control and diagnosis mechanisms for the complex nonlinear plant.

  13. Cluster growth mechanisms in Lennard-Jones fluids: A comparison between molecular dynamics and Brownian dynamics simulations

    NASA Astrophysics Data System (ADS)

    Jung, Jiyun; Lee, Jumin; Kim, Jun Soo

    2015-03-01

    We present a simulation study on the mechanisms of a phase separation in dilute fluids of Lennard-Jones (LJ) particles as a model of self-interacting molecules. Molecular dynamics (MD) and Brownian dynamics (BD) simulations of the LJ fluids are employed to model the condensation of a liquid droplet in the vapor phase and the mesoscopic aggregation in the solution phase, respectively. With emphasis on the cluster growth at late times well beyond the nucleation stage, we find that the growth mechanisms can be qualitatively different: cluster diffusion and coalescence in the MD simulations and Ostwald ripening in the BD simulations. We also show that the rates of the cluster growth have distinct scaling behaviors during cluster growth. This work suggests that in the solution phase the random Brownian nature of the solute dynamics may lead to the Ostwald ripening that is qualitatively different from the cluster coalescence in the vapor phase.

  14. Cluster dynamics and cluster size distributions in systems of self-propelled particles

    NASA Astrophysics Data System (ADS)

    Peruani, F.; Schimansky-Geier, L.; Bär, M.

    2010-12-01

    Systems of self-propelled particles (SPP) interacting by a velocity alignment mechanism in the presence of noise exhibit rich clustering dynamics. Often, clusters are responsible for the distribution of (local) information in these systems. Here, we investigate the properties of individual clusters in SPP systems, in particular the asymmetric spreading behavior of clusters with respect to their direction of motion. In addition, we formulate a Smoluchowski-type kinetic model to describe the evolution of the cluster size distribution (CSD). This model predicts the emergence of steady-state CSDs in SPP systems. We test our theoretical predictions in simulations of SPP with nematic interactions and find that our simple kinetic model reproduces qualitatively the transition to aggregation observed in simulations.

  15. Exploring the Dynamics of Exoplanetary Systems in a Young Stellar Cluster

    NASA Astrophysics Data System (ADS)

    Thornton, Jonathan Daniel; Glaser, Joseph Paul; Wall, Joshua Edward

    2018-01-01

    I describe a dynamical simulation of planetary systems in a young star cluster. One rather arbitrary aspect of cluster simulations is the choice of initial conditions. These are typically chosen from some standard model, such as Plummer or King, or from a “fractal” distribution to try to model young clumpy systems. Here I adopt the approach of realizing an initial cluster model directly from a detailed magnetohydrodynamical model of cluster formation from a 1000-solar-mass interstellar gas cloud, with magnetic fields and radiative and wind feedback from massive stars included self-consistently. The N-body simulation of the stars and planets starts once star formation is largely over and feedback has cleared much of the gas from the region where the newborn stars reside. It continues until the cluster dissolves in the galactic field. Of particular interest is what would happen to the free-floating planets created in the gas cloud simulation. Are they captured by a star or are they ejected from the cluster? This method of building a dynamical cluster simulation directly from the results of a cluster formation model allows us to better understand the evolution of young star clusters and enriches our understanding of extrasolar planet development in them. These simulations were performed within the AMUSE simulation framework, and combine N-body, multiples and background potential code.

  16. Simulating star clusters with the AMUSE software framework. I. Dependence of cluster lifetimes on model assumptions and cluster dissolution modes

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

    Whitehead, Alfred J.; McMillan, Stephen L. W.; Vesperini, Enrico

    2013-12-01

    We perform a series of simulations of evolving star clusters using the Astrophysical Multipurpose Software Environment (AMUSE), a new community-based multi-physics simulation package, and compare our results to existing work. These simulations model a star cluster beginning with a King model distribution and a selection of power-law initial mass functions and contain a tidal cutoff. They are evolved using collisional stellar dynamics and include mass loss due to stellar evolution. After studying and understanding that the differences between AMUSE results and results from previous studies are understood, we explored the variation in cluster lifetimes due to the random realization noisemore » introduced by transforming a King model to specific initial conditions. This random realization noise can affect the lifetime of a simulated star cluster by up to 30%. Two modes of star cluster dissolution were identified: a mass evolution curve that contains a runaway cluster dissolution with a sudden loss of mass, and a dissolution mode that does not contain this feature. We refer to these dissolution modes as 'dynamical' and 'relaxation' dominated, respectively. For Salpeter-like initial mass functions, we determined the boundary between these two modes in terms of the dynamical and relaxation timescales.« less

  17. Dynamical Formation of Low-mass Merging Black Hole Binaries like GW151226

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

    Chatterjee, Sourav; Rodriguez, Carl L.; Kalogera, Vicky

    2017-02-20

    Using numerical models for star clusters spanning a wide range in ages and metallicities (Z) we study the masses of binary black holes (BBHs) produced dynamically and merging in the local universe ( z ≲ 0.2). After taking into account cosmological constraints on star formation rate and metallicity evolution, which realistically relate merger delay times obtained from models with merger redshifts, we show here for the first time that while old, metal-poor globular clusters can naturally produce merging BBHs with heavier components, as observed in GW150914, lower-mass BBHs like GW151226 are easily formed dynamically in younger, higher-metallicity clusters. More specifically,more » we show that the mass of GW151226 is well within 1 σ of the mass distribution obtained from our models for clusters with Z/Z{sub ⊙} ≳ 0.5. Indeed, dynamical formation of a system like GW151226 likely requires a cluster that is younger and has a higher metallicity than typical Galactic globular clusters. The LVT151012 system, if real, could have been created in any cluster with Z/Z{sub ⊙} ≲ 0.25. On the other hand, GW150914 is more massive (beyond 1 σ ) than typical BBHs from even the lowest-metallicity (Z/Z{sub ⊙} = 0.005) clusters we consider, but is within 2 σ of the intrinsic mass distribution from our cluster models with Z/Z{sub ⊙} ≲ 0.05; of course, detection biases also push the observed distributions toward higher masses.« less

  18. A dynamical study of Galactic globular clusters under different relaxation conditions

    NASA Astrophysics Data System (ADS)

    Zocchi, A.; Bertin, G.; Varri, A. L.

    2012-03-01

    Aims: We perform a systematic combined photometric and kinematic analysis of a sample of globular clusters under different relaxation conditions, based on their core relaxation time (as listed in available catalogs), by means of two well-known families of spherical stellar dynamical models. Systems characterized by shorter relaxation time scales are expected to be better described by isotropic King models, while less relaxed systems might be interpreted by means of non-truncated, radially-biased anisotropic f(ν) models, originally designed to represent stellar systems produced by a violent relaxation formation process and applied here for the first time to the study of globular clusters. Methods: The comparison between dynamical models and observations is performed by fitting simultaneously surface brightness and velocity dispersion profiles. For each globular cluster, the best-fit model in each family is identified, along with a full error analysis on the relevant parameters. Detailed structural properties and mass-to-light ratios are also explicitly derived. Results: We find that King models usually offer a good representation of the observed photometric profiles, but often lead to less satisfactory fits to the kinematic profiles, independently of the relaxation condition of the systems. For some less relaxed clusters, f(ν) models provide a good description of both observed profiles. Some derived structural characteristics, such as the total mass or the half-mass radius, turn out to be significantly model-dependent. The analysis confirms that, to answer some important dynamical questions that bear on the formation and evolution of globular clusters, it would be highly desirable to acquire larger numbers of accurate kinematic data-points, well distributed over the cluster field. Appendices are available in electronic form at http://www.aanda.org

  19. Control of clustered action potential firing in a mathematical model of entorhinal cortex stellate cells.

    PubMed

    Tait, Luke; Wedgwood, Kyle; Tsaneva-Atanasova, Krasimira; Brown, Jon T; Goodfellow, Marc

    2018-07-14

    The entorhinal cortex is a crucial component of our memory and spatial navigation systems and is one of the first areas to be affected in dementias featuring tau pathology, such as Alzheimer's disease and frontotemporal dementia. Electrophysiological recordings from principle cells of medial entorhinal cortex (layer II stellate cells, mEC-SCs) demonstrate a number of key identifying properties including subthreshold oscillations in the theta (4-12 Hz) range and clustered action potential firing. These single cell properties are correlated with network activity such as grid firing and coupling between theta and gamma rhythms, suggesting they are important for spatial memory. As such, experimental models of dementia have revealed disruption of organised dorsoventral gradients in clustered action potential firing. To better understand the mechanisms underpinning these different dynamics, we study a conductance based model of mEC-SCs. We demonstrate that the model, driven by extrinsic noise, can capture quantitative differences in clustered action potential firing patterns recorded from experimental models of tau pathology and healthy animals. The differential equation formulation of our model allows us to perform numerical bifurcation analyses in order to uncover the dynamic mechanisms underlying these patterns. We show that clustered dynamics can be understood as subcritical Hopf/homoclinic bursting in a fast-slow system where the slow sub-system is governed by activation of the persistent sodium current and inactivation of the slow A-type potassium current. In the full system, we demonstrate that clustered firing arises via flip bifurcations as conductance parameters are varied. Our model analyses confirm the experimentally suggested hypothesis that the breakdown of clustered dynamics in disease occurs via increases in AHP conductance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. A model of metastable dynamics during ongoing and evoked cortical activity

    NASA Astrophysics Data System (ADS)

    La Camera, Giancarlo

    The dynamics of simultaneously recorded spike trains in alert animals often evolve through temporal sequences of metastable states. Little is known about the network mechanisms responsible for the genesis of such sequences, or their potential role in neural coding. In the gustatory cortex of alert rates, state sequences can be observed also in the absence of overt sensory stimulation, and thus form the basis of the so-called `ongoing activity'. This activity is characterized by a partial degree of coordination among neurons, sharp transitions among states, and multi-stability of single neurons' firing rates. A recurrent spiking network model with clustered topology can account for both the spontaneous generation of state sequences and the (network-generated) multi-stability. In the model, each network state results from the activation of specific neural clusters with potentiated intra-cluster connections. A mean field solution of the model shows a large number of stable states, each characterized by a subset of simultaneously active clusters. The firing rate in each cluster during ongoing activity depends on the number of active clusters, so that the same neuron can have different firing rates depending on the state of the network. Because of dense intra-cluster connectivity and recurrent inhibition, in finite networks the stable states lose stability due to finite size effects. Simulations of the dynamics show that the model ensemble activity continuously hops among the different states, reproducing the ongoing dynamics observed in the data. Moreover, when probed with external stimuli, the model correctly predicts the quenching of single neuron multi-stability into bi-stability, the reduction of dimensionality of the population activity, the reduction of trial-to-trial variability, and a potential role for metastable states in the anticipation of expected events. Altogether, these results provide a unified mechanistic model of ongoing and evoked cortical dynamics. NSF IIS-1161852, NIDCD K25-DC013557, NIDCD R01-DC010389.

  1. Modeling Dynamic Regulatory Processes in Stroke.

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

    McDermott, Jason E.; Jarman, Kenneth D.; Taylor, Ronald C.

    2012-10-11

    The ability to examine in silico the behavior of biological systems can greatly accelerate the pace of discovery in disease pathologies, such as stroke, where in vivo experimentation is lengthy and costly. In this paper we describe an approach to in silico examination of blood genomic responses to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) relating regulators and functional clusters from the data. These ODEs were used to developmore » dynamic models that simulate the expression of regulated functional clusters using system dynamics as the modeling paradigm. The dynamic model has the considerable advantage of only requiring an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. The manipulation of input model parameters, such as changing the magnitude of gene expression, made it possible to assess the behavior of the networks through time under varying conditions. We report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different preconditioning paradigms.« less

  2. Experimental and theoretical investigation of the magnetization dynamics of an artificial square spin ice cluster

    NASA Astrophysics Data System (ADS)

    Pohlit, Merlin; Stockem, Irina; Porrati, Fabrizio; Huth, Michael; Schröder, Christian; Müller, Jens

    2016-10-01

    We study the magnetization dynamics of a spin ice cluster which is a building block of an artificial square spin ice fabricated by focused electron-beam-induced deposition both experimentally and theoretically. The spin ice cluster is composed of twelve interacting Co nanoislands grown directly on top of a high-resolution micro-Hall sensor. By employing micromagnetic simulations and a macrospin model, we calculate the magnetization and the experimentally investigated stray field emanating from a single nanoisland. The parameters determined from a comparison with the experimental hysteresis loop are used to derive an effective single-dipole macrospin model that allows us to investigate the dynamics of the spin ice cluster. Our model reproduces the experimentally observed non-deterministic sequences in the magnetization curves as well as the distinct temperature dependence of the hysteresis loop.

  3. The relation between the mass-to-light ratio and the relaxation state of globular clusters

    NASA Astrophysics Data System (ADS)

    Bianchini, P.; Sills, A.; van de Ven, G.; Sippel, A. C.

    2017-08-01

    The internal dynamics of globular clusters (GCs) is strongly affected by two-body interactions that bring the systems to a state of partial energy equipartition. Using a set of Monte Carlo clusters simulations, we investigate the role of the onset of energy equipartition in shaping the mass-to-light ratio (M/L) in GCs. Our simulations show that the M/L profiles cannot be considered constant and their specific shape strongly depends on the dynamical age of the clusters. Dynamically younger clusters display a central peak up to M/L ≃ 25 M⊙/L⊙ caused by the retention of dark remnants; this peak flattens out for dynamically older clusters. Moreover, we find that also the global values of M/L correlate with the dynamical state of a cluster quantified as either the number of relaxation times a system has experienced nrel or the equipartition parameter meq: clusters closer to full equipartition (higher nrel or lower meq) display a lower M/L. We show that the decrease of M/L is primarily driven by the dynamical ejection of dark remnants, rather than by the escape of low-mass stars. The predictions of our models are in good agreement with observations of GCs in the Milky Way and M31, indicating that differences in relaxation state alone can explain variations of M/L up to a factor of ≃3. Our characterization of the M/L as a function of relaxation state is of primary relevance for the application and interpretation of dynamical models.

  4. Observing the clustering properties of galaxy clusters in dynamical dark-energy cosmologies

    NASA Astrophysics Data System (ADS)

    Fedeli, C.; Moscardini, L.; Bartelmann, M.

    2009-06-01

    We study the clustering properties of galaxy clusters expected to be observed by various forthcoming surveys both in the X-ray and sub-mm regimes by the thermal Sunyaev-Zel'dovich effect. Several different background cosmological models are assumed, including the concordance ΛCDM and various cosmologies with dynamical evolution of the dark energy. Particular attention is paid to models with a significant contribution of dark energy at early times which affects the process of structure formation. Past light cone and selection effects in cluster catalogs are carefully modeled by realistic scaling relations between cluster mass and observables and by properly taking into account the selection functions of the different instruments. The results show that early dark-energy models are expected to produce significantly lower values of effective bias and both spatial and angular correlation amplitudes with respect to the standard ΛCDM model. Among the cluster catalogs studied in this work, it turns out that those based on eRosita, Planck, and South Pole Telescope observations are the most promising for distinguishing between various dark-energy models.

  5. Observing Stellar Clusters in the Computer

    NASA Astrophysics Data System (ADS)

    Borch, A.; Spurzem, R.; Hurley, J.

    2006-08-01

    We present a new approach to combine direct N-body simulations to stellar population synthesis modeling in order to model the dynamical evolution and color evolution of globular clusters at the same time. This allows us to model the spectrum, colors and luminosities of each star in the simulated cluster. For this purpose the NBODY6++ code (Spurzem 1999) is used, which is a parallel version of the NBODY code. J. Hurley implemented simple recipes to follow the changes of stellar masses, radii, and luminosities due to stellar evolution into the NBODY6++ code (Hurley et al. 2001), in the sense that each simulation particle represents one star. These prescriptions cover all evolutionary phases and solar to globular cluster metallicities. We used the stellar parameters obtained by this stellar evolution routine and coupled them to the stellar library BaSeL 2.0 (Lejeune et al. 1997). As a first application we investigated the integrated broad band colors of simulated clusters. We modeled tidally disrupted globular clusters and compared the results with isolated globular clusters. Due to energy equipartition we expected a relative blueing of tidally disrupted clusters, because of the higher escape probability of red, low-mass stars. This behaviour we actually observe for concentrated globular clusters. The mass-to-light ratio of isolated clusters follows exactly a color-M/L correlation, similar as described in Bell and de Jong (2001) in the case of spiral galaxies. At variance to this correlation, in tidally disrupted clusters the M/L ratio becomes significantly lower at the time of cluster dissolution. Hence, for isolated clusters the behavior of the stellar population is not influenced by dynamical evolution, whereas the stellar population of tidally disrupted clusters is strongly influenced by dynamical effects.

  6. 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

  7. Dynamics analysis of SIR epidemic model with correlation coefficients and clustering coefficient in networks.

    PubMed

    Zhang, Juping; Yang, Chan; Jin, Zhen; Li, Jia

    2018-07-14

    In this paper, the correlation coefficients between nodes in states are used as dynamic variables, and we construct SIR epidemic dynamic models with correlation coefficients by using the pair approximation method in static networks and dynamic networks, respectively. Considering the clustering coefficient of the network, we analytically investigate the existence and the local asymptotic stability of each equilibrium of these models and derive threshold values for the prevalence of diseases. Additionally, we obtain two equivalent epidemic thresholds in dynamic networks, which are compared with the results of the mean field equations. Copyright © 2018 Elsevier Ltd. All rights reserved.

  8. Direct construction of mesoscopic models from microscopic simulations

    NASA Astrophysics Data System (ADS)

    Lei, Huan; Caswell, Bruce; Karniadakis, George Em

    2010-02-01

    Starting from microscopic molecular-dynamics (MD) simulations of constrained Lennard-Jones (LJ) clusters (with constant radius of gyration Rg ), we construct two mesoscopic models [Langevin dynamics and dissipative particle dynamics (DPD)] by coarse graining the LJ clusters into single particles. Both static and dynamic properties of the coarse-grained models are investigated and compared with the MD results. The effective mean force field is computed as a function of the intercluster distance, and the corresponding potential scales linearly with the number of particles per cluster and the temperature. We verify that the mean force field can reproduce the equation of state of the atomistic systems within a wide density range but the radial distribution function only within the dilute and the semidilute regime. The friction force coefficients for both models are computed directly from the time-correlation function of the random force field of the microscopic system. For high density or a large cluster size the friction force is overestimated and the diffusivity underestimated due to the omission of many-body effects as a result of the assumed pairwise form of the coarse-grained force field. When the many-body effect is not as pronounced (e.g., smaller Rg or semidilute system), the DPD model can reproduce the dynamic properties of the MD system.

  9. Rumor Diffusion in an Interests-Based Dynamic Social Network

    PubMed Central

    Mao, Xinjun; Guessoum, Zahia; Zhou, Huiping

    2013-01-01

    To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1) positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2) with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3) a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4) a network with a smaller clustering coefficient has a larger efficiency. PMID:24453911

  10. Rumor diffusion in an interests-based dynamic social network.

    PubMed

    Tang, Mingsheng; Mao, Xinjun; Guessoum, Zahia; Zhou, Huiping

    2013-01-01

    To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1) positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2) with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3) a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4) a network with a smaller clustering coefficient has a larger efficiency.

  11. Using experimental data to test an n -body dynamical model coupled with an energy-based clusterization algorithm at low incident energies

    NASA Astrophysics Data System (ADS)

    Kumar, Rohit; Puri, Rajeev K.

    2018-03-01

    Employing the quantum molecular dynamics (QMD) approach for nucleus-nucleus collisions, we test the predictive power of the energy-based clusterization algorithm, i.e., the simulating annealing clusterization algorithm (SACA), to describe the experimental data of charge distribution and various event-by-event correlations among fragments. The calculations are constrained into the Fermi-energy domain and/or mildly excited nuclear matter. Our detailed study spans over different system masses, and system-mass asymmetries of colliding partners show the importance of the energy-based clusterization algorithm for understanding multifragmentation. The present calculations are also compared with the other available calculations, which use one-body models, statistical models, and/or hybrid models.

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

    PubMed

    Li, Yan; Dong, Zigang

    2016-06-27

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

  13. Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

    NASA Astrophysics Data System (ADS)

    Zhang, Ying; Moges, Semu; Block, Paul

    2018-01-01

    Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

  14. Dynamic and Contextual Information in HMM Modeling for Handwritten Word Recognition.

    PubMed

    Bianne-Bernard, Anne-Laure; Menasri, Farès; Al-Hajj Mohamad, Rami; Mokbel, Chafic; Kermorvant, Christopher; Likforman-Sulem, Laurence

    2011-10-01

    This study aims at building an efficient word recognition system resulting from the combination of three handwriting recognizers. The main component of this combined system is an HMM-based recognizer which considers dynamic and contextual information for a better modeling of writing units. For modeling the contextual units, a state-tying process based on decision tree clustering is introduced. Decision trees are built according to a set of expert-based questions on how characters are written. Questions are divided into global questions, yielding larger clusters, and precise questions, yielding smaller ones. Such clustering enables us to reduce the total number of models and Gaussians densities by 10. We then apply this modeling to the recognition of handwritten words. Experiments are conducted on three publicly available databases based on Latin or Arabic languages: Rimes, IAM, and OpenHart. The results obtained show that contextual information embedded with dynamic modeling significantly improves recognition.

  15. Cluster dynamics transcending chemical dynamics toward nuclear fusion

    PubMed Central

    Heidenreich, Andreas; Jortner, Joshua; Last, Isidore

    2006-01-01

    Ultrafast cluster dynamics encompasses femtosecond nuclear dynamics, attosecond electron dynamics, and electron-nuclear dynamics in ultraintense laser fields (peak intensities 1015–1020 W·cm−2). Extreme cluster multielectron ionization produces highly charged cluster ions, e.g., (C4+(D+)4)n and (D+I22+)n at IM = 1018 W·cm−2, that undergo Coulomb explosion (CE) with the production of high-energy (5 keV to 1 MeV) ions, which can trigger nuclear reactions in an assembly of exploding clusters. The laser intensity and the cluster size dependence of the dynamics and energetics of CE of (D2)n, (HT)n, (CD4)n, (DI)n, (CD3I)n, and (CH3I)n clusters were explored by electrostatic models and molecular dynamics simulations, quantifying energetic driving effects, and kinematic run-over effects. The optimization of table-top dd nuclear fusion driven by CE of deuterium containing heteroclusters is realized for light-heavy heteroclusters of the largest size, which allows for the prevalence of cluster vertical ionization at the highest intensity of the laser field. We demonstrate a 7-orders-of-magnitude enhancement of the yield of dd nuclear fusion driven by CE of light-heavy heteroclusters as compared with (D2)n clusters of the same size. Prospective applications for the attainment of table-top nucleosynthesis reactions, e.g., 12C(P,γ)13N driven by CE of (CH3I)n clusters, were explored. PMID:16740666

  16. Cluster dynamics transcending chemical dynamics toward nuclear fusion.

    PubMed

    Heidenreich, Andreas; Jortner, Joshua; Last, Isidore

    2006-07-11

    Ultrafast cluster dynamics encompasses femtosecond nuclear dynamics, attosecond electron dynamics, and electron-nuclear dynamics in ultraintense laser fields (peak intensities 10(15)-10(20) W.cm(-2)). Extreme cluster multielectron ionization produces highly charged cluster ions, e.g., (C(4+)(D(+))(4))(n) and (D(+)I(22+))(n) at I(M) = 10(18) W.cm(-2), that undergo Coulomb explosion (CE) with the production of high-energy (5 keV to 1 MeV) ions, which can trigger nuclear reactions in an assembly of exploding clusters. The laser intensity and the cluster size dependence of the dynamics and energetics of CE of (D(2))(n), (HT)(n), (CD(4))(n), (DI)(n), (CD(3)I)(n), and (CH(3)I)(n) clusters were explored by electrostatic models and molecular dynamics simulations, quantifying energetic driving effects, and kinematic run-over effects. The optimization of table-top dd nuclear fusion driven by CE of deuterium containing heteroclusters is realized for light-heavy heteroclusters of the largest size, which allows for the prevalence of cluster vertical ionization at the highest intensity of the laser field. We demonstrate a 7-orders-of-magnitude enhancement of the yield of dd nuclear fusion driven by CE of light-heavy heteroclusters as compared with (D(2))(n) clusters of the same size. Prospective applications for the attainment of table-top nucleosynthesis reactions, e.g., (12)C(P,gamma)(13)N driven by CE of (CH(3)I)(n) clusters, were explored.

  17. A general framework to test gravity using galaxy clusters - I. Modelling the dynamical mass of haloes in f(R) gravity

    NASA Astrophysics Data System (ADS)

    Mitchell, Myles A.; He, Jian-hua; Arnold, Christian; Li, Baojiu

    2018-06-01

    We propose a new framework for testing gravity using cluster observations, which aims to provide an unbiased constraint on modified gravity models from Sunyaev-Zel'dovich (SZ) and X-ray cluster counts and the cluster gas fraction, among other possible observables. Focusing on a popular f(R) model of gravity, we propose a novel procedure to recalibrate mass scaling relations from Λ cold dark matter (ΛCDM) to f(R) gravity for SZ and X-ray cluster observables. We find that the complicated modified gravity effects can be simply modelled as a dependence on a combination of the background scalar field and redshift, fR(z)/(1 + z), regardless of the f(R) model parameter. By employing a large suite of N-body simulations, we demonstrate that a theoretically derived tanh fitting formula is in excellent agreement with the dynamical mass enhancement of dark matter haloes for a large range of background field parameters and redshifts. Our framework is sufficiently flexible to allow for tests of other models and inclusion of further observables, and the one-parameter description of the dynamical mass enhancement can have important implications on the theoretical modelling of observables and on practical tests of gravity.

  18. Cluster adsorption on amorphous and crystalline surfaces - A molecular dynamics study of model Pt on Cu and model Pd on Pt

    NASA Technical Reports Server (NTRS)

    Garofalini, S. H.; Halicioglu, T.; Pound, G. M.

    1981-01-01

    Molecular dynamics was used to study the structure, dispersion and short-time behavior of ten-atom clusters adsorbed onto amorphous and crystalline substrates, in which the cluster atoms differed from the substrate atoms. Two adatom-substrate model systems were chosen; one, in which the interaction energy between adatom pairs was greater than that between substrate pairs, and the other, in which the reverse was true. At relatively low temperature ranges, increased dispersion of cluster atoms occurred: (a) on the amorphous substrate as compared to the FCC(100) surface, (b) with increasing reduced temperature, and (c) with adatom-substrate interaction energy stronger than adatom-adatom interaction. Two-dimensional clusters (rafts) on the FCC(100) surface displayed migration of edge atoms only, indicating a mechanism for the cluster rotation and shape changes found in experimental studies.

  19. Sliding states of a soft-colloid cluster crystal: Cluster versus single-particle hopping

    NASA Astrophysics Data System (ADS)

    Rossini, Mirko; Consonni, Lorenzo; Stenco, Andrea; Reatto, Luciano; Manini, Nicola

    2018-05-01

    We study a two-dimensional model for interacting colloidal particles which displays spontaneous clustering. Within this model we investigate the competition between the pinning to a periodic corrugation potential and a sideways constant pulling force which would promote a sliding state. For a few sample particle densities and amplitudes of the periodic corrugation potential we investigate the depinning from the statically pinned to the dynamically sliding regime. This sliding state exhibits the competition between a dynamics where entire clusters are pulled from a minimum to the next and a dynamics where single colloids or smaller groups leave a cluster and move across the corrugation energy barrier to join the next cluster downstream in the force direction. Both kinds of sliding states can occur either coherently across the entire sample or asynchronously: the two regimes result in different average mobilities. Finite temperature tends to destroy separate sliding regimes, generating a smoother dependence of the mobility on the driving force.

  20. 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.

  1. Cooperative effects in the structuring of fluoride water clusters: Ab initio hybrid quantum mechanical/molecular mechanical model incorporating polarizable fluctuating charge solvent

    NASA Astrophysics Data System (ADS)

    Bryce, Richard A.; Vincent, Mark A.; Malcolm, Nathaniel O. J.; Hillier, Ian H.; Burton, Neil A.

    1998-08-01

    A new hybrid quantum mechanical/molecular mechanical model of solvation is developed and used to describe the structure and dynamics of small fluoride/water clusters, using an ab initio wave function to model the ion and a fluctuating charge potential to model the waters. Appropriate parameters for the water-water and fluoride-water interactions are derived, with the fluoride anion being described by density functional theory and a large Gaussian basis. The role of solvent polarization in determining the structure and energetics of F(H2O)4- clusters is investigated, predicting a slightly greater stability of the interior compared to the surface structure, in agreement with ab initio studies. An extended Lagrangian treatment of the polarizable water, in which the water atomic charges fluctuate dynamically, is used to study the dynamics of F(H2O)4- cluster. A simulation using a fixed solvent charge distribution indicates principally interior, solvated states for the cluster. However, a preponderance of trisolvated configurations is observed using the polarizable model at 300 K, which involves only three direct fluoride-water hydrogen bonds. Ab initio calculations confirm this trisolvated species as a thermally accessible state at room temperature, in addition to the tetrasolvated interior and surface structures. Extension of this polarizable water model to fluoride clusters with five and six waters gave less satisfactory agreement with experimental energies and with ab initio geometries. However, our results do suggest that a quantitative model of solvent polarization is fundamental for an accurate understanding of the properties of anionic water clusters.

  2. DID THE INFANT R136 AND NGC 3603 CLUSTERS UNDERGO RESIDUAL GAS EXPULSION?

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

    Banerjee, Sambaran; Kroupa, Pavel, E-mail: sambaran@astro.uni-bonn.de, E-mail: pavel@astro.uni-bonn.de

    2013-02-10

    Based on kinematic data observed for very young, massive clusters that appear to be in dynamical equilibrium, it has recently been argued that such young systems are examples of where the early residual gas expulsion did not happen or had no dynamical effect. The intriguing scenario of a star cluster forming through a single starburst has thereby been challenged. Choosing the case of the R136 cluster of the Large Magellanic Cloud, the most cited one in this context, we perform direct N-body computations that mimic the early evolution of this cluster including the gas-removal phase (on a thermal timescale). Ourmore » calculations show that under plausible initial conditions which are consistent with observational data, a large fraction (>60%) of a gas-expelled, expanding R136-like cluster is bound to regain dynamical equilibrium by its current age. Therefore, the recent measurements of velocity dispersion in the inner regions of R136, which indicate that the cluster is in dynamical equilibrium, are consistent with an earlier substantial gas expulsion of R136 followed by a rapid re-virialization (in Almost-Equal-To 1 Myr). Additionally, we find that the less massive Galactic NGC 3603 Young Cluster (NYC), with a substantially longer re-virialization time, is likely to be found to have deviated from dynamical equilibrium at its present age ( Almost-Equal-To 1 Myr). The recently obtained stellar proper motions in the central part of the NYC indeed suggest this and are consistent with the computed models. This work significantly extends previous models of the Orion Nebula Cluster which already demonstrated that the re-virialization time of young post-gas-expulsion clusters decreases with increasing pre-expulsion density.« less

  3. Did the Infant R136 and NGC 3603 Clusters Undergo Residual Gas Expulsion?

    NASA Astrophysics Data System (ADS)

    Banerjee, Sambaran; Kroupa, Pavel

    2013-02-01

    Based on kinematic data observed for very young, massive clusters that appear to be in dynamical equilibrium, it has recently been argued that such young systems are examples of where the early residual gas expulsion did not happen or had no dynamical effect. The intriguing scenario of a star cluster forming through a single starburst has thereby been challenged. Choosing the case of the R136 cluster of the Large Magellanic Cloud, the most cited one in this context, we perform direct N-body computations that mimic the early evolution of this cluster including the gas-removal phase (on a thermal timescale). Our calculations show that under plausible initial conditions which are consistent with observational data, a large fraction (>60%) of a gas-expelled, expanding R136-like cluster is bound to regain dynamical equilibrium by its current age. Therefore, the recent measurements of velocity dispersion in the inner regions of R136, which indicate that the cluster is in dynamical equilibrium, are consistent with an earlier substantial gas expulsion of R136 followed by a rapid re-virialization (in ≈1 Myr). Additionally, we find that the less massive Galactic NGC 3603 Young Cluster (NYC), with a substantially longer re-virialization time, is likely to be found to have deviated from dynamical equilibrium at its present age (≈1 Myr). The recently obtained stellar proper motions in the central part of the NYC indeed suggest this and are consistent with the computed models. This work significantly extends previous models of the Orion Nebula Cluster which already demonstrated that the re-virialization time of young post-gas-expulsion clusters decreases with increasing pre-expulsion density.

  4. Dynamical evolution of stars and gas of young embedded stellar sub-clusters

    NASA Astrophysics Data System (ADS)

    Sills, Alison; Rieder, Steven; Scora, Jennifer; McCloskey, Jessica; Jaffa, Sarah

    2018-06-01

    We present simulations of the dynamical evolution of young embedded star clusters. Our initial conditions are directly derived from X-ray, infrared, and radio observations of local systems, and our models evolve both gas and stars simultaneously. Our regions begin with both clustered and extended distributions of stars, and a gas distribution that can include a filamentary structure in addition to gas surrounding the stellar sub-clusters. We find that the regions become spherical, monolithic, and smooth quite quickly, and that the dynamical evolution is dominated by the gravitational interactions between the stars. In the absence of stellar feedback, the gas moves gently out of the centre of our regions but does not have a significant impact on the motions of the stars at the earliest stages of cluster formation. Our models at later times are consistent with observations of similar regions in the local neighbourhood. We conclude that the evolution of young protostar clusters is relatively insensitive to reasonable choices of initial conditions. Models with more realism, such as an initial population of binary and multiple stars and ongoing star formation, are the next step needed to confirm these findings.

  5. Self-organization and positioning of bacterial protein clusters

    NASA Astrophysics Data System (ADS)

    Murray, Seán M.; Sourjik, Victor

    2017-10-01

    Many cellular processes require proteins to be precisely positioned within the cell. In some cases this can be attributed to passive mechanisms such as recruitment by other proteins in the cell or by exploiting the curvature of the membrane. However, in bacteria, active self-positioning is likely to play a role in multiple processes, including the positioning of the future site of cell division and cytoplasmic protein clusters. How can such dynamic clusters be formed and positioned? Here, we present a model for the self-organization and positioning of dynamic protein clusters into regularly repeating patterns based on a phase-locked Turing pattern. A single peak in the concentration is always positioned at the midpoint of the model cell, and two peaks are positioned at the midpoint of each half. Furthermore, domain growth results in peak splitting and pattern doubling. We argue that the model may explain the regular positioning of the highly conserved structural maintenance of chromosomes complexes on the bacterial nucleoid and that it provides an attractive mechanism for the self-positioning of dynamic protein clusters in other systems.

  6. Cluster Dynamics Modeling with Bubble Nucleation, Growth and Coalescence

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

    de Almeida, Valmor F.; Blondel, Sophie; Bernholdt, David E.

    The topic of this communication pertains to defect formation in irradiated solids such as plasma-facing tungsten submitted to helium implantation in fusion reactor com- ponents, and nuclear fuel (metal and oxides) submitted to volatile ssion product generation in nuclear reactors. The purpose of this progress report is to describe ef- forts towards addressing the prediction of long-time evolution of defects via continuum cluster dynamics simulation. The di culties are twofold. First, realistic, long-time dynamics in reactor conditions leads to a non-dilute di usion regime which is not accommodated by the prevailing dilute, stressless cluster dynamics theory. Second, long-time dynamics callsmore » for a large set of species (ideally an in nite set) to capture all possible emerging defects, and this represents a computational bottleneck. Extensions beyond the dilute limit is a signi cant undertaking since no model has been advanced to extend cluster dynamics to non-dilute, deformable conditions. Here our proposed approach to model the non-dilute limit is to monitor the appearance of a spatially localized void volume fraction in the solid matrix with a bell shape pro le and insert an explicit geometrical bubble onto the support of the bell function. The newly cre- ated internal moving boundary provides the means to account for the interfacial ux of mobile species into the bubble, and the growth of bubbles allows for coalescence phenomena which captures highly non-dilute interactions. We present a preliminary interfacial kinematic model with associated interfacial di usion transport to follow the evolution of the bubble in any number of spatial dimensions and any number of bubbles, which can be further extended to include a deformation theory. Finally we comment on a computational front-tracking method to be used in conjunction with conventional cluster dynamics simulations in the non-dilute model proposed.« less

  7. Galaxy cluster lensing masses in modified lensing potentials

    DOE PAGES

    Barreira, Alexandre; Li, Baojiu; Jennings, Elise; ...

    2015-10-28

    In this study, we determine the concentration–mass relation of 19 X-ray selected galaxy clusters from the Cluster Lensing and Supernova Survey with Hubble survey in theories of gravity that directly modify the lensing potential. We model the clusters as Navarro–Frenk–White haloes and fit their lensing signal, in the Cubic Galileon and Nonlocal gravity models, to the lensing convergence profiles of the clusters. We discuss a number of important issues that need to be taken into account, associated with the use of non-parametric and parametric lensing methods, as well as assumptions about the background cosmology. Our results show that the concentrationmore » and mass estimates in the modified gravity models are, within the error bars, the same as in Λ cold dark matter. This result demonstrates that, for the Nonlocal model, the modifications to gravity are too weak at the cluster redshifts, and for the Galileon model, the screening mechanism is very efficient inside the cluster radius. However, at distances ~ [2–20] Mpc/h from the cluster centre, we find that the surrounding force profiles are enhanced by ~ 20–40% in the Cubic Galileon model. This has an impact on dynamical mass estimates, which means that tests of gravity based on comparisons between lensing and dynamical masses can also be applied to the Cubic Galileon model.« less

  8. Stochastic fire-diffuse-fire model with realistic cluster dynamics.

    PubMed

    Calabrese, Ana; Fraiman, Daniel; Zysman, Daniel; Ponce Dawson, Silvina

    2010-09-01

    Living organisms use waves that propagate through excitable media to transport information. Ca2+ waves are a paradigmatic example of this type of processes. A large hierarchy of Ca2+ signals that range from localized release events to global waves has been observed in Xenopus laevis oocytes. In these cells, Ca2+ release occurs trough inositol 1,4,5-trisphosphate receptors (IP3Rs) which are organized in clusters of channels located on the membrane of the endoplasmic reticulum. In this article we construct a stochastic model for a cluster of IP3R 's that replicates the experimental observations reported in [D. Fraiman, Biophys. J. 90, 3897 (2006)]. We then couple this phenomenological cluster model with a reaction-diffusion equation, so as to have a discrete stochastic model for calcium dynamics. The model we propose describes the transition regimes between isolated release and steadily propagating waves as the IP3 concentration is increased.

  9. A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq.

    PubMed

    Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling

    2015-03-01

    Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  10. Fragmentation dynamics of ionized neon clusters (Ne(n), n=3-14) embedded in helium nanodroplets.

    PubMed

    Bonhommeau, David; Halberstadt, Nadine; Viel, Alexandra

    2006-01-14

    We report a theoretical study of the nonadiabatic fragmentation dynamics of ionized neon clusters embedded in helium nanodroplets for cluster sizes up to n=14 atoms. The dynamics of the neon atoms is modeled using the molecular dynamics with quantum transitions method of Tully [J. Chem. Phys. 93, 1061 (1990)] with the nuclei treated classically and transitions between electronic states quantum mechanically. The potential-energy surfaces are derived from a diatomics-in-molecules model to which induced dipole-induced dipole interactions are added. The effect of the spin-orbit interaction is also discussed. The helium environment is modeled by a friction force acting on charged atoms whose speed exceeds the critical Landau velocity. The dependence of the fragment size distribution on the friction strength and on the initial nanodroplet size is investigated. By comparing with the available experimental data obtained for Ne3+ and Ne4+, a reasonable value for the friction coefficient, the only parameter of the model, is deduced. This value is then used to predict the effect of the helium environment on the dissociation dynamics of larger neon clusters, n=5-14. The results show stabilization of larger fragments than in the gas phase, but fragmentation is not completely caged. In addition, two types of dynamics are characterized for Ne4+: fast and explosive, therefore leaving no time for friction to cool down the process when dynamics starts on one of the highest electronic states, and slower, therefore leading to some stabilization by helium when it starts on one of the lowest electronic states.

  11. Cell cycle dynamics in a response/signalling feedback system with a gap.

    PubMed

    Gong, Xue; Buckalew, Richard; Young, Todd; Boczko, Erik

    2014-01-01

    We consider a dynamical model of cell cycles of n cells in a culture in which cells in one specific phase (S for signalling) of the cell cycle produce chemical agents that influence the growth/cell cycle progression of cells in another phase (R for responsive). In the case that the feedback is negative, it is known that subpopulations of cells tend to become clustered in the cell cycle; while for a positive feedback, all the cells tend to become synchronized. In this paper, we suppose that there is a gap between the two phases. The gap can be thought of as modelling the physical reality of a time delay in the production and action of the signalling agents. We completely analyse the dynamics of this system when the cells are arranged into two cell cycle clusters. We also consider the stability of certain important periodic solutions in which clusters of cells have a cyclic arrangement and there are just enough clusters to allow interactions between them. We find that the inclusion of a small gap does not greatly alter the global dynamics of the system; there are still large open sets of parameters for which clustered solutions are stable. Thus, we add to the evidence that clustering can be a robust phenomenon in biological systems. However, the gap does effect the system by enhancing the stability of the stable clustered solutions. We explain this phenomenon in terms of contraction rates (Floquet exponents) in various invariant subspaces of the system. We conclude that in systems for which these models are reasonable, a delay in signalling is advantageous to the emergence of clustering.

  12. On aggregation in CA models in biology

    NASA Astrophysics Data System (ADS)

    Alber, Mark S.; Kiskowski, Audi

    2001-12-01

    Aggregation of randomly distributed particles into clusters of aligned particles is modeled using a cellular automata (CA) approach. The CA model accounts for interactions between more than one type of particle, in which pressures for angular alignment with neighbors compete with pressures for grouping by cell type. In the case of only one particle type clusters tend to unite into one big cluster. In the case of several types of particles the dynamics of clusters is more complicated and for specific choices of parameters particle sorting occurs simultaneously with the formation of clusters of aligned particles.

  13. R144: a very massive binary likely ejected from R136 through a binary-binary encounter

    NASA Astrophysics Data System (ADS)

    Oh, Seungkyung; Kroupa, Pavel; Banerjee, Sambaran

    2014-02-01

    R144 is a recently confirmed very massive, spectroscopic binary which appears isolated from the core of the massive young star cluster R136. The dynamical ejection hypothesis as an origin for its location is claimed improbable by Sana et al. due to its binary nature and high mass. We demonstrate here by means of direct N-body calculations that a very massive binary system can be readily dynamically ejected from an R136-like cluster, through a close encounter with a very massive system. One out of four N-body cluster models produces a dynamically ejected very massive binary system with a mass comparable to R144. The system has a system mass of ≈355 M⊙ and is located at 36.8 pc from the centre of its parent cluster, moving away from the cluster with a velocity of 57 km s-1 at 2 Myr as a result of a binary-binary interaction. This implies that R144 could have been ejected from R136 through a strong encounter with another massive binary or single star. In addition, we discuss all massive binaries and single stars which are ejected dynamically from their parent cluster in the N-body models.

  14. Galaxy Kinematics and Mass Calibration in Massive SZE Selected Galaxy Clusters to z=1.3

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

    Capasso, R.; et al.

    The galaxy phase-space distribution in galaxy clusters provides insights into the formation and evolution of cluster galaxies, and it can also be used to measure cluster mass profiles. We present a dynamical study based onmore » $$\\sim$$3000 passive, non-emission line cluster galaxies drawn from 110 galaxy clusters. The galaxy clusters were selected using the Sunyaev-Zel'dovich effect (SZE) in the 2500 deg$^2$ SPT-SZ survey and cover the redshift range $0.2 < z < 1.3$. We model the clusters using the Jeans equation, while adopting NFW mass profiles and a broad range of velocity dispersion anisotropy profiles. The data prefer velocity dispersion anisotropy profiles that are approximately isotropic near the center and increasingly radial toward the cluster virial radius, and this is true for all redshifts and masses we study. The pseudo-phase-space density profile of the passive galaxies is consistent with expectations for dark matter particles and subhalos from cosmological $N$-body simulations. The dynamical mass constraints are in good agreement with external mass estimates of the SPT cluster sample from either weak lensing, velocity dispersions, or X-ray $$Y_X$$ measurements. However, the dynamical masses are lower (at the 2.2$$\\sigma$$ level) when compared to the mass calibration favored when fitting the SPT cluster data to a LCDM model with external cosmological priors, including CMB anisotropy data from Planck. The tension grows with redshift, where in the highest redshift bin the ratio of dynamical to SPT+Planck masses is $$\\eta=0.63^{+0.13}_{-0.08}\\pm0.05$$ (statistical and systematic), corresponding to 2.6$$\\sigma$$ tension.« less

  15. The mass function and dynamical mass of young star clusters: why their initial crossing-time matters crucially

    NASA Astrophysics Data System (ADS)

    Parmentier, Geneviève; Baumgardt, Holger

    2012-12-01

    We highlight the impact of cluster-mass-dependent evolutionary rates upon the evolution of the cluster mass function during violent relaxation, that is, while clusters dynamically respond to the expulsion of their residual star-forming gas. Mass-dependent evolutionary rates arise when the mean volume density of cluster-forming regions is mass-dependent. In that case, even if the initial conditions are such that the cluster mass function at the end of violent relaxation has the same shape as the embedded-cluster mass function (i.e. infant weight-loss is mass-independent), the shape of the cluster mass function does change transiently during violent relaxation. In contrast, for cluster-forming regions of constant mean volume density, the cluster mass function shape is preserved all through violent relaxation since all clusters then evolve at the same mass-independent rate. On the scale of individual clusters, we model the evolution of the ratio of the dynamical mass to luminous mass of a cluster after gas expulsion. Specifically, we map the radial dependence of the time-scale for a star cluster to return to equilibrium. We stress that fields of view a few pc in size only, typical of compact clusters with rapid evolutionary rates, are likely to reveal cluster regions which have returned to equilibrium even if the cluster experienced a major gas expulsion episode a few Myr earlier. We provide models with the aperture and time expressed in units of the initial half-mass radius and initial crossing-time, respectively, so that our results can be applied to clusters with initial densities, sizes, and apertures different from ours.

  16. Electrostatic effects on clustering and ion dynamics in ionomer melts

    NASA Astrophysics Data System (ADS)

    Ma, Boran; Nguyen, Trung; Pryamitsyn, Victor; Olvera de La Cruz, Monica

    An understanding of the relationships between ionomer chain morphology, dynamics and counter-ion mobility is a key factor in the design of ion conducting membranes for battery applications. In this study, we investigate the influence of electrostatic coupling between randomly charged copolymers (ionomers) and counter ions on the structural and dynamic features of a model system of ionomer melts. Using coarse-grained molecular dynamics (CGMD) simulations, we found that variations in electrostatic coupling strength (Γ) remarkably affect the formation of ion-counter ion clusters, ion mobility, and polymer dynamics for a range of charged monomer fractions. Specifically, an increase in Γ leads to larger ionic cluster sizes and reduced polymer and ion mobility. Analysis of the distribution of the radius of gyration of the clusters further reveals that the fractal dimension of the ion clusters is nearly independent from Γ for all the cases studied. Finally, at sufficiently high values of Γ, we observed arrested heterogeneous ions mobility, which is correlated with an increase in ion cluster size. These findings provide insight into the role of electrostatics in governing the nanostructures formed by ionomers.

  17. Primordial binary populations in low-density star clusters as seen by Chandra: globular clusters versus old open clusters

    NASA Astrophysics Data System (ADS)

    van den Berg, Maureen C.

    2015-08-01

    The binaries in the core of a star cluster are the energy source that prevents the cluster from experiencing core collapse. To model the dynamical evolution of a cluster, it is important to have constraints on the primordial binary content. X-ray observations of old star clusters are very efficient in detecting the close interacting binaries among the cluster members. The X-ray sources in star clusters are a mix of binaries that were dynamically formed and primordial binaries. In massive, dense star clusters, dynamical encounters play an important role in shaping the properties and numbers of the binaries. In contrast, in the low-density clusters the impact of dynamical encounters is presumed to be very small, and the close binaries detected in X-rays represent a primordial population. The lowest density globular clusters have current masses and central densities similar to those of the oldest open clusters in our Milky Way. I will discuss the results of studies with the Chandra X-ray Observatory that have nevertheless revealed a clear dichotomy: far fewer (if any at all) X-ray sources are detected in the central regions of the low-density globular clusters compared to the number of secure cluster members that have been detected in old open clusters (above a limiting X-ray luminosity of typically 4e30 erg/s). The low stellar encounter rates imply that dynamical destruction of binaries can be ignored at present, therefore an explanation must be sought elsewhere. I will discuss several factors that can shed light on the implied differences between the primordial close binary populations in the two types of star clusters.

  18. 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.

  19. 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

  20. Post-Newtonian Dynamics in Dense Star Clusters: Highly Eccentric, Highly Spinning, and Repeated Binary Black Hole Mergers

    NASA Astrophysics Data System (ADS)

    Rodriguez, Carl L.; Amaro-Seoane, Pau; Chatterjee, Sourav; Rasio, Frederic A.

    2018-04-01

    We present models of realistic globular clusters with post-Newtonian dynamics for black holes. By modeling the relativistic accelerations and gravitational-wave emission in isolated binaries and during three- and four-body encounters, we find that nearly half of all binary black hole mergers occur inside the cluster, with about 10% of those mergers entering the LIGO/Virgo band with eccentricities greater than 0.1. In-cluster mergers lead to the birth of a second generation of black holes with larger masses and high spins, which, depending on the black hole natal spins, can sometimes be retained in the cluster and merge again. As a result, globular clusters can produce merging binaries with detectable spins regardless of the birth spins of black holes formed from massive stars. These second-generation black holes would also populate any upper mass gap created by pair-instability supernovae.

  1. Post-Newtonian Dynamics in Dense Star Clusters: Highly Eccentric, Highly Spinning, and Repeated Binary Black Hole Mergers.

    PubMed

    Rodriguez, Carl L; Amaro-Seoane, Pau; Chatterjee, Sourav; Rasio, Frederic A

    2018-04-13

    We present models of realistic globular clusters with post-Newtonian dynamics for black holes. By modeling the relativistic accelerations and gravitational-wave emission in isolated binaries and during three- and four-body encounters, we find that nearly half of all binary black hole mergers occur inside the cluster, with about 10% of those mergers entering the LIGO/Virgo band with eccentricities greater than 0.1. In-cluster mergers lead to the birth of a second generation of black holes with larger masses and high spins, which, depending on the black hole natal spins, can sometimes be retained in the cluster and merge again. As a result, globular clusters can produce merging binaries with detectable spins regardless of the birth spins of black holes formed from massive stars. These second-generation black holes would also populate any upper mass gap created by pair-instability supernovae.

  2. Imprints of dynamical interactions on brown dwarf pairing statistics and kinematics

    NASA Astrophysics Data System (ADS)

    Sterzik, M. F.; Durisen, R. H.

    2003-03-01

    We present statistically robust predictions of brown dwarf properties arising from dynamical interactions during their early evolution in small clusters. Our conclusions are based on numerical calculations of the internal cluster dynamics as well as on Monte-Carlo models. Accounting for recent observational constraints on the sub-stellar mass function and initial properties in fragmenting star forming clumps, we derive multiplicity fractions, mass ratios, separation distributions, and velocity dispersions. We compare them with observations of brown dwarfs in the field and in young clusters. Observed brown dwarf companion fractions around 15 +/- 7% for very low-mass stars as reported recently by Close et al. (\\cite{CSFB03}) are consistent with certain dynamical decay models. A significantly smaller mean separation distribution for brown dwarf binaries than for binaries of late-type stars can be explained by similar specific energy at the time of cluster formation for all cluster masses. Due to their higher velocity dispersions, brown-dwarfs and low-mass single stars will undergo time-dependent spatial segregation from higher-mass stars and multiple systems. This will cause mass functions and binary statistics in star forming regions to vary with the age of the region and the volume sampled.

  3. An algebraic cluster model based on the harmonic oscillator basis

    NASA Technical Reports Server (NTRS)

    Levai, Geza; Cseh, J.

    1995-01-01

    We discuss the semimicroscopic algebraic cluster model introduced recently, in which the internal structure of the nuclear clusters is described by the harmonic oscillator shell model, while their relative motion is accounted for by the Vibron model. The algebraic formulation of the model makes extensive use of techniques associated with harmonic oscillators and their symmetry group, SU(3). The model is applied to some cluster systems and is found to reproduce important characteristics of nuclei in the sd-shell region. An approximate SU(3) dynamical symmetry is also found to hold for the C-12 + C-12 system.

  4. Study of clusters and hypernuclei production within PHSD+FRIGA model

    NASA Astrophysics Data System (ADS)

    Kireyeu, Viktar; Le Fèvre, Arnaud; Bratkovskaya, Elena

    2017-03-01

    We report on the results on the dynamical modelling of cluster formation with the new combined PHSD+FRIGA model at Nuclotron and NICA energies. The FRIGA clusterization algorithm, which can be applied to the transport models, is based on the simulated annealing technique to obtain the most bound configuration of fragments and nucleons. The PHSD+FRIGA model is able to predict isotope yields as well as hypernucleus production. Based on present predictions of the combined model we study the possibility to detect such clusters and hypernuclei in the BM@N and MPD/NICA detectors.

  5. DIFFERENT DYNAMICAL AGES FOR THE TWO YOUNG AND COEVAL LMC STAR CLUSTERS, NGC 1805 AND NGC 1818, IMPRINTED ON THEIR BINARY POPULATIONS

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

    Geller, Aaron M.; Grijs, Richard de; Li, Chengyuan

    2015-05-20

    The two Large Magellanic Cloud star clusters, NGC 1805 and NGC 1818, are approximately the same chronological age (∼30 Myr), but show different radial trends in binary frequency. The F-type stars (1.3–2.2 M{sub ⊙}) in NGC 1818 have a binary frequency that decreases toward the core, while the binary frequency for stars of similar mass in NGC 1805 is flat with radius, or perhaps bimodal (with a peak in the core). We show here, through detailed N-body modeling, that both clusters could have formed with the same primordial binary frequency and with binary orbital elements and masses drawn from themore » same distributions (defined from observations of open clusters and the field of our Galaxy). The observed radial trends in binary frequency for both clusters are best matched with models that have initial substructure. Furthermore, both clusters may be evolving along a very similar dynamical sequence, with the key difference that NGC 1805 is dynamically older than NGC 1818. The F-type binaries in NGC 1818 still show evidence of an initial period of rapid dynamical disruptions (which occur preferentially in the core), while NGC 1805 has already begun to recover a higher core binary frequency, owing to mass segregation (which will eventually produce a distribution in binary frequency that rises only toward the core, as is observed in old Milky Way star clusters). This recovery rate increases for higher-mass binaries, and therefore even at one age in one cluster, we predict a similar dynamical sequence in the radial distribution of the binary frequency as a function of binary primary mass.« less

  6. Dynamical structure factor of the J1-J2 Heisenberg model in one dimension: The variational Monte Carlo approach

    NASA Astrophysics Data System (ADS)

    Ferrari, Francesco; Parola, Alberto; Sorella, Sandro; Becca, Federico

    2018-06-01

    The dynamical spin structure factor is computed within a variational framework to study the one-dimensional J1-J2 Heisenberg model. Starting from Gutzwiller-projected fermionic wave functions, the low-energy spectrum is constructed from two-spinon excitations. The direct comparison with Lanczos calculations on small clusters demonstrates the excellent description of both gapless and gapped (dimerized) phases, including incommensurate structures for J2/J1>0.5 . Calculations on large clusters show how the intensity evolves when increasing the frustrating ratio and give an unprecedented accurate characterization of the dynamical properties of (nonintegrable) frustrated spin models.

  7. Are Binary Separations related to their System Mass?

    NASA Astrophysics Data System (ADS)

    Sterzik, M. F.; Durisen, R. H.

    2004-08-01

    We compile most recent multiplicity fractions and binary separation distributions for different primary masses, including very low-mass and brown dwarf primaries, and compare them with dynamical decay models of small-N clusters. The model predictions are based on detailed numerical calculations of the internal cluster dynamics, as well as on Monte-Carlo methods. Both observations and models reflect the same trends: (1) The multiplicity fraction is an increasing function of the primary mass. (2) The mean binary separations are increasing with the system mass in the sense that very low-mass binaries have average separations around ≈ 4AU, while the binary separation distribution for solar-type primaries peaks at ≈ 40AU. M-type binary systems apparently preferentially populate intermediate separations. Similar specific energy at the time of cluster formation for all cluster masses can possibly explain this trend.

  8. STRUCTURAL PARAMETERS FOR 10 HALO GLOBULAR CLUSTERS IN M33

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

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

    2015-05-15

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

  9. Effect of Policy Analysis on Indonesia’s Maritime Cluster Development Using System Dynamics Modeling

    NASA Astrophysics Data System (ADS)

    Nursyamsi, A.; Moeis, A. O.; Komarudin

    2018-03-01

    As an archipelago with two third of its territory consist of water, Indonesia should address more attention to its maritime industry development. One of the catalyst to fasten the maritime industry growth is by developing a maritime cluster. The purpose of this research is to gain understanding of the effect if Indonesia implement maritime cluster policy to the growth of maritime economic and its role to enhance the maritime cluster performance, hence enhancing Indonesia’s maritime industry as well. The result of the constructed system dynamic model simulation shows that with the effect of maritime cluster, the growth of employment rate and maritime economic is much bigger that the business as usual case exponentially. The result implies that the government should act fast to form a legitimate cluster maritime organizer institution so that there will be a synergize, sustainable, and positive maritime cluster environment that will benefit the performance of Indonesia’s maritime industry.

  10. Activity-induced clustering in model dumbbell swimmers: the role of hydrodynamic interactions.

    PubMed

    Furukawa, Akira; Marenduzzo, Davide; Cates, Michael E

    2014-08-01

    Using a fluid-particle dynamics approach, we numerically study the effects of hydrodynamic interactions on the collective dynamics of active suspensions within a simple model for bacterial motility: each microorganism is modeled as a stroke-averaged dumbbell swimmer with prescribed dipolar force pairs. Using both simulations and qualitative arguments, we show that, when the separation between swimmers is comparable to their size, the swimmers' motions are strongly affected by activity-induced hydrodynamic forces. To further understand these effects, we investigate semidilute suspensions of swimmers in the presence of thermal fluctuations. A direct comparison between simulations with and without hydrodynamic interactions shows these to enhance the dynamic clustering at a relatively small volume fraction; with our chosen model the key ingredient for this clustering behavior is hydrodynamic trapping of one swimmer by another, induced by the active forces. Furthermore, the density dependence of the motility (of both the translational and rotational motions) exhibits distinctly different behaviors with and without hydrodynamic interactions; we argue that this is linked to the clustering tendency. Our study illustrates the fact that hydrodynamic interactions not only affect kinetic pathways in active suspensions, but also cause major changes in their steady state properties.

  11. Activity-induced clustering in model dumbbell swimmers: The role of hydrodynamic interactions

    NASA Astrophysics Data System (ADS)

    Furukawa, Akira; Marenduzzo, Davide; Cates, Michael E.

    2014-08-01

    Using a fluid-particle dynamics approach, we numerically study the effects of hydrodynamic interactions on the collective dynamics of active suspensions within a simple model for bacterial motility: each microorganism is modeled as a stroke-averaged dumbbell swimmer with prescribed dipolar force pairs. Using both simulations and qualitative arguments, we show that, when the separation between swimmers is comparable to their size, the swimmers' motions are strongly affected by activity-induced hydrodynamic forces. To further understand these effects, we investigate semidilute suspensions of swimmers in the presence of thermal fluctuations. A direct comparison between simulations with and without hydrodynamic interactions shows these to enhance the dynamic clustering at a relatively small volume fraction; with our chosen model the key ingredient for this clustering behavior is hydrodynamic trapping of one swimmer by another, induced by the active forces. Furthermore, the density dependence of the motility (of both the translational and rotational motions) exhibits distinctly different behaviors with and without hydrodynamic interactions; we argue that this is linked to the clustering tendency. Our study illustrates the fact that hydrodynamic interactions not only affect kinetic pathways in active suspensions, but also cause major changes in their steady state properties.

  12. MOCCA-SURVEY Database I: Is NGC 6535 a dark star cluster harbouring an IMBH?

    NASA Astrophysics Data System (ADS)

    Askar, Abbas; Bianchini, Paolo; de Vita, Ruggero; Giersz, Mirek; Hypki, Arkadiusz; Kamann, Sebastian

    2017-01-01

    We describe the dynamical evolution of a unique type of dark star cluster model in which the majority of the cluster mass at Hubble time is dominated by an intermediate-mass black hole (IMBH). We analysed results from about 2000 star cluster models (Survey Database I) simulated using the Monte Carlo code MOnte Carlo Cluster simulAtor and identified these dark star cluster models. Taking one of these models, we apply the method of simulating realistic `mock observations' by utilizing the Cluster simulatiOn Comparison with ObservAtions (COCOA) and Simulating Stellar Cluster Observation (SISCO) codes to obtain the photometric and kinematic observational properties of the dark star cluster model at 12 Gyr. We find that the perplexing Galactic globular cluster NGC 6535 closely matches the observational photometric and kinematic properties of the dark star cluster model presented in this paper. Based on our analysis and currently observed properties of NGC 6535, we suggest that this globular cluster could potentially harbour an IMBH. If it exists, the presence of this IMBH can be detected robustly with proposed kinematic observations of NGC 6535.

  13. Spatial cluster detection using dynamic programming.

    PubMed

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

    2012-03-25

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

  14. Spatial cluster detection using dynamic programming

    PubMed Central

    2012-01-01

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

  15. Effects of Combined Stellar Feedback on Star Formation in Stellar Clusters

    NASA Astrophysics Data System (ADS)

    Wall, Joshua Edward; McMillan, Stephen; Pellegrino, Andrew; Mac Low, Mordecai; Klessen, Ralf; Portegies Zwart, Simon

    2018-01-01

    We present results of hybrid MHD+N-body simulations of star cluster formation and evolution including self consistent feedback from the stars in the form of radiation, winds, and supernovae from all stars more massive than 7 solar masses. The MHD is modeled with the adaptive mesh refinement code FLASH, while the N-body computations are done with a direct algorithm. Radiation is modeled using ray tracing along long characteristics in directions distributed using the HEALPIX algorithm, and causes ionization and momentum deposition, while winds and supernova conserve momentum and energy during injection. Stellar evolution is followed using power-law fits to evolution models in SeBa. We use a gravity bridge within the AMUSE framework to couple the N-body dynamics of the stars to the gas dynamics in FLASH. Feedback from the massive stars alters the structure of young clusters as gas ejection occurs. We diagnose this behavior by distinguishing between fractal distribution and central clustering using a Q parameter computed from the minimum spanning tree of each model cluster. Global effects of feedback in our simulations will also be discussed.

  16. Clustering in Cell Cycle Dynamics with General Response/Signaling Feedback

    PubMed Central

    Young, Todd R.; Fernandez, Bastien; Buckalew, Richard; Moses, Gregory; Boczko, Erik M.

    2011-01-01

    Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call Responsive/Signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behaviour of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as “uniform” solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments. PMID:22001733

  17. Positive feedback can lead to dynamic nanometer-scale clustering on cell membranes

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

    Wehrens, Martijn; Rein ten Wolde, Pieter; Mugler, Andrew, E-mail: amugler@purdue.edu

    2014-11-28

    Clustering of molecules on biological membranes is a widely observed phenomenon. A key example is the clustering of the oncoprotein Ras, which is known to be important for signal transduction in mammalian cells. Yet, the mechanism by which Ras clusters form and are maintained remains unclear. Recently, it has been discovered that activated Ras promotes further Ras activation. Here we show using particle-based simulation that this positive feedback is sufficient to produce persistent clusters of active Ras molecules at the nanometer scale via a dynamic nucleation mechanism. Furthermore, we find that our cluster statistics are consistent with experimental observations ofmore » the Ras system. Interestingly, we show that our model does not support a Turing regime of macroscopic reaction-diffusion patterning, and therefore that the clustering we observe is a purely stochastic effect, arising from the coupling of positive feedback with the discrete nature of individual molecules. These results underscore the importance of stochastic and dynamic properties of reaction diffusion systems for biological behavior.« less

  18. Measuring consistent masses for 25 Milky Way globular clusters

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

    Kimmig, Brian; Seth, Anil; Ivans, Inese I.

    2015-02-01

    We present central velocity dispersions, masses, mass-to-light ratios (M/Ls ), and rotation strengths for 25 Galactic globular clusters (GCs). We derive radial velocities of 1951 stars in 12 GCs from single order spectra taken with Hectochelle on the MMT telescope. To this sample we add an analysis of available archival data of individual stars. For the full set of data we fit King models to derive consistent dynamical parameters for the clusters. We find good agreement between single-mass King models and the observed radial dispersion profiles. The large, uniform sample of dynamical masses we derive enables us to examine trendsmore » of M/L with cluster mass and metallicity. The overall values of M/L and the trends with mass and metallicity are consistent with existing measurements from a large sample of M31 clusters. This includes a clear trend of increasing M/L with cluster mass and lower than expected M/Ls for the metal-rich clusters. We find no clear trend of increasing rotation with increasing cluster metallicity suggested in previous work.« less

  19. Star-forming galaxies in intermediate-redshift clusters: stellar versus dynamical masses of luminous compact blue galaxies

    NASA Astrophysics Data System (ADS)

    Randriamampandry, S. M.; Crawford, S. M.; Bershady, M. A.; Wirth, G. D.; Cress, C. M.

    2017-10-01

    We investigate the stellar masses of the class of star-forming objects known as luminous compact blue galaxies (LCBGs) by studying a sample of galaxies in the distant cluster MS 0451.6-0305 at z ≈ 0.54 with ground-based multicolour imaging and spectroscopy. For a sample of 16 spectroscopically confirmed cluster LCBGs (colour B - V < 0.5, surface brightness μB < 21 mag arcsec-2 and magnitude MB < -18.5), we measure stellar masses by fitting spectral energy distribution (SED) models to multiband photometry, and compare with dynamical masses [determined from velocity dispersion in the range 10 < σv(km s- 1) < 80] we previously obtained from their emission-line spectra. We compare two different stellar population models that measure stellar mass in star-bursting galaxies, indicating correlations between the stellar age, extinction and stellar mass derived from the two different SED models. The stellar masses of cluster LCBGs are distributed similarly to those of field LCBGs, but the cluster LCBGs show lower dynamical-to-stellar mass ratios (Mdyn/M⋆ = 2.6) than their field LCBG counterparts (Mdyn/M⋆ = 4.8), echoing trends noted previously in low-redshift dwarf elliptical galaxies. Within this limited sample, the specific star formation rate declines steeply with increasing mass, suggesting that these cluster LCBGs have undergone vigorous star formation.

  20. Experimental and theoretical investigation of the magnetization dynamics of an artificial square spin ice cluster

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

    Pohlit, Merlin, E-mail: pohlit@physik.uni-frankfurt.de; Porrati, Fabrizio; Huth, Michael

    We study the magnetization dynamics of a spin ice cluster which is a building block of an artificial square spin ice fabricated by focused electron-beam-induced deposition both experimentally and theoretically. The spin ice cluster is composed of twelve interacting Co nanoislands grown directly on top of a high-resolution micro-Hall sensor. By employing micromagnetic simulations and a macrospin model, we calculate the magnetization and the experimentally investigated stray field emanating from a single nanoisland. The parameters determined from a comparison with the experimental hysteresis loop are used to derive an effective single-dipole macrospin model that allows us to investigate the dynamicsmore » of the spin ice cluster. Our model reproduces the experimentally observed non-deterministic sequences in the magnetization curves as well as the distinct temperature dependence of the hysteresis loop.« less

  1. Density-based cluster algorithms for the identification of core sets

    NASA Astrophysics Data System (ADS)

    Lemke, Oliver; Keller, Bettina G.

    2016-10-01

    The core-set approach is a discretization method for Markov state models of complex molecular dynamics. Core sets are disjoint metastable regions in the conformational space, which need to be known prior to the construction of the core-set model. We propose to use density-based cluster algorithms to identify the cores. We compare three different density-based cluster algorithms: the CNN, the DBSCAN, and the Jarvis-Patrick algorithm. While the core-set models based on the CNN and DBSCAN clustering are well-converged, constructing core-set models based on the Jarvis-Patrick clustering cannot be recommended. In a well-converged core-set model, the number of core sets is up to an order of magnitude smaller than the number of states in a conventional Markov state model with comparable approximation error. Moreover, using the density-based clustering one can extend the core-set method to systems which are not strongly metastable. This is important for the practical application of the core-set method because most biologically interesting systems are only marginally metastable. The key point is to perform a hierarchical density-based clustering while monitoring the structure of the metric matrix which appears in the core-set method. We test this approach on a molecular-dynamics simulation of a highly flexible 14-residue peptide. The resulting core-set models have a high spatial resolution and can distinguish between conformationally similar yet chemically different structures, such as register-shifted hairpin structures.

  2. Persistent Topology and Metastable State in Conformational Dynamics

    PubMed Central

    Chang, Huang-Wei; Bacallado, Sergio; Pande, Vijay S.; Carlsson, Gunnar E.

    2013-01-01

    The large amount of molecular dynamics simulation data produced by modern computational models brings big opportunities and challenges to researchers. Clustering algorithms play an important role in understanding biomolecular kinetics from the simulation data, especially under the Markov state model framework. However, the ruggedness of the free energy landscape in a biomolecular system makes common clustering algorithms very sensitive to perturbations of the data. Here, we introduce a data-exploratory tool which provides an overview of the clustering structure under different parameters. The proposed Multi-Persistent Clustering analysis combines insights from recent studies on the dynamics of systems with dominant metastable states with the concept of multi-dimensional persistence in computational topology. We propose to explore the clustering structure of the data based on its persistence on scale and density. The analysis provides a systematic way to discover clusters that are robust to perturbations of the data. The dominant states of the system can be chosen with confidence. For the clusters on the borderline, the user can choose to do more simulation or make a decision based on their structural characteristics. Furthermore, our multi-resolution analysis gives users information about the relative potential of the clusters and their hierarchical relationship. The effectiveness of the proposed method is illustrated in three biomolecules: alanine dipeptide, Villin headpiece, and the FiP35 WW domain. PMID:23565139

  3. Small Modifications to Network Topology Can Induce Stochastic Bistable Spiking Dynamics in a Balanced Cortical Model

    PubMed Central

    McDonnell, Mark D.; Ward, Lawrence M.

    2014-01-01

    Abstract Directed random graph models frequently are used successfully in modeling the population dynamics of networks of cortical neurons connected by chemical synapses. Experimental results consistently reveal that neuronal network topology is complex, however, in the sense that it differs statistically from a random network, and differs for classes of neurons that are physiologically different. This suggests that complex network models whose subnetworks have distinct topological structure may be a useful, and more biologically realistic, alternative to random networks. Here we demonstrate that the balanced excitation and inhibition frequently observed in small cortical regions can transiently disappear in otherwise standard neuronal-scale models of fluctuation-driven dynamics, solely because the random network topology was replaced by a complex clustered one, whilst not changing the in-degree of any neurons. In this network, a small subset of cells whose inhibition comes only from outside their local cluster are the cause of bistable population dynamics, where different clusters of these cells irregularly switch back and forth from a sparsely firing state to a highly active state. Transitions to the highly active state occur when a cluster of these cells spikes sufficiently often to cause strong unbalanced positive feedback to each other. Transitions back to the sparsely firing state rely on occasional large fluctuations in the amount of non-local inhibition received. Neurons in the model are homogeneous in their intrinsic dynamics and in-degrees, but differ in the abundance of various directed feedback motifs in which they participate. Our findings suggest that (i) models and simulations should take into account complex structure that varies for neuron and synapse classes; (ii) differences in the dynamics of neurons with similar intrinsic properties may be caused by their membership in distinctive local networks; (iii) it is important to identify neurons that share physiological properties and location, but differ in their connectivity. PMID:24743633

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

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

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

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

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

    NASA Astrophysics Data System (ADS)

    Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong

    2014-06-01

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

  6. Stellar-mass black holes in young massive and open stellar clusters and their role in gravitational-wave generation - II

    NASA Astrophysics Data System (ADS)

    Banerjee, Sambaran

    2018-01-01

    The study of stellar-remnant black holes (BH) in dense stellar clusters is now in the spotlight, especially due to their intrinsic ability to form binary black holes (BBH) through dynamical encounters, which potentially coalesce via gravitational-wave (GW) radiation. In this work, which is a continuation from a recent study (Paper I), additional models of compact stellar clusters with initial masses ≲ 105 M⊙ and also those with small fractions of primordial binaries (≲ 10 per cent) are evolved for long term, applying the direct N-body approach, assuming state-of-the-art stellar-wind and remnant-formation prescriptions. That way, a substantially broader range of computed models than that in Paper I is achieved. As in Paper I, the general-relativistic BBH mergers continue to be mostly mediated by triples that are bound to the clusters rather than happen among the ejected BBHs. In fact, the number of such in situ BBH mergers, per cluster, tends to increase significantly with the introduction of a small population of primordial binaries. Despite the presence of massive primordial binaries, the merging BBHs, especially the in situ ones, are found to be exclusively dynamically assembled and hence would be spin-orbit misaligned. The BBHs typically traverse through both the LISA's and the LIGO's detection bands, being audible to both instruments. The 'dynamical heating' of the BHs keeps the electron-capture-supernova (ECS) neutron stars (NS) from effectively mass segregating and participating in exchange interactions; the dynamically active BHs would also exchange into any NS binary within ≲1 Gyr. Such young massive and open clusters have the potential to contribute to the dynamical BBH merger detection rate to a similar extent as their more massive globular-cluster counterparts.

  7. Evolution of the Mass and Luminosity Functions of Globular Star Clusters

    NASA Astrophysics Data System (ADS)

    Goudfrooij, Paul; Fall, S. Michael

    2016-12-01

    We reexamine the dynamical evolution of the mass and luminosity functions of globular star clusters (GCMF and GCLF). Fall & Zhang (2001, FZ01) showed that a power-law MF, as commonly seen among young cluster systems, would evolve by dynamical processes over a Hubble time into a peaked MF with a shape very similar to the observed GCMF in the Milky Way and other galaxies. To simplify the calculations, the semi-analytical FZ01 model adopted the “classical” theory of stellar escape from clusters, and neglected variations in the M/L ratios of clusters. Kruijssen & Portegies Zwart (2009, KPZ09) modified the FZ01 model to include “retarded” and mass-dependent stellar escape, the latter causing significant M/L variations. KPZ09 asserted that their model was compatible with observations, whereas the FZ01 model was not. We show here that this claim is not correct; the FZ01 and KPZ09 models fit the observed Galactic GCLF equally well. We also show that there is no detectable correlation between M/L and L for GCs in the Milky Way and Andromeda galaxies, in contradiction with the KPZ09 model. Our comparisons of the FZ01 and KPZ09 models with observations can be explained most simply if stars escape at rates approaching the classical limit for high-mass clusters, as expected on theoretical grounds.

  8. Dynamical Organization of Syntaxin-1A at the Presynaptic Active Zone

    PubMed Central

    Ullrich, Alexander; Böhme, Mathias A.; Schöneberg, Johannes; Depner, Harald; Sigrist, Stephan J.; Noé, Frank

    2015-01-01

    Synaptic vesicle fusion is mediated by SNARE proteins forming in between synaptic vesicle (v-SNARE) and plasma membrane (t-SNARE), one of which is Syntaxin-1A. Although exocytosis mainly occurs at active zones, Syntaxin-1A appears to cover the entire neuronal membrane. By using STED super-resolution light microscopy and image analysis of Drosophila neuro-muscular junctions, we show that Syntaxin-1A clusters are more abundant and have an increased size at active zones. A computational particle-based model of syntaxin cluster formation and dynamics is developed. The model is parametrized to reproduce Syntaxin cluster-size distributions found by STED analysis, and successfully reproduces existing FRAP results. The model shows that the neuronal membrane is adjusted in a way to strike a balance between having most syntaxins stored in large clusters, while still keeping a mobile fraction of syntaxins free or in small clusters that can efficiently search the membrane or be traded between clusters. This balance is subtle and can be shifted toward almost no clustering and almost complete clustering by modifying the syntaxin interaction energy on the order of only 1 kBT. This capability appears to be exploited at active zones. The larger active-zone syntaxin clusters are more stable and provide regions of high docking and fusion capability, whereas the smaller clusters outside may serve as flexible reserve pool or sites of spontaneous ectopic release. PMID:26367029

  9. Review of Recent Development of Dynamic Wind Farm Equivalent Models Based on Big Data Mining

    NASA Astrophysics Data System (ADS)

    Wang, Chenggen; Zhou, Qian; Han, Mingzhe; Lv, Zhan’ao; Hou, Xiao; Zhao, Haoran; Bu, Jing

    2018-04-01

    Recently, the big data mining method has been applied in dynamic wind farm equivalent modeling. In this paper, its recent development with present research both domestic and overseas is reviewed. Firstly, the studies of wind speed prediction, equivalence and its distribution in the wind farm are concluded. Secondly, two typical approaches used in the big data mining method is introduced, respectively. For single wind turbine equivalent modeling, it focuses on how to choose and identify equivalent parameters. For multiple wind turbine equivalent modeling, the following three aspects are concentrated, i.e. aggregation of different wind turbine clusters, the parameters in the same cluster, and equivalence of collector system. Thirdly, an outlook on the development of dynamic wind farm equivalent models in the future is discussed.

  10. 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.

  11. A Kinematic Survey in the Perseus Molecular Cloud: Results from the APOGEE Infrared Survey of Young Nebulous Clusters (IN-SYNC)

    NASA Astrophysics Data System (ADS)

    Covey, Kevin R.; Cottaar, M.; Foster, J. B.; Nidever, D. L.; Meyer, M.; Tan, J.; Da Rio, N.; Flaherty, K. M.; Stassun, K.; Frinchaboy, P. M.; Majewski, S.; APOGEE IN-SYNC Team

    2014-01-01

    Demographic studies of stellar clusters indicate that relatively few persist as bound structures for 100 Myrs or longer. If cluster dispersal is a 'violent' process, it could strongly influence the formation and early evolution of stellar binaries and planetary systems. Unfortunately, measuring the dynamical state of 'typical' (i.e., ~300-1000 member) young star clusters has been difficult, particularly for clusters still embedded within their parental molecular cloud. The near-infrared spectrograph for the Apache Point Observatory Galactic Evolution Experiment (APOGEE), which can measure precise radial velocities for 230 cluster stars simultaneously, is uniquely suited to diagnosing the dynamics of Galactic star formation regions. We give an overview of the INfrared Survey of Young Nebulous Clusters (IN-SYNC), an APOGEE ancillary science program that is carrying out a comparative study of young clusters in the Perseus molecular cloud: NGC 1333, a heavily embedded cluster, and IC 348, which has begun to disperse its surrounding molecular gas. These observations appear to rule out a significantly super-virial velocity dispersion in IC 348, contrary to predictions of models where a cluster's dynamics is strongly influenced by the dispersal of its primordial gas. We also summarize the properties of two newly identified spectroscopic binaries; binary systems such as these play a key role in the dynamical evolution of young clusters, and introduce velocity offsets that must be accounted for in measuring cluster velocity dispersions.

  12. Invasive advance of an advantageous mutation: nucleation theory.

    PubMed

    O'Malley, Lauren; Basham, James; Yasi, Joseph A; Korniss, G; Allstadt, Andrew; Caraco, Thomas

    2006-12-01

    For sedentary organisms with localized reproduction, spatially clustered growth drives the invasive advance of a favorable mutation. We model competition between two alleles where recurrent mutation introduces a genotype with a rate of local propagation exceeding the resident's rate. We capture ecologically important properties of the rare invader's stochastic dynamics by assuming discrete individuals and local neighborhood interactions. To understand how individual-level processes may govern population patterns, we invoke the physical theory for nucleation of spatial systems. Nucleation theory discriminates between single-cluster and multi-cluster dynamics. A sufficiently low mutation rate, or a sufficiently small environment, generates single-cluster dynamics, an inherently stochastic process; a favorable mutation advances only if the invader cluster reaches a critical radius. For this mode of invasion, we identify the probability distribution of waiting times until the favored allele advances to competitive dominance, and we ask how the critical cluster size varies as propagation or mortality rates vary. Increasing the mutation rate or system size generates multi-cluster invasion, where spatial averaging produces nearly deterministic global dynamics. For this process, an analytical approximation from nucleation theory, called Avrami's Law, describes the time-dependent behavior of the genotype densities with remarkable accuracy.

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  14. Relaxation dynamics of maximally clustered networks

    NASA Astrophysics Data System (ADS)

    Klaise, Janis; Johnson, Samuel

    2018-01-01

    We study the relaxation dynamics of fully clustered networks (maximal number of triangles) to an unclustered state under two different edge dynamics—the double-edge swap, corresponding to degree-preserving randomization of the configuration model, and single edge replacement, corresponding to full randomization of the Erdős-Rényi random graph. We derive expressions for the time evolution of the degree distribution, edge multiplicity distribution and clustering coefficient. We show that under both dynamics networks undergo a continuous phase transition in which a giant connected component is formed. We calculate the position of the phase transition analytically using the Erdős-Rényi phenomenology.

  15. Early dynamical evolution of substructured stellar clusters

    NASA Astrophysics Data System (ADS)

    Dorval, Julien; Boily, Christian

    2015-08-01

    It is now widely accepted that stellar clusters form with a high level of substructure (Kuhn et al. 2014, Bate 2009), inherited from the molecular cloud and the star formation process. Evidence from observations and simulations also indicate the stars in such young clusters form a subvirial system (Kirk et al. 2007, Maschberger et al. 2010). The subsequent dynamical evolution can cause important mass loss, ejecting a large part of the birth population in the field. It can also imprint the stellar population and still be inferred from observations of evolved clusters. Nbody simulations allow a better understanding of these early twists and turns, given realistic initial conditions. Nowadays, substructured, clumpy young clusters are usually obtained through pseudo-fractal growth (Goodwin et al. 2004) and velocity inheritance. Such models are visually realistics and are very useful, they are however somewhat artificial in their velocity distribution. I introduce a new way to create clumpy initial conditions through a "Hubble expansion" which naturally produces self consistent clumps, velocity-wise. A velocity distribution analysis shows the new method produces realistic models, consistent with the dynamical state of the newly created cores in hydrodynamic simulation of cluster formation (Klessen & Burkert 2000). I use these initial conditions to investigate the dynamical evolution of young subvirial clusters, up to 80000 stars. I find an overall soft evolution, with hierarchical merging leading to a high level of mass segregation. I investigate the influence of the mass function on the fate of the cluster, specifically on the amount of mass loss induced by the early violent relaxation. Using a new binary detection algorithm, I also find a strong processing of the native binary population.

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

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

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

    2013-08-01

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

  17. The dynamics of aloof baby Skyrmions

    DOE PAGES

    Salmi, Petja; Sutcliffe, Paul

    2016-01-25

    The aloof baby Skyrme model is a (2+1)-dimensional theory with solitons that are lightly bound. It is a low-dimensional analogue of a similar Skyrme model in (3+1)- dimensions, where the lightly bound solitons have binding energies comparable to nuclei. A previous study of static solitons in the aloof baby Skyrme model revealed that multi-soliton bound states have a cluster structure, with constituents that preserve their individual identities due to the short-range repulsion and long-range attraction between solitons. Furthermore, there are many different local energy minima that are all well-described by a simple binary species particle model. In this paper wemore » present the first results on soliton dynamics in the aloof baby Skyrme model. Numerical field theory simulations reveal that the lightly bound cluster structure results in a variety of exotic soliton scattering events that are novel in comparison to standard Skyrmion scattering. A dynamical version of the binary species point particle model is shown to provide a good qualitative description of the dynamics.« less

  18. The dynamics of aloof baby Skyrmions

    NASA Astrophysics Data System (ADS)

    Salmi, Petja; Sutcliffe, Paul

    2016-01-01

    The aloof baby Skyrme model is a (2+1)-dimensional theory with solitons that are lightly bound. It is a low-dimensional analogue of a similar Skyrme model in (3+1)-dimensions, where the lightly bound solitons have binding energies comparable to nuclei. A previous study of static solitons in the aloof baby Skyrme model revealed that multi-soliton bound states have a cluster structure, with constituents that preserve their individual identities due to the short-range repulsion and long-range attraction between solitons. Furthermore, there are many different local energy minima that are all well-described by a simple binary species particle model. In this paper we present the first results on soliton dynamics in the aloof baby Skyrme model. Numerical field theory simulations reveal that the lightly bound cluster structure results in a variety of exotic soliton scattering events that are novel in comparison to standard Skyrmion scattering. A dynamical version of the binary species point particle model is shown to provide a good qualitative description of the dynamics.

  19. Clustering and assembly dynamics of a one-dimensional microphase former.

    PubMed

    Hu, Yi; Charbonneau, Patrick

    2018-05-23

    Both ordered and disordered microphases ubiquitously form in suspensions of particles that interact through competing short-range attraction and long-range repulsion (SALR). While ordered microphases are more appealing materials targets, understanding the rich structural and dynamical properties of their disordered counterparts is essential to controlling their mesoscale assembly. Here, we study the disordered regime of a one-dimensional (1D) SALR model, whose simplicity enables detailed analysis by transfer matrices and Monte Carlo simulations. We first characterize the signature of the clustering process on macroscopic observables, and then assess the equilibration dynamics of various simulation algorithms. We notably find that cluster moves markedly accelerate the mixing time, but that event chains are of limited help in the clustering regime. These insights will inspire further study of three-dimensional microphase formers.

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

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

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

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

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

    DOE PAGES

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

    2016-08-19

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

  2. Clustering determines the dynamics of complex contagions in multiplex networks

    NASA Astrophysics Data System (ADS)

    Zhuang, Yong; Arenas, Alex; Yaǧan, Osman

    2017-01-01

    We present the mathematical analysis of generalized complex contagions in a class of clustered multiplex networks. The model is intended to understand spread of influence, or any other spreading process implying a threshold dynamics, in setups of interconnected networks with significant clustering. The contagion is assumed to be general enough to account for a content-dependent linear threshold model, where each link type has a different weight (for spreading influence) that may depend on the content (e.g., product, rumor, political view) that is being spread. Using the generating functions formalism, we determine the conditions, probability, and expected size of the emergent global cascades. This analysis provides a generalization of previous approaches and is especially useful in problems related to spreading and percolation. The results present nontrivial dependencies between the clustering coefficient of the networks and its average degree. In particular, several phase transitions are shown to occur depending on these descriptors. Generally speaking, our findings reveal that increasing clustering decreases the probability of having global cascades and their size, however, this tendency changes with the average degree. There exists a certain average degree from which on clustering favors the probability and size of the contagion. By comparing the dynamics of complex contagions over multiplex networks and their monoplex projections, we demonstrate that ignoring link types and aggregating network layers may lead to inaccurate conclusions about contagion dynamics, particularly when the correlation of degrees between layers is high.

  3. Stochastic cellular automata model for stock market dynamics

    NASA Astrophysics Data System (ADS)

    Bartolozzi, M.; Thomas, A. W.

    2004-04-01

    In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, σi (t)=+1 , or sell, σi (t)=-1 , a stock at a certain discrete time step. The remaining cells are inactive, σi (t)=0 . The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P500 index.

  4. A cluster expansion model for predicting activation barrier of atomic processes

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

    Rehman, Tafizur; Jaipal, M.; Chatterjee, Abhijit, E-mail: achatter@iitk.ac.in

    2013-06-15

    We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEBmore » results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog.« less

  5. Spatial dynamics of invasion: the geometry of introduced species.

    PubMed

    Korniss, Gyorgy; Caraco, Thomas

    2005-03-07

    Many exotic species combine low probability of establishment at each introduction with rapid population growth once introduction does succeed. To analyse this phenomenon, we note that invaders often cluster spatially when rare, and consequently an introduced exotic's population dynamics should depend on locally structured interactions. Ecological theory for spatially structured invasion relies on deterministic approximations, and determinism does not address the observed uncertainty of the exotic-introduction process. We take a new approach to the population dynamics of invasion and, by extension, to the general question of invasibility in any spatial ecology. We apply the physical theory for nucleation of spatial systems to a lattice-based model of competition between plant species, a resident and an invader, and the analysis reaches conclusions that differ qualitatively from the standard ecological theories. Nucleation theory distinguishes between dynamics of single- and multi-cluster invasion. Low introduction rates and small system size produce single-cluster dynamics, where success or failure of introduction is inherently stochastic. Single-cluster invasion occurs only if the cluster reaches a critical size, typically preceded by a number of failed attempts. For this case, we identify the functional form of the probability distribution of time elapsing until invasion succeeds. Although multi-cluster invasion for sufficiently large systems exhibits spatial averaging and almost-deterministic dynamics of the global densities, an analytical approximation from nucleation theory, known as Avrami's law, describes our simulation results far better than standard ecological approximations.

  6. HOW SIGNIFICANT IS RADIATION PRESSURE IN THE DYNAMICS OF THE GAS AROUND YOUNG STELLAR CLUSTERS?

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

    Silich, Sergiy; Tenorio-Tagle, Guillermo, E-mail: silich@inaoep.mx

    2013-03-01

    The impact of radiation pressure on the dynamics of the gas in the vicinity of young stellar clusters is thoroughly discussed. The radiation over the thermal/ram pressure ratio time evolution is calculated explicitly and the crucial roles of the cluster mechanical power, the strong time evolution of the ionizing photon flux, and the bolometric luminosity of the exciting cluster are stressed. It is shown that radiation has only a narrow window of opportunity to dominate the wind-driven shell dynamics. This may occur only at early stages of the bubble evolution and if the shell expands into a dusty and/or amore » very dense proto-cluster medium. The impact of radiation pressure on the wind-driven shell always becomes negligible after about 3 Myr. Finally, the wind-driven model results allow one to compare the model predictions with the distribution of thermal pressure derived from X-ray observations. The shape of the thermal pressure profile then allows us to distinguish between the energy and the momentum-dominated regimes of expansion and thus conclude whether radiative losses of energy or the leakage of hot gas from the bubble interior have been significant during bubble evolution.« less

  7. Ab initio molecular dynamics simulation of binary Cu64Zr36 bulk metallic glass: Validation of the cluster-plus-glue-atom model

    NASA Astrophysics Data System (ADS)

    Tian, Hua; Zhang, Chong; Wang, Lu; Zhao, JiJun; Dong, Chuang; Wen, Bin; Wang, Qing

    2011-06-01

    We have performed ab initio molecular dynamics simulation of Cu64Zr36 alloy at descending temperatures (from 2000 K to 400 K) and discussed the evolution of short-range order with temperature. The pair-correlation functions, coordination numbers, and chemical compositions of the most abundant local clusters have been analyzed. We found that icosahedral short-range order exists in the liquid, undercooled, and glass states, and it becomes dominant in the glass states. Moreover, we demonstrated the existence of Cu-centered Cu8Zr5 icosahedral clusters as the major local structural unit in the Cu64Zr36 amorphous alloy. This finding agrees well with our previous cluster model of Cu-Zr-based BMG as well as experimental evidences from synchrotron x ray and neutron diffraction measurements.

  8. Electron and nuclear dynamics of molecular clusters in ultraintense laser fields. III. Coulomb explosion of deuterium clusters.

    PubMed

    Last, Isidore; Jortner, Joshua

    2004-08-15

    In this paper we present a theoretical and computational study of the energetics and temporal dynamics of Coulomb explosion of molecular clusters of deuterium (D2)n/2 (n = 480 - 7.6 x 10(4), cluster radius R0 = 13.1 - 70 A) in ultraintense laser fields (laser peak intensity I = 10(15) - 10(20)W cm(-2)). The energetics of Coulomb explosion was inferred from the dependence of the maximal energy EM and the average energy Eav of the product D+ ions on the laser intensity, the laser pulse shape, the cluster radius, and the laser frequency. Electron dynamics of outer cluster ionization and nuclear dynamics of Coulomb explosion were investigated by molecular dynamics simulations. Several distinct laser pulse shape envelopes, involving a rectangular field, a Gaussian field, and a truncated Gaussian field, were employed to determine the validity range of the cluster vertical ionization (CVI) approximation. The CVI predicts that Eav, EM proportional to R0(2) and that the energy distribution is P(E) proportional to E1/2. For a rectangular laser pulse the CVI conditions are satisfied when complete outer ionization is obtained, with the outer ionization time toi being shorter than both the pulse width and the cluster radius doubling time tau2. By increasing toi, due to the increase of R0 or the decrease of I, we have shown that the deviation of Eav from the corresponding CVI value (Eav(CVI)) is (Eav(CVI) - Eav)/Eav(CVI) approximately (toi/2.91tau2)2. The Gaussian pulses trigger outer ionization induced by adiabatic following of the laser field and of the cluster size, providing a pseudo-CVI behavior at sufficiently large laser fields. The energetics manifest the existence of a finite range of CVI size dependence, with the validity range for the applicability of the CVI being R0 < or = (R0)I, with (R0)I representing an intensity dependent boundary radius. Relating electron dynamics of outer ionization to nuclear dynamics for Coulomb explosion induced by a Gaussian pulse, the boundary radius (R0)I and the corresponding ion average energy (Eav)I were inferred from simulations and described in terms of an electrostatic model. Two independent estimates of (R0)I, which involve the cluster size where the CVI relation breaks down and the cluster size for the attainment of complete outer ionization, are in good agreement with each other, as well as with the electrostatic model for cluster barrier suppression. The relation (Eav)I proportional to (R0)I(2) provides the validity range of the pseudo-CVI domain for the cluster sizes and laser intensities, where the energetics of D+ ions produced by Coulomb explosion of (D)n clusters is optimized. The currently available experimental data [Madison et al., Phys. Plasmas 11, 1 (2004)] for the energetics of Coulomb explosion of (D)n clusters (Eav = 5 - 7 keV at I = 2 x 10(18) W cm(-2)), together with our simulation data, lead to the estimates of R0 = 51 - 60 A, which exceed the experimental estimate of R0 = 45 A. The predicted anisotropy of the D+ ion energies in the Coulomb explosion at I = 10(18) W cm(-2) is in accord with experiment. We also explored the laser frequency dependence of the energetics of Coulomb explosion in the range nu = 0.1 - 2.1 fs(-1) (lambda = 3000 - 140 nm), which can be rationalized in terms of the electrostatic model. (c) 2004 American Institute of Physics.

  9. Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

    DOE PAGES

    Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

    2015-04-01

    The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu 40Zr 51Al 9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at T x ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (T m ~ 900K),more » and the crossover temperature is roughly twice of the glass-transition temperature (T g). Below T x, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below T x and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.« less

  10. Price Formation Based on Particle-Cluster Aggregation

    NASA Astrophysics Data System (ADS)

    Wang, Shijun; Zhang, Changshui

    In the present work, we propose a microscopic model of financial markets based on particle-cluster aggregation on a two-dimensional small-world information network in order to simulate the dynamics of the stock markets. "Stylized facts" of the financial market time series, such as fat-tail distribution of returns, volatility clustering and multifractality, are observed in the model. The results of the model agree with empirical data taken from historical records of the daily closures of the NYSE composite index.

  11. Study of Clusters and Hypernuclei production within PHSD+FRIGA model

    NASA Astrophysics Data System (ADS)

    Kireyeu, V.; Le Fèvre, A.; Bratkovskaya, E.

    2017-01-01

    We report on the results on the dynamical modelling of cluster formation with the new combined PHSD+FRIGA model at Nuclotron and NICA energies. The FRIGA clusterisation algorithm, which can be applied to the transport models, is based on the simulated annealing technique to obtain the most bound configuration of fragments and nucleons. The PHSD+FRIGA model is able to predict isotope yields as well as hyper-nucleus production. Based on present predictions of the combined model we study the possibility to detect such clusters and hypernuclei in the BM@N and MPD/NICA detectors.

  12. An opinion-driven behavioral dynamics model for addictive behaviors

    NASA Astrophysics Data System (ADS)

    Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; Ambrose, Bridget K.; Brodsky, Nancy S.; Brown, Theresa J.; Husten, Corinne; Glass, Robert J.

    2015-04-01

    We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual's behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters provide targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. This has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.

  13. Formation and Assembly of Massive Star Clusters

    NASA Astrophysics Data System (ADS)

    McMillan, Stephen

    The formation of stars and star clusters is a major unresolved problem in astrophysics. It is central to modeling stellar populations and understanding galaxy luminosity distributions in cosmological models. Young massive clusters are major components of starburst galaxies, while globular clusters are cornerstones of the cosmic distance scale and represent vital laboratories for studies of stellar dynamics and stellar evolution. Yet how these clusters form and how rapidly and efficiently they expel their natal gas remain unclear, as do the consequences of this gas expulsion for cluster structure and survival. Also unclear is how the properties of low-mass clusters, which form from small-scale instabilities in galactic disks and inform much of our understanding of cluster formation and star-formation efficiency, differ from those of more massive clusters, which probably formed in starburst events driven by fast accretion at high redshift, or colliding gas flows in merging galaxies. Modeling cluster formation requires simulating many simultaneous physical processes, placing stringent demands on both software and hardware. Simulations of galaxies evolving in cosmological contexts usually lack the numerical resolution to simulate star formation in detail. They do not include detailed treatments of important physical effects such as magnetic fields, radiation pressure, ionization, and supernova feedback. Simulations of smaller clusters include these effects, but fall far short of the mass of even single young globular clusters. With major advances in computing power and software, we can now directly address this problem. We propose to model the formation of massive star clusters by integrating the FLASH adaptive mesh refinement magnetohydrodynamics (MHD) code into the Astrophysical Multi-purpose Software Environment (AMUSE) framework, to work with existing stellar-dynamical and stellar evolution modules in AMUSE. All software will be freely distributed on-line, allowing open access to state-of- the-art simulation techniques within a modern, modular software environment. We will follow the gravitational collapse of 0.1-10 million-solar mass gas clouds through star formation and coalescence into a star cluster, modeling in detail the coupling of the gas and the newborn stars. We will study the effects of star formation by detecting accreting regions of gas in self-gravitating, turbulent, MHD, FLASH models that we will translate into collisional dynamical systems of stars modeled with an N-body code, coupled together in the AMUSE framework. Our FLASH models will include treatments of radiative transfer from the newly formed stars, including heating and radiative acceleration of the surrounding gas. Specific questions to be addressed are: (1) How efficiently does the gas in a star forming region form stars, how does this depend on mass, metallicity, and other parameters, and what terminates star formation? What observational predictions can be made to constrain our models? (2) How important are different mechanisms for driving turbulence and removing gas from a cluster: accretion, radiative feedback, and mechanical feedback? (3) How does the infant mortality rate of young clusters depend on the initial properties of the parent cloud? (4) What are the characteristic formation timescales of massive star clusters, and what observable imprints does the assembly process leave on their structure at an age of 10-20 Myr, when formation is essentially complete and many clusters can be observed? These studies are directly relevant to NASA missions at many electromagnetic wavelengths, including Chandra, GALEX, Hubble, and Spitzer. Each traces different aspects of cluster formation and evolution: X-rays trace supernovae, ultraviolet traces young stars, visible colors can distinguish between young blue stars and older red stars, and the infrared directly shows young embedded star clusters.

  14. Modified Baryonic Dynamics: two-component cosmological simulations with light sterile neutrinos

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

    Angus, G.W.; Gentile, G.; Diaferio, A.

    2014-10-01

    In this article we continue to test cosmological models centred on Modified Newtonian Dynamics (MOND) with light sterile neutrinos, which could in principle be a way to solve the fine-tuning problems of the standard model on galaxy scales while preserving successful predictions on larger scales. Due to previous failures of the simple MOND cosmological model, here we test a speculative model where the modified gravitational field is produced only by the baryons and the sterile neutrinos produce a purely Newtonian field (hence Modified Baryonic Dynamics). We use two-component cosmological simulations to separate the baryonic N-body particles from the sterile neutrinomore » ones. The premise is to attenuate the over-production of massive galaxy cluster halos which were prevalent in the original MOND plus light sterile neutrinos scenario. Theoretical issues with such a formulation notwithstanding, the Modified Baryonic Dynamics model fails to produce the correct amplitude for the galaxy cluster mass function for any reasonable value of the primordial power spectrum normalisation.« less

  15. Phase diagram and quench dynamics of the cluster-XY spin chain

    NASA Astrophysics Data System (ADS)

    Montes, Sebastián; Hamma, Alioscia

    2012-08-01

    We study the complete phase space and the quench dynamics of an exactly solvable spin chain, the cluster-XY model. In this chain, the cluster term and the XY couplings compete to give a rich phase diagram. The phase diagram is studied by means of the quantum geometric tensor. We study the time evolution of the system after a critical quantum quench using the Loschmidt echo. The structure of the revivals after critical quantum quenches presents a nontrivial behavior depending on the phase of the initial state and the critical point.

  16. Phase diagram and quench dynamics of the cluster-XY spin chain.

    PubMed

    Montes, Sebastián; Hamma, Alioscia

    2012-08-01

    We study the complete phase space and the quench dynamics of an exactly solvable spin chain, the cluster-XY model. In this chain, the cluster term and the XY couplings compete to give a rich phase diagram. The phase diagram is studied by means of the quantum geometric tensor. We study the time evolution of the system after a critical quantum quench using the Loschmidt echo. The structure of the revivals after critical quantum quenches presents a nontrivial behavior depending on the phase of the initial state and the critical point.

  17. Dynamical equivalence, the origin of the Galactic field stellar and binary population, and the initial radius-mass relation of embedded clusters

    NASA Astrophysics Data System (ADS)

    Belloni, Diogo; Kroupa, Pavel; Rocha-Pinto, Helio J.; Giersz, Mirek

    2018-03-01

    In order to allow a better understanding of the origin of Galactic field populations, dynamical equivalence of stellar-dynamical systems has been postulated by Kroupa and Belloni et al. to allow mapping of solutions of the initial conditions of embedded clusters such that they yield, after a period of dynamical processing, the Galactic field population. Dynamically equivalent systems are defined to initially and finally have the same distribution functions of periods, mass ratios and eccentricities of binary stars. Here, we search for dynamically equivalent clusters using the MOCCA code. The simulations confirm that dynamically equivalent solutions indeed exist. The result is that the solution space is next to identical to the radius-mass relation of Marks & Kroupa, ( r_h/pc )= 0.1^{+0.07}_{-0.04} ( M_ecl/M_{⊙} )^{0.13± 0.04}. This relation is in good agreement with the oIMF. This is achieved by applying a similar procedurebserved density of molecular cloud clumps. According to the solutions, the time-scale to reach dynamical equivalence is about 0.5 Myr which is, interestingly, consistent with the lifetime of ultra-compact H II regions and the time-scale needed for gas expulsion to be active in observed very young clusters as based on their dynamical modelling.

  18. On the multi-scale description of micro-structured fluids composed of aggregating rods

    NASA Astrophysics Data System (ADS)

    Perez, Marta; Scheuer, Adrien; Abisset-Chavanne, Emmanuelle; Ammar, Amine; Chinesta, Francisco; Keunings, Roland

    2018-05-01

    When addressing the flow of concentrated suspensions composed of rods, dense clusters are observed. Thus, the adequate modelling and simulation of such a flow requires addressing the kinematics of these dense clusters and their impact on the flow in which they are immersed. In a former work, we addressed a first modelling framework of these clusters, assumed so dense that they were considered rigid and their kinematics (flow-induced rotation) were totally defined by a symmetric tensor c with unit trace representing the cluster conformation. Then, the rigid nature of the clusters was relaxed, assuming them deformable, and a model giving the evolution of both the cluster shape and its microstructural orientation descriptor (the so-called shape and orientation tensors) was proposed. This paper compares the predictions coming from those models with finer-scale discrete simulations inspired from molecular dynamics modelling.

  19. DIRECT N-BODY MODELING OF THE OLD OPEN CLUSTER NGC 188: A DETAILED COMPARISON OF THEORETICAL AND OBSERVED BINARY STAR AND BLUE STRAGGLER POPULATIONS

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

    Geller, Aaron M.; Hurley, Jarrod R.; Mathieu, Robert D., E-mail: a-geller@northwestern.edu, E-mail: mathieu@astro.wisc.edu, E-mail: jhurley@astro.swin.edu.au

    2013-01-01

    Following on from a recently completed radial-velocity survey of the old (7 Gyr) open cluster NGC 188 in which we studied in detail the solar-type hard binaries and blue stragglers of the cluster, here we investigate the dynamical evolution of NGC 188 through a sophisticated N-body model. Importantly, we employ the observed binary properties of the young (180 Myr) open cluster M35, where possible, to guide our choices for parameters of the initial binary population. We apply pre-main-sequence tidal circularization and a substantial increase to the main-sequence tidal circularization rate, both of which are necessary to match the observed tidalmore » circularization periods in the literature, including that of NGC 188. At 7 Gyr the main-sequence solar-type hard-binary population in the model matches that of NGC 188 in both binary frequency and distributions of orbital parameters. This agreement between the model and observations is in a large part due to the similarities between the NGC 188 and M35 solar-type binaries. Indeed, among the 7 Gyr main-sequence binaries in the model, only those with P {approx}> 1000 days begin to show potentially observable evidence for modifications by dynamical encounters, even after 7 Gyr of evolution within the star cluster. This emphasizes the importance of defining accurate initial conditions for star cluster models, which we propose is best accomplished through comparisons with observations of young open clusters like M35. Furthermore, this finding suggests that observations of the present-day binaries in even old open clusters can provide valuable information on their primordial binary populations. However, despite the model's success at matching the observed solar-type main-sequence population, the model underproduces blue stragglers and produces an overabundance of long-period circular main-sequence-white-dwarf binaries as compared with the true cluster. We explore several potential solutions to the paucity of blue stragglers and conclude that the model dramatically underproduces blue stragglers through mass-transfer processes. We suggest that common-envelope evolution may have been incorrectly imposed on the progenitors of the spurious long-period circular main-sequence-white-dwarf binaries, which perhaps instead should have gone through stable mass transfer to create blue stragglers, thereby bringing both the number and binary frequency of the blue straggler population in the model into agreement with the true blue stragglers in NGC 188. Thus, improvements in the physics of mass transfer and common-envelope evolution employed in the model may in fact solve both discrepancies with the observations. This project highlights the unique accessibility of open clusters to both comprehensive observational surveys and full-scale N-body simulations, both of which have only recently matured sufficiently to enable such a project, and underscores the importance of open clusters to the study of star cluster dynamics.« less

  20. GEMINI/GMOS SPECTROSCOPY OF 26 STRONG-LENSING-SELECTED GALAXY CLUSTER CORES

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

    Bayliss, Matthew B.; Gladders, Michael D.; Koester, Benjamin P.

    2011-03-15

    We present results from a spectroscopic program targeting 26 strong-lensing cluster cores that were visually identified in the Sloan Digital Sky Survey (SDSS) and the Second Red-Sequence Cluster Survey (RCS-2). The 26 galaxy cluster lenses span a redshift range of 0.2 < z < 0.65, and our spectroscopy reveals 69 unique background sources with redshifts as high as z = 5.200. We also identify redshifts for 262 cluster member galaxies and measure the velocity dispersions and dynamical masses for 18 clusters where we have redshifts for N {>=} 10 cluster member galaxies. We account for the expected biases in dynamicalmore » masses of strong-lensing-selected clusters as predicted by results from numerical simulations and discuss possible sources of bias in our observations. The median dynamical mass of the 18 clusters with N {>=} 10 spectroscopic cluster members is M {sub Vir} = 7.84 x 10{sup 14} M {sub sun} h {sup -1} {sub 0.7}, which is somewhat higher than predictions for strong-lensing-selected clusters in simulations. The disagreement is not significant considering the large uncertainty in our dynamical data, systematic uncertainties in the velocity dispersion calibration, and limitations of the theoretical modeling. Nevertheless our study represents an important first step toward characterizing large samples of clusters that are identified in a systematic way as systems exhibiting dramatic strong-lensing features.« less

  1. Estimating long-wavelength dynamic topographic change of passive continental margins since the Early Cretaceous

    NASA Astrophysics Data System (ADS)

    Müller, Dietmar; Hassan, Rakib; Gurnis, Michael; Flament, Nicolas; Williams, Simon

    2017-04-01

    The influence of mantle convection on dynamic topographic change along continental margins is difficult to unravel, because their stratigraphic record is dominated by tectonic subsidence caused by rifting. Yet, dynamic topography can potentially introduce significant depth anomalies along passive margins, influencing their water depth, sedimentary environments and geohistory. Here we follow a three-fold approach to estimate changes in dynamic topography along both continental interiors and passive margins based on a set of seven global mantle convection models. These models include different methodologies (forward and hybrid backward-forward methods), different plate reconstructions and alternative mantle rheologies. We demonstrate that a geodynamic forward model that includes adiabatic heating in addition to internal heating from radiogenic sources, and a mantle viscosity profile with a gradual increase in viscosity below the mantle transition zone, provides a greatly improved match to the spectral range of residual topography end-members as compared with previous models at very long wavelengths (spherical degrees 2-3). We combine global sea level estimates with predicted surface dynamic topography to evaluate the match between predicted continental flooding patterns and published paleo-coastlines by comparing predicted versus geologically reconstructed land fractions and spatial overlaps of flooded regions for individual continents since 140 Ma. Modelled versus geologically reconstructed land fractions match within 10% for most models, and the spatial overlaps of inundated regions are mostly between 85% and 100% for the Cenozoic, dropping to about 75-100% in the Cretaceous. We categorise the evolution of modelled dynamic topography in both continental interiors and along passive margins using cluster analysis to investigate how clusters of similar dynamic topography time series are distributed spatially. A subdivision of four clusters is found to best reveal end-members of dynamic topography evolution along passive margins and their hinterlands, differentiating topographic stability, long-term pronounced subsidence, initial stability over a dynamic high followed by moderate subsidence and regions that are relatively proximal to subduction zones with varied dynamic topography histories. Along passive continental margins the most commonly observed process is a gradual move from dynamic highs towards lows during the fragmentation of Pangea, reflecting that many passive margins now overly slabs sinking in the lower mantle. Our best-fit model results in up to 500 ±150 m of total dynamic subsidence of continental interiors while along passive margins the maximum predicted dynamic topographic change over 140 million years is about 350 ±150 m of subsidence. Models with plumes exhibit clusters of transient passive margin uplift of about 200 ±200m. The good overall match between predicted dynamic topography and geologically mapped paleo-coastlines makes a convincing case that mantle-driven topographic change is a critical component of relative sea level change, and one of the main driving forces generating the observed geometries and timings of large-scale shifts in paleo-coastlines.

  2. Nature of the Congested Traffic and Quasi-steady States of the General Motor Models

    NASA Astrophysics Data System (ADS)

    Yang, Bo; Xu, Xihua; Pang, John Z. F.; Monterola, Christopher

    2015-03-01

    We look at the general motor (GM) class microscopic traffic models and analyze some of the universal features of the (multi-)cluster solutions, including the emergence of an intrinsic scale and the quasisoliton dynamics. We show that the GM models can capture the essential physics of the real traffic dynamics, especially the phase transition from the free flow to the congested phase, from which the wide moving jams emerges (the F-S-J transition pioneered by B.S. Kerner). In particular, the congested phase can be associated with either the multi-cluster quasi-steady states, or their more homogeneous precursor states. In both cases the states can last for a long time, and the narrow clusters will eventually grow and merge, leading to the formation of the wide moving jams. We present a general method to fit the empirical parameters so that both quantitative and qualitative macroscopic empirical features can be reproduced with a minimal GM model. We present numerical results for the traffic dynamics both with and without the bottleneck, including various types of spontaneous and induced ``synchronized flow,'' as well as the evolution of wide moving jams. We also discuss its implications to the nature of different phases in traffic dynamics.

  3. Effects of radiation and turbulence on the diabatic heating and water budget of the stratiform region of a tropical cloud cluster

    NASA Technical Reports Server (NTRS)

    Churchill, Dean D.; Houze, Robert A., Jr.

    1991-01-01

    A twi-dimensional kinematic model has been used to diagnose the thermodynamic, water vapor, and hydrometeor fields of the stratiform clouds associated with a mesoscale tropical cloud cluster. The model incorporates ice- and water-cloud microphysics, visible and infrared radiation, and convective adjustment. It is intended to determine the relative contributions of radiation, mycrophysics, and turbulence to diabatic heating, and the effects that radiation has on the water budget of the cluster in the absence of dynamical interactions. The model has been initialized with thermodynamic fields and wind velocities diagnosed from a GATE tropical squall line. It is found that radiation does not directly affect the water budget of the stratiform region, and any radiative effect on hydrometeors must involve interaction with dynamics.

  4. Long memory and volatility clustering: Is the empirical evidence consistent across stock markets?

    NASA Astrophysics Data System (ADS)

    Bentes, Sónia R.; Menezes, Rui; Mendes, Diana A.

    2008-06-01

    Long memory and volatility clustering are two stylized facts frequently related to financial markets. Traditionally, these phenomena have been studied based on conditionally heteroscedastic models like ARCH, GARCH, IGARCH and FIGARCH, inter alia. One advantage of these models is their ability to capture nonlinear dynamics. Another interesting manner to study the volatility phenomenon is by using measures based on the concept of entropy. In this paper we investigate the long memory and volatility clustering for the SP 500, NASDAQ 100 and Stoxx 50 indexes in order to compare the US and European Markets. Additionally, we compare the results from conditionally heteroscedastic models with those from the entropy measures. In the latter, we examine Shannon entropy, Renyi entropy and Tsallis entropy. The results corroborate the previous evidence of nonlinear dynamics in the time series considered.

  5. Nature of multiple-nucleus cluster galaxies

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

    Merritt, D.

    1984-05-01

    In models for the evolution of galaxy clusters which include dynamical friction with the dark binding matter, the distribution of galaxies becomes more concentrated to the cluster center with time. In a cluster like Coma, this evolution could increase by a factor of approximately 3 the probability of finding a galaxy very close to the cluster center, without decreasing the typical velocity of such a galaxy significantly below the cluster mean. Such an enhancement is roughly what is needed to explain the large number of first-ranked cluster galaxies which are observed to have extra ''nuclei''; it is also consistent withmore » the high velocities typically measured for these ''nuclei.'' Unlike the cannibalism model, this model predicts that the majority of multiple-nucleus systems are transient phenomena, and not galaxies in the process of merging.« less

  6. Kinetics of carbon clustering in detonation of high explosives: Does theory match experiment?

    NASA Astrophysics Data System (ADS)

    Velizhanin, Kirill; Watkins, Erik; Dattelbaum, Dana; Gustavsen, Richard; Aslam, Tariq; Podlesak, David; Firestone, Millicent; Huber, Rachel; Ringstrand, Bryan; Willey, Trevor; Bagge-Hansen, Michael; Hodgin, Ralph; Lauderbach, Lisa; van Buuren, Tony; Sinclair, Nicholas; Rigg, Paulo; Seifert, Soenke; Gog, Thomas

    2017-06-01

    Chemical reactions in detonation of carbon-rich high explosives yield carbon clusters as major constituents of the products. Efforts to model carbon clustering as a diffusion-limited irreversible coagulation of carbon clusters go back to the seminal paper by Shaw and Johnson. However, first direct experimental observations of the kinetics of clustering yielded cluster growth one to two orders of magnitude slower than theoretical predictions. Multiple efforts were undertaken to test and revise the basic assumptions of the model in order to achieve better agreement with experiment. We discuss our very recent direct experimental observations of carbon clustering dynamics and demonstrate that these new results are in much better agreement with the modified Shaw-Johnson model. The implications of this much better agreement on our present understanding of detonation carbon clustering processes and possible ways to increase the agreement between theory and experiment even further are discussed.

  7. Orbits of Selected Globular Clusters in the Galactic Bulge

    NASA Astrophysics Data System (ADS)

    Pérez-Villegas, A.; Rossi, L.; Ortolani, S.; Casotto, S.; Barbuy, B.; Bica, E.

    2018-05-01

    We present orbit analysis for a sample of eight inner bulge globular clusters, together with one reference halo object. We used proper motion values derived from long time base CCD data. Orbits are integrated in both an axisymmetric model and a model including the Galactic bar potential. The inclusion of the bar proved to be essential for the description of the dynamical behaviour of the clusters. We use the Monte Carlo scheme to construct the initial conditions for each cluster, taking into account the uncertainties in the kinematical data and distances. The sample clusters show typically maximum height to the Galactic plane below 1.5 kpc, and develop rather eccentric orbits. Seven of the bulge sample clusters share the orbital properties of the bar/bulge, having perigalactic and apogalatic distances, and maximum vertical excursion from the Galactic plane inside the bar region. NGC 6540 instead shows a completely different orbital behaviour, having a dynamical signature of the thick disc. Both prograde and prograde-retrograde orbits with respect to the direction of the Galactic rotation were revealed, which might characterise a chaotic behaviour.

  8. 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.

  9. Multi-scale study of condensation in water jets using ellipsoidal-statistical Bhatnagar-Gross-Krook and molecular dynamics modeling

    NASA Astrophysics Data System (ADS)

    Li, Zheng; Borner, Arnaud; Levin, Deborah A.

    2014-06-01

    Homogeneous water condensation and ice formation in supersonic expansions to vacuum for stagnation pressures from 12 to 1000 mbar are studied using the particle-based Ellipsoidal-Statistical Bhatnagar-Gross-Krook (ES-BGK) method. We find that when condensation starts to occur, at a stagnation pressure of 96 mbar, the increase in the degree of condensation causes an increase in the rotational temperature due to the latent heat of vaporization. The simulated rotational temperature profiles along the plume expansion agree well with measurements confirming the kinetic homogeneous condensation models and the method of simulation. Comparisons of the simulated gas and cluster number densities, cluster size for different stagnation pressures along the plume centerline were made and it is found that the cluster size increase linearly with respect to stagnation pressure, consistent with classical nucleation theory. The sensitivity of our results to cluster nucleation model and latent heat values based on bulk water, specific cluster size, or bulk ice are examined. In particular, the ES-BGK simulations are found to be too coarse-grained to provide information on the phase or structure of the clusters formed. For this reason, molecular dynamics simulations of water condensation in a one-dimensional free expansion to simulate the conditions in the core of a plume are performed. We find that the internal structure of the clusters formed depends on the stagnation temperature. A larger cluster of average size 21 was tracked down the expansion, and a calculation of its average internal temperature as well as a comparison of its radial distribution functions (RDFs) with values measured for solid amorphous ice clusters lead us to conclude that this cluster is in a solid-like rather than liquid form. In another molecular-dynamics simulation at a much lower stagnation temperature, a larger cluster of size 324 and internal temperature 200 K was extracted from an expansion plume and equilibrated to determine its RDF and self-diffusion coefficient. The value of the latter shows that this cluster is formed in a supercooled liquid state rather than in an amorphous solid state.

  10. Putting Humpty-Dumpty Together: Clustering the Functional Dynamics of Single Biomolecular Machines Such as the Spliceosome.

    PubMed

    Rohlman, C E; Blanco, M R; Walter, N G

    2016-01-01

    The spliceosome is a biomolecular machine that, in all eukaryotes, accomplishes site-specific splicing of introns from precursor messenger RNAs (pre-mRNAs) with high fidelity. Operating at the nanometer scale, where inertia and friction have lost the dominant role they play in the macroscopic realm, the spliceosome is highly dynamic and assembles its active site around each pre-mRNA anew. To understand the structural dynamics underlying the molecular motors, clocks, and ratchets that achieve functional accuracy in the yeast spliceosome (a long-standing model system), we have developed single-molecule fluorescence resonance energy transfer (smFRET) approaches that report changes in intra- and intermolecular interactions in real time. Building on our work using hidden Markov models (HMMs) to extract kinetic and conformational state information from smFRET time trajectories, we recognized that HMM analysis of individual state transitions as independent stochastic events is insufficient for a biomolecular machine as complex as the spliceosome. In this chapter, we elaborate on the recently developed smFRET-based Single-Molecule Cluster Analysis (SiMCAn) that dissects the intricate conformational dynamics of a pre-mRNA through the splicing cycle in a model-free fashion. By leveraging hierarchical clustering techniques developed for Bioinformatics, SiMCAn efficiently analyzes large datasets to first identify common molecular behaviors. Through a second level of clustering based on the abundance of dynamic behaviors exhibited by defined functional intermediates that have been stalled by biochemical or genetic tools, SiMCAn then efficiently assigns pre-mRNA FRET states and transitions to specific splicing complexes, with the potential to find heretofore undescribed conformations. SiMCAn thus arises as a general tool to analyze dynamic cellular machines more broadly. © 2016 Elsevier Inc. All rights reserved.

  11. Growth of Ni nanoclusters on irradiated graphene: a molecular dynamics study.

    PubMed

    Valencia, F J; Hernandez-Vazquez, E E; Bringa, E M; Moran-Lopez, J L; Rogan, J; Gonzalez, R I; Munoz, F

    2018-04-23

    We studied the soft landing of Ni atoms on a previously damaged graphene sheet by means of molecular dynamics simulations. We found a monotonic decrease of the cluster frequency as a function of its size, but few big clusters comprise an appreciable fraction of the total number of Ni atoms. The aggregation of Ni atoms is also modeled by means of a simple phenomenological model. The results are in clear contrast with the case of hard or energetic landing of metal atoms, where there is a tendency to form mono-disperse metal clusters. This behavior is attributed to the high diffusion of unattached Ni atoms, together with vacancies acting as capture centers. The findings of this work show that a simple study of the energetics of the system is not enough in the soft landing regime, where it is unavoidable to also consider the growth process of metal clusters.

  12. A self-adapting herding model: The agent judge-abilities influence the dynamic behaviors

    NASA Astrophysics Data System (ADS)

    Dong, Linrong

    2008-10-01

    We propose a self-adapting herding model, in which the financial markets consist of agent clusters with different sizes and market desires. The ratio of successful exchange and merger depends on the volatility of the market and the market desires of the agent clusters. The desires are assigned in term of the wealth of the agent clusters when they merge. After an exchange, the beneficial cluster’s desire keeps on the same, the losing one’s desire is altered which is correlative with the agent judge-ability. A parameter R is given to all agents to denote the judge-ability. The numerical calculation shows that the dynamic behaviors of the market are influenced distinctly by R, which includes the exponential magnitudes of the probability distribution of sizes of the agent clusters and the volatility autocorrelation of the returns, the intensity and frequency of the volatility.

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

    PubMed

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

    2018-06-21

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

  14. Validation of gait analysis with dynamic radiostereometric analysis (RSA) in patients operated with total hip arthroplasty.

    PubMed

    Zügner, Roland; Tranberg, Roy; Lisovskaja, Vera; Shareghi, Bita; Kärrholm, Johan

    2017-07-01

    We simultaneously examined 14 patients with OTS and dynamic radiostereometric analysis (RSA) to evaluate the accuracy of both skin- and a cluster-marker models. The mean differences between the OTS and RSA system in hip flexion, abduction, and rotation varied up to 9.5° for the skin-marker and up to 11.3° for the cluster-marker models, respectively. Both models tended to underestimate the amount of flexion and abduction, but a significant systematic difference between the marker and RSA evaluations could only be established for recordings of hip abduction using cluster markers (p = 0.04). The intra-class correlation coefficient (ICC) was 0.7 or higher during flexion for both models and during abduction using skin markers, but decreased to 0.5-0.6 when abduction motion was studied with cluster markers. During active hip rotation, the two marker models tended to deviate from the RSA recordings in different ways with poor correlations at the end of the motion (ICC ≤0.4). During active hip motions soft tissue displacements occasionally induced considerable differences when compared to skeletal motions. The best correlation between RSA recordings and the skin- and cluster-marker model was found for studies of hip flexion and abduction with the skin-marker model. Studies of hip abduction with use of cluster markers were associated with a constant underestimation of the motion. Recordings of skeletal motions with use of skin or cluster markers during hip rotation were associated with high mean errors amounting up to about 10° at certain positions. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:1515-1522, 2017. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

  15. Long-time atomistic dynamics through a new self-adaptive accelerated molecular dynamics method

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

    Gao, N.; Yang, L.; Gao, F.

    2017-02-27

    A self-adaptive accelerated molecular dynamics method is developed to model infrequent atomic- scale events, especially those events that occur on a rugged free-energy surface. Key in the new development is the use of the total displacement of the system at a given temperature to construct a boost-potential, which is slowly increased to accelerate the dynamics. The temperature is slowly increased to accelerate the dynamics. By allowing the system to evolve from one steady-state con guration to another by overcoming the transition state, this self-evolving approach makes it possible to explore the coupled motion of species that migrate on vastly differentmore » time scales. The migrations of single vacancy (V) and small He-V clusters, and the growth of nano-sized He-V clusters in Fe for times in the order of seconds are studied by this new method. An interstitial- assisted mechanism is rst explored for the migration of a helium-rich He-V cluster, while a new two-component Ostwald ripening mechanism is suggested for He-V cluster growth.« less

  16. Clustering molecular dynamics trajectories for optimizing docking experiments.

    PubMed

    De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C

    2015-01-01

    Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

  17. Dynamics of fragment formation in neutron-rich matter

    NASA Astrophysics Data System (ADS)

    Alcain, P. N.; Dorso, C. O.

    2018-01-01

    Background: Neutron stars are astronomical systems with nucleons subjected to extreme conditions. Due to the longer range Coulomb repulsion between protons, the system has structural inhomogeneities. Several interactions tailored to reproduce nuclear matter plus a screened Coulomb term reproduce these inhomogeneities known as nuclear pasta. These structural inhomogeneities, located in the crusts of neutron stars, can also arise in expanding systems depending on the thermodynamic conditions (temperature, proton fraction, etc.) and the expansion velocity. Purpose: We aim to find the dynamics of the fragment formation for expanding systems simulated according to the little big bang model. This expansion resembles the evolution of merging neutron stars. Method: We study the dynamics of the nucleons with semiclassical molecular dynamics models. Starting with an equilibrium configuration, we expand the system homogeneously until we arrive at an asymptotic configuration (i.e., very low final densities). We study, with four different cluster recognition algorithms, the fragment distribution throughout this expansion and the dynamics of the cluster formation. Results: Studying the topology of the equilibrium states, before the expansion, we reproduced the known pasta phases plus a novel phase we called pregnocchi, consisting of proton aggregates embedded in a neutron sea. We have identified different fragmentation regimes, depending on the initial temperature and fragment velocity. In particular, for the already mentioned pregnocchi, a neutron cloud surrounds the clusters during the early stages of the expansion, resulting in systems that give rise to configurations compatible with the emergence of the r process. Conclusions: We showed that a proper identification of the cluster distribution is highly dependent on the cluster recognition algorithm chosen, and found that the early cluster recognition algorithm (ECRA) was the most stable one. This approach allowed us to identify the dynamics of the fragment formation. These calculations pave the way to a comparison between Earth experiments and neutron star studies.

  18. Molecular dynamics modelling of EGCG clusters on ceramide bilayers

    NASA Astrophysics Data System (ADS)

    Yeo, Jingjie; Cheng, Yuan; Li, Weifeng; Zhang, Yong-Wei

    2015-12-01

    A novel method of atomistic modelling and characterization of both pure ceramide and mixed lipid bilayers is being developed, using only the General Amber ForceField. Lipid bilayers modelled as pure ceramides adopt hexagonal packing after equilibration, and the area per lipid and bilayer thickness are consistent with previously reported theoretical results. Mixed lipid bilayers are modelled as a combination of ceramides, cholesterol, and free fatty acids. This model is shown to be stable after equilibration. Green tea extract, also known as epigallocatechin-3-gallate, is introduced as a spherical cluster on the surface of the mixed lipid bilayer. It is demonstrated that the cluster is able to bind to the bilayers as a cluster without diffusing into the surrounding water.

  19. Cluster analysis of dynamic contrast enhanced MRI reveals tumor subregions related to locoregional relapse for cervical cancer patients.

    PubMed

    Torheim, Turid; Groendahl, Aurora R; Andersen, Erlend K F; Lyng, Heidi; Malinen, Eirik; Kvaal, Knut; Futsaether, Cecilia M

    2016-11-01

    Solid tumors are known to be spatially heterogeneous. Detection of treatment-resistant tumor regions can improve clinical outcome, by enabling implementation of strategies targeting such regions. In this study, K-means clustering was used to group voxels in dynamic contrast enhanced magnetic resonance images (DCE-MRI) of cervical cancers. The aim was to identify clusters reflecting treatment resistance that could be used for targeted radiotherapy with a dose-painting approach. Eighty-one patients with locally advanced cervical cancer underwent DCE-MRI prior to chemoradiotherapy. The resulting image time series were fitted to two pharmacokinetic models, the Tofts model (yielding parameters K trans and ν e ) and the Brix model (A Brix , k ep and k el ). K-means clustering was used to group similar voxels based on either the pharmacokinetic parameter maps or the relative signal increase (RSI) time series. The associations between voxel clusters and treatment outcome (measured as locoregional control) were evaluated using the volume fraction or the spatial distribution of each cluster. One voxel cluster based on the RSI time series was significantly related to locoregional control (adjusted p-value 0.048). This cluster consisted of low-enhancing voxels. We found that tumors with poor prognosis had this RSI-based cluster gathered into few patches, making this cluster a potential candidate for targeted radiotherapy. None of the voxels clusters based on Tofts or Brix parameter maps were significantly related to treatment outcome. We identified one group of tumor voxels significantly associated with locoregional relapse that could potentially be used for dose painting. This tumor voxel cluster was identified using the raw MRI time series rather than the pharmacokinetic maps.

  20. The Dynamical Evolution of Stellar-Mass Black Holes in Dense Star Clusters

    NASA Astrophysics Data System (ADS)

    Morscher, Maggie

    Globular clusters are gravitationally bound systems containing up to millions of stars, and are found ubiquitously in massive galaxies, including the Milky Way. With densities as high as a million stars per cubic parsec, they are one of the few places in the Universe where stars interact with one another. They therefore provide us with a unique laboratory for studying how gravitational interactions can facilitate the formation of exotic systems, such as X-ray binaries containing black holes, and merging double black hole binaries, which are produced much less efficiently in isolation. While telescopes can provide us with a snapshot of what these dense clusters look like at present, we must rely on detailed numerical simulations to learn about their evolution. These simulations are quite challenging, however, since dense star clusters are described by a complicated set of physical processes occurring on many different length and time scales, including stellar and binary evolution, weak gravitational scattering encounters, strong resonant binary interactions, and tidal stripping by the host galaxy. Until very recently, it was not possible to model the evolution of systems with millions of stars, the actual number contained in the largest clusters, including all the relevant physics required describe these systems accurately. The Northwestern Group's Henon Monte Carlo code, CMC, which has been in development for over a decade, is a powerful tool that can be used to construct detailed evolutionary models of large star clusters. With its recent parallelization, CMC is now capable of addressing a particularly interesting unsolved problem in astrophysics: the dynamical evolution of stellar black holes in dense star clusters. Our current understanding of the stellar initial mass function and massive star evolution suggests that young globular clusters may have formed hundreds to thousands of stellar-mass black holes, the remnants of stars with initial masses from 20 - 100 Solar masses. Birth kicks from supernova explosions may eject some black holes from their birth clusters, but most should be retained initially. Using our Monte Carlo code, we have investigated the long-term dynamical evolution of globular clusters containing large numbers of stellar black holes. Our study is the first to explore in detail the dynamics of BHs in clusters through a large number of realistic simulations covering a wide range of initial conditions (cluster masses from 105 -- 106 Solar masses, as well as variation in other key parameters, such as the virial radius, central concentration, and metallicity), that also includes all the required physics. In almost all of our models we find that significant numbers of black holes (up to about a 1000) are retained all the way to the present. This is in contrast to previous theoretical expectations that most black holes should be ejected dynamically within a few Gyr. The main reason for this difference is that core collapse driven by black holes (through the Spitzer "mass segregation instability'') is easily reverted through three-body processes, and involves only a small number of the most massive black holes, while lower-mass black holes remain well-mixed with ordinary stars far from the central cusp. Thus the rapid segregation of stellar black holes does not lead to a long-term physical separation of most black holes into a dynamically decoupled inner core, as often assumed previously; this is one of the most important results of this dissertation. Combined with the recent detections of several black hole X-ray binary candidates in Galactic globular clusters, our results suggest that stellar black holes could still be present in large numbers in many globular clusters today, and that they may play a significant role in shaping the long-term dynamical evolution and the present-day dynamical structure of many clusters.

  1. mocca-SURVEY database I. Accreting white dwarf binary systems in globular clusters - III. Cataclysmic variables - implications of model assumptions

    NASA Astrophysics Data System (ADS)

    Belloni, Diogo; Zorotovic, Mónica; Schreiber, Matthias R.; Leigh, Nathan W. C.; Giersz, Mirek; Askar, Abbas

    2017-06-01

    In this third of a series of papers related to cataclysmic variables (CVs) and related objects, we analyse the population of CVs in a set of 12 globular cluster models evolved with the MOCCA Monte Carlo code, for two initial binary populations (IBPs), two choices of common-envelope phase (CEP) parameters, and three different models for the evolution of CVs and the treatment of angular momentum loss. When more realistic models and parameters are considered, we find that present-day cluster CV duty cycles are extremely low (≲0.1 per cent) that makes their detection during outbursts rather difficult. Additionally, the IBP plays a significant role in shaping the CV population properties, and models that follow the Kroupa IBP are less affected by enhanced angular momentum loss. We also predict from our simulations that CVs formed dynamically in the past few Gyr (massive CVs) correspond to bright CVs (as expected) and that faint CVs formed several Gyr ago (dynamically or not) represent the overwhelming majority. Regarding the CV formation rate, we rule out the notion that it is similar irrespective of the cluster properties. Finally, we discuss the differences in the present-day CV properties related to the IBPs, the initial cluster conditions, the CEP parameters, formation channels, the CV evolution models and the angular momentum loss treatments.

  2. Quasi-dynamic earthquake fault systems with rheological heterogeneity

    NASA Astrophysics Data System (ADS)

    Brietzke, G. B.; Hainzl, S.; Zoeller, G.; Holschneider, M.

    2009-12-01

    Seismic risk and hazard estimates mostly use pure empirical, stochastic models of earthquake fault systems tuned specifically to the vulnerable areas of interest. Although such models allow for reasonable risk estimates, such models cannot allow for physical statements of the described seismicity. In contrary such empirical stochastic models, physics based earthquake fault systems models allow for a physical reasoning and interpretation of the produced seismicity and system dynamics. Recently different fault system earthquake simulators based on frictional stick-slip behavior have been used to study effects of stress heterogeneity, rheological heterogeneity, or geometrical complexity on earthquake occurrence, spatial and temporal clustering of earthquakes, and system dynamics. Here we present a comparison of characteristics of synthetic earthquake catalogs produced by two different formulations of quasi-dynamic fault system earthquake simulators. Both models are based on discretized frictional faults embedded in an elastic half-space. While one (1) is governed by rate- and state-dependent friction with allowing three evolutionary stages of independent fault patches, the other (2) is governed by instantaneous frictional weakening with scheduled (and therefore causal) stress transfer. We analyze spatial and temporal clustering of events and characteristics of system dynamics by means of physical parameters of the two approaches.

  3. 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.

  4. Cluster analysis of multiple planetary flow regimes

    NASA Technical Reports Server (NTRS)

    Mo, Kingtse; Ghil, Michael

    1987-01-01

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

  5. Integrating association data and disease dynamics: an illustration using African Buffalo in Kruger National Park

    USGS Publications Warehouse

    Cross, Paul C.; James O, Lloyd-Smith; Bowers, Justin A.; Hay, Craig T.; Hofmeyr, Markus; Getz, Wayne M.

    2004-01-01

    Recognition is a prerequisite for non-random association amongst individuals. We explore how non-random association patterns (i.e. who spends time with whom) affect disease dynamics. We estimated the amount of time individuals spent together per month using radio-tracking data from African buffalo and incorporated these data into a dynamic social network model. The dynamic nature of the network has a strong influence on simulated disease dynamics particularly for diseases with shorter infectious periods. Cluster analyses of the association data demonstrated that buffalo herds were not as well defined as previously thought. Associations were more tightly clustered in 2002 than 2003, perhaps due to drier conditions in 2003. As a result, diseases may spread faster during drought conditions due to increased population mixing. Association data are often collected but this is the first use of empirical data in a network disease model in a wildlife population.

  6. Self-organization in a bimotility mixture of model microswimmers

    NASA Astrophysics Data System (ADS)

    Agrawal, Adyant; Babu, Sujin B.

    2018-02-01

    We study the cooperation and segregation dynamics in a bimotility mixture of microorganisms which swim at low Reynolds numbers via periodic deformations along the body. We employ a multiparticle collision dynamics method to simulate a two component mixture of artificial swimmers, termed as Taylor lines, which differ from each other only in the propulsion speed. The analysis reveals that a contribution of slower swimmers towards clustering, on average, is much larger as compared to the faster ones. We notice distinctive self-organizing dynamics, depending on the percentage difference in the speed of the two kinds. If this difference is large, the faster ones fragment the clusters of the slower ones in order to reach the boundary and form segregated clusters. Contrarily, when it is small, both kinds mix together at first, the faster ones usually leading the cluster and then gradually the slower ones slide out thereby also leading to segregation.

  7. A model for sputtering from solid surfaces bombarded by energetic clusters

    NASA Astrophysics Data System (ADS)

    Benguerba, Messaoud

    2018-04-01

    A model is developed to explain and predict the sputtering from solid surfaces bombarded by energetic clusters, on the basis of shock wave generated at the impact of cluster. Under the shock compression the temperature increases causing the vaporization of material that requires an internal energy behind the shock, at least, of about twice the cohesive energy of target. The sputtering is treated as a gas of vaporized particles from a hemispherical volume behind the shock front. The sputter yield per cluster atoms is given as a universal function depending on the ratio of target to cluster atomic density and the ratio of cluster velocity to the velocity calculated on the basis of an internal energy equals about twice cohesive energy. The predictions of the model for self sputter yield of copper, gold, tungsten and of silver bombarded by C60 clusters agree well, with the corresponding data simulated by molecular dynamics.

  8. The Atacama Cosmology Telescope: Dynamical Masses for 44 SZ-Selected Galaxy Clusters over 755 Square Degrees

    NASA Technical Reports Server (NTRS)

    Sifon, Cristobal; Battaglia, Nick; Hasselfield, Matthew; Menanteau, Felipe; Barrientos, L. Felipe; Bond, J. Richard; Crichton, Devin; Devlin, Mark J.; Dunner, Rolando; Hilton, Matt; hide

    2016-01-01

    We present galaxy velocity dispersions and dynamical mass estimates for 44 galaxy clusters selected via the Sunyaev-Zeldovich (SZ) effect by the Atacama Cosmology Telescope. Dynamical masses for 18 clusters are reported here for the first time. Using N-body simulations, we model the different observing strategies used to measure the velocity dispersions and account for systematic effects resulting from these strategies. We find that the galaxy velocity distributions may be treated as isotropic, and that an aperture correction of up to 7 per cent in the velocity dispersion is required if the spectroscopic galaxy sample is sufficiently concentrated towards the cluster centre. Accounting for the radial profile of the velocity dispersion in simulations enables consistent dynamical mass estimates regardless of the observing strategy. Cluster masses M200 are in the range (1 - 15) times 10 (sup 14) Solar Masses. Comparing with masses estimated from the SZ distortion assuming a gas pressure profile derived from X-ray observations gives a mean SZ-to-dynamical mass ratio of 1:10 plus or minus 0:13, but there is an additional 0.14 systematic uncertainty due to the unknown velocity bias; the statistical uncertainty is dominated by the scatter in the mass-velocity dispersion scaling relation. This ratio is consistent with previous determinations at these mass scales.

  9. Simple Epidemiological Dynamics Explain Phylogenetic Clustering of HIV from Patients with Recent Infection

    PubMed Central

    Volz, Erik M.; Koopman, James S.; Ward, Melissa J.; Brown, Andrew Leigh; Frost, Simon D. W.

    2012-01-01

    Phylogenies of highly genetically variable viruses such as HIV-1 are potentially informative of epidemiological dynamics. Several studies have demonstrated the presence of clusters of highly related HIV-1 sequences, particularly among recently HIV-infected individuals, which have been used to argue for a high transmission rate during acute infection. Using a large set of HIV-1 subtype B pol sequences collected from men who have sex with men, we demonstrate that virus from recent infections tend to be phylogenetically clustered at a greater rate than virus from patients with chronic infection (‘excess clustering’) and also tend to cluster with other recent HIV infections rather than chronic, established infections (‘excess co-clustering’), consistent with previous reports. To determine the role that a higher infectivity during acute infection may play in excess clustering and co-clustering, we developed a simple model of HIV infection that incorporates an early period of intensified transmission, and explicitly considers the dynamics of phylogenetic clusters alongside the dynamics of acute and chronic infected cases. We explored the potential for clustering statistics to be used for inference of acute stage transmission rates and found that no single statistic explains very much variance in parameters controlling acute stage transmission rates. We demonstrate that high transmission rates during the acute stage is not the main cause of excess clustering of virus from patients with early/acute infection compared to chronic infection, which may simply reflect the shorter time since transmission in acute infection. Higher transmission during acute infection can result in excess co-clustering of sequences, while the extent of clustering observed is most sensitive to the fraction of infections sampled. PMID:22761556

  10. Swarm Intelligence for Urban Dynamics Modelling

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

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

    2009-04-16

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  11. Swarm Intelligence for Urban Dynamics Modelling

    NASA Astrophysics Data System (ADS)

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

    2009-04-01

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  12. Shape and dynamics of thermoregulating honey bee clusters.

    PubMed

    Sumpter, D J; Broomhead, D S

    2000-05-07

    A model of simple algorithmic "agents" acting in a discrete temperature field is used to investigate the movement of individuals in thermoregulating honey bee (Apis mellifera) clusters. Thermoregulation in over-wintering clusters is thought to be the result of individual bees attempting to regulate their own body temperatures. At ambient temperatures above 0( degrees )C, a clustering bee will move relative to its neighbours so as to put its local temperature within some ideal range. The proposed model incorporates this behaviour into an algorithm for bee agents moving on a two-dimensional lattice. Heat transport on the lattice is modelled by a discrete diffusion process. Computer simulation of this model demonstrates qualitative behaviour which agrees with that of real honey bee clusters. In particular, we observe the formation of both disc- and ring-like cluster shapes. The simulation also suggests that at lower ambient temperatures, clusters do not always have a stable shape but can oscillate between insulating rings of different sizes and densities. Copyright 2000 Academic Press.

  13. Molecular dynamics study of the melting of a supported 887-atom Pd decahedron.

    PubMed

    Schebarchov, D; Hendy, S C; Polak, W

    2009-04-08

    We employ classical molecular dynamics simulations to investigate the melting behaviour of a decahedral Pd(887) cluster on a single layer of graphite (graphene). The interaction between Pd atoms is modelled with an embedded-atom potential, while the adhesion of Pd atoms to the substrate is approximated with a Lennard-Jones potential. We find that the decahedral structure persists at temperatures close to the melting point, but that just below the melting transition, the cluster accommodates to the substrate by means of complete melting and then recrystallization into an fcc structure. These structural changes are in qualitative agreement with recently proposed models, and they verify the existence of an energy barrier preventing softly deposited clusters from 'wetting' the substrate at temperatures below the melting point.

  14. On the symmetries of the 12C nucleus

    NASA Astrophysics Data System (ADS)

    Cseh, J.; Trencsényi, R.

    The consequences of some symmetries of the three-alpha system are discussed. In particular, the recent description of the low-energy spectrum of the 12C nucleus in terms of the algebraic cluster model (ACM) is compared to that of the multichannel dynamical symmetry (MUSY), which is the intersection of the shell and cluster models. The previous one applies interactions of a D3h geometric symmetry [D. J. Marin-Lambarri et al., Phys. Rev. Lett. 113 (2014) 012502], while the latter one has a U(3) dynamical symmetry. The available data is in line with both descriptions.

  15. Time-resolved explosion of intense-laser-heated clusters.

    PubMed

    Kim, K Y; Alexeev, I; Parra, E; Milchberg, H M

    2003-01-17

    We investigate the femtosecond explosive dynamics of intense laser-heated argon clusters by measuring the cluster complex transient polarizability. The time evolution of the polarizability is characteristic of competition in the optical response between supercritical and subcritical density regions of the expanding cluster. The results are consistent with time-resolved Rayleigh scattering measurements, and bear out the predictions of a recent laser-cluster interaction model [H. M. Milchberg, S. J. McNaught, and E. Parra, Phys. Rev. E 64, 056402 (2001)

  16. An opinion-driven behavioral dynamics model for addictive behaviors

    DOE PAGES

    Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; ...

    2015-04-08

    We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual’s behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Additionally, individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters providemore » targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. Furthermore, this has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.« less

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

    Salmi, Petja; Sutcliffe, Paul

    The aloof baby Skyrme model is a (2+1)-dimensional theory with solitons that are lightly bound. It is a low-dimensional analogue of a similar Skyrme model in (3+1)- dimensions, where the lightly bound solitons have binding energies comparable to nuclei. A previous study of static solitons in the aloof baby Skyrme model revealed that multi-soliton bound states have a cluster structure, with constituents that preserve their individual identities due to the short-range repulsion and long-range attraction between solitons. Furthermore, there are many different local energy minima that are all well-described by a simple binary species particle model. In this paper wemore » present the first results on soliton dynamics in the aloof baby Skyrme model. Numerical field theory simulations reveal that the lightly bound cluster structure results in a variety of exotic soliton scattering events that are novel in comparison to standard Skyrmion scattering. A dynamical version of the binary species point particle model is shown to provide a good qualitative description of the dynamics.« less

  18. Manifestations of Dynamical Localization in the Disordered XXZ Spin Chain

    NASA Astrophysics Data System (ADS)

    Elgart, Alexander; Klein, Abel; Stolz, Günter

    2018-04-01

    We study disordered XXZ spin chains in the Ising phase exhibiting droplet localization, a single cluster localization property we previously proved for random XXZ spin chains. It holds in an energy interval I near the bottom of the spectrum, known as the droplet spectrum. We establish dynamical manifestations of localization in the energy window I, including non-spreading of information, zero-velocity Lieb-Robinson bounds, and general dynamical clustering. Our results do not rely on knowledge of the dynamical characteristics of the model outside the droplet spectrum. A byproduct of our analysis is that for random XXZ spin chains this droplet localization can happen only inside the droplet spectrum.

  19. The ACS Survey of Galactic Globular Clusters. VIII. Effects of Environment on Globular Cluster Global Mass Functions

    NASA Astrophysics Data System (ADS)

    Paust, Nathaniel E. Q.; Reid, I. Neill; Piotto, Giampaolo; Aparicio, Antonio; Anderson, Jay; Sarajedini, Ata; Bedin, Luigi R.; Chaboyer, Brian; Dotter, Aaron; Hempel, Maren; Majewski, Steven; Marín-Franch, A.; Milone, Antonino; Rosenberg, Alfred; Siegel, Michael

    2010-02-01

    We have used observations obtained as part of the Hubble Space Telescope/ACS Survey of Galactic Globular Clusters to construct global present-day mass functions for 17 globular clusters utilizing multi-mass King models to extrapolate from our observations to the global cluster behavior. The global present-day mass functions for these clusters are well matched by power laws from the turnoff, ≈0.8 M sun, to 0.2-0.3 M sun on the lower main sequence. The slopes of those power-law fits, α, have been correlated with an extensive set of intrinsic and extrinsic cluster properties to investigate which parameters may influence the form of the present-day mass function. We do not confirm previous suggestions of correlations between α and either metallicity or Galactic location. However, we do find a strong statistical correlation with the related parameters central surface brightness, μ V , and inferred central density, ρ0. The correlation is such that clusters with denser cores (stronger binding energy) tend to have steeper mass functions (a higher proportion of low-mass stars), suggesting that dynamical evolution due to external interactions may have played a key role in determining α. Thus, the present-day mass function may owe more to nurture than to nature. Detailed modeling of external dynamical effects is therefore a requisite for determining the initial mass function for Galactic globular clusters.

  20. 2n-emission from 205Pb* nucleus using clusterization approach at Ebeam˜14-20 MeV

    NASA Astrophysics Data System (ADS)

    Kaur, Amandeep; Sandhu, Kiran; Sharma, Manoj Kumar

    2016-05-01

    The dynamics involved in n-induced reaction with 204Pb target is analyzed and the decay of the composite system 205Pb* is governed within the collective clusterization approach of the Dynamical Cluster-decay Model (DCM). The experimental data for 2n-evaporation channel is available for neutron energy range of 14-20 MeV and is addressed by optimizing the only parameter of the model, the neck-length parameter (ΔR). The calculations are done by taking the quadrupole (β2) deformations of the decaying fragments and the calculated 2n-emission cross-sections find nice agreement with available data. An effort is made to study the role of level density parameter in the decay of hot-rotating nucleus, and the mass dependence in level density parameter is exercised for the first time in DCM based calculations. It is to be noted that the effect of deformation, temperature and angular momentum etc. is studied to extract better description of the dynamics involved.

  1. Dynamical Modeling of NGC 6397: Simulated HST Imaging

    NASA Astrophysics Data System (ADS)

    Dull, J. D.; Cohn, H. N.; Lugger, P. M.; Slavin, S. D.; Murphy, B. W.

    1994-12-01

    The proximity of NGC 6397 (2.2 kpc) provides an ideal opportunity to test current dynamical models for globular clusters with the HST Wide-Field/Planetary Camera (WFPC2)\\@. We have used a Monte Carlo algorithm to generate ensembles of simulated Planetary Camera (PC) U-band images of NGC 6397 from evolving, multi-mass Fokker-Planck models. These images, which are based on the post-repair HST-PC point-spread function, are used to develop and test analysis methods for recovering structural information from actual HST imaging. We have considered a range of exposure times up to 2.4times 10(4) s, based on our proposed HST Cycle 5 observations. Our Fokker-Planck models include energy input from dynamically-formed binaries. We have adopted a 20-group mass spectrum extending from 0.16 to 1.4 M_sun. We use theoretical luminosity functions for red giants and main sequence stars. Horizontal branch stars, blue stragglers, white dwarfs, and cataclysmic variables are also included. Simulated images are generated for cluster models at both maximal core collapse and at a post-collapse bounce. We are carrying out stellar photometry on these images using ``DAOPHOT-assisted aperture photometry'' software that we have developed. We are testing several techniques for analyzing the resulting star counts, to determine the underlying cluster structure, including parametric model fits and the nonparametric density estimation methods. Our simulated images also allow us to investigate the accuracy and completeness of methods for carrying out stellar photometry in HST Planetary Camera images of dense cluster cores.

  2. Parameters of oscillation generation regions in open star cluster models

    NASA Astrophysics Data System (ADS)

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

    2017-07-01

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

  3. Phase separation and large deviations of lattice active matter

    NASA Astrophysics Data System (ADS)

    Whitelam, Stephen; Klymko, Katherine; Mandal, Dibyendu

    2018-04-01

    Off-lattice active Brownian particles form clusters and undergo phase separation even in the absence of attractions or velocity-alignment mechanisms. Arguments that explain this phenomenon appeal only to the ability of particles to move persistently in a direction that fluctuates, but existing lattice models of hard particles that account for this behavior do not exhibit phase separation. Here we present a lattice model of active matter that exhibits motility-induced phase separation in the absence of velocity alignment. Using direct and rare-event sampling of dynamical trajectories, we show that clustering and phase separation are accompanied by pronounced fluctuations of static and dynamic order parameters. This model provides a complement to off-lattice models for the study of motility-induced phase separation.

  4. Using reflection time-of-flight mass spectrometer techniques to investigate cluster dynamics and bonding

    NASA Astrophysics Data System (ADS)

    Wei, Shiqing; Castleman, A. W., Jr.

    1994-02-01

    Lase based time-of-flight mass spectrometer systems affixed with reflectrons are valuable tools for investigating cluster dynamics and reactions, spectroscopy and structures. Utilizing the reflectron time-of-flight mass spectrometer techniques, both decay fractions and kinetic energy releases of metastable cluster ions can be measured with high precision. By applying related theoretical models, the desired thermochemical values of metastable species can be deduced, which are otherwise very difficult to obtain. Several examples are discussed with attention focused on ammonia as a test case for hydrogen bond systems, and xenon for weaker van der Waals clusters. A brief overview of applications to investigating solvation effects on reactions and structures, delayed electron transfer and ionization through intracluster Penning ionization is also given.

  5. Clusters in nonsmooth oscillator networks

    NASA Astrophysics Data System (ADS)

    Nicks, Rachel; Chambon, Lucie; Coombes, Stephen

    2018-03-01

    For coupled oscillator networks with Laplacian coupling, the master stability function (MSF) has proven a particularly powerful tool for assessing the stability of the synchronous state. Using tools from group theory, this approach has recently been extended to treat more general cluster states. However, the MSF and its generalizations require the determination of a set of Floquet multipliers from variational equations obtained by linearization around a periodic orbit. Since closed form solutions for periodic orbits are invariably hard to come by, the framework is often explored using numerical techniques. Here, we show that further insight into network dynamics can be obtained by focusing on piecewise linear (PWL) oscillator models. Not only do these allow for the explicit construction of periodic orbits, their variational analysis can also be explicitly performed. The price for adopting such nonsmooth systems is that many of the notions from smooth dynamical systems, and in particular linear stability, need to be modified to take into account possible jumps in the components of Jacobians. This is naturally accommodated with the use of saltation matrices. By augmenting the variational approach for studying smooth dynamical systems with such matrices we show that, for a wide variety of networks that have been used as models of biological systems, cluster states can be explicitly investigated. By way of illustration, we analyze an integrate-and-fire network model with event-driven synaptic coupling as well as a diffusively coupled network built from planar PWL nodes, including a reduction of the popular Morris-Lecar neuron model. We use these examples to emphasize that the stability of network cluster states can depend as much on the choice of single node dynamics as it does on the form of network structural connectivity. Importantly, the procedure that we present here, for understanding cluster synchronization in networks, is valid for a wide variety of systems in biology, physics, and engineering that can be described by PWL oscillators.

  6. Off-stoichiometric defect clustering in irradiated oxides

    NASA Astrophysics Data System (ADS)

    Khalil, Sarah; Allen, Todd; EL-Azab, Anter

    2017-04-01

    A cluster dynamics model describing the formation of vacancy and interstitial clusters in irradiated oxides has been developed. The model, which tracks the composition of the oxide matrix and the defect clusters, was applied to the early stage formation of voids and dislocation loops in UO2, and the effects of irradiation temperature and dose rate on the evolution of their densities and composition was investigated. The results show that Frenkel defects dominate the nucleation process in irradiated UO2. The results also show that oxygen vacancies drive vacancy clustering while the migration energy of uranium vacancies is a rate-limiting factor for the nucleation and growth of voids. In a stoichiometric UO2 under irradiation, off-stoichiometric vacancy clusters exist with a higher concentration of hyper-stoichiometric clusters. Similarly, off-stoichiometric interstitial clusters form with a higher concentration of hyper-stoichiometric clusters. The UO2 matrix was found to be hyper-stoichiometric due to the accumulation of uranium vacancies.

  7. Effects of lateral diffusion on morphology and dynamics of a microscopic lattice-gas model of pulsed electrodeposition.

    PubMed

    Frank, Stefan; Roberts, Daniel E; Rikvold, Per Arne

    2005-02-08

    The influence of nearest-neighbor diffusion on the decay of a metastable low-coverage phase (monolayer adsorption) in a square lattice-gas model of electrochemical metal deposition is investigated by kinetic Monte Carlo simulations. The phase-transformation dynamics are compared to the well-established Kolmogorov-Johnson-Mehl-Avrami theory. The phase transformation is accelerated by diffusion, but remains in accord with the theory for continuous nucleation up to moderate diffusion rates. At very high diffusion rates the phase-transformation kinetic shows a crossover to instantaneous nucleation. Then, the probability of medium-sized clusters is reduced in favor of large clusters. Upon reversal of the supersaturation, the adsorbate desorbs, but large clusters still tend to grow during the initial stages of desorption. Calculation of the free energy of subcritical clusters by enumeration of lattice animals yields a quasiequilibrium distribution which is in reasonable agreement with the simulation results. This is an improvement relative to classical droplet theory, which fails to describe the distributions, since the macroscopic surface tension is a bad approximation for small clusters.

  8. Coarsening of protein clusters on subcellular drops exhibits strong and sudden size selectivity

    NASA Astrophysics Data System (ADS)

    Brown, Aidan; Rutenberg, Andrew

    2015-03-01

    Autophagy is an important process for the degradation of cellular components, with receptor proteins targeting substrates to downstream autophagy machinery. An important question is how receptor protein interactions lead to their selective accumulation on autophagy substrates. Receptor proteins have recently been observed in clusters, raising the possibility that clustering could affect autophagy selectivity. We investigate the clustering dynamics of the autophagy receptor protein NBR1. In addition to standard receptor protein domains, NBR1 has a ``J'' domain that anchors it to membranes, and a coiled-coil domain that enhances self-interaction. We model coarsening clusters of NBR1 on the surfaces of a polydisperse collection of drops, representing organelles. Despite the disconnected nature of the drop surfaces, we recover dynamical scaling of cluster sizes. Significantly, we find that at a well-defined time after coarsening begins, clusters evaporate from smaller drops and grow on larger drops. Thus, coarsening-driven size selection will localize protein clusters to larger substrates, leaving smaller substrates without clusters. This provides a possible physical mechanism for autophagy selectivity, and can explain reports of size selection during peroxisome degradation.

  9. Inherent Structure versus Geometric Metric for State Space Discretization

    PubMed Central

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

    2016-01-01

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

  10. Earth system modelling on system-level heterogeneous architectures: EMAC (version 2.42) on the Dynamical Exascale Entry Platform (DEEP)

    NASA Astrophysics Data System (ADS)

    Christou, Michalis; Christoudias, Theodoros; Morillo, Julián; Alvarez, Damian; Merx, Hendrik

    2016-09-01

    We examine an alternative approach to heterogeneous cluster-computing in the many-core era for Earth system models, using the European Centre for Medium-Range Weather Forecasts Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model as a pilot application on the Dynamical Exascale Entry Platform (DEEP). A set of autonomous coprocessors interconnected together, called Booster, complements a conventional HPC Cluster and increases its computing performance, offering extra flexibility to expose multiple levels of parallelism and achieve better scalability. The EMAC model atmospheric chemistry code (Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA)) was taskified with an offload mechanism implemented using OmpSs directives. The model was ported to the MareNostrum 3 supercomputer to allow testing with Intel Xeon Phi accelerators on a production-size machine. The changes proposed in this paper are expected to contribute to the eventual adoption of Cluster-Booster division and Many Integrated Core (MIC) accelerated architectures in presently available implementations of Earth system models, towards exploiting the potential of a fully Exascale-capable platform.

  11. Interlaced coarse-graining for the dynamical cluster approximation

    NASA Astrophysics Data System (ADS)

    Haehner, Urs; Staar, Peter; Jiang, Mi; Maier, Thomas; Schulthess, Thomas

    The negative sign problem remains a challenging limiting factor in quantum Monte Carlo simulations of strongly correlated fermionic many-body systems. The dynamical cluster approximation (DCA) makes this problem less severe by coarse-graining the momentum space to map the bulk lattice to a cluster embedded in a dynamical mean-field host. Here, we introduce a new form of an interlaced coarse-graining and compare it with the traditional coarse-graining. We show that it leads to more controlled results with weaker cluster shape and smoother cluster size dependence, which with increasing cluster size converge to the results obtained using the standard coarse-graining. In addition, the new coarse-graining reduces the severity of the fermionic sign problem. Therefore, it enables calculations on much larger clusters and can allow the evaluation of the exact infinite cluster size result via finite size scaling. To demonstrate this, we study the hole-doped two-dimensional Hubbard model and show that the interlaced coarse-graining in combination with the DCA+ algorithm permits the determination of the superconducting Tc on cluster sizes, for which the results can be fitted with the Kosterlitz-Thouless scaling law. This research used resources of the Oak Ridge Leadership Computing Facility (OLCF) awarded by the INCITE program, and of the Swiss National Supercomputing Center. OLCF is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

  12. 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.

  13. Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

    PubMed Central

    De Paris, Renata; Quevedo, Christian V.; Ruiz, Duncan D.; Norberto de Souza, Osmar; Barros, Rodrigo C.

    2015-01-01

    Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand. PMID:25873944

  14. Dynamical Models of Elliptical Galaxies in z = 0.5 Clusters. I. Data-Model Comparison and Evolution of Galaxy Rotation

    NASA Astrophysics Data System (ADS)

    van der Marel, Roeland P.; van Dokkum, Pieter G.

    2007-10-01

    We present spatially resolved stellar rotation velocity and velocity dispersion profiles from Keck/LRIS absorption-line spectra for 25 galaxies, mostly visually classified ellipticals, in three clusters at z~0.5. We interpret the kinematical data and HST photometry using oblate axisymmetric two-integral f(E,Lz) dynamical models based on the Jeans equations. This yields good fits, provided that the seeing and observational characteristics are carefully modeled. The fits yield for each galaxy the dynamical mass-to-light ratio (M/L) and a measure of the galaxy rotation rate. Paper II addresses the implied M/L evolution. Here we study the rotation-rate evolution by comparison to a sample of local elliptical galaxies of similar present-day luminosity. The brightest galaxies in the sample all rotate too slowly to account for their flattening, as is also observed at z=0. But the average rotation rate is higher at z~0.5 than locally. This may be due to a higher fraction of misclassified S0 galaxies (although this effect is insufficient to explain the observed strong evolution of the cluster S0 fraction with redshift). Alternatively, dry mergers between early-type galaxies may have decreased the average rotation rate over time. It is unclear whether such mergers are numerous enough in clusters to explain the observed trend quantitatively. Disk-disk mergers may affect the comparison through the so-called ``progenitor bias,'' but this cannot explain the direction of the observed rotation-rate evolution. Additional samples are needed to constrain possible environmental dependencies and cosmic variance in galaxy rotation rates. Either way, studies of the internal stellar dynamics of distant galaxies provide a valuable new approach for exploring galaxy evolution.

  15. Duality in Phase Space and Complex Dynamics of an Integrated Pest Management Network Model

    NASA Astrophysics Data System (ADS)

    Yuan, Baoyin; Tang, Sanyi; Cheke, Robert A.

    Fragmented habitat patches between which plants and animals can disperse can be modeled as networks with varying degrees of connectivity. A predator-prey model with network structures is proposed for integrated pest management (IPM) with impulsive control actions. The model was analyzed using numerical methods to investigate how factors such as the impulsive period, the releasing constant of natural enemies and the mode of connections between the patches affect pest outbreak patterns and the success or failure of pest control. The concept of the cluster as defined by Holland and Hastings is used to describe variations in results ranging from global synchrony when all patches have identical fluctuations to n-cluster solutions with all patches having different dynamics. Heterogeneity in the initial densities of either pest or natural enemy generally resulted in a variety of cluster oscillations. Surprisingly, if n > 1, the clusters fall into two groups one with low amplitude fluctuations and the other with high amplitude fluctuations (i.e. duality in phase space), implying that control actions radically alter the system's characteristics by inducing duality and more complex dynamics. When the impulsive period is small enough, i.e. the control strategy is undertaken frequently, the pest can be eradicated. As the period increases, the pest's dynamics shift from a steady state to become chaotic with periodic windows and more multicluster oscillations arise for heterogenous initial density distributions. Period-doubling bifurcation and periodic halving cascades occur as the releasing constant of the natural enemy increases. For the same ecological system with five differently connected networks, as the randomness of the connectedness increases, the transient duration becomes smaller and the probability of multicluster oscillations appearing becomes higher.

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

    NASA Astrophysics Data System (ADS)

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

    2011-09-01

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

  17. Three-cluster dynamics within an ab initio framework

    DOE PAGES

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

    2013-09-26

    In this study, we introduce a fully antisymmetrized treatment of three-cluster dynamics within the ab initio framework of the no-core shell model/resonating-group method. Energy-independent nonlocal interactions among the three nuclear fragments are obtained from realistic nucleon-nucleon interactions and consistent ab initio many-body wave functions of the clusters. The three-cluster Schrödinger equation is solved with bound-state boundary conditions by means of the hyperspherical-harmonic method on a Lagrange mesh. We discuss the formalism in detail and give algebraic expressions for systems of two single nucleons plus a nucleus. Using a soft similarity-renormalization-group evolved chiral nucleon-nucleon potential, we apply the method to amore » 4He+n+n description of 6He and compare the results to experiment and to a six-body diagonalization of the Hamiltonian performed within the harmonic-oscillator expansions of the no-core shell model. Differences between the two calculations provide a measure of core ( 4He) polarization effects.« less

  18. The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping.

    PubMed

    Bahlmann, Claus; Burkhardt, Hans

    2004-03-01

    In this paper, we give a comprehensive description of our writer-independent online handwriting recognition system frog on hand. The focus of this work concerns the presentation of the classification/training approach, which we call cluster generative statistical dynamic time warping (CSDTW). CSDTW is a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling. It can handle general classification problems that rely on this sequential type of data, e.g., speech recognition, genome processing, robotics, etc. Contrary to previous attempts, clustering and statistical sequence modeling are embedded in a single feature space and use a closely related distance measure. We show character recognition experiments of frog on hand using CSDTW on the UNIPEN online handwriting database. The recognition accuracy is significantly higher than reported results of other handwriting recognition systems. Finally, we describe the real-time implementation of frog on hand on a Linux Compaq iPAQ embedded device.

  19. Relating dynamics of model unentangled, crystallizable polymeric liquids to their local structure

    NASA Astrophysics Data System (ADS)

    Nguyen, Hong T.; Hoy, Robert S.

    We study the liquid-state dynamics of a recently developed, crystallizable bead-spring polymer model. The model possesses a single ground state (NCP, wherein monomers close-pack and chains are nematically aligned) for all finite bending stiffnesses kb, but the solid morphologies formed under cooling vary strongly with kb, varying from NCP to amorphous. We find that systems with kb producing amorphous order are good glass-formers exhibiting the classic Vogel-Fulcher slowdown with decreasing temperature T. In contrast, systems with kb producing crystalline solids exhibit a simpler dynamics when kb is small. Larger kb produce more complex dynamics, but these are associated with the existence of an intermediate nematic liquid rather than glassy slowdown. We relate these differences to local, cluster-level structure measured via TCC analyses. Formation propensities and lifetimes of various clusters (associated with amorphous or crystalline order) vary strongly with kb and T. We relate these differences to those measured by the self-intermediate scattering function and other macroscopic measures of dynamics. Our results should aid in understanding the competition between crystallization and glass-formation in synthetic polymers.

  20. Multi-mode clustering model for hierarchical wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Hu, Xiangdong; Li, Yongfu; Xu, Huifen

    2017-03-01

    The topology management, i.e., clusters maintenance, of wireless sensor networks (WSNs) is still a challenge due to its numerous nodes, diverse application scenarios and limited resources as well as complex dynamics. To address this issue, a multi-mode clustering model (M2 CM) is proposed to maintain the clusters for hierarchical WSNs in this study. In particular, unlike the traditional time-trigger model based on the whole-network and periodic style, the M2 CM is proposed based on the local and event-trigger operations. In addition, an adaptive local maintenance algorithm is designed for the broken clusters in the WSNs using the spatial-temporal demand changes accordingly. Numerical experiments are performed using the NS2 network simulation platform. Results validate the effectiveness of the proposed model with respect to the network maintenance costs, node energy consumption and transmitted data as well as the network lifetime.

  1. The mond external field effect on the dynamics of the globular clusters: general considerations and application to NGC 2419

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

    Derakhshani, Kamran, E-mail: kderakhshani@iasbs.ac.ir

    2014-03-01

    In this paper, we investigate the external field effect in the context of the MOdified Newtonian Dynamics (MOND) on the surface brightness and velocity dispersion profiles of globular clusters (GCs). Using N-MODY, which is an N-body simulation code with a MOND potential solver, we show that the general effect of the external field for diffuse clusters, which obey MOND in most of their parts, is that it pushes the dynamics toward the Newtonian regime. On the other hand, for more compact clusters, which are essentially Newtonian in their inner parts, the external field is effective mainly in the outer partsmore » of compact clusters. As a case study, we then choose the remote Galactic GC NGC 2419. By varying the cluster mass, half-light radius, and mass-to-light ratio, we aim to find a model that will reproduce the observational data most effectively, using N-MODY. We find that even if we take the Galactic external field into account, a Newtonian Plummer sphere represents the observational data better than MOND to an order of magnitude in terms of the total χ{sup 2} of surface brightness and velocity dispersion.« less

  2. The MOND External Field Effect on the Dynamics of the Globular Clusters: General Considerations and Application to NGC 2419

    NASA Astrophysics Data System (ADS)

    Derakhshani, Kamran

    2014-03-01

    In this paper, we investigate the external field effect in the context of the MOdified Newtonian Dynamics (MOND) on the surface brightness and velocity dispersion profiles of globular clusters (GCs). Using N-MODY, which is an N-body simulation code with a MOND potential solver, we show that the general effect of the external field for diffuse clusters, which obey MOND in most of their parts, is that it pushes the dynamics toward the Newtonian regime. On the other hand, for more compact clusters, which are essentially Newtonian in their inner parts, the external field is effective mainly in the outer parts of compact clusters. As a case study, we then choose the remote Galactic GC NGC 2419. By varying the cluster mass, half-light radius, and mass-to-light ratio, we aim to find a model that will reproduce the observational data most effectively, using N-MODY. We find that even if we take the Galactic external field into account, a Newtonian Plummer sphere represents the observational data better than MOND to an order of magnitude in terms of the total χ2 of surface brightness and velocity dispersion.

  3. Improving Memory for Optimization and Learning in Dynamic Environments

    DTIC Science & Technology

    2011-07-01

    algorithm uses simple, in- cremental clustering to separate solutions into memory entries. The cluster centers are used as the models in the memory. This is...entire days of traffic with realistic traffic de - mands and turning ratios on a 32 intersection network modeled on downtown Pittsburgh, Pennsyl- vania...early/tardy problem. Management Science, 35(2):177–191, 1989. [78] Daniel Parrott and Xiaodong Li. A particle swarm model for tracking multiple peaks in

  4. Study of atmospheric dynamics and pollution in the coastal area of English Channel using clustering technique

    NASA Astrophysics Data System (ADS)

    Sokolov, Anton; Dmitriev, Egor; Delbarre, Hervé; Augustin, Patrick; Gengembre, Cyril; Fourmenten, Marc

    2016-04-01

    The problem of atmospheric contamination by principal air pollutants was considered in the industrialized coastal region of English Channel in Dunkirk influenced by north European metropolitan areas. MESO-NH nested models were used for the simulation of the local atmospheric dynamics and the online calculation of Lagrangian backward trajectories with 15-minute temporal resolution and the horizontal resolution down to 500 m. The one-month mesoscale numerical simulation was coupled with local pollution measurements of volatile organic components, particulate matter, ozone, sulphur dioxide and nitrogen oxides. Principal atmospheric pathways were determined by clustering technique applied to backward trajectories simulated. Six clusters were obtained which describe local atmospheric dynamics, four winds blowing through the English Channel, one coming from the south, and the biggest cluster with small wind speeds. This last cluster includes mostly sea breeze events. The analysis of meteorological data and pollution measurements allows relating the principal atmospheric pathways with local air contamination events. It was shown that contamination events are mostly connected with a channelling of pollution from local sources and low-turbulent states of the local atmosphere.

  5. Black hole binaries dynamically formed in globular clusters

    NASA Astrophysics Data System (ADS)

    Park, Dawoo; Kim, Chunglee; Lee, Hyung Mok; Bae, Yeong-Bok; Belczynski, Krzysztof

    2017-08-01

    We investigate properties of black hole (BH) binaries formed in globular clusters via dynamical processes, using directN-body simulations. We pay attention to effects of BH mass function on the total mass and mass ratio distributions of BH binaries ejected from clusters. First, we consider BH populations with two different masses in order to learn basic differences from models with single-mass BHs only. Secondly, we consider continuous BH mass functions adapted from recent studies on massive star evolution in a low metallicity environment, where globular clusters are formed. In this work, we consider only binaries that are formed by three-body processes and ignore stellar evolution and primordial binaries for simplicity. Our results imply that most BH binary mergers take place after they get ejected from the cluster. Also, mass ratios of dynamically formed binaries should be close to 1 or likely to be less than 2:1. Since the binary formation efficiency is larger for higher-mass BHs, it is likely that a BH mass function sampled by gravitational-wave observations would be weighed towards higher masses than the mass function of single BHs for a dynamically formed population. Applying conservative assumptions regarding globular cluster populations such as small BH mass fraction and no primordial binaries, the merger rate of BH binaries originated from globular clusters is estimated to be at least 6.5 yr-1 Gpc-3. Actual rate can be up to more than several times of our conservative estimate.

  6. Inferring Viral Dynamics in Chronically HCV Infected Patients from the Spatial Distribution of Infected Hepatocytes

    DOE PAGES

    Graw, Frederik; Balagopal, Ashwin; Kandathil, Abraham J.; ...

    2014-11-13

    Chronic liver infection by hepatitis C virus (HCV) is a major public health concern. Despite partly successful treatment options, several aspects of intrahepatic HCV infection dynamics are still poorly understood, including the preferred mode of viral propagation, as well as the proportion of infected hepatocytes. Answers to these questions have important implications for the development of therapeutic interventions. In this study, we present methods to analyze the spatial distribution of infected hepatocytes obtained by single cell laser capture microdissection from liver biopsy samples of patients chronically infected with HCV. By characterizing the internal structure of clusters of infected cells, wemore » are able to evaluate hypotheses about intrahepatic infection dynamics. We found that individual clusters on biopsy samples range in size from 4-50 infected cells. In addition, the HCV RNA content in a cluster declines from the cell that presumably founded the cluster to cells at the maximal cluster extension. These observations support the idea that HCV infection in the liver is seeded randomly (e.g. from the blood) and then spreads locally. Assuming that the amount of intracellular HCV RNA is a proxy for how long a cell has been infected, we estimate based on models of intracellular HCV RNA replication and accumulation that cells in clusters have been infected on average for less than a week. Further, we do not find a relationship between the cluster size and the estimated cluster expansion time. Lastly, our method represents a novel approach to make inferences about infection dynamics in solid tissues from static spatial data.« less

  7. Inferring Viral Dynamics in Chronically HCV Infected Patients from the Spatial Distribution of Infected Hepatocytes

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

    Graw, Frederik; Balagopal, Ashwin; Kandathil, Abraham J.

    Chronic liver infection by hepatitis C virus (HCV) is a major public health concern. Despite partly successful treatment options, several aspects of intrahepatic HCV infection dynamics are still poorly understood, including the preferred mode of viral propagation, as well as the proportion of infected hepatocytes. Answers to these questions have important implications for the development of therapeutic interventions. In this study, we present methods to analyze the spatial distribution of infected hepatocytes obtained by single cell laser capture microdissection from liver biopsy samples of patients chronically infected with HCV. By characterizing the internal structure of clusters of infected cells, wemore » are able to evaluate hypotheses about intrahepatic infection dynamics. We found that individual clusters on biopsy samples range in size from 4-50 infected cells. In addition, the HCV RNA content in a cluster declines from the cell that presumably founded the cluster to cells at the maximal cluster extension. These observations support the idea that HCV infection in the liver is seeded randomly (e.g. from the blood) and then spreads locally. Assuming that the amount of intracellular HCV RNA is a proxy for how long a cell has been infected, we estimate based on models of intracellular HCV RNA replication and accumulation that cells in clusters have been infected on average for less than a week. Further, we do not find a relationship between the cluster size and the estimated cluster expansion time. Lastly, our method represents a novel approach to make inferences about infection dynamics in solid tissues from static spatial data.« less

  8. Hierarchical cluster-based partial least squares regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models.

    PubMed

    Tøndel, Kristin; Indahl, Ulf G; Gjuvsland, Arne B; Vik, Jon Olav; Hunter, Peter; Omholt, Stig W; Martens, Harald

    2011-06-01

    Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. HC-PLSR is a promising approach for metamodelling in systems biology, especially for highly nonlinear or non-monotone parameter to phenotype maps. The algorithm can be flexibly adjusted to suit the complexity of the dynamic model behaviour, inviting automation in the metamodelling of complex systems.

  9. Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models

    PubMed Central

    2011-01-01

    Background Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Results Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. Conclusions HC-PLSR is a promising approach for metamodelling in systems biology, especially for highly nonlinear or non-monotone parameter to phenotype maps. The algorithm can be flexibly adjusted to suit the complexity of the dynamic model behaviour, inviting automation in the metamodelling of complex systems. PMID:21627852

  10. Mesoscale energy deposition footprint model for kiloelectronvolt cluster bombardment of solids.

    PubMed

    Russo, Michael F; Garrison, Barbara J

    2006-10-15

    Molecular dynamics simulations have been performed to model 5-keV C60 and Au3 projectile bombardment of an amorphous water substrate. The goal is to obtain detailed insights into the dynamics of motion in order to develop a straightforward and less computationally demanding model of the process of ejection. The molecular dynamics results provide the basis for the mesoscale energy deposition footprint model. This model provides a method for predicting relative yields based on information from less than 1 ps of simulation time.

  11. Three-dimensional discrete-time Lotka-Volterra models with an application to industrial clusters

    NASA Astrophysics Data System (ADS)

    Bischi, G. I.; Tramontana, F.

    2010-10-01

    We consider a three-dimensional discrete dynamical system that describes an application to economics of a generalization of the Lotka-Volterra prey-predator model. The dynamic model proposed is used to describe the interactions among industrial clusters (or districts), following a suggestion given by [23]. After studying some local and global properties and bifurcations in bidimensional Lotka-Volterra maps, by numerical explorations we show how some of them can be extended to their three-dimensional counterparts, even if their analytic and geometric characterization becomes much more difficult and challenging. We also show a global bifurcation of the three-dimensional system that has no two-dimensional analogue. Besides the particular economic application considered, the study of the discrete version of Lotka-Volterra dynamical systems turns out to be a quite rich and interesting topic by itself, i.e. from a purely mathematical point of view.

  12. The Gaia-ESO Survey: dynamical models of flattened, rotating globular clusters

    NASA Astrophysics Data System (ADS)

    Jeffreson, S. M. R.; Sanders, J. L.; Evans, N. W.; Williams, A. A.; Gilmore, G. F.; Bayo, A.; Bragaglia, A.; Casey, A. R.; Flaccomio, E.; Franciosini, E.; Hourihane, A.; Jackson, R. J.; Jeffries, R. D.; Jofré, P.; Koposov, S.; Lardo, C.; Lewis, J.; Magrini, L.; Morbidelli, L.; Pancino, E.; Randich, S.; Sacco, G. G.; Worley, C. C.; Zaggia, S.

    2017-08-01

    We present a family of self-consistent axisymmetric rotating globular cluster models which are fitted to spectroscopic data for NGC 362, NGC 1851, NGC 2808, NGC 4372, NGC 5927 and NGC 6752 to provide constraints on their physical and kinematic properties, including their rotation signals. They are constructed by flattening Modified Plummer profiles, which have the same asymptotic behaviour as classical Plummer models, but can provide better fits to young clusters due to a slower turnover in the density profile. The models are in dynamical equilibrium as they depend solely on the action variables. We employ a fully Bayesian scheme to investigate the uncertainty in our model parameters (including mass-to-light ratios and inclination angles) and evaluate the Bayesian evidence ratio for rotating to non-rotating models. We find convincing levels of rotation only in NGC 2808. In the other clusters, there is just a hint of rotation (in particular, NGC 4372 and NGC 5927), as the data quality does not allow us to draw strong conclusions. Where rotation is present, we find that it is confined to the central regions, within radii of R ≤ 2rh. As part of this work, we have developed a novel q-Gaussian basis expansion of the line-of-sight velocity distributions, from which general models can be constructed via interpolation on the basis coefficients.

  13. The dynamics of z ~ 1 clusters of galaxies from the GCLASS survey

    NASA Astrophysics Data System (ADS)

    Biviano, A.; van der Burg, R. F. J.; Muzzin, A.; Sartoris, B.; Wilson, G.; Yee, H. K. C.

    2016-10-01

    Context. The dynamics of clusters of galaxies and its evolution provide information on their formation and growth, on the nature of dark matter and on the evolution of the baryonic components. Poor observational constraints exist so far on the dynamics of clusters at redshift z > 0.8. Aims: We aim to constrain the internal dynamics of clusters of galaxies at redshift z ~ 1, namely their mass profile M(r), velocity anisotropy profile β(r), and pseudo-phase-space density profiles Q(r) and Qr(r), obtained from the ratio between the mass density profile and the third power of the (total and, respectively, radial) velocity dispersion profiles of cluster galaxies. Methods: We used the spectroscopic and photometric data-set of 10 clusters at 0.87 < z < 1.34 from the Gemini Cluster Astrophysics Spectroscopic Survey (GCLASS). We determined the individual cluster masses from their velocity dispersions, then stack the clusters in projected phase-space. We investigated the internal dynamics of this stack cluster, using the spatial and velocity distribution of its member galaxies. We determined the stack cluster M(r) using the MAMPOSSt method, and its β(r) by direct inversion of the Jeans equation. The procedures used to determine the two aforementioned profiles also allowed us to determine Q(r) and Qr(r). Results: Several M(r) models are statistically acceptable for the stack cluster (Burkert, Einasto, Hernquist, NFW). The stack cluster total mass concentration, c ≡ r200/r-2 = 4.0-0.6+1.0, is in agreement with theoretical expectations. The total mass distribution is less concentrated than both the cluster stellar-mass and the cluster galaxies distributions. The stack cluster β(r) indicates that galaxy orbits are isotropic near the cluster center and become increasingly radially elongated with increasing cluster-centric distance. Passive and star-forming galaxies have similar β(r). The observed β(r) is similar to that of dark matter particles in simulated cosmological halos. Q(r) and Qr(r) are almost power-law relations with slopes similar to those predicted from numerical simulations of dark matter halos. Conclusions: Comparing our results with those obtained for lower-redshift clusters, we conclude that the evolution of the concentration-total mass relation and pseudo-phase-space density profiles agree with the expectations from ΛCDM cosmological simulations. The fact that Q(r) and Qr(r) already follow the theoretical expectations in z ~ 1 clusters suggest these profiles are the result of rapid dynamical relaxation processes, such as violent relaxation. The different concentrations of the total and stellar mass distribution, and their subsequent evolution, can be explained by merging processes of central galaxies leading to the formation of the brightest cluster galaxy. The orbits of passive cluster galaxies appear to become more isotropic with time, while those of star-forming galaxies do not evolve, presumably because star-formation is quenched on a shorter timescale than that required for orbital isotropization.

  14. Control of Chemical Effects in the Separation Process of a Differential Mobility / Mass Spectrometer System

    PubMed Central

    Schneider, Bradley B.; Coy, Stephen L.; Krylov, Evgeny V.; Nazarov, Erkinjon G.

    2013-01-01

    Differential mobility spectrometry (DMS) separates ions on the basis of the difference in their migration rates under high versus low electric fields. Several models describing the physical nature of this field mobility dependence have been proposed but emerging as a dominant effect is the clusterization model sometimes referred to as the dynamic cluster-decluster model. DMS resolution and peak capacity is strongly influenced by the addition of modifiers which results in the formation and dissociation of clusters. This process increases selectivity due to the unique chemical interactions that occur between an ion and neutral gas phase molecules. It is thus imperative to bring the parameters influencing the chemical interactions under control and find ways to exploit them in order to improve the analytical utility of the device. In this paper we describe three important areas that need consideration in order to stabilize and capitalize on the chemical processes that dominate a DMS separation. The first involves means of controlling the dynamic equilibrium of the clustering reactions with high concentrations of specific reagents. The second area involves a means to deal with the unwanted heterogeneous cluster ion populations emitted from the electrospray ionization process that degrade resolution and sensitivity. The third involves fine control of parameters that affect the fundamental collision processes, temperature and pressure. PMID:20065515

  15. Dynamic Transition and Resonance in Coupled Oscillators Under Symmetry-Breaking Fields

    NASA Astrophysics Data System (ADS)

    Choi, J.; Choi, M. Y.; Chung, M. S.; Yoon, B.-G.

    2013-06-01

    We investigate numerically the dynamic properties of a system of globally coupled oscillators driven by periodic symmetry-breaking fields in the presence of noise. The phase distribution of the oscillators is computed and a dynamic transition is disclosed. It is further found that the stochastic resonance is closely related to the behavior of the dynamic order parameter, which is in turn explained by the formation of a bi-cluster in the system. Here noise tends to symmetrize the motion of the oscillators, facilitating the bi-cluster formation. The observed resonance appears to be of the same class as the resonance present in the two-dimensional Ising model under oscillating fields.

  16. Multiscale modelling of precipitation in concentrated alloys: from atomistic Monte Carlo simulations to cluster dynamics I thermodynamics

    NASA Astrophysics Data System (ADS)

    Lépinoux, J.; Sigli, C.

    2018-01-01

    In a recent paper, the authors showed how the clusters free energies are constrained by the coagulation probability, and explained various anomalies observed during the precipitation kinetics in concentrated alloys. This coagulation probability appeared to be a too complex function to be accurately predicted knowing only the cluster distribution in Cluster Dynamics (CD). Using atomistic Monte Carlo (MC) simulations, it is shown that during a transformation at constant temperature, after a short transient regime, the transformation occurs at quasi-equilibrium. It is proposed to use MC simulations until the system quasi-equilibrates then to switch to CD which is mean field but not limited by a box size like MC. In this paper, we explain how to take into account the information available before the quasi-equilibrium state to establish guidelines to safely predict the cluster free energies.

  17. Pattern Selection and Super-Patterns in Opinion Dynamics

    NASA Astrophysics Data System (ADS)

    Ben-Naim, Eli; Scheel, Arnd

    We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.

  18. Deep HST Imaging in 47 Tucanae: A Global Dynamical Model

    NASA Astrophysics Data System (ADS)

    Heyl, J.; Caiazzo, I.; Richer, H.; Anderson, J.; Kalirai, J.; Parada, J.

    2017-12-01

    Multi-epoch observations with the Advanced Camera Survey and WFC3 on the Hubble Space Telescope provide a unique and comprehensive probe of stellar dynamics within 47 Tucanae. We confront analytic models of the globular cluster with the observed stellar proper motions that probe along the main sequence from just above 0.8-0.1M ⊙ as well as white dwarfs younger than 1 Gyr. One field lies just beyond the half-light radius where dynamical models (e.g., lowered Maxwellian distributions) make robust predictions for the stellar proper motions. The observed proper motions in this outer field show evidence for anisotropy in the velocity distribution as well as skewness; the latter is evidence of rotation. The measured velocity dispersions and surface brightness distributions agree in detail with a rotating anisotropic model of the stellar distribution function with mild dependence of the proper-motion dispersion on mass. However, the best-fitting models underpredict the rotation and skewness of the stellar velocities. In the second field, centered on the core of the cluster, the mass segregation in proper motion is much stronger. Nevertheless the model developed in the outer field can be extended inward by taking this mass segregation into account in a heuristic fashion. The proper motions of the main-sequence stars yield a mass estimate of the cluster of 1.31+/- 0.02× {10}6{M}⊙ at a distance of 4.7 kpc. By comparing the proper motions of a sample of giant and subgiant stars with the observed radial velocities we estimate the distance to the cluster kinematically to be 4.29 ± 0.47 kpc.

  19. Experiments in clustered neuronal networks: A paradigm for complex modular dynamics

    NASA Astrophysics Data System (ADS)

    Teller, Sara; Soriano, Jordi

    2016-06-01

    Uncovering the interplay activity-connectivity is one of the major challenges in neuroscience. To deepen in the understanding of how a neuronal circuit shapes network dynamics, neuronal cultures have emerged as remarkable systems given their accessibility and easy manipulation. An attractive configuration of these in vitro systems consists in an ensemble of interconnected clusters of neurons. Using calcium fluorescence imaging to monitor spontaneous activity in these clustered neuronal networks, we were able to draw functional maps and reveal their topological features. We also observed that these networks exhibit a hierarchical modular dynamics, in which clusters fire in small groups that shape characteristic communities in the network. The structure and stability of these communities is sensitive to chemical or physical action, and therefore their analysis may serve as a proxy for network health. Indeed, the combination of all these approaches is helping to develop models to quantify damage upon network degradation, with promising applications for the study of neurological disorders in vitro.

  20. Cluster Synchronization of Diffusively Coupled Nonlinear Systems: A Contraction-Based Approach

    NASA Astrophysics Data System (ADS)

    Aminzare, Zahra; Dey, Biswadip; Davison, Elizabeth N.; Leonard, Naomi Ehrich

    2018-04-01

    Finding the conditions that foster synchronization in networked nonlinear systems is critical to understanding a wide range of biological and mechanical systems. However, the conditions proved in the literature for synchronization in nonlinear systems with linear coupling, such as has been used to model neuronal networks, are in general not strict enough to accurately determine the system behavior. We leverage contraction theory to derive new sufficient conditions for cluster synchronization in terms of the network structure, for a network where the intrinsic nonlinear dynamics of each node may differ. Our result requires that network connections satisfy a cluster-input-equivalence condition, and we explore the influence of this requirement on network dynamics. For application to networks of nodes with FitzHugh-Nagumo dynamics, we show that our new sufficient condition is tighter than those found in previous analyses that used smooth or nonsmooth Lyapunov functions. Improving the analytical conditions for when cluster synchronization will occur based on network configuration is a significant step toward facilitating understanding and control of complex networked systems.

  1. Effect of Dust Coagulation Dynamics on the Geometry of Aggregates

    NASA Technical Reports Server (NTRS)

    Nakamura, R.

    1996-01-01

    Master equation gives a more fundamental description of stochastic coagulation processes rather than popular Smoluchowski's equation. In order to examine the effect of the dynamics on the geometry of resulting aggregates, we study Master equation with a rigorous Monte Carlo algorithm. It is found that Cluster-Cluster aggregation model is a good approximation of orderly growth and the aggregates have fluffy structures with a fractal dimension approx. 2. A scaling analysis of Smoluchowski's equation also supports this conclusion.

  2. Principal component and clustering analysis on molecular dynamics data of the ribosomal L11·23S subdomain.

    PubMed

    Wolf, Antje; Kirschner, Karl N

    2013-02-01

    With improvements in computer speed and algorithm efficiency, MD simulations are sampling larger amounts of molecular and biomolecular conformations. Being able to qualitatively and quantitatively sift these conformations into meaningful groups is a difficult and important task, especially when considering the structure-activity paradigm. Here we present a study that combines two popular techniques, principal component (PC) analysis and clustering, for revealing major conformational changes that occur in molecular dynamics (MD) simulations. Specifically, we explored how clustering different PC subspaces effects the resulting clusters versus clustering the complete trajectory data. As a case example, we used the trajectory data from an explicitly solvated simulation of a bacteria's L11·23S ribosomal subdomain, which is a target of thiopeptide antibiotics. Clustering was performed, using K-means and average-linkage algorithms, on data involving the first two to the first five PC subspace dimensions. For the average-linkage algorithm we found that data-point membership, cluster shape, and cluster size depended on the selected PC subspace data. In contrast, K-means provided very consistent results regardless of the selected subspace. Since we present results on a single model system, generalization concerning the clustering of different PC subspaces of other molecular systems is currently premature. However, our hope is that this study illustrates a) the complexities in selecting the appropriate clustering algorithm, b) the complexities in interpreting and validating their results, and c) by combining PC analysis with subsequent clustering valuable dynamic and conformational information can be obtained.

  3. An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

    PubMed

    Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

    2003-11-01

    Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

  4. Merging Galaxy Clusters: A Case Study of ZwCl 2341.1+0000 and the Development of a New Forward Modeled Lensing Technique

    NASA Astrophysics Data System (ADS)

    Benson, Bryant Joseph

    Context: Galaxy clusters are the most massive gravitationally bound structures in the universe and are formed through the process of hierarchical clustering, in which smaller systems undergo a series of mergers to form ever larger clusters. Because of the masses involved, mergers between these giants provide a unique laboratory for observing many interesting astrophysical processes. These merging systems also act as large dark matter colliders, because the dark matter halos of the clusters involved pass through each other during of the merger. This offers us a means to observe if dark matter-dark matter collisions result in momentum exchange beyond what occurs from gravity alone. Such observations can help us to unravel some of the mysteries behind dark matter, such as does it interact with itself through mechanisms beyond gravity, and how strong are those interactions. Answers to questions like these are what will eventually allow us to discover what dark matter really is. However, the extremely long time scales for these mergers (˜several billion years) make each observation a single snapshot in the long merger history, and we must infer many of the details necessary for understanding the full merger process. Furthermore, current weak lensing analyses lack the precision required to detect a signal from self-interacting dark matter. Uncertain weak lensing mass and position estimates also yield large uncertainties in the dynamical reconstruction of the merger scenarios. Need: In order to better model the dynamics of merging galaxy cluster systems, and to potentially measure any signal from self-interacting dark matter, we need to obtain more precise measurements on the masses and positions of the dark matter halos involved. Gravitational lensing offers a robust method for mapping the mass in these clusters because it directly measures the gravitational field, and does not depend on the dynamical state of the system that has been disturbed in the merger process. Of the lensing methods, weak gravitational lensing is the only way that we can probe a wide field and measure the total mass of the cluster. However, the precision of conventional weak lensing techniques is currently limited by shape noise (uncertainty in the shear due to the dispersion in the intrinsic shapes and orientations of unlensed galaxies). A possible avenue forward is to eliminate shape noise as a source of uncertainty in shear measurements via a technique to be described below. This would eliminate the largest source of uncertainty in weak lensing analyses, and enable us to obtain mass and position estimates of dark matter halos with a much higher level of precision. Task: In this dissertation we perform statistical clustering, conventional weak lensing analyses, and dynamical reconstruction on the merging galaxy cluster system ZwCl 2341.1+0000 in order to test the capabilities of the dynamical modeling on a complex, multiple merger. We use targeted optical spectroscopy to identify cluster member galaxies, which we then use to model the galaxy substructures. We also obtain a dynamical mass estimate using the galaxy velocity dispersions, and perform weak lensing analyses in the forms of aperture densitometry to place an upper bound on the total cluster mass, and multiple NFW profile halo fitting to approximate the masses and positions of the individual dark matter halos present in the merger. The masses, positions, and line of sight velocities of those clusters are then used to constrain the parameters describing the best fit merger scenario, with radio relic positions and polarization used to further tighten those constraints. We also develop a new method for obtaining weak lensing data from individual source galaxies in the form of shear measurements that are independent of shape noise, and direct measurements of the convergence. We accomplish this by simultaneously modeling the pre-lensing velocity and intensity profiles of a lensed, rotating disk galaxy, and the lensing transform required to distort those into the lensed profiles we observe. We test this method with a host of idealized simulations to characterize its capabilities in a best-case scenario and forecast the possible improvements it can bring to the precision of weak lensing analyses on galaxy clusters. (Abstract shortened by ProQuest.).

  5. Accreting Black Hole Binaries in Globular Clusters

    NASA Astrophysics Data System (ADS)

    Kremer, Kyle; Chatterjee, Sourav; Rodriguez, Carl L.; Rasio, Frederic A.

    2018-01-01

    We explore the formation of mass-transferring binary systems containing black holes (BHs) within globular clusters (GC). We show that it is possible to form mass-transferring BH binaries with main sequence, giant, and white dwarf companions with a variety of orbital parameters in GCs spanning a large range in present-day properties. All mass-transferring BH binaries found in our models at late times are dynamically created. The BHs in these systems experienced a median of ∼30 dynamical encounters within the cluster before and after acquiring the donor. Furthermore, we show that the presence of mass-transferring BH systems has little correlation with the total number of BHs within the cluster at any time. This is because the net rate of formation of BH–non-BH binaries in a cluster is largely independent of the total number of retained BHs. Our results suggest that the detection of a mass-transferring BH binary in a GC does not necessarily indicate that the host cluster contains a large BH population.

  6. Study of multiband disordered systems using the typical medium dynamical cluster approximation

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

    Zhang, Yi; Terletska, Hanna; Moore, C.

    We generalize the typical medium dynamical cluster approximation to multiband disordered systems. Using our extended formalism, we perform a systematic study of the nonlocal correlation effects induced by disorder on the density of states and the mobility edge of the three-dimensional two-band Anderson model. We include interband and intraband hopping and an intraband disorder potential. Our results are consistent with those obtained by the transfer matrix and the kernel polynomial methods. We also apply the method to K xFe 2-ySe 2 with Fe vacancies. Despite the strong vacancy disorder and anisotropy, we find the material is not an Anderson insulator.more » Moreover our results demonstrate the application of the typical medium dynamical cluster approximation method to study Anderson localization in real materials.« less

  7. Study of multiband disordered systems using the typical medium dynamical cluster approximation

    DOE PAGES

    Zhang, Yi; Terletska, Hanna; Moore, C.; ...

    2015-11-06

    We generalize the typical medium dynamical cluster approximation to multiband disordered systems. Using our extended formalism, we perform a systematic study of the nonlocal correlation effects induced by disorder on the density of states and the mobility edge of the three-dimensional two-band Anderson model. We include interband and intraband hopping and an intraband disorder potential. Our results are consistent with those obtained by the transfer matrix and the kernel polynomial methods. We also apply the method to K xFe 2-ySe 2 with Fe vacancies. Despite the strong vacancy disorder and anisotropy, we find the material is not an Anderson insulator.more » Moreover our results demonstrate the application of the typical medium dynamical cluster approximation method to study Anderson localization in real materials.« less

  8. Dynamic Information Networks: Geometry, Topology and Statistical Learning for the Articulation of Structure

    DTIC Science & Technology

    2015-06-23

    T. Bates, S. Brocklebank, S. Pauls, and D.Rockmore, A spectral clustering approach to the structure of personality: contrasting the FFM and...A spectral clustering approach to the structure of personality: contrasting the FFM and HEXACO models, Journal of Research in Personality, Volume 57

  9. MYStIX: Dynamical evolution of young clusters

    NASA Astrophysics Data System (ADS)

    Kuhn, Michael A.

    2014-08-01

    The spatial structure of young stellar clusters in Galactic star-forming regions provides insight into these clusters’ dynamical evolution---a topic with implications for open questions in star-formation and cluster survival. The Massive Young Star-Forming Complex Study in Infrared and X-ray (MYStIX) provides a sample of >30,000 young stars in star-forming regions (d<3.6 kpc) that contain at least one O-type star. We use the finite mixture model analysis to identify subclusters of stars and determine their properties: including subcluster radii, intrinsic numbers of stars, central density, ellipticity, obscuration, and age. In 17 MYStIX regions we find 142 subclusters, with a diverse radii and densities and age spreads of up to ~1 Myr in a region. There is a strong negative correlation between subcluster radius and density, which indicates that embedded subclusters expand but also gain stars as they age. Subcluster expansion is also shown by a positive radius--age correlation, which indicates that subclusters are expanding at <1 km/s. The subcluster ellipticity distribution and number--density relation show signs of a hierarchical merger scenario, whereby young stellar clusters are built up through mergers of smaller clumps, causing evolution from a clumpy spatial distribution of stars (seen in some regions) to a simpler distribution of stars (seen in other regions). Many of the simple young stellar clusters show signs of dynamically relaxation, even though they are not old enough for this to have occurred through two-body interactions. However, this apparent contradiction might be explained if small subcluster, which have shorter dynamical relaxation times, can produce dynamically relaxed clusters through hierarchical mergers.

  10. Brighter galaxy bias: underestimating the velocity dispersions of galaxy clusters

    NASA Astrophysics Data System (ADS)

    Old, L.; Gray, M. E.; Pearce, F. R.

    2013-09-01

    We study the systematic bias introduced when selecting the spectroscopic redshifts of brighter cluster galaxies to estimate the velocity dispersion of galaxy clusters from both simulated and observational galaxy catalogues. We select clusters with Ngal ≥ 50 at five low-redshift snapshots from the publicly available De Lucia & Blaziot semi-analytic model galaxy catalogue. Clusters are also selected from the Tempel Sloan Digital Sky Survey Data Release 8 groups and clusters catalogue across the redshift range 0.021 ≤ z ≤ 0.098. We employ various selection techniques to explore whether the velocity dispersion bias is simply due to a lack of dynamical information or is the result of an underlying physical process occurring in the cluster, for example, dynamical friction experienced by the brighter cluster members. The velocity dispersions of the parent dark matter (DM) haloes are compared to the galaxy cluster dispersions and the stacked distribution of DM particle velocities is examined alongside the corresponding galaxy velocity distribution. We find a clear bias between the halo and the semi-analytic galaxy cluster velocity dispersion on the order of σgal/σDM ˜ 0.87-0.95 and a distinct difference in the stacked galaxy and DM particle velocities distribution. We identify a systematic underestimation of the velocity dispersions when imposing increasing absolute I-band magnitude limits. This underestimation is enhanced when using only the brighter cluster members for dynamical analysis on the order of 5-35 per cent, indicating that dynamical friction is a serious source of bias when using galaxy velocities as tracers of the underlying gravitational potential. In contrast to the literature we find that the resulting bias is not only halo mass dependent but also that the nature of the dependence changes according to the galaxy selection strategy. We make a recommendation that, in the realistic case of limited availability of spectral observations, a strictly magnitude-limited sample should be avoided to ensure an unbiased estimate of the velocity dispersion.

  11. Sparsity enabled cluster reduced-order models for control

    NASA Astrophysics Data System (ADS)

    Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.

    2018-01-01

    Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.

  12. The dynamics of cyclone clustering in re-analysis and a high-resolution climate model

    NASA Astrophysics Data System (ADS)

    Priestley, Matthew; Pinto, Joaquim; Dacre, Helen; Shaffrey, Len

    2017-04-01

    Extratropical cyclones have a tendency to occur in groups (clusters) in the exit of the North Atlantic storm track during wintertime, potentially leading to widespread socioeconomic impacts. The Winter of 2013/14 was the stormiest on record for the UK and was characterised by the recurrent clustering of intense extratropical cyclones. This clustering was associated with a strong, straight and persistent North Atlantic 250 hPa jet with Rossby wave-breaking (RWB) on both flanks, pinning the jet in place. Here, we provide for the first time an analysis of all clustered events in 36 years of the ERA-Interim Re-analysis at three latitudes (45˚ N, 55˚ N, 65˚ N) encompassing various regions of Western Europe. The relationship between the occurrence of RWB and cyclone clustering is studied in detail. Clustering at 55˚ N is associated with an extended and anomalously strong jet flanked on both sides by RWB. However, clustering at 65(45)˚ N is associated with RWB to the south (north) of the jet, deflecting the jet northwards (southwards). A positive correlation was found between the intensity of the clustering and RWB occurrence to the north and south of the jet. However, there is considerable spread in these relationships. Finally, analysis has shown that the relationships identified in the re-analysis are also present in a high-resolution coupled global climate model (HiGEM). In particular, clustering is associated with the same dynamical conditions at each of our three latitudes in spite of the identified biases in frequency and intensity of RWB.

  13. Towards Effective Clustering Techniques for the Analysis of Electric Power Grids

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

    Hogan, Emilie A.; Cotilla Sanchez, Jose E.; Halappanavar, Mahantesh

    2013-11-30

    Clustering is an important data analysis technique with numerous applications in the analysis of electric power grids. Standard clustering techniques are oblivious to the rich structural and dynamic information available for power grids. Therefore, by exploiting the inherent topological and electrical structure in the power grid data, we propose new methods for clustering with applications to model reduction, locational marginal pricing, phasor measurement unit (PMU or synchrophasor) placement, and power system protection. We focus our attention on model reduction for analysis based on time-series information from synchrophasor measurement devices, and spectral techniques for clustering. By comparing different clustering techniques onmore » two instances of realistic power grids we show that the solutions are related and therefore one could leverage that relationship for a computational advantage. Thus, by contrasting different clustering techniques we make a case for exploiting structure inherent in the data with implications for several domains including power systems.« less

  14. 2n-emission from {sup 205}Pb* nucleus using clusterization approach at E{sub beam}∼14-20 MeV

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

    Kaur, Amandeep, E-mail: adeepkaur89@gmail.com; Sandhu, Kiran; Sharma, Manoj Kumar, E-mail: msharma@thapar.edu

    2016-05-06

    The dynamics involved in n-induced reaction with {sup 204}Pb target is analyzed and the decay of the composite system {sup 205}Pb* is governed within the collective clusterization approach of the Dynamical Cluster-decay Model (DCM). The experimental data for 2n-evaporation channel is available for neutron energy range of 14-20 MeV and is addressed by optimizing the only parameter of the model, the neck-length parameter (ΔR). The calculations are done by taking the quadrupole (β{sub 2}) deformations of the decaying fragments and the calculated 2n-emission cross-sections find nice agreement with available data. An effort is made to study the role of levelmore » density parameter in the decay of hot-rotating nucleus, and the mass dependence in level density parameter is exercised for the first time in DCM based calculations. It is to be noted that the effect of deformation, temperature and angular momentum etc. is studied to extract better description of the dynamics involved.« less

  15. Dynamics of Multistable States during Ongoing and Evoked Cortical Activity

    PubMed Central

    Mazzucato, Luca

    2015-01-01

    Single-trial analyses of ensemble activity in alert animals demonstrate that cortical circuits dynamics evolve through temporal sequences of metastable states. Metastability has been studied for its potential role in sensory coding, memory, and decision-making. Yet, very little is known about the network mechanisms responsible for its genesis. It is often assumed that the onset of state sequences is triggered by an external stimulus. Here we show that state sequences can be observed also in the absence of overt sensory stimulation. Analysis of multielectrode recordings from the gustatory cortex of alert rats revealed ongoing sequences of states, where single neurons spontaneously attain several firing rates across different states. This single-neuron multistability represents a challenge to existing spiking network models, where typically each neuron is at most bistable. We present a recurrent spiking network model that accounts for both the spontaneous generation of state sequences and the multistability in single-neuron firing rates. Each state results from the activation of neural clusters with potentiated intracluster connections, with the firing rate in each cluster depending on the number of active clusters. Simulations show that the model's ensemble activity hops among the different states, reproducing the ongoing dynamics observed in the data. When probed with external stimuli, the model predicts the quenching of single-neuron multistability into bistability and the reduction of trial-by-trial variability. Both predictions were confirmed in the data. Together, these results provide a theoretical framework that captures both ongoing and evoked network dynamics in a single mechanistic model. PMID:26019337

  16. Running and rotating: modelling the dynamics of migrating cell clusters

    NASA Astrophysics Data System (ADS)

    Copenhagen, Katherine; Gov, Nir; Gopinathan, Ajay

    Collective motion of cells is a common occurrence in many biological systems, including tissue development and repair, and tumor formation. Recent experiments have shown cells form clusters in a chemical gradient, which display three different phases of motion: translational, rotational, and random. We present a model for cell clusters based loosely on other models seen in the literature that involves a Vicsek-like alignment as well as physical collisions and adhesions between cells. With this model we show that a mechanism for driving rotational motion in this kind of system is an increased motility of rim cells. Further, we examine the details of the relationship between rim and core cells, and find that the phases of the cluster as a whole are correlated with the creation and annihilation of topological defects in the tangential component of the velocity field.

  17. A model of jam formation in congested traffic

    NASA Astrophysics Data System (ADS)

    Bunzarova, N. Zh; Pesheva, N. C.; Priezzhev, V. B.; Brankov, J. G.

    2017-12-01

    We study a model of irreversible jam formation in congested vehicular traffic on an open segment of a single-lane road. The vehicles obey a stochastic discrete-time dynamics which is a limiting case of the generalized Totally Asymmetric Simple Exclusion Process. Its characteristic features are: (a) the existing clusters of jammed cars cannot break into parts; (b) when the leading vehicle of a cluster hops to the right, the whole cluster follows it deterministically, and (c) any two clusters of vehicles, occupying consecutive positions on the chain, may become nearest-neighbors and merge irreversibly into a single cluster. The above dynamics was used in a one-dimensional model of irreversible aggregation by Bunzarova and Pesheva [Phys. Rev. E 95, 052105 (2017)]. The model has three stationary non-equilibrium phases, depending on the probabilities of injection (α), ejection (β), and hopping (p) of particles: a many-particle one, MP, a completely jammed phase CF, and a mixed MP+CF phase. An exact expression for the stationary probability P(1) of a completely jammed configuration in the mixed MP+CF phase is obtained. The gap distribution between neighboring clusters of jammed cars at large lengths L of the road is studied. Three regimes of evolution of the width of a single gap are found: (i) growing gaps with length of the order O(L) when β > p; (ii) shrinking gaps with length of the order O(1) when β < p; and (iii) critical gaps at β = p, of the order O(L 1/2). These results are supported by extensive Monte Carlo calculations.

  18. Navigation of a Satellite Cluster with Realistic Dynamics

    DTIC Science & Technology

    1991-12-01

    20 2.2.1 Dynamics ( Clohessy - Wiltshire Equations) ............ 21 2.2.2 Iterated, Extended Kalman Filter.................26 iv I1l...8 Figure 4. Point mass and Clohessy - Wiltshire orbits (10 orbits) .......... 16 Figure 5. Real dynamics and Clohessy - Wiltshire orbits (10...filter ..... 31 Figure 8. Comparison of the Clohessy - Wiltshire and truth model solutions

  19. Vibrational dynamics of aniline (N2)1 clusters in their first excited singlet state

    NASA Astrophysics Data System (ADS)

    Hineman, M. F.; Kim, S. K.; Bernstein, E. R.; Kelley, D. F.

    1992-04-01

    The first excited singlet state S1 vibrational dynamics of aniline(N2)1 clusters are studied and compared to previous results on aniline(CH4)1 and aniline(Ar)1. Intramolecular vibrational energy redistribution (IVR) and vibrational predissociation (VP) rates fall between the two extremes of the CH4 (fast IVR, slow VP) and Ar (slow IVR, fast VP) cluster results as is predicted by a serial IVR/VP model using Fermi's golden rule to describe IVR processes and a restricted Rice-Ramsperger-Kassel-Marcus (RRKM) theory to describe unimolecular VP rates. The density of states is the most important factor determining the rates. Two product states, 00 and 10b1, of bare aniline and one intermediate state ˜(00) in the overall IVR/VP process are observed and time resolved measurements are obtained for the 000 and ˜(000) transitions. The results are modeled with the serial mechanism described above.

  20. Emergence of increased frequency and severity of multiple infections by viruses due to spatial clustering of hosts

    NASA Astrophysics Data System (ADS)

    Taylor, Bradford P.; Penington, Catherine J.; Weitz, Joshua S.

    2016-12-01

    Multiple virus particles can infect a target host cell. Such multiple infections (MIs) have significant and varied ecological and evolutionary consequences for both virus and host populations. Yet, the in situ rates and drivers of MIs in virus-microbe systems remain largely unknown. Here, we develop an individual-based model (IBM) of virus-microbe dynamics to probe how spatial interactions drive the frequency and nature of MIs. In our IBMs, we identify increasingly spatially correlated clusters of viruses given sufficient decreases in viral movement. We also identify increasingly spatially correlated clusters of viruses and clusters of hosts given sufficient increases in viral infectivity. The emergence of clusters is associated with an increase in multiply infected hosts as compared to expectations from an analogous mean field model. We also observe long-tails in the distribution of the multiplicity of infection in contrast to mean field expectations that such events are exponentially rare. We show that increases in both the frequency and severity of MIs occur when viruses invade a cluster of uninfected microbes. We contend that population-scale enhancement of MI arises from an aggregate of invasion dynamics over a distribution of microbe cluster sizes. Our work highlights the need to consider spatially explicit interactions as a potentially key driver underlying the ecology and evolution of virus-microbe communities.

  1. Nuclear Potential Clustering As a New Tool to Detect Patterns in High Dimensional Datasets

    NASA Astrophysics Data System (ADS)

    Tonkova, V.; Paulus, D.; Neeb, H.

    2013-02-01

    We present a new approach for the clustering of high dimensional data without prior assumptions about the structure of the underlying distribution. The proposed algorithm is based on a concept adapted from nuclear physics. To partition the data, we model the dynamic behaviour of nucleons interacting in an N-dimensional space. An adaptive nuclear potential, comprised of a short-range attractive (strong interaction) and a long-range repulsive term (Coulomb force) is assigned to each data point. By modelling the dynamics, nucleons that are densely distributed in space fuse to build nuclei (clusters) whereas single point clusters repel each other. The formation of clusters is completed when the system reaches the state of minimal potential energy. The data are then grouped according to the particles' final effective potential energy level. The performance of the algorithm is tested with several synthetic datasets showing that the proposed method can robustly identify clusters even when complex configurations are present. Furthermore, quantitative MRI data from 43 multiple sclerosis patients were analyzed, showing a reasonable splitting into subgroups according to the individual patients' disease grade. The good performance of the algorithm on such highly correlated non-spherical datasets, which are typical for MRI derived image features, shows that Nuclear Potential Clustering is a valuable tool for automated data analysis, not only in the MRI domain.

  2. Competitive aggregation dynamics using phase wave signals.

    PubMed

    Sakaguchi, Hidetsugu; Maeyama, Satomi

    2014-10-21

    Coupled equations of the phase equation and the equation of cell concentration n are proposed for competitive aggregation dynamics of slime mold in two dimensions. Phase waves are used as tactic signals of aggregation in this model. Several aggregation clusters are formed initially, and target patterns appear around the localized aggregation clusters. Owing to the competition among target patterns, the number of the localized aggregation clusters decreases, and finally one dominant localized pattern survives. If the phase equation is replaced with the complex Ginzburg-Landau equation, several spiral patterns appear, and n is localized near the center of the spiral patterns. After the competition among spiral patterns, one dominant spiral survives. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. The origin of and conditions for clustering in fluids with competing interactions

    NASA Astrophysics Data System (ADS)

    Jadrich, Ryan; Bollinger, Jonathan; Truskett, Thomas

    2015-03-01

    Fluids with competing short-range attractions and long-range repulsions exhibit a rich phase behavior characterized by intermediate range order (IRO), as quantified via the static structure factor. This phase behavior includes cluster formation depending upon density-controlled packing effects and the magnitude and range of the attractive and repulsive interactions. Such model systems mimic (to zeroth order) screened, charge-stabilized, aqueous colloidal dispersions of, e.g., proteins. We employ molecular dynamics simulations and integral equation theory to elucidate a more fundamental microscopic explanation for IRO-driven clustering. A simple criterion is identified that indicates when dynamic, amorphous clustering emerges in a polydisperse system, namely when the Ornstein-Zernike thermal correlation length in the system exceeds the repulsive potential tail range. Remarkably, this criterion also appears tightly correlated to crystalline cluster formation in a monodisperse system. Our new gauge is compared to another phenomenological condition for clustering which is when the IRO peak magnitude exceeds ~ 2.7. Ramifications of crystalline versus amorphous clustering are discussed and potential ways of using our new measure in experiment are put forward.

  4. Self-assembled clusters of spheres related to spherical codes.

    PubMed

    Phillips, Carolyn L; Jankowski, Eric; Marval, Michelle; Glotzer, Sharon C

    2012-10-01

    We consider the thermodynamically driven self-assembly of spheres onto the surface of a central sphere. This assembly process forms self-limiting, or terminal, anisotropic clusters (N-clusters) with well-defined structures. We use Brownian dynamics to model the assembly of N-clusters varying in size from two to twelve outer spheres and free energy calculations to predict the expected cluster sizes and shapes as a function of temperature and inner particle diameter. We show that the arrangements of outer spheres at finite temperatures are related to spherical codes, an ideal mathematical sequence of points corresponding to the densest possible sphere packings. We demonstrate that temperature and the ratio of the diameters of the inner and outer spheres dictate cluster morphology. We present a surprising result for the equilibrium structure of a 5-cluster, for which the square pyramid arrangement is preferred over a more symmetric structure. We show this result using Brownian dynamics, a Monte Carlo simulation, and a free energy approximation. Our results suggest a promising way to assemble anisotropic building blocks from constituent colloidal spheres.

  5. The relationship of dynamical heterogeneity to the Adam-Gibbs and random first-order transition theories of glass formation.

    PubMed

    Starr, Francis W; Douglas, Jack F; Sastry, Srikanth

    2013-03-28

    We carefully examine common measures of dynamical heterogeneity for a model polymer melt and test how these scales compare with those hypothesized by the Adam and Gibbs (AG) and random first-order transition (RFOT) theories of relaxation in glass-forming liquids. To this end, we first analyze clusters of highly mobile particles, the string-like collective motion of these mobile particles, and clusters of relative low mobility. We show that the time scale of the high-mobility clusters and strings is associated with a diffusive time scale, while the low-mobility particles' time scale relates to a structural relaxation time. The difference of the characteristic times for the high- and low-mobility particles naturally explains the well-known decoupling of diffusion and structural relaxation time scales. Despite the inherent difference of dynamics between high- and low-mobility particles, we find a high degree of similarity in the geometrical structure of these particle clusters. In particular, we show that the fractal dimensions of these clusters are consistent with those of swollen branched polymers or branched polymers with screened excluded-volume interactions, corresponding to lattice animals and percolation clusters, respectively. In contrast, the fractal dimension of the strings crosses over from that of self-avoiding walks for small strings, to simple random walks for longer, more strongly interacting, strings, corresponding to flexible polymers with screened excluded-volume interactions. We examine the appropriateness of identifying the size scales of either mobile particle clusters or strings with the size of cooperatively rearranging regions (CRR) in the AG and RFOT theories. We find that the string size appears to be the most consistent measure of CRR for both the AG and RFOT models. Identifying strings or clusters with the "mosaic" length of the RFOT model relaxes the conventional assumption that the "entropic droplets" are compact. We also confirm the validity of the entropy formulation of the AG theory, constraining the exponent values of the RFOT theory. This constraint, together with the analysis of size scales, enables us to estimate the characteristic exponents of RFOT.

  6. Evidence for feedback and stellar-dynamically regulated bursty star cluster formation: the case of the Orion Nebula Cluster

    NASA Astrophysics Data System (ADS)

    Kroupa, Pavel; Jeřábková, Tereza; Dinnbier, František; Beccari, Giacomo; Yan, Zhiqiang

    2018-04-01

    A scenario for the formation of multiple co-eval populations separated in age by about 1 Myr in very young clusters (VYCs, ages less than 10 Myr) and with masses in the range 600-20 000 M⊙ is outlined. It rests upon a converging inflow of molecular gas building up a first population of pre-main sequence stars. The associated just-formed O stars ionise the inflow and suppress star formation in the embedded cluster. However, they typically eject each other out of the embedded cluster within 106 yr, that is before the molecular cloud filament can be ionised entirely. The inflow of molecular gas can then resume forming a second population. This sequence of events can be repeated maximally over the life-time of the molecular cloud (about 10 Myr), but is not likely to be possible in VYCs with mass <300 M⊙, because such populations are not likely to contain an O star. Stellar populations heavier than about 2000 M⊙ are likely to have too many O stars for all of these to eject each other from the embedded cluster before they disperse their natal cloud. VYCs with masses in the range 600-2000 M⊙ are likely to have such multi-age populations, while VYCs with masses in the range 2000-20 000 M⊙ can also be composed solely of co-eval, mono-age populations. More massive VYCs are not likely to host sub-populations with age differences of about 1 Myr. This model is applied to the Orion Nebula Cluster (ONC), in which three well-separated pre-main sequences in the colour-magnitude diagram of the cluster have recently been discovered. The mass-inflow history is constrained using this model and the number of OB stars ejected from each population are estimated for verification using Gaia data. As a further consequence of the proposed model, the three runaway O star systems, AE Aur, μ Col and ι Ori, are considered as significant observational evidence for stellar-dynamical ejections of massive stars from the oldest population in the ONC. Evidence for stellar-dynamical ejections of massive stars in the currently forming population is also discussed.

  7. Anharmonic resonance absorption of short laser pulses in clusters: A molecular dynamics simulation study

    NASA Astrophysics Data System (ADS)

    Mahalik, S. S.; Kundu, M.

    2016-12-01

    Linear resonance (LR) absorption of an intense 800 nm laser light in a nano-cluster requires a long laser pulse >100 fs when Mie-plasma frequency ( ω M ) of electrons in the expanding cluster matches the laser frequency (ω). For a short duration of the pulse, the condition for LR is not satisfied. In this case, it was shown by a model and particle-in-cell (PIC) simulations [Phys. Rev. Lett. 96, 123401 (2006)] that electrons absorb laser energy by anharmonic resonance (AHR) when the position-dependent frequency Ω [ r ( t ) ] of an electron in the self-consistent anharmonic potential of the cluster satisfies Ω [ r ( t ) ] = ω . However, AHR remains to be a debate and still obscure in multi-particle plasma simulations. Here, we identify AHR mechanism in a laser driven cluster using molecular dynamics (MD) simulations. By analyzing the trajectory of each MD electron and extracting its Ω [ r ( t ) ] in the self-generated anharmonic plasma potential, it is found that electron is outer ionized only when AHR is met. An anharmonic oscillator model, introduced here, brings out most of the features of MD electrons while passing the AHR. Thus, we not only bridge the gap between PIC simulations, analytical models, and MD calculations for the first time but also unequivocally prove that AHR process is a universal dominant collisionless mechanism of absorption in the short pulse regime or in the early time of longer pulses in clusters.

  8. Master-equation approach to the study of phase-change processes in data storage media

    NASA Astrophysics Data System (ADS)

    Blyuss, K. B.; Ashwin, P.; Bassom, A. P.; Wright, C. D.

    2005-07-01

    We study the dynamics of crystallization in phase-change materials using a master-equation approach in which the state of the crystallizing material is described by a cluster size distribution function. A model is developed using the thermodynamics of the processes involved and representing the clusters of size two and greater as a continuum but clusters of size one (monomers) as a separate equation. We present some partial analytical results for the isothermal case and for large cluster sizes, but principally we use numerical simulations to investigate the model. We obtain results that are in good agreement with experimental data and the model appears to be useful for the fast simulation of reading and writing processes in phase-change optical and electrical memories.

  9. Spectra of random networks in the weak clustering regime

    NASA Astrophysics Data System (ADS)

    Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen; Rodrigues, Francisco A.

    2018-03-01

    The asymptotic behavior of dynamical processes in networks can be expressed as a function of spectral properties of the corresponding adjacency and Laplacian matrices. Although many theoretical results are known for the spectra of traditional configuration models, networks generated through these models fail to describe many topological features of real-world networks, in particular non-null values of the clustering coefficient. Here we study effects of cycles of order three (triangles) in network spectra. By using recent advances in random matrix theory, we determine the spectral distribution of the network adjacency matrix as a function of the average number of triangles attached to each node for networks without modular structure and degree-degree correlations. Implications to network dynamics are discussed. Our findings can shed light in the study of how particular kinds of subgraphs influence network dynamics.

  10. MC 2: A Deeper Look at ZwCl 2341.1+0000 with Bayesian Galaxy Clustering and Weak Lensing Analyses

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

    Benson, B.; Wittman, D. M.; Golovich, N.

    ZwCl 2341.1+0000, a merging galaxy cluster with disturbed X-ray morphology and widely separated (~3 Mpc) double radio relics, was thought to be an extremely massive (10 - 30 X 10 14M⊙) and complex system with little known about its merger history. We present JVLA 2-4 GHz observations of the cluster, along with new spectroscopy from our Keck/DEIMOS survey, and apply Gaussian Mixture Modeling to the three-dimensional distribution of 227 con rmed cluster galaxies. After adopting the Bayesian Information Criterion to avoid over tting, which we discover can bias total dynamical mass estimates high, we nd that a three-substructure model withmore » a total dynamical mass estimate of 9:39 ± 0:81 X 10 14M⊙ is favored. We also present deep Subaru imaging and perform the rst weak lensing analysis on this system, obtaining a weak lensing mass estimate of 5:57±2:47X10 14M⊙. This is a more robust estimate because it does not depend on the dynamical state of the system, which is disturbed due to the merger. Our results indicate that ZwCl 2341.1+0000 is a multiple merger system comprised of at least three substructures, with the main merger that produced the radio relics occurring near to the plane of the sky, and a younger merger in the North occurring closer to the line of sight. Dynamical modeling of the main merger reproduces observed quantities (relic positions and polarizations, subcluster separation and radial velocity difference), if the merger axis angle of ~10 +34 -6 degrees and the collision speed at pericenter is ~1900 +300 -200 km/s.« less

  11. MC 2: A Deeper Look at ZwCl 2341.1+0000 with Bayesian Galaxy Clustering and Weak Lensing Analyses

    DOE PAGES

    Benson, B.; Wittman, D. M.; Golovich, N.; ...

    2017-05-16

    ZwCl 2341.1+0000, a merging galaxy cluster with disturbed X-ray morphology and widely separated (~3 Mpc) double radio relics, was thought to be an extremely massive (10 - 30 X 10 14M⊙) and complex system with little known about its merger history. We present JVLA 2-4 GHz observations of the cluster, along with new spectroscopy from our Keck/DEIMOS survey, and apply Gaussian Mixture Modeling to the three-dimensional distribution of 227 con rmed cluster galaxies. After adopting the Bayesian Information Criterion to avoid over tting, which we discover can bias total dynamical mass estimates high, we nd that a three-substructure model withmore » a total dynamical mass estimate of 9:39 ± 0:81 X 10 14M⊙ is favored. We also present deep Subaru imaging and perform the rst weak lensing analysis on this system, obtaining a weak lensing mass estimate of 5:57±2:47X10 14M⊙. This is a more robust estimate because it does not depend on the dynamical state of the system, which is disturbed due to the merger. Our results indicate that ZwCl 2341.1+0000 is a multiple merger system comprised of at least three substructures, with the main merger that produced the radio relics occurring near to the plane of the sky, and a younger merger in the North occurring closer to the line of sight. Dynamical modeling of the main merger reproduces observed quantities (relic positions and polarizations, subcluster separation and radial velocity difference), if the merger axis angle of ~10 +34 -6 degrees and the collision speed at pericenter is ~1900 +300 -200 km/s.« less

  12. Rényi information flow in the Ising model with single-spin dynamics.

    PubMed

    Deng, Zehui; Wu, Jinshan; Guo, Wenan

    2014-12-01

    The n-index Rényi mutual information and transfer entropies for the two-dimensional kinetic Ising model with arbitrary single-spin dynamics in the thermodynamic limit are derived as functions of ensemble averages of observables and spin-flip probabilities. Cluster Monte Carlo algorithms with different dynamics from the single-spin dynamics are thus applicable to estimate the transfer entropies. By means of Monte Carlo simulations with the Wolff algorithm, we calculate the information flows in the Ising model with the Metropolis dynamics and the Glauber dynamics, respectively. We find that not only the global Rényi transfer entropy, but also the pairwise Rényi transfer entropy, peaks in the disorder phase.

  13. The geometry of chaotic dynamics — a complex network perspective

    NASA Astrophysics Data System (ADS)

    Donner, R. V.; Heitzig, J.; Donges, J. F.; Zou, Y.; Marwan, N.; Kurths, J.

    2011-12-01

    Recently, several complex network approaches to time series analysis have been developed and applied to study a wide range of model systems as well as real-world data, e.g., geophysical or financial time series. Among these techniques, recurrence-based concepts and prominently ɛ-recurrence networks, most faithfully represent the geometrical fine structure of the attractors underlying chaotic (and less interestingly non-chaotic) time series. In this paper we demonstrate that the well known graph theoretical properties local clustering coefficient and global (network) transitivity can meaningfully be exploited to define two new local and two new global measures of dimension in phase space: local upper and lower clustering dimension as well as global upper and lower transitivity dimension. Rigorous analytical as well as numerical results for self-similar sets and simple chaotic model systems suggest that these measures are well-behaved in most non-pathological situations and that they can be estimated reasonably well using ɛ-recurrence networks constructed from relatively short time series. Moreover, we study the relationship between clustering and transitivity dimensions on the one hand, and traditional measures like pointwise dimension or local Lyapunov dimension on the other hand. We also provide further evidence that the local clustering coefficients, or equivalently the local clustering dimensions, are useful for identifying unstable periodic orbits and other dynamically invariant objects from time series. Our results demonstrate that ɛ-recurrence networks exhibit an important link between dynamical systems and graph theory.

  14. A Dynamical N-body model for the central region of ω Centauri

    NASA Astrophysics Data System (ADS)

    Jalali, B.; Baumgardt, H.; Kissler-Patig, M.; Gebhardt, K.; Noyola, E.; Lützgendorf, N.; de Zeeuw, P. T.

    2012-02-01

    Context. Supermassive black holes (SMBHs) are fundamental keys to understand the formation and evolution of their host galaxies. However, the formation and growth of SMBHs are not yet well understood. One of the proposed formation scenarios is the growth of SMBHs from seed intermediate-mass black holes (IMBHs, 102 to 105 M⊙) formed in star clusters. In this context, and also with respect to the low mass end of the M• - σ relation for galaxies, globular clusters are in a mass range that make them ideal systems to look for IMBHs. Among Galactic star clusters, the massive cluster ω Centauri is a special target due to its central high velocity dispersion and also its multiple stellar populations. Aims: We study the central structure and dynamics of the star cluster ω Centauri to examine whether an IMBH is necessary to explain the observed velocity dispersion and surface brightness profiles. Methods: We perform direct N-body simulations on GPU and GRAPE special purpose computers to follow the dynamical evolution of ω Centauri. The simulations are compared to the most recent data-sets in order to explain the present-day conditions of the cluster and to constrain the initial conditions leading to the observed profiles. Results: We find that starting from isotropic spherical multi-mass King models and within our canonical assumptions, a model with a central IMBH mass of 2% of the cluster stellar mass, i.e. a 5. × 104 M⊙ IMBH, provides a satisfactory fit to both the observed shallow cusp in surface brightness and the continuous rise towards the center of the radial velocity dispersion profile. In our isotropic spherical models, the predicted proper motion dispersion for the best-fit model is the same as the radial velocity dispersion one. Conclusions: We conclude that with the presence of a central IMBH in our models, we reproduce consistently the rise in the radial velocity dispersion. Furthermore, we always end up with a shallow cusp in the projected surface brightness of our model clusters containing an IMBH. In addition, we find that the M/L ratio seems to be constant in the central region, and starts to rise slightly from the core radius outwards for all models independent of the presence of a black hole. Considering our initial parameter space, it is not possible to explain the observations without a central IMBH for ω Centauri. To further strengthen the presence of an IMBH as a unique explanation of the observed light and kinematics more detailed analysis such as investigating the contribution of primordial binaries and different anisotropy profiles should be studied.

  15. Sub-nanometer glass surface dynamics induced by illumination

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

    Nguyen, Duc; Nienhaus, Lea; Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801

    2015-06-21

    Illumination is known to induce stress and morphology changes in opaque glasses. Amorphous silicon carbide (a-SiC) has a smaller bandgap than the crystal. Thus, we were able to excite with 532 nm light a 1 μm amorphous surface layer on a SiC crystal while recording time-lapse movies of glass surface dynamics by scanning tunneling microscopy (STM). Photoexcitation of the a-SiC surface layer through the transparent crystal avoids heating the STM tip. Up to 6 × 10{sup 4} s, long movies of surface dynamics with 40 s time resolution and sub-nanometer spatial resolution were obtained. Clusters of ca. 3-5 glass formingmore » units diameter are seen to cooperatively hop between two states at the surface. Photoexcitation with green laser light recruits immobile clusters to hop, rather than increasing the rate at which already mobile clusters hop. No significant laser heating was observed. Thus, we favor an athermal mechanism whereby electronic excitation of a-SiC directly controls glassy surface dynamics. This mechanism is supported by an exciton migration-relaxation-thermal diffusion model. Individual clusters take ∼1 h to populate states differently after the light intensity has changed. We believe the surrounding matrix rearranges slowly when it is stressed by a change in laser intensity, and clusters serve as a diagnostic. Such cluster hopping and matrix rearrangement could underlie the microscopic mechanism of photoinduced aging of opaque glasses.« less

  16. Dynamic competitive probabilistic principal components analysis.

    PubMed

    López-Rubio, Ezequiel; Ortiz-DE-Lazcano-Lobato, Juan Miguel

    2009-04-01

    We present a new neural model which extends the classical competitive learning (CL) by performing a Probabilistic Principal Components Analysis (PPCA) at each neuron. The model also has the ability to learn the number of basis vectors required to represent the principal directions of each cluster, so it overcomes a drawback of most local PCA models, where the dimensionality of a cluster must be fixed a priori. Experimental results are presented to show the performance of the network with multispectral image data.

  17. DO INTERMEDIATE-MASS BLACK HOLES EXIST IN GLOBULAR CLUSTERS?

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

    Sun, Mou-Yuan; Jin, Ya-Ling; Gu, Wei-Min

    2013-10-20

    The existence of intermediate-mass black holes (IMBHs) in globular clusters (GCs) remains a crucial problem. Searching for IMBHs in GCs reveals a discrepancy between radio observations and dynamical modelings: the upper mass limits constrained by radio observations are systematically lower than that of dynamical modelings. One possibility for such a discrepancy is that, as we suggest in this work, there exist outflows in accretion flows. Our results indicate that, for most sources, current radio observations cannot rule out the possibility that IMBHs may exist in GCs. In addition, we adopt an M-dot -L{sub R} relation to revisit this issue, whichmore » confirms the results obtained by the fundamental plane relation.« less

  18. EM Transition Sum Rules Within the Framework of sdg Proton-Neutron Interacting Boson Model, Nuclear Pair Shell Model and Fermion Dynamical Symmetry Model

    NASA Astrophysics Data System (ADS)

    Zhao, Yumin

    1997-07-01

    By the techniques of the Wick theorem for coupled clusters, the no-energy-weighted electromagnetic sum-rule calculations are presented in the sdg neutron-proton interacting boson model, the nuclear pair shell model and the fermion-dynamical symmetry model. The project supported by Development Project Foundation of China, National Natural Science Foundation of China, Doctoral Education Fund of National Education Committee, Fundamental Research Fund of Southeast University

  19. Bidirectional Coupling between Astrocytes and Neurons Mediates Learning and Dynamic Coordination in the Brain: A Multiple Modeling Approach

    PubMed Central

    Wade, John J.; McDaid, Liam J.; Harkin, Jim; Crunelli, Vincenzo; Kelso, J. A. Scott

    2011-01-01

    In recent years research suggests that astrocyte networks, in addition to nutrient and waste processing functions, regulate both structural and synaptic plasticity. To understand the biological mechanisms that underpin such plasticity requires the development of cell level models that capture the mutual interaction between astrocytes and neurons. This paper presents a detailed model of bidirectional signaling between astrocytes and neurons (the astrocyte-neuron model or AN model) which yields new insights into the computational role of astrocyte-neuronal coupling. From a set of modeling studies we demonstrate two significant findings. Firstly, that spatial signaling via astrocytes can relay a “learning signal” to remote synaptic sites. Results show that slow inward currents cause synchronized postsynaptic activity in remote neurons and subsequently allow Spike-Timing-Dependent Plasticity based learning to occur at the associated synapses. Secondly, that bidirectional communication between neurons and astrocytes underpins dynamic coordination between neuron clusters. Although our composite AN model is presently applied to simplified neural structures and limited to coordination between localized neurons, the principle (which embodies structural, functional and dynamic complexity), and the modeling strategy may be extended to coordination among remote neuron clusters. PMID:22242121

  20. Analysis of candidates for interacting galaxy clusters. I. A1204 and A2029/A2033

    NASA Astrophysics Data System (ADS)

    Gonzalez, Elizabeth Johana; de los Rios, Martín; Oio, Gabriel A.; Lang, Daniel Hernández; Tagliaferro, Tania Aguirre; Domínguez R., Mariano J.; Castellón, José Luis Nilo; Cuevas L., Héctor; Valotto, Carlos A.

    2018-04-01

    Context. Merging galaxy clusters allow for the study of different mass components, dark and baryonic, separately. Also, their occurrence enables to test the ΛCDM scenario, which can be used to put constraints on the self-interacting cross-section of the dark-matter particle. Aim. It is necessary to perform a homogeneous analysis of these systems. Hence, based on a recently presented sample of candidates for interacting galaxy clusters, we present the analysis of two of these cataloged systems. Methods: In this work, the first of a series devoted to characterizing galaxy clusters in merger processes, we perform a weak lensing analysis of clusters A1204 and A2029/A2033 to derive the total masses of each identified interacting structure together with a dynamical study based on a two-body model. We also describe the gas and the mass distributions in the field through a lensing and an X-ray analysis. This is the first of a series of works which will analyze these type of system in order to characterize them. Results: Neither merging cluster candidate shows evidence of having had a recent merger event. Nevertheless, there is dynamical evidence that these systems could be interacting or could interact in the future. Conclusions: It is necessary to include more constraints in order to improve the methodology of classifying merging galaxy clusters. Characterization of these clusters is important in order to properly understand the nature of these systems and their connection with dynamical studies.

  1. Influence of Ganglioside GM1 Concentration on Lipid Clustering and Membrane Properties and Curvature.

    PubMed

    Patel, Dhilon S; Park, Soohyung; Wu, Emilia L; Yeom, Min Sun; Widmalm, Göran; Klauda, Jeffery B; Im, Wonpil

    2016-11-01

    Gangliosides are a class of glycosphingolipids (GSLs) with amphiphilic character that are found at the outer leaflet of the cell membranes, where their ability to organize into special domains makes them vital cell membrane components. However, a molecular understanding of GSL-rich membranes in terms of their clustered organization, stability, and dynamics is still elusive. To gain molecular insight into the organization and dynamics of GSL-rich membranes, we performed all-atom molecular-dynamics simulations of bicomponent ganglioside GM1 in 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) phospholipid bilayers with varying concentrations of GM1 (10%, 20%, and 30%). Overall, the simulations show very good agreement with available experimental data, including x-ray electron density profiles along the membrane normal, NMR carbohydrate proton-proton distances, and x-ray crystal structures. This validates the quality of our model systems for investigating GM1 clustering through an ordered-lipid-cluster analysis. The increase in GM1 concentration induces tighter lipid packing, driven mainly by inter-GM1 carbohydrate-carbohydrate interactions, leading to a greater preference for the positive curvature of GM1-containing membranes and larger cluster sizes of ordered-lipid clusters (with a composite of GM1 and POPC). These clusters tend to segregate and form a large percolated cluster at a 30% GM1 concentration at 293 K. At a higher temperature of 330 K, however, the segregation is not maintained. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  2. Thermodynamic scaling of dynamic properties of liquid crystals: Verifying the scaling parameters using a molecular model

    NASA Astrophysics Data System (ADS)

    Satoh, Katsuhiko

    2013-08-01

    The thermodynamic scaling of molecular dynamic properties of rotation and thermodynamic parameters in a nematic phase was investigated by a molecular dynamic simulation using the Gay-Berne potential. A master curve for the relaxation time of flip-flop motion was obtained using thermodynamic scaling, and the dynamic property could be solely expressed as a function of TV^{γ _τ }, where T and V are the temperature and volume, respectively. The scaling parameter γτ was in excellent agreement with the thermodynamic parameter Γ, which is the logarithm of the slope of a line plotted for the temperature and volume at constant P2. This line was fairly linear, and as good as the line for p-azoxyanisole or using the highly ordered small cluster model. The equivalence relation between Γ and γτ was compared with results obtained from the highly ordered small cluster model. The possibility of adapting the molecular model for the thermodynamic scaling of other dynamic rotational properties was also explored. The rotational diffusion constant and rotational viscosity coefficients, which were calculated using established theoretical and experimental expressions, were rescaled onto master curves with the same scaling parameters. The simulation illustrates the universal nature of the equivalence relation for liquid crystals.

  3. Speculative behavior and asset price dynamics.

    PubMed

    Westerhoff, Frank

    2003-07-01

    This paper deals with speculative trading. Guided by empirical observations, a nonlinear deterministic asset pricing model is developed in which traders repeatedly choose between technical and fundamental analysis to determine their orders. The interaction between the trading rules produces complex dynamics. The model endogenously replicates the stylized facts of excess volatility, high trading volumes, shifts in the level of asset prices, and volatility clustering.

  4. Applying the Dynamic Social Systems Model to HIV Prevention in a Rural African Context: The Maasai and the "Esoto" Dance

    ERIC Educational Resources Information Center

    Siegler, Aaron J.; Mbwambo, Jessie K.; DiClemente, Ralph J.

    2013-01-01

    This study applied the Dynamic Social Systems Model (DSSM) to the issue of HIV risk among the Maasai tribe of Tanzania, using data from a cross-sectional, cluster survey among 370 randomly selected participants from Ngorongoro and Siha Districts. A culturally appropriate survey instrument was developed to explore traditions reportedly coadunate…

  5. Star Formation History In Merging Galaxies

    NASA Astrophysics Data System (ADS)

    Chien, Li-Hsin

    2009-01-01

    Interacting and merging galaxies are believed to play an important role in many aspects of galactic evolution. Their violent interactions can trigger starbursts, which lead to formation of young globular clusters. Therefore the ages of these young globular clusters can be interpreted to yield the timing of interaction-triggered events, and thus provide a key to reconstruct the star formation history in merging galaxies. The link between galaxy interaction and star formation is well established, but the triggers of star formation in interacting galaxies are still not understood. To date there are two competing formulas that describe the star formation mechanism--density-dependent and shock-induced rules. Numerical models implementing the two rules predict significantly different star formation histories in merging galaxies. My dissertation combines these two distinct areas of astrophysics, stellar evolution and galactic dynamics, to investigate the star formation history in galaxies at various merging stages. Begin with NGC 4676 as an example, I will briefly describe its model and illustrate the idea of using the ages of clusters to constrain the modeling. The ages of the clusters are derived from spectra that were taken with multi-object spectroscopy on Keck. Using NGC 7252 as a second example, I will present a state of the art dynamical model which predicts NGC7252's star formation history and other properties. I will then show a detailed comparison and analysis between the clusters and the modeling. In the end, I will address this important link as the key to answer the fundamental question of my thesis: what is the trigger of star formation in merging galaxies?

  6. Dimension dependence of clustering dynamics in models of ballistic aggregation and freely cooling granular gas

    NASA Astrophysics Data System (ADS)

    Paul, Subhajit; Das, Subir K.

    2018-03-01

    Via event-driven molecular dynamics simulations we study kinetics of clustering in assemblies of inelastic particles in various space dimensions. We consider two models, viz., the ballistic aggregation model (BAM) and the freely cooling granular gas model (GGM), for each of which we quantify the time dependence of kinetic energy and average mass of clusters (that form due to inelastic collisions). These quantities, for both the models, exhibit power-law behavior, at least in the long time limit. For the BAM, corresponding exponents exhibit strong dimension dependence and follow a hyperscaling relation. In addition, in the high packing fraction limit the behavior of these quantities become consistent with a scaling theory that predicts an inverse relation between energy and mass. On the other hand, in the case of the GGM we do not find any evidence for such a picture. In this case, even though the energy decay, irrespective of packing fraction, matches quantitatively with that for the high packing fraction picture of the BAM, it is inversely proportional to the growth of mass only in one dimension, and the growth appears to be rather insensitive to the choice of the dimension, unlike the BAM.

  7. ODE, RDE and SDE models of cell cycle dynamics and clustering in yeast.

    PubMed

    Boczko, Erik M; Gedeon, Tomas; Stowers, Chris C; Young, Todd R

    2010-07-01

    Biologists have long observed periodic-like oxygen consumption oscillations in yeast populations under certain conditions, and several unsatisfactory explanations for this phenomenon have been proposed. These ‘autonomous oscillations’ have often appeared with periods that are nearly integer divisors of the calculated doubling time of the culture. We hypothesize that these oscillations could be caused by a form of cell cycle synchronization that we call clustering. We develop some novel ordinary differential equation models of the cell cycle. For these models, and for random and stochastic perturbations, we give both rigorous proofs and simulations showing that both positive and negative growth rate feedback within the cell cycle are possible agents that can cause clustering of populations within the cell cycle. It occurs for a variety of models and for a broad selection of parameter values. These results suggest that the clustering phenomenon is robust and is likely to be observed in nature. Since there are necessarily an integer number of clusters, clustering would lead to periodic-like behaviour with periods that are nearly integer divisors of the period of the cell cycle. Related experiments have shown conclusively that cell cycle clustering occurs in some oscillating yeast cultures.

  8. A discrete in continuous mathematical model of cardiac progenitor cells formation and growth as spheroid clusters (Cardiospheres).

    PubMed

    Di Costanzo, Ezio; Giacomello, Alessandro; Messina, Elisa; Natalini, Roberto; Pontrelli, Giuseppe; Rossi, Fabrizio; Smits, Robert; Twarogowska, Monika

    2018-03-14

    We propose a discrete in continuous mathematical model describing the in vitro growth process of biophsy-derived mammalian cardiac progenitor cells growing as clusters in the form of spheres (Cardiospheres). The approach is hybrid: discrete at cellular scale and continuous at molecular level. In the present model, cells are subject to the self-organizing collective dynamics mechanism and, additionally, they can proliferate and differentiate, also depending on stochastic processes. The two latter processes are triggered and regulated by chemical signals present in the environment. Numerical simulations show the structure and the development of the clustered progenitors and are in a good agreement with the results obtained from in vitro experiments.

  9. Transcription factor clusters regulate genes in eukaryotic cells

    PubMed Central

    Hedlund, Erik G; Friemann, Rosmarie; Hohmann, Stefan

    2017-01-01

    Transcription is regulated through binding factors to gene promoters to activate or repress expression, however, the mechanisms by which factors find targets remain unclear. Using single-molecule fluorescence microscopy, we determined in vivo stoichiometry and spatiotemporal dynamics of a GFP tagged repressor, Mig1, from a paradigm signaling pathway of Saccharomyces cerevisiae. We find the repressor operates in clusters, which upon extracellular signal detection, translocate from the cytoplasm, bind to nuclear targets and turnover. Simulations of Mig1 configuration within a 3D yeast genome model combined with a promoter-specific, fluorescent translation reporter confirmed clusters are the functional unit of gene regulation. In vitro and structural analysis on reconstituted Mig1 suggests that clusters are stabilized by depletion forces between intrinsically disordered sequences. We observed similar clusters of a co-regulatory activator from a different pathway, supporting a generalized cluster model for transcription factors that reduces promoter search times through intersegment transfer while stabilizing gene expression. PMID:28841133

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

    Sills, Alison; Glebbeek, Evert; Chatterjee, Sourav

    We created artificial color-magnitude diagrams of Monte Carlo dynamical models of globular clusters and then used observational methods to determine the number of blue stragglers in those clusters. We compared these blue stragglers to various cluster properties, mimicking work that has been done for blue stragglers in Milky Way globular clusters to determine the dominant formation mechanism(s) of this unusual stellar population. We find that a mass-based prescription for selecting blue stragglers will select approximately twice as many blue stragglers than a selection criterion that was developed for observations of real clusters. However, the two numbers of blue stragglers aremore » well-correlated, so either selection criterion can be used to characterize the blue straggler population of a cluster. We confirm previous results that the simplified prescription for the evolution of a collision or merger product in the BSE code overestimates their lifetimes. We show that our model blue stragglers follow similar trends with cluster properties (core mass, binary fraction, total mass, collision rate) as the true Milky Way blue stragglers as long as we restrict ourselves to model clusters with an initial binary fraction higher than 5%. We also show that, in contrast to earlier work, the number of blue stragglers in the cluster core does have a weak dependence on the collisional parameter Γ in both our models and in Milky Way globular clusters.« less

  11. Environment overwhelms both nature and nurture in a model spin glass

    NASA Astrophysics Data System (ADS)

    Middleton, A. Alan; Yang, Jie

    We are interested in exploring what information determines the particular history of the glassy long term dynamics in a disordered material. We study the effect of initial configurations and the realization of stochastic dynamics on the long time evolution of configurations in a two-dimensional Ising spin glass model. The evolution of nearest neighbor correlations is computed using patchwork dynamics, a coarse-grained numerical heuristic for temporal evolution. The dependence of the nearest neighbor spin correlations at long time on both initial spin configurations and noise histories are studied through cross-correlations of long-time configurations and the spin correlations are found to be independent of both. We investigate how effectively rigid bond clusters coarsen. Scaling laws are used to study the convergence of configurations and the distribution of sizes of nearly rigid clusters. The implications of the computational results on simulations and phenomenological models of spin glasses are discussed. We acknowledge NSF support under DMR-1410937 (CMMT program).

  12. Community detection using Kernel Spectral Clustering with memory

    NASA Astrophysics Data System (ADS)

    Langone, Rocco; Suykens, Johan A. K.

    2013-02-01

    This work is related to the problem of community detection in dynamic scenarios, which for instance arises in the segmentation of moving objects, clustering of telephone traffic data, time-series micro-array data etc. A desirable feature of a clustering model which has to capture the evolution of communities over time is the temporal smoothness between clusters in successive time-steps. In this way the model is able to track the long-term trend and in the same time it smooths out short-term variation due to noise. We use the Kernel Spectral Clustering with Memory effect (MKSC) which allows to predict cluster memberships of new nodes via out-of-sample extension and has a proper model selection scheme. It is based on a constrained optimization formulation typical of Least Squares Support Vector Machines (LS-SVM), where the objective function is designed to explicitly incorporate temporal smoothness as a valid prior knowledge. The latter, in fact, allows the model to cluster the current data well and to be consistent with the recent history. Here we propose a generalization of the MKSC model with an arbitrary memory, not only one time-step in the past. The experiments conducted on toy problems confirm our expectations: the more memory we add to the model, the smoother over time are the clustering results. We also compare with the Evolutionary Spectral Clustering (ESC) algorithm which is a state-of-the art method, and we obtain comparable or better results.

  13. Graph partitions and cluster synchronization in networks of oscillators

    PubMed Central

    Schaub, Michael T.; O’Clery, Neave; Billeh, Yazan N.; Delvenne, Jean-Charles; Lambiotte, Renaud; Barahona, Mauricio

    2017-01-01

    Synchronization over networks depends strongly on the structure of the coupling between the oscillators. When the coupling presents certain regularities, the dynamics can be coarse-grained into clusters by means of External Equitable Partitions of the network graph and their associated quotient graphs. We exploit this graph-theoretical concept to study the phenomenon of cluster synchronization, in which different groups of nodes converge to distinct behaviors. We derive conditions and properties of networks in which such clustered behavior emerges, and show that the ensuing dynamics is the result of the localization of the eigenvectors of the associated graph Laplacians linked to the existence of invariant subspaces. The framework is applied to both linear and non-linear models, first for the standard case of networks with positive edges, before being generalized to the case of signed networks with both positive and negative interactions. We illustrate our results with examples of both signed and unsigned graphs for consensus dynamics and for partial synchronization of oscillator networks under the master stability function as well as Kuramoto oscillators. PMID:27781454

  14. The effect of host cluster gravitational tidal forces on the internal dynamics of spiral galaxies

    NASA Astrophysics Data System (ADS)

    Mayer, Alexander

    2013-04-01

    New empirical observation by Bidin, Carraro, Mendez & Smith finds ``a lack of dark matter in the Solar neighborhood" (2012 ApJ 751, 30). This, and the discovery of a vast polar structure of Milky Way satellites by Pawlowski, Pflamm-Altenburg & Kroupa (2012 MNRAS 423, 1109), conflict with the prevailing interpretation of the measured Galactic rotation curve. Simulating the dynamical effects of host cluster tidal forces on galaxy disks reveals radial migration in a spiral structure and an orbital velocity that accelerates with increasing galactocentric radial coordinate. A virtual ``toy model,'' which is based on an Earth-orbiting system of particles and is physically realizable in principle, is available at GravitySim.net. Given the perturbing gravitational effect of the host cluster on a spiral galaxy disk and that a similar effect does not exist for the Solar System, the two systems represent distinct classes of gravitational dynamical systems. The observed `flat' and accelerating rotation curves of spiral galaxies can be attributed to gravitational interaction with the host cluster; no `dark matter halo' is required to explain the observable.

  15. IoT Service Clustering for Dynamic Service Matchmaking.

    PubMed

    Zhao, Shuai; Yu, Le; Cheng, Bo; Chen, Junliang

    2017-07-27

    As the adoption of service-oriented paradigms in the IoT (Internet of Things) environment, real-world devices will open their capabilities through service interfaces, which enable other functional entities to interact with them. In an IoT application, it is indispensable to find suitable services for satisfying users' requirements or replacing the unavailable services. However, from the perspective of performance, it is inappropriate to find desired services from the service repository online directly. Instead, clustering services offline according to their similarity and matchmaking or discovering service online in limited clusters is necessary. This paper proposes a multidimensional model-based approach to measure the similarity between IoT services. Then, density-peaks-based clustering is employed to gather similar services together according to the result of similarity measurement. Based on the service clustering, the algorithms of dynamic service matchmaking, discovery, and replacement will be performed efficiently. Evaluating experiments are conducted to validate the performance of proposed approaches, and the results are promising.

  16. IoT Service Clustering for Dynamic Service Matchmaking

    PubMed Central

    Yu, Le; Cheng, Bo; Chen, Junliang

    2017-01-01

    As the adoption of service-oriented paradigms in the IoT (Internet of Things) environment, real-world devices will open their capabilities through service interfaces, which enable other functional entities to interact with them. In an IoT application, it is indispensable to find suitable services for satisfying users’ requirements or replacing the unavailable services. However, from the perspective of performance, it is inappropriate to find desired services from the service repository online directly. Instead, clustering services offline according to their similarity and matchmaking or discovering service online in limited clusters is necessary. This paper proposes a multidimensional model-based approach to measure the similarity between IoT services. Then, density-peaks-based clustering is employed to gather similar services together according to the result of similarity measurement. Based on the service clustering, the algorithms of dynamic service matchmaking, discovery, and replacement will be performed efficiently. Evaluating experiments are conducted to validate the performance of proposed approaches, and the results are promising. PMID:28749431

  17. Cluster dynamics of pulse coupled oscillators

    NASA Astrophysics Data System (ADS)

    O'Keeffe, Kevin; Strogatz, Steven; Krapivsky, Paul

    2015-03-01

    We study the dynamics of networks of pulse coupled oscillators. Much attention has been devoted to the ultimate fate of the system: which conditions lead to a steady state in which all the oscillators are firing synchronously. But little is known about how synchrony builds up from an initially incoherent state. The current work addresses this question. Oscillators start to synchronize by forming clusters of different sizes that fire in unison. First pairs of oscillators, then triplets and so on. These clusters progressively grow by coalescing with others, eventually resulting in the fully synchronized state. We study the mean field model in which the coupling between oscillators is all to all. We use probabilistic arguments to derive a recursive set of evolution equations for these clusters. Using a generating function formalism, we derive simple equations for the moments of these clusters. Our results are in good agreement simulation. We then numerically explore the effects of non-trivial connectivity. Our results have potential application to ultra-low power ``impulse radio'' & sensor networks.

  18. Diffusion dynamics of the Li+ ion on a model surface of amorphous carbon: a direct molecular orbital dynamics study.

    PubMed

    Tachikawa, Hiroto; Shimizu, Akira

    2005-07-14

    Diffusion processes of the Li+ ion on a model surface of amorphous carbon (Li+C96H24 system) have been investigated by means of the direct molecular orbital (MO) dynamics method at the semiempirical AM1 level. The total energy and energy gradient on the full-dimensional AM1 potential energy surface were calculated at each time step in the dynamics calculation. The optimized structure, where Li+ is located in the center of the cluster, was used as the initial structure at time zero. The dynamics calculation was carried out in the temperature range 100-1000 K. The calculations showed that the Li+ ion vibrates around the equilibrium point below 200 K, while the Li+ ion moves on the surface above 250 K. At intermediate temperatures (300 K < T < 400 K), the ion moves on the surface and falls in the edge regions of the cluster. At higher temperatures (600 K < T), the Li+ ion transfers freely on the surface and edge regions. The diffusion pathway of the Li+ ion was discussed on the basis of theoretical results.

  19. Binary black hole mergers from globular clusters: Masses, merger rates, and the impact of stellar evolution

    NASA Astrophysics Data System (ADS)

    Rodriguez, Carl L.; Chatterjee, Sourav; Rasio, Frederic A.

    2016-04-01

    The recent discovery of GW150914, the binary black hole merger detected by Advanced LIGO, has the potential to revolutionize observational astrophysics. But to fully utilize this new window into the Universe, we must compare these new observations to detailed models of binary black hole formation throughout cosmic time. Expanding upon our previous work [C. L. Rodriguez, M. Morscher, B. Pattabiraman, S. Chatterjee, C.-J. Haster, and F. A. Rasio, Phys. Rev. Lett. 115, 051101 (2015).], we study merging binary black holes formed in globular clusters using our Monte Carlo approach to stellar dynamics. We have created a new set of 52 cluster models with different masses, metallicities, and radii to fully characterize the binary black hole merger rate. These models include all the relevant dynamical processes (such as two-body relaxation, strong encounters, and three-body binary formation) and agree well with detailed direct N -body simulations. In addition, we have enhanced our stellar evolution algorithms with updated metallicity-dependent stellar wind and supernova prescriptions, allowing us to compare our results directly to the most recent population synthesis predictions for merger rates from isolated binary evolution. We explore the relationship between a cluster's global properties and the population of binary black holes that it produces. In particular, we derive a numerically calibrated relationship between the merger times of ejected black hole binaries and a cluster's mass and radius. With our improved treatment of stellar evolution, we find that globular clusters can produce a significant population of massive black hole binaries that merge in the local Universe. We explore the masses and mass ratios of these binaries as a function of redshift, and find a merger rate of ˜5 Gpc-3yr-1 in the local Universe, with 80% of sources having total masses from 32 M⊙ to 64 M⊙. Under standard assumptions, approximately one out of every seven binary black hole mergers in the local Universe will have originated in a globular cluster, but we also explore the sensitivity of this result to different assumptions for binary stellar evolution. If black holes were born with significant natal kicks, comparable to those of neutron stars, then the merger rate of binary black holes from globular clusters would be comparable to that from the field, with approximately 1 /2 of mergers originating in clusters. Finally we point out that population synthesis results for the field may also be modified by dynamical interactions of binaries taking place in dense star clusters which, unlike globular clusters, dissolved before the present day.

  20. On the spatial dynamics and oscillatory behavior of a predator-prey model based on cellular automata and local particle swarm optimization.

    PubMed

    Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan

    2013-11-07

    A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior. © 2013 Elsevier Ltd. All rights reserved.

  1. Mechanism for Collective Cell Alignment in Myxococcus xanthus Bacteria

    PubMed Central

    Balagam, Rajesh; Igoshin, Oleg A.

    2015-01-01

    Myxococcus xanthus cells self-organize into aligned groups, clusters, at various stages of their lifecycle. Formation of these clusters is crucial for the complex dynamic multi-cellular behavior of these bacteria. However, the mechanism underlying the cell alignment and clustering is not fully understood. Motivated by studies of clustering in self-propelled rods, we hypothesized that M. xanthus cells can align and form clusters through pure mechanical interactions among cells and between cells and substrate. We test this hypothesis using an agent-based simulation framework in which each agent is based on the biophysical model of an individual M. xanthus cell. We show that model agents, under realistic cell flexibility values, can align and form cell clusters but only when periodic reversals of cell directions are suppressed. However, by extending our model to introduce the observed ability of cells to deposit and follow slime trails, we show that effective trail-following leads to clusters in reversing cells. Furthermore, we conclude that mechanical cell alignment combined with slime-trail-following is sufficient to explain the distinct clustering behaviors observed for wild-type and non-reversing M. xanthus mutants in recent experiments. Our results are robust to variation in model parameters, match the experimentally observed trends and can be applied to understand surface motility patterns of other bacterial species. PMID:26308508

  2. Stability and dynamic of strain mediated adatom superlattices on Cu<111 >

    NASA Astrophysics Data System (ADS)

    Kappus, Wolfgang

    2013-03-01

    Substrate strain mediated adatom equilibrium density distributions have been calculated for Cu<111 > surfaces using two complementing methods. A hexagonal adatom superlattice in a coverage range up to 0.045 ML is derived for repulsive short range interactions. For zero short range interactions a hexagonal superstructure of adatom clusters is derived in a coverage range about 0.08 ML. Conditions for the stability of the superlattice against formation of dimers or clusters and degradation are analyzed using simple neighborhood models. Such models are also used to investigate the dynamic of adatoms within their superlattice neighborhood. Collective modes of adatom diffusion are proposed from the analogy with bulk lattice dynamics and methods for measurement are suggested. The recently put forward explanation of surface state mediated interactions for superstructures found in scanning tunneling microscopy experiments is put in question and strain mediated interactions are proposed as an alternative.

  3. Ballistic aggregation in systems of inelastic particles: Cluster growth, structure, and aging

    NASA Astrophysics Data System (ADS)

    Paul, Subhajit; Das, Subir K.

    2017-07-01

    We study far-from-equilibrium dynamics in models of freely cooling granular gas and ballistically aggregating compact clusters. For both the cases, from event-driven molecular dynamics simulations, we have presented detailed results on structure and dynamics in space dimensions d =1 and 2. Via appropriate analyses it has been confirmed that the ballistic aggregation mechanism applies in d =1 granular gases as well. Aging phenomena for this mechanism, in both the dimensions, have been studied via the two-time density autocorrelation function. This quantity is demonstrated to exhibit scaling property similar to that in the standard phase transition kinetics. The corresponding functional forms have been quantified and the outcomes have been discussed in connection with the structural properties. Our results on aging establish a more complete equivalence between the granular gas and the ballistic aggregation models in d =1 .

  4. Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Support Distribution Machines

    NASA Astrophysics Data System (ADS)

    Ntampaka, Michelle; Trac, Hy; Sutherland, Dougal; Fromenteau, Sebastien; Poczos, Barnabas; Schneider, Jeff

    2018-01-01

    We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning (ML) algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark’s publicly available N-body MDPL1 simulation, one with perfect galaxy cluster membership infor- mation and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power-law scaling relation to infer cluster mass from galaxy line-of-sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with a width E=0.87. Interlopers introduce additional scatter, significantly widening the error distribution further (E=2.13). We employ the support distribution machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement (E=0.67) for the contaminated case. Remarkably, SDM applied to contaminated clusters is better able to recover masses than even the scaling relation approach applied to uncon- taminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.

  5. Calculation of the wetting parameter from a cluster model in the framework of nanothermodynamics.

    PubMed

    García-Morales, V; Cervera, J; Pellicer, J

    2003-06-01

    The critical wetting parameter omega(c) determines the strength of interfacial fluctuations in critical wetting transitions. In this Brief Report, we calculate omega(c) from considerations on critical liquid clusters inside a vapor phase. The starting point is a cluster model developed by Hill and Chamberlin in the framework of nanothermodynamics [Proc. Natl. Acad. Sci. USA 95, 12779 (1998)]. Our calculations yield results for omega(c) between 0.52 and 1.00, depending on the degrees of freedom considered. The findings are in agreement with previous experimental results and give an idea of the universal dynamical behavior of the clusters when approaching criticality. We suggest that this behavior is a combination of translation and vortex rotational motion (omega(c)=0.84).

  6. Cluster geometry and survival probability in systems driven by reaction diffusion dynamics

    NASA Astrophysics Data System (ADS)

    Windus, Alastair; Jensen, Henrik J.

    2008-11-01

    We consider a reaction-diffusion model incorporating the reactions A→phi, A→2A and 2A→3A. Depending on the relative rates for sexual and asexual reproduction of the quantity A, the model exhibits either a continuous or first-order absorbing phase transition to an extinct state. A tricritical point separates the two phase lines. While we comment on this critical behaviour, the main focus of the paper is on the geometry of the population clusters that form. We observe the different cluster structures that arise at criticality for the three different types of critical behaviour and show that there exists a linear relationship for the survival probability against initial cluster size at the tricritical point only.

  7. A Modified Dynamic Evolving Neural-Fuzzy Approach to Modeling Customer Satisfaction for Affective Design

    PubMed Central

    Kwong, C. K.; Fung, K. Y.; Jiang, Huimin; Chan, K. Y.

    2013-01-01

    Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1) the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS) failed to run due to a large number of inputs; (2) the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort. PMID:24385884

  8. A modified dynamic evolving neural-fuzzy approach to modeling customer satisfaction for affective design.

    PubMed

    Kwong, C K; Fung, K Y; Jiang, Huimin; Chan, K Y; Siu, Kin Wai Michael

    2013-01-01

    Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1) the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS) failed to run due to a large number of inputs; (2) the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

  9. Binary Black Hole Mergers from Globular Clusters: Implications for Advanced LIGO.

    PubMed

    Rodriguez, Carl L; Morscher, Meagan; Pattabiraman, Bharath; Chatterjee, Sourav; Haster, Carl-Johan; Rasio, Frederic A

    2015-07-31

    The predicted rate of binary black hole mergers from galactic fields can vary over several orders of magnitude and is extremely sensitive to the assumptions of stellar evolution. But in dense stellar environments such as globular clusters, binary black holes form by well-understood gravitational interactions. In this Letter, we study the formation of black hole binaries in an extensive collection of realistic globular cluster models. By comparing these models to observed Milky Way and extragalactic globular clusters, we find that the mergers of dynamically formed binaries could be detected at a rate of ∼100 per year, potentially dominating the binary black hole merger rate. We also find that a majority of cluster-formed binaries are more massive than their field-formed counterparts, suggesting that Advanced LIGO could identify certain binaries as originating from dense stellar environments.

  10. Fusion And Inference From Multiple And Massive Disparate Distributed Dynamic Data Sets

    DTIC Science & Technology

    2017-07-01

    principled methodology for two-sample graph testing; designed a provably almost-surely perfect vertex clustering algorithm for block model graphs; proved...3.7 Semi-Supervised Clustering Methodology ...................................................................... 9 3.8 Robust Hypothesis Testing...dimensional Euclidean space – allows the full arsenal of statistical and machine learning methodology for multivariate Euclidean data to be deployed for

  11. Spreading of correlations in the Falicov-Kimball model

    NASA Astrophysics Data System (ADS)

    Herrmann, Andreas J.; Antipov, Andrey E.; Werner, Philipp

    2018-04-01

    We study dynamical properties of the one- and two-dimensional Falicov-Kimball model using lattice Monte Carlo simulations. In particular, we calculate the spreading of charge correlations in the equilibrium model and after an interaction quench. The results show a reduction of the light-cone velocity with interaction strength at low temperature, while the phase velocity increases. At higher temperature, the initial spreading is determined by the Fermi velocity of the noninteracting system and the maximum range of the correlations decreases with increasing interaction strength. Charge order correlations in the disorder potential enhance the range of the correlations. We also use the numerically exact lattice Monte Carlo results to benchmark the accuracy of equilibrium and nonequilibrium dynamical cluster approximation calculations. It is shown that the bias introduced by the mapping to a periodized cluster is substantial, and that from a numerical point of view, it is more efficient to simulate the lattice model directly.

  12. Robust sequential working memory recall in heterogeneous cognitive networks

    PubMed Central

    Rabinovich, Mikhail I.; Sokolov, Yury; Kozma, Robert

    2014-01-01

    Psychiatric disorders are often caused by partial heterogeneous disinhibition in cognitive networks, controlling sequential and spatial working memory (SWM). Such dynamic connectivity changes suggest that the normal relationship between the neuronal components within the network deteriorates. As a result, competitive network dynamics is qualitatively altered. This dynamics defines the robust recall of the sequential information from memory and, thus, the SWM capacity. To understand pathological and non-pathological bifurcations of the sequential memory dynamics, here we investigate the model of recurrent inhibitory-excitatory networks with heterogeneous inhibition. We consider the ensemble of units with all-to-all inhibitory connections, in which the connection strengths are monotonically distributed at some interval. Based on computer experiments and studying the Lyapunov exponents, we observed and analyzed the new phenomenon—clustered sequential dynamics. The results are interpreted in the context of the winnerless competition principle. Accordingly, clustered sequential dynamics is represented in the phase space of the model by two weakly interacting quasi-attractors. One of them is similar to the sequential heteroclinic chain—the regular image of SWM, while the other is a quasi-chaotic attractor. Coexistence of these quasi-attractors means that the recall of the normal information sequence is intermittently interrupted by episodes with chaotic dynamics. We indicate potential dynamic ways for augmenting damaged working memory and other cognitive functions. PMID:25452717

  13. Modelling conflicts with cluster dynamics in networks

    NASA Astrophysics Data System (ADS)

    Tadić, Bosiljka; Rodgers, G. J.

    2010-12-01

    We introduce cluster dynamical models of conflicts in which only the largest cluster can be involved in an action. This mimics the situations in which an attack is planned by a central body, and the largest attack force is used. We study the model in its annealed random graph version, on a fixed network, and on a network evolving through the actions. The sizes of actions are distributed with a power-law tail, however, the exponent is non-universal and depends on the frequency of actions and sparseness of the available connections between units. Allowing the network reconstruction over time in a self-organized manner, e.g., by adding the links based on previous liaisons between units, we find that the power-law exponent depends on the evolution time of the network. Its lower limit is given by the universal value 5/2, derived analytically for the case of random fragmentation processes. In the temporal patterns behind the size of actions we find long-range correlations in the time series of the number of clusters and the non-trivial distribution of time that a unit waits between two actions. In the case of an evolving network the distribution develops a power-law tail, indicating that through repeated actions, the system develops an internal structure with a hierarchy of units.

  14. 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.

  15. Cluster-based adaptive power control protocol using Hidden Markov Model for Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Vinutha, C. B.; Nalini, N.; Nagaraja, M.

    2017-06-01

    This paper presents strategies for an efficient and dynamic transmission power control technique, in order to reduce packet drop and hence energy consumption of power-hungry sensor nodes operated in highly non-linear channel conditions of Wireless Sensor Networks. Besides, we also focus to prolong network lifetime and scalability by designing cluster-based network structure. Specifically we consider weight-based clustering approach wherein, minimum significant node is chosen as Cluster Head (CH) which is computed stemmed from the factors distance, remaining residual battery power and received signal strength (RSS). Further, transmission power control schemes to fit into dynamic channel conditions are meticulously implemented using Hidden Markov Model (HMM) where probability transition matrix is formulated based on the observed RSS measurements. Typically, CH estimates initial transmission power of its cluster members (CMs) from RSS using HMM and broadcast this value to its CMs for initialising their power value. Further, if CH finds that there are variations in link quality and RSS of the CMs, it again re-computes and optimises the transmission power level of the nodes using HMM to avoid packet loss due noise interference. We have demonstrated our simulation results to prove that our technique efficiently controls the power levels of sensing nodes to save significant quantity of energy for different sized network.

  16. Observations and Modeling of Merging Galaxy Clusters

    NASA Astrophysics Data System (ADS)

    Golovich, Nathan Ryan

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

  17. Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

    PubMed

    Zhou, Feng; De la Torre, Fernando; Hodgins, Jessica K

    2013-03-01

    Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion. We pose the problem of learning motion primitives as one of temporal clustering, and derive an unsupervised hierarchical bottom-up framework called hierarchical aligned cluster analysis (HACA). HACA finds a partition of a given multidimensional time series into m disjoint segments such that each segment belongs to one of k clusters. HACA combines kernel k-means with the generalized dynamic time alignment kernel to cluster time series data. Moreover, it provides a natural framework to find a low-dimensional embedding for time series. HACA is efficiently optimized with a coordinate descent strategy and dynamic programming. Experimental results on motion capture and video data demonstrate the effectiveness of HACA for segmenting complex motions and as a visualization tool. We also compare the performance of HACA to state-of-the-art algorithms for temporal clustering on data of a honey bee dance. The HACA code is available online.

  18. Experimental and ab initio molecular dynamics simulation studies of liquid Al60Cu40 alloy

    NASA Astrophysics Data System (ADS)

    Wang, S. Y.; Kramer, M. J.; Xu, M.; Wu, S.; Hao, S. G.; Sordelet, D. J.; Ho, K. M.; Wang, C. Z.

    2009-04-01

    X-ray diffraction and ab initio molecular dynamics simulation studies of molten Al60Cu40 have been carried out between 973 and 1323 K. The structures obtained from our simulated atomic models are fully consistent with the experimental results. The local structures of the models analyzed using Honeycutt-Andersen and Voronoi tessellation methods clearly demonstrate that as the temperatures of the liquid is lowered it becomes more ordered. While no one cluster-type dominates the local structure of this liquid, the most prevalent polyhedra in the liquid structure can be described as distorted icosahedra. No obvious correlations between the clusters observed in the liquid and known stable crystalline phases in this system were observed.

  19. Modeling fractal cities using the correlated percolation model.

    NASA Astrophysics Data System (ADS)

    Makse, Hernán A.; Havlin, Shlomo; Stanley, H. Eugene

    1996-03-01

    Cities grow in a way that might be expected to resemble the growth of two-dimensional aggregates of particles, and this has led to recent attempts to model urban growth using ideas from the statistical physics of clusters. In particular, the model of diffusion limited aggregation (DLA) has been invoked to rationalize the apparently fractal nature of urban morphologies(M. Batty and P. Longley, Fractal Cities) (Academic, San Diego, 1994). The DLA model predicts that there should exist only one large fractal cluster, which is almost perfectly screened from incoming 'development units' (representing, for example, people, capital or resources), so that almost all of the cluster growth takes place at the tips of the cluster's branches. We show that an alternative model(H. A. Makse, S. Havlin, H. E. Stanley, Nature 377), 608 (1995), in which development units are correlated rather than being added to the cluster at random, is better able to reproduce the observed morphology of cities and the area distribution of sub-clusters ('towns') in an urban system, and can also describe urban growth dynamics. Our physical model, which corresponds to the correlated percolation model in the presence of a density gradient, is motivated by the fact that in urban areas development attracts further development. The model offers the possibility of predicting the global properties (such as scaling behavior) of urban morphologies.

  20. Cluster Cooperation in Wireless-Powered Sensor Networks: Modeling and Performance Analysis.

    PubMed

    Zhang, Chao; Zhang, Pengcheng; Zhang, Weizhan

    2017-09-27

    A wireless-powered sensor network (WPSN) consisting of one hybrid access point (HAP), a near cluster and the corresponding far cluster is investigated in this paper. These sensors are wireless-powered and they transmit information by consuming the harvested energy from signal ejected by the HAP. Sensors are able to harvest energy as well as store the harvested energy. We propose that if sensors in near cluster do not have their own information to transmit, acting as relays, they can help the sensors in a far cluster to forward information to the HAP in an amplify-and-forward (AF) manner. We use a finite Markov chain to model the dynamic variation process of the relay battery, and give a general analyzing model for WPSN with cluster cooperation. Though the model, we deduce the closed-form expression for the outage probability as the metric of this network. Finally, simulation results validate the start point of designing this paper and correctness of theoretical analysis and show how parameters have an effect on system performance. Moreover, it is also known that the outage probability of sensors in far cluster can be drastically reduced without sacrificing the performance of sensors in near cluster if the transmit power of HAP is fairly high. Furthermore, in the aspect of outage performance of far cluster, the proposed scheme significantly outperforms the direct transmission scheme without cooperation.

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

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

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

    2016-04-21

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

  2. Cluster Cooperation in Wireless-Powered Sensor Networks: Modeling and Performance Analysis

    PubMed Central

    Zhang, Chao; Zhang, Pengcheng; Zhang, Weizhan

    2017-01-01

    A wireless-powered sensor network (WPSN) consisting of one hybrid access point (HAP), a near cluster and the corresponding far cluster is investigated in this paper. These sensors are wireless-powered and they transmit information by consuming the harvested energy from signal ejected by the HAP. Sensors are able to harvest energy as well as store the harvested energy. We propose that if sensors in near cluster do not have their own information to transmit, acting as relays, they can help the sensors in a far cluster to forward information to the HAP in an amplify-and-forward (AF) manner. We use a finite Markov chain to model the dynamic variation process of the relay battery, and give a general analyzing model for WPSN with cluster cooperation. Though the model, we deduce the closed-form expression for the outage probability as the metric of this network. Finally, simulation results validate the start point of designing this paper and correctness of theoretical analysis and show how parameters have an effect on system performance. Moreover, it is also known that the outage probability of sensors in far cluster can be drastically reduced without sacrificing the performance of sensors in near cluster if the transmit power of HAP is fairly high. Furthermore, in the aspect of outage performance of far cluster, the proposed scheme significantly outperforms the direct transmission scheme without cooperation. PMID:28953231

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

    NASA Astrophysics Data System (ADS)

    Turi, László

    2016-04-01

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

  4. Few-Photon Model of the Optical Emission of Semiconductor Quantum Dots

    NASA Astrophysics Data System (ADS)

    Richter, Marten; Carmele, Alexander; Sitek, Anna; Knorr, Andreas

    2009-08-01

    The Jaynes-Cummings model provides a well established theoretical framework for single electron two level systems in a radiation field. Similar exactly solvable models for semiconductor light emitters such as quantum dots dominated by many particle interactions are not known. We access these systems by a generalized cluster expansion, the photon-probability cluster expansion: a reliable approach for few-photon dynamics in many body electron systems. As a first application, we discuss vacuum Rabi oscillations and show that their amplitude determines the number of electrons in the quantum dot.

  5. Competitive repetition suppression (CoRe) clustering: a biologically inspired learning model with application to robust clustering.

    PubMed

    Bacciu, Davide; Starita, Antonina

    2008-11-01

    Determining a compact neural coding for a set of input stimuli is an issue that encompasses several biological memory mechanisms as well as various artificial neural network models. In particular, establishing the optimal network structure is still an open problem when dealing with unsupervised learning models. In this paper, we introduce a novel learning algorithm, named competitive repetition-suppression (CoRe) learning, inspired by a cortical memory mechanism called repetition suppression (RS). We show how such a mechanism is used, at various levels of the cerebral cortex, to generate compact neural representations of the visual stimuli. From the general CoRe learning model, we derive a clustering algorithm, named CoRe clustering, that can automatically estimate the unknown cluster number from the data without using a priori information concerning the input distribution. We illustrate how CoRe clustering, besides its biological plausibility, posses strong theoretical properties in terms of robustness to noise and outliers, and we provide an error function describing CoRe learning dynamics. Such a description is used to analyze CoRe relationships with the state-of-the art clustering models and to highlight CoRe similitude with rival penalized competitive learning (RPCL), showing how CoRe extends such a model by strengthening the rival penalization estimation by means of loss functions from robust statistics.

  6. Temporal clustering of tropical cyclones on the Great Barrier Reef and its ecological importance

    NASA Astrophysics Data System (ADS)

    Wolff, Nicholas H.; Wong, Aaron; Vitolo, Renato; Stolberg, Kristin; Anthony, Kenneth R. N.; Mumby, Peter J.

    2016-06-01

    Tropical cyclones have been a major cause of reef coral decline during recent decades, including on the Great Barrier Reef (GBR). While cyclones are a natural element of the disturbance regime of coral reefs, the role of temporal clustering has previously been overlooked. Here, we examine the consequences of different types of cyclone temporal distributions (clustered, stochastic or regular) on reef ecosystems. We subdivided the GBR into 14 adjoining regions, each spanning roughly 300 km, and quantified both the rate and clustering of cyclones using dispersion statistics. To interpret the consequences of such cyclone variability for coral reef health, we used a model of observed coral population dynamics. Results showed that clustering occurs on the margins of the cyclone belt, being strongest in the southern reefs and the far northern GBR, which also has the lowest cyclone rate. In the central GBR, where rates were greatest, cyclones had a relatively regular temporal pattern. Modelled dynamics of the dominant coral genus, Acropora, suggest that the long-term average cover might be more than 13 % greater (in absolute cover units) under a clustered cyclone regime compared to stochastic or regular regimes. Thus, not only does cyclone clustering vary significantly along the GBR but such clustering is predicted to have a marked, and management-relevant, impact on the status of coral populations. Additionally, we use our regional clustering and rate results to sample from a library of over 7000 synthetic cyclone tracks for the GBR. This allowed us to provide robust reef-scale maps of annual cyclone frequency and cyclone impacts on Acropora. We conclude that assessments of coral reef vulnerability need to account for both spatial and temporal cyclone distributions.

  7. Cascades on a class of clustered random networks

    NASA Astrophysics Data System (ADS)

    Hackett, Adam; Melnik, Sergey; Gleeson, James P.

    2011-05-01

    We present an analytical approach to determining the expected cascade size in a broad range of dynamical models on the class of random networks with arbitrary degree distribution and nonzero clustering introduced previously in [M. E. J. Newman, Phys. Rev. Lett. PRLTAO0031-900710.1103/PhysRevLett.103.058701103, 058701 (2009)]. A condition for the existence of global cascades is derived as well as a general criterion that determines whether increasing the level of clustering will increase, or decrease, the expected cascade size. Applications, examples of which are provided, include site percolation, bond percolation, and Watts’ threshold model; in all cases analytical results give excellent agreement with numerical simulations.

  8. A segmentation/clustering model for the analysis of array CGH data.

    PubMed

    Picard, F; Robin, S; Lebarbier, E; Daudin, J-J

    2007-09-01

    Microarray-CGH (comparative genomic hybridization) experiments are used to detect and map chromosomal imbalances. A CGH profile can be viewed as a succession of segments that represent homogeneous regions in the genome whose representative sequences share the same relative copy number on average. Segmentation methods constitute a natural framework for the analysis, but they do not provide a biological status for the detected segments. We propose a new model for this segmentation/clustering problem, combining a segmentation model with a mixture model. We present a new hybrid algorithm called dynamic programming-expectation maximization (DP-EM) to estimate the parameters of the model by maximum likelihood. This algorithm combines DP and the EM algorithm. We also propose a model selection heuristic to select the number of clusters and the number of segments. An example of our procedure is presented, based on publicly available data sets. We compare our method to segmentation methods and to hidden Markov models, and we show that the new segmentation/clustering model is a promising alternative that can be applied in the more general context of signal processing.

  9. Dark Matter Halos with VIRUS-P

    NASA Astrophysics Data System (ADS)

    Murphy, Jeremy; Gebhardt, K.

    2010-05-01

    We present new, two-dimensional stellar kinematic data on several of the most massive galaxies in the local universe. These data were taken with the integral field spectrograph, VIRUS-P, and extend to unprecedented radial distances. Once robust stellar kinematics are in hand, we run orbit-based axisymmetric dynamical models in order to constrain the stellar mass-to-light ratio and dark matter halo parameters. We have run a large set of dynamical models on the second rank galaxy in the Virgo cluster, M87, and find clear evidence for a massive dark matter halo. The two-dimensional stellar kinematics for several of our other targets, all first and second rank galaxies, are also presented. Dark matter halos are known to dominate the mass profile of elliptical galaxies somewhere between one to two effective radii, yet due to the low surface brightness at these radial distances, determining stellar dynamics is technologically challenging. To overcome this, constraints on the dark matter halo are often made with planetary nebulae or globular clusters at large radii. However, as results from different groups have returned contradictory results, it remains unclear whether different dynamical tracers always follow the stellar kinematics. Due to VIRUS-P's large field of view and on-sky fiber diameter, we are able to determine stellar kinematics at radial distances that overlap with other dynamical tracers. Understanding what the dynamics of stars, planetary nebula and globular clusters tell us about both the extent of the dark matter halo profile and the formation histories of the largest elliptical galaxies is a primary science driver for this work.

  10. A systemic investigation of hydrogen peroxide clusters (H2O2)n (n = 1-6) and liquid-state hydrogen peroxide: based on atom-bond electronegativity equalization method fused into molecular mechanics and molecular dynamics.

    PubMed

    Yu, Chun-Yang; Yang, Zhong-Zhi

    2011-03-31

    Hydrogen peroxide (HP) clusters (H(2)O(2))(n) (n = 1-6) and liquid-state HP have been systemically investigated by the newly constructed ABEEM/MM fluctuating charge model. Because of the explicit description of charge distribution and special treatment of the hydrogen-bond interaction region, the ABEEM/MM potential model gives reasonable properties of HP clusters, including geometries, interaction energies, and dipole moments, when comparing with the present ab initio results. Meanwhile, the average dipole moment, static dielectric constant, heats of vaporization, radial distribution function, and diffusion constant for the dynamic properties of liquid HP at 273 K and 1 atm are fairly consistent with the available experimental data. To the best of our knowledge, this is the first theoretical investigation of condensed HP. The properties of HP monomer are studied in detail involving the structure, torsion potentials, molecular orbital analysis, charge distribution, dipole moment, and vibrational frequency.

  11. Cluster-cluster aggregation with particle replication and chemotaxy: a simple model for the growth of animal cells in culture

    NASA Astrophysics Data System (ADS)

    Alves, S. G.; Martins, M. L.

    2010-09-01

    Aggregation of animal cells in culture comprises a series of motility, collision and adhesion processes of basic relevance for tissue engineering, bioseparations, oncology research and in vitro drug testing. In the present paper, a cluster-cluster aggregation model with stochastic particle replication and chemotactically driven motility is investigated as a model for the growth of animal cells in culture. The focus is on the scaling laws governing the aggregation kinetics. Our simulations reveal that in the absence of chemotaxy the mean cluster size and the total number of clusters scale in time as stretched exponentials dependent on the particle replication rate. Also, the dynamical cluster size distribution functions are represented by a scaling relation in which the scaling function involves a stretched exponential of the time. The introduction of chemoattraction among the particles leads to distribution functions decaying as power laws with exponents that decrease in time. The fractal dimensions and size distributions of the simulated clusters are qualitatively discussed in terms of those determined experimentally for several normal and tumoral cell lines growing in culture. It is shown that particle replication and chemotaxy account for the simplest cluster size distributions of cellular aggregates observed in culture.

  12. Will water act as a photocatalyst for cluster phase chemical reactions? Vibrational overtone-induced dehydration reaction of methanediol

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

    Kramer, Zeb C.; Takahashi, Kaito; Skodje, Rex T.

    2012-04-28

    The possibility of water catalysis in the vibrational overtone-induced dehydration reaction of methanediol is investigated using ab initio dynamical simulations of small methanediol-water clusters. Quantum chemistry calculations employing clusters with one or two water molecules reveal that the barrier to dehydration is lowered by over 20 kcal/mol because of hydrogen-bonding at the transition state. Nevertheless, the simulations of the reaction dynamics following OH-stretch excitation show little catalytic effect of water and, in some cases, even show an anticatalytic effect. The quantum yield for the dehydration reaction exhibits a delayed threshold effect where reaction does not occur until the photon energymore » is far above the barrier energy. Unlike thermally induced reactions, it is argued that competition between reaction and the irreversible dissipation of photon energy may be expected to raise the dynamical threshold for the reaction above the transition state energy. It is concluded that quantum chemistry calculations showing barrier lowering are not sufficient to infer water catalysis in photochemical reactions, which instead require dynamical modeling.« less

  13. Emergent patterns in interacting neuronal sub-populations

    NASA Astrophysics Data System (ADS)

    Kamal, Neeraj Kumar; Sinha, Sudeshna

    2015-05-01

    We investigate an ensemble of coupled model neurons, consisting of groups of varying sizes and intrinsic dynamics, ranging from periodic to chaotic, where the inter-group coupling interaction is effectively like a dynamic signal from a different sub-population. We observe that the minority group can significantly influence the majority group. For instance, when a small chaotic group is coupled to a large periodic group, the chaotic group de-synchronizes. However, counter-intuitively, when a small periodic group couples strongly to a large chaotic group, it leads to complete synchronization in the majority chaotic population, which also spikes at the frequency of the small periodic group. It then appears that the small group of periodic neurons can act like a pacemaker for the whole network. Further, we report the existence of varied clustering patterns, ranging from sets of synchronized clusters to anti-phase clusters, governed by the interplay of the relative sizes and dynamics of the sub-populations. So these results have relevance in understanding how a group can influence the synchrony of another group of dynamically different elements, reminiscent of event-related synchronization/de-synchronization in complex networks.

  14. Dynamical resonance shift and unification of resonances in short-pulse laser-cluster interaction

    NASA Astrophysics Data System (ADS)

    Mahalik, S. S.; Kundu, M.

    2018-06-01

    Pronounced maximum absorption of laser light irradiating a rare-gas or metal cluster is widely expected during the linear resonance (LR) when Mie-plasma wavelength λM of electrons equals the laser wavelength λ . On the contrary, by performing molecular dynamics (MD) simulations of an argon cluster irradiated by short 5-fs (FWHM) laser pulses it is revealed that, for a given laser pulse energy and a cluster, at each peak intensity there exists a λ —shifted from the expected λM—that corresponds to a unified dynamical LR at which evolution of the cluster happens through very efficient unification of possible resonances in various stages, including (i) the LR in the initial time of plasma creation, (ii) the LR in the Coulomb expanding phase in the later time, and (iii) anharmonic resonance in the marginally overdense regime for a relatively longer pulse duration, leading to maximum laser absorption accompanied by maximum removal of electrons from cluster and also maximum allowed average charge states for the argon cluster. Increasing the laser intensity, the absorption maxima is found to shift to a higher wavelength in the band of λ ≈(1 -1.5 ) λM than permanently staying at the expected λM. A naive rigid sphere model also corroborates the wavelength shift of the absorption peak as found in MD and unequivocally proves that maximum laser absorption in a cluster happens at a shifted λ in the marginally overdense regime of λ ≈(1 -1.5 ) λM instead of λM of LR. The present study is important for guiding an optimal condition laser-cluster interaction experiment in the short-pulse regime.

  15. QAARM: quasi-anharmonic autoregressive model reveals molecular recognition pathways in ubiquitin

    PubMed Central

    Savol, Andrej J.; Burger, Virginia M.; Agarwal, Pratul K.; Ramanathan, Arvind; Chennubhotla, Chakra S.

    2011-01-01

    Motivation: Molecular dynamics (MD) simulations have dramatically improved the atomistic understanding of protein motions, energetics and function. These growing datasets have necessitated a corresponding emphasis on trajectory analysis methods for characterizing simulation data, particularly since functional protein motions and transitions are often rare and/or intricate events. Observing that such events give rise to long-tailed spatial distributions, we recently developed a higher-order statistics based dimensionality reduction method, called quasi-anharmonic analysis (QAA), for identifying biophysically-relevant reaction coordinates and substates within MD simulations. Further characterization of conformation space should consider the temporal dynamics specific to each identified substate. Results: Our model uses hierarchical clustering to learn energetically coherent substates and dynamic modes of motion from a 0.5 μs ubiqutin simulation. Autoregressive (AR) modeling within and between states enables a compact and generative description of the conformational landscape as it relates to functional transitions between binding poses. Lacking a predictive component, QAA is extended here within a general AR model appreciative of the trajectory's temporal dependencies and the specific, local dynamics accessible to a protein within identified energy wells. These metastable states and their transition rates are extracted within a QAA-derived subspace using hierarchical Markov clustering to provide parameter sets for the second-order AR model. We show the learned model can be extrapolated to synthesize trajectories of arbitrary length. Contact: ramanathana@ornl.gov; chakracs@pitt.edu PMID:21685101

  16. Collisional model for granular impact dynamics.

    PubMed

    Clark, Abram H; Petersen, Alec J; Behringer, Robert P

    2014-01-01

    When an intruder strikes a granular material from above, the grains exert a stopping force which decelerates and stops the intruder. Many previous studies have used a macroscopic force law, including a drag force which is quadratic in velocity, to characterize the decelerating force on the intruder. However, the microscopic origins of the force-law terms are still a subject of debate. Here, drawing from previous experiments with photoelastic particles, we present a model which describes the velocity-squared force in terms of repeated collisions with clusters of grains. From our high speed photoelastic data, we infer that "clusters" correspond to segments of the strong force network that are excited by the advancing intruder. The model predicts a scaling relation for the velocity-squared drag force that accounts for the intruder shape. Additionally, we show that the collisional model predicts an instability to rotations, which depends on the intruder shape. To test this model, we perform a comprehensive experimental study of the dynamics of two-dimensional granular impacts on beds of photoelastic disks, with different profiles for the leading edge of the intruder. We particularly focus on a simple and useful case for testing shape effects by using triangular-nosed intruders. We show that the collisional model effectively captures the dynamics of intruder deceleration and rotation; i.e., these two dynamical effects can be described as two different manifestations of the same grain-scale physical processes.

  17. Wave failure at strong coupling in intracellular C a2 + signaling system with clustered channels

    NASA Astrophysics Data System (ADS)

    Li, Xiang; Wu, Yuning; Gao, Xuejuan; Cai, Meichun; Shuai, Jianwei

    2018-01-01

    As an important intracellular signal, C a2 + ions control diverse cellular functions. In this paper, we discuss the C a2 + signaling with a two-dimensional model in which the inositol 1,4,5-trisphosphate (I P3 ) receptor channels are distributed in clusters on the endoplasmic reticulum membrane. The wave failure at large C a2 + diffusion coupling is discussed in detail in the model. We show that with varying model parameters the wave failure is a robust behavior with either deterministic or stochastic channel dynamics. We suggest that the wave failure should be a general behavior in inhomogeneous diffusing systems with clustered excitable regions and may occur in biological C a2 + signaling systems.

  18. Towards Cluster-Assembled Materials of True Monodispersity in Size and Chemical Environment: Synthesis, Dynamics and Activity

    DTIC Science & Technology

    2016-10-27

    AFRL-AFOSR-UK-TR-2016-0037 Towards cluster-assembled materials of true monodispersity in size and chemical environment: Synthesis, Dynamics and...Towards cluster-assembled materials of true monodispersity in size and chemical environment: synthesis, dynamics and activity 5a.  CONTRACT NUMBER 5b...report Towards cluster-assembled materials of true monodispersity in size and chemical environment: Synthesis, Dynamics and Activity Ulrich Heiz

  19. The abundance of galaxy clusters in modified Newtonian dynamics: cosmological simulations with massive neutrinos

    NASA Astrophysics Data System (ADS)

    Angus, G. W.; Diaferio, Antonaldo

    2011-10-01

    We present a new particle mesh cosmological N-body code for accurately solving the modified Poisson equation of the quasi-linear formulation of modified Newtonian dynamics (MOND). We generate initial conditions for the Angus cosmological model, which is identical to Λ cold dark matter (ΛCDM) except that the CDM is switched for a single species of thermal sterile neutrinos. We set the initial conditions at z= 250 for a (512 Mpc h-1)3 box with 2563 particles, and we evolve them down to z= 0. We clearly demonstrate the ability of MOND to develop the large-scale structure in a hot dark matter cosmology and contradict the naive expectation that MOND cannot form galaxy clusters. We find that the correct order of magnitude of X-ray clusters (with TX > 4.5 keV) can be formed, but that we overpredict the number of very rich clusters and seriously underpredict the number of lower mass clusters. We present evidence that suggests the density profiles of our simulated clusters are compatible with those of the observed X-ray clusters in MOND. As a last test, we computed the relative velocity between pairs of haloes within 10 Mpc and find that pairs with velocities larger than 3000 km s-1, like the bullet cluster, can form without difficulty.

  20. Real-time observation of formation and relaxation dynamics of NH4 in (CH3OH)m(NH3)n clusters.

    PubMed

    Yamada, Yuji; Nishino, Yoko; Fujihara, Akimasa; Ishikawa, Haruki; Fuke, Kiyokazu

    2009-03-26

    The formation and relaxation dynamics of NH4(CH3OH)m(NH3)n clusters produced by photolysis of ammonia-methanol mixed clusters has been observed by a time-resolved pump-probe method with femtosecond pulse lasers. From the detailed analysis of the time evolutions of the protonated cluster ions, NH4(+)(CH3OH)m(NH3)n, the kinetic model has been constructed, which consists of sequential three-step reaction: ultrafast hydrogen-atom transfer producing the radical pair (NH4-NH2)*, the relaxation process of radical-pair clusters, and dissociation of the solvated NH4 clusters. The initial hydrogen transfer hardly occurs between ammonia and methanol, implying the unfavorable formation of radical pair, (CH3OH2-NH2)*. The remarkable dependence of the time constants in each step on the number and composition of solvents has been explained by the following factors: hydrogen delocalization within the clusters, the internal conversion of the excited-state radical pair, and the stabilization of NH4 by solvation. The dependence of the time profiles on the probe wavelength is attributed to the different ionization efficiency of the NH4(CH3OH)m(NH3)n clusters.

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

    NASA Astrophysics Data System (ADS)

    Wirth, Gregory

    2017-08-01

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

  2. Density-based clustering analyses to identify heterogeneous cellular sub-populations

    NASA Astrophysics Data System (ADS)

    Heaster, Tiffany M.; Walsh, Alex J.; Landman, Bennett A.; Skala, Melissa C.

    2017-02-01

    Autofluorescence microscopy of NAD(P)H and FAD provides functional metabolic measurements at the single-cell level. Here, density-based clustering algorithms were applied to metabolic autofluorescence measurements to identify cell-level heterogeneity in tumor cell cultures. The performance of the density-based clustering algorithm, DENCLUE, was tested in samples with known heterogeneity (co-cultures of breast carcinoma lines). DENCLUE was found to better represent the distribution of cell clusters compared to Gaussian mixture modeling. Overall, DENCLUE is a promising approach to quantify cell-level heterogeneity, and could be used to understand single cell population dynamics in cancer progression and treatment.

  3. Critical behavior of the contact process on small-world networks

    NASA Astrophysics Data System (ADS)

    Ferreira, Ronan S.; Ferreira, Silvio C.

    2013-11-01

    We investigate the role of clustering on the critical behavior of the contact process (CP) on small-world networks using the Watts-Strogatz (WS) network model with an edge rewiring probability p. The critical point is well predicted by a homogeneous cluster-approximation for the limit of vanishing clustering ( p → 1). The critical exponents and dimensionless moment ratios of the CP are in agreement with those predicted by the mean-field theory for any p > 0. This independence on the network clustering shows that the small-world property is a sufficient condition for the mean-field theory to correctly predict the universality of the model. Moreover, we compare the CP dynamics on WS networks with rewiring probability p = 1 and random regular networks and show that the weak heterogeneity of the WS network slightly changes the critical point but does not alter other critical quantities of the model.

  4. Understanding the Current Dynamical States of Globular Clusters

    NASA Astrophysics Data System (ADS)

    Pooley, David

    2008-09-01

    We appear to be on the verge of a major paradigm shift in our understanding of the current dynamical states of Galactic globular clusters. Fregeau (2008) brought together two recent theoretical breakthroughs as well as an observational breakthrough made possible by Chandra -- that a globular cluster's X-ray source population scales with its dynamical encounter frequency -- to persuasively argue that we have misunderstood the dynamical states of Galactic globular clusters. The observational evidence hinges on Chandra results from clusters which are classified as "core collapsed," of which there are only a handful of observations. I propose a nearly complete census with Chandra of the rest of the "core collapsed" globular clusters.

  5. Dynamical age differences among coeval star clusters as revealed by blue stragglers.

    PubMed

    Ferraro, F R; Lanzoni, B; Dalessandro, E; Beccari, G; Pasquato, M; Miocchi, P; Rood, R T; Sigurdsson, S; Sills, A; Vesperini, E; Mapelli, M; Contreras, R; Sanna, N; Mucciarelli, A

    2012-12-20

    Globular star clusters that formed at the same cosmic time may have evolved rather differently from the dynamical point of view (because that evolution depends on the internal environment) through a variety of processes that tend progressively to segregate stars more massive than the average towards the cluster centre. Therefore clusters with the same chronological age may have reached quite different stages of their dynamical history (that is, they may have different 'dynamical ages'). Blue straggler stars have masses greater than those at the turn-off point on the main sequence and therefore must be the result of either a collision or a mass-transfer event. Because they are among the most massive and luminous objects in old clusters, they can be used as test particles with which to probe dynamical evolution. Here we report that globular clusters can be grouped into a few distinct families on the basis of the radial distribution of blue stragglers. This grouping corresponds well to an effective ranking of the dynamical stage reached by stellar systems, thereby permitting a direct measure of the cluster dynamical age purely from observed properties.

  6. Simulating the Birth of Massive Star Clusters: Is Destruction Inevitable?

    NASA Astrophysics Data System (ADS)

    Rosen, Anna

    2013-10-01

    Very early in its operation, the Hubble Space Telescope {HST} opened an entirely new frontier: study of the demographics and properties of star clusters far beyond the Milky Way. However, interpretation of HST's observations has proven difficult, and has led to the development of two conflicting models. One view is that most massive star clusters are disrupted during their infancy by feedback from newly formed stars {i.e., "infant mortality"}, independent of cluster mass or environment. The other model is that most star clusters survive their infancy and are disrupted later by mass-dependent dynamical processes. Since observations at present have failed to discriminate between these views, we propose a theoretical investigation to provide new insight. We will perform radiation-hydrodynamic simulations of the formation of massive star clusters, including for the first time a realistic treatment of the most important stellar feedback processes. These simulations will elucidate the physics of stellar feedback, and allow us to determine whether cluster disruption is mass-dependent or -independent. We will also use our simulations to search for observational diagnostics that can distinguish bound from unbound clusters, and to predict how cluster disruption affects the cluster luminosity function in a variety of galactic environments.

  7. Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

    PubMed

    NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

    2017-08-01

    Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

  8. Superresolution Modeling of Calcium Release in the Heart

    PubMed Central

    Walker, Mark A.; Williams, George S.B.; Kohl, Tobias; Lehnart, Stephan E.; Jafri, M. Saleet; Greenstein, Joseph L.; Lederer, W.J.; Winslow, Raimond L.

    2014-01-01

    Stable calcium-induced calcium release (CICR) is critical for maintaining normal cellular contraction during cardiac excitation-contraction coupling. The fundamental element of CICR in the heart is the calcium (Ca2+) spark, which arises from a cluster of ryanodine receptors (RyR). Opening of these RyR clusters is triggered to produce a local, regenerative release of Ca2+ from the sarcoplasmic reticulum (SR). The Ca2+ leak out of the SR is an important process for cellular Ca2+ management, and it is critically influenced by spark fidelity, i.e., the probability that a spontaneous RyR opening triggers a Ca2+ spark. Here, we present a detailed, three-dimensional model of a cardiac Ca2+ release unit that incorporates diffusion, intracellular buffering systems, and stochastically gated ion channels. The model exhibits realistic Ca2+ sparks and robust Ca2+ spark termination across a wide range of geometries and conditions. Furthermore, the model captures the details of Ca2+ spark and nonspark-based SR Ca2+ leak, and it produces normal excitation-contraction coupling gain. We show that SR luminal Ca2+-dependent regulation of the RyR is not critical for spark termination, but it can explain the exponential rise in the SR Ca2+ leak-load relationship demonstrated in previous experimental work. Perturbations to subspace dimensions, which have been observed in experimental models of disease, strongly alter Ca2+ spark dynamics. In addition, we find that the structure of RyR clusters also influences Ca2+ release properties due to variations in inter-RyR coupling via local subspace Ca2+ concentration ([Ca2+]ss). These results are illustrated for RyR clusters based on super-resolution stimulated emission depletion microscopy. Finally, we present a believed-novel approach by which the spark fidelity of a RyR cluster can be predicted from structural information of the cluster using the maximum eigenvalue of its adjacency matrix. These results provide critical insights into CICR dynamics in heart, under normal and pathological conditions. PMID:25517166

  9. Asymptotic Dynamics of Self-driven Vehicles in a Closed Boundary

    NASA Astrophysics Data System (ADS)

    Lee, Chi-Lun; Huang, Chia-Ling

    2011-08-01

    We study the asymptotic dynamics of self-driven vehicles in a loop using a car-following model with the consideration of volume exclusions. In particular, we derive the dynamical steady states for the single-cluster case and obtain the corresponding fundamental diagrams, exhibiting two branches representative of entering and leaving the jam, respectively. By simulations we find that the speed average over all vehicles eventually reaches the same value, regardless of final clustering states. The autocorrelation functions for overall speed average and single-vehicle speed are studied, each revealing a unique time scale. We also discuss the role of noises in vehicular accelerations. Based on our observations we give trial definitions about the degree of chaoticity for general self-driven many-body systems.

  10. Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons.

    PubMed

    Moon, Sung Joon; Cook, Katherine A; Rajendran, Karthikeyan; Kevrekidis, Ioannis G; Cisternas, Jaime; Laing, Carlo R

    2015-12-01

    The formation of oscillating phase clusters in a network of identical Hodgkin-Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition-through [Formula: see text] (possibly perturbed) period-doubling and subsequent bifurcations-to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar "fine" states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron's "identity" (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established "identity-state" correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.

  11. Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning

    NASA Astrophysics Data System (ADS)

    Ntampaka, M.; Trac, H.; Sutherland, D. J.; Fromenteau, S.; Póczos, B.; Schneider, J.

    2016-11-01

    We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark’s publicly available N-body MDPL1 simulation, one with perfect galaxy cluster membership information and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power-law scaling relation to infer cluster mass from galaxy line-of-sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with a width of {{Δ }}ε ≈ 0.87. Interlopers introduce additional scatter, significantly widening the error distribution further ({{Δ }}ε ≈ 2.13). We employ the support distribution machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement ({{Δ }}ε ≈ 0.67) for the contaminated case. Remarkably, SDM applied to contaminated clusters is better able to recover masses than even the scaling relation approach applied to uncontaminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.

  12. Million-body star cluster simulations: comparisons between Monte Carlo and direct N-body

    NASA Astrophysics Data System (ADS)

    Rodriguez, Carl L.; Morscher, Meagan; Wang, Long; Chatterjee, Sourav; Rasio, Frederic A.; Spurzem, Rainer

    2016-12-01

    We present the first detailed comparison between million-body globular cluster simulations computed with a Hénon-type Monte Carlo code, CMC, and a direct N-body code, NBODY6++GPU. Both simulations start from an identical cluster model with 106 particles, and include all of the relevant physics needed to treat the system in a highly realistic way. With the two codes `frozen' (no fine-tuning of any free parameters or internal algorithms of the codes) we find good agreement in the overall evolution of the two models. Furthermore, we find that in both models, large numbers of stellar-mass black holes (>1000) are retained for 12 Gyr. Thus, the very accurate direct N-body approach confirms recent predictions that black holes can be retained in present-day, old globular clusters. We find only minor disagreements between the two models and attribute these to the small-N dynamics driving the evolution of the cluster core for which the Monte Carlo assumptions are less ideal. Based on the overwhelming general agreement between the two models computed using these vastly different techniques, we conclude that our Monte Carlo approach, which is more approximate, but dramatically faster compared to the direct N-body, is capable of producing an accurate description of the long-term evolution of massive globular clusters even when the clusters contain large populations of stellar-mass black holes.

  13. Composition-dependent metallic glass alloys correlate atomic mobility with collective glass surface dynamics.

    PubMed

    Nguyen, Duc; Zhu, Zhi-Guang; Pringle, Brian; Lyding, Joseph; Wang, Wei-Hua; Gruebele, Martin

    2016-06-22

    Glassy metallic alloys are richly tunable model systems for surface glassy dynamics. Here we study the correlation between atomic mobility, and the hopping rate of surface regions (clusters) that rearrange collectively on a minute to hour time scale. Increasing the proportion of low-mobility copper atoms in La-Ni-Al-Cu alloys reduces the cluster hopping rate, thus establishing a microscopic connection between atomic mobility and dynamics of collective rearrangements at a glass surface made from freshly exposed bulk glass. One composition, La60Ni15Al15Cu10, has a surface resistant to re-crystallization after three heating cycles. When thermally cycled, surface clusters grow in size from about 5 glass-forming units to about 8 glass-forming units, evidence of surface aging without crystal formation, although its bulk clearly forms larger crystalline domains. Such kinetically stable glass surfaces may be of use in applications where glassy coatings stable against heating are needed.

  14. STAR CLUSTER FORMATION WITH STELLAR FEEDBACK AND LARGE-SCALE INFLOW

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

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

    2015-12-10

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

  15. A Motor-Gradient and Clustering Model of the Centripetal Motility of MTOCs in Meiosis I of Mouse Oocytes

    PubMed Central

    2016-01-01

    Asters nucleated by Microtubule (MT) organizing centers (MTOCs) converge on chromosomes during spindle assembly in mouse oocytes undergoing meiosis I. Time-lapse imaging suggests that this centripetal motion is driven by a biased ‘search-and-capture’ mechanism. Here, we develop a model of a random walk in a drift field to test the nature of the bias and the spatio-temporal dynamics of the search process. The model is used to optimize the spatial field of drift in simulations, by comparison to experimental motility statistics. In a second step, this optimized gradient is used to determine the location of immobilized dynein motors and MT polymerization parameters, since these are hypothesized to generate the gradient of forces needed to move MTOCs. We compare these scenarios to self-organized mechanisms by which asters have been hypothesized to find the cell-center- MT pushing at the cell-boundary and clustering motor complexes. By minimizing the error between simulation outputs and experiments, we find a model of “pulling” by a gradient of dynein motors alone can drive the centripetal motility. Interestingly, models of passive MT based “pushing” at the cortex, clustering by cross-linking motors and MT-dynamic instability gradients alone, by themselves do not result in the observed motility. The model predicts the sensitivity of the results to motor density and stall force, but not MTs per aster. A hybrid model combining a chromatin-centered immobilized dynein gradient, diffusible minus-end directed clustering motors and pushing at the cell cortex, is required to comprehensively explain the available data. The model makes experimentally testable predictions of a spatial bias and self-organized mechanisms by which MT asters can find the center of a large cell. PMID:27706163

  16. A Motor-Gradient and Clustering Model of the Centripetal Motility of MTOCs in Meiosis I of Mouse Oocytes.

    PubMed

    Khetan, Neha; Athale, Chaitanya A

    2016-10-01

    Asters nucleated by Microtubule (MT) organizing centers (MTOCs) converge on chromosomes during spindle assembly in mouse oocytes undergoing meiosis I. Time-lapse imaging suggests that this centripetal motion is driven by a biased 'search-and-capture' mechanism. Here, we develop a model of a random walk in a drift field to test the nature of the bias and the spatio-temporal dynamics of the search process. The model is used to optimize the spatial field of drift in simulations, by comparison to experimental motility statistics. In a second step, this optimized gradient is used to determine the location of immobilized dynein motors and MT polymerization parameters, since these are hypothesized to generate the gradient of forces needed to move MTOCs. We compare these scenarios to self-organized mechanisms by which asters have been hypothesized to find the cell-center- MT pushing at the cell-boundary and clustering motor complexes. By minimizing the error between simulation outputs and experiments, we find a model of "pulling" by a gradient of dynein motors alone can drive the centripetal motility. Interestingly, models of passive MT based "pushing" at the cortex, clustering by cross-linking motors and MT-dynamic instability gradients alone, by themselves do not result in the observed motility. The model predicts the sensitivity of the results to motor density and stall force, but not MTs per aster. A hybrid model combining a chromatin-centered immobilized dynein gradient, diffusible minus-end directed clustering motors and pushing at the cell cortex, is required to comprehensively explain the available data. The model makes experimentally testable predictions of a spatial bias and self-organized mechanisms by which MT asters can find the center of a large cell.

  17. Probing the formation history of the nuclear star cluster at the Galactic Centre with millisecond pulsars

    NASA Astrophysics Data System (ADS)

    Abbate, F.; Mastrobuono-Battisti, A.; Colpi, M.; Possenti, A.; Sippel, A. C.; Dotti, M.

    2018-01-01

    The origin of the nuclear star cluster in the centre of our Galaxy is still unknown. One possibility is that it formed after the disruption of stellar clusters that spiralled into the Galactic Centre due to dynamical friction. We trace the formation of the nuclear star cluster around the central black hole, using state-of-the-art N-body simulations, and follow the dynamics of the neutron stars born in the clusters. We then estimate the number of millisecond pulsars (MSPs) that are released in the nuclear star cluster during its formation. The assembly and tidal dismemberment of globular clusters lead to a population of MSPs distributed over a radius of about 20 pc, with a peak near 3 pc. No clustering is found on the subparsec scale. We simulate the detectability of this population with future radio telescopes like the MeerKAT radio telescope and SKA1, and find that about an order of 10 MSPs can be observed over this large volume, with a paucity of MSPs within the central parsec. This helps discriminating this scenario from the in situ formation model for the nuclear star cluster that would predict an overabundance of MSPs closer to the black hole. We then discuss the potential contribution of our MSP population to the gamma-ray excess at the Galactic Centre.

  18. Dynamics of Galaxy Clusters and Expectations from Astro-H

    NASA Technical Reports Server (NTRS)

    Markevitch, Maxim

    2012-01-01

    Galaxy clusters span a range of dynamical states, from violent mergers -- the most energetic events in the Universe -- to systems near hydrostatic equilibrium that allow us to map their dark matter distribution using X-ray observations of the intracluster gas. Accurate knowledge of the cluster physics, and in particular, the physics of the hot intracluster gas, is required to realize the full potential of clusters as cosmological probes. So far, we have been studying the cluster dynamics indirectly, deducing merger geometries, cluster masses, etc., using X-ray brightness and gas temperature mapping. For the first time, the calorimeter onboard Astro-H will provide direct measurements of line-of-sight velocities and turbulent broadening in the intracluster gas, testing many of our key assumptions about clusters. This talk will summarize expectations for cluster dynamic studies with this new instrument.

  19. Plasma Instabilities in the Context of Current Helium Sedimentation Models: Dynamical Implications for the ICM in Galaxy Clusters

    NASA Astrophysics Data System (ADS)

    Berlok, Thomas; Pessah, Martin E.

    2015-11-01

    Understanding whether Helium can sediment to the core of galaxy clusters is important for a number of problems in cosmology and astrophysics. All current models addressing this question are one-dimensional and do not account for the fact that magnetic fields can effectively channel ions and electrons, leading to anisotropic transport of momentum, heat, and particle diffusion in the weakly collisional intracluster medium (ICM). This anisotropy can lead to a wide variety of instabilities, which could be relevant for understanding the dynamics of heterogeneous media. In this paper, we consider the radial temperature and composition profiles as obtained from a state-of-the-art Helium sedimentation model and analyze its stability properties. We find that the associated radial profiles are unstable to different kinds of instabilities depending on the magnetic field orientation at all radii. The fastest growing modes are usually related to generalizations of the magnetothermal instability (MTI) and the heat-flux-driven buoyancy instability which operate in heterogeneous media. We find that the effect of sedimentation is to increase (decrease) the predicted growth rates in the inner (outer) cluster region. The unstable modes grow quickly compared to the sedimentation timescale. This suggests that the composition gradients as inferred from sedimentation models, which do not fully account for the anisotropic character of the weakly collisional environment, might not be very robust. Our results emphasize the subtleties involved in understanding the gas dynamics of the ICM and argue for the need of a comprehensive approach to address the issue of Helium sedimentation beyond current models.

  20. PLASMA INSTABILITIES IN THE CONTEXT OF CURRENT HELIUM SEDIMENTATION MODELS: DYNAMICAL IMPLICATIONS FOR THE ICM IN GALAXY CLUSTERS

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

    Berlok, Thomas; Pessah, Martin E., E-mail: berlok@nbi.dk, E-mail: mpessah@nbi.dk

    2015-11-01

    Understanding whether Helium can sediment to the core of galaxy clusters is important for a number of problems in cosmology and astrophysics. All current models addressing this question are one-dimensional and do not account for the fact that magnetic fields can effectively channel ions and electrons, leading to anisotropic transport of momentum, heat, and particle diffusion in the weakly collisional intracluster medium (ICM). This anisotropy can lead to a wide variety of instabilities, which could be relevant for understanding the dynamics of heterogeneous media. In this paper, we consider the radial temperature and composition profiles as obtained from a state-of-the-artmore » Helium sedimentation model and analyze its stability properties. We find that the associated radial profiles are unstable to different kinds of instabilities depending on the magnetic field orientation at all radii. The fastest growing modes are usually related to generalizations of the magnetothermal instability (MTI) and the heat-flux-driven buoyancy instability which operate in heterogeneous media. We find that the effect of sedimentation is to increase (decrease) the predicted growth rates in the inner (outer) cluster region. The unstable modes grow quickly compared to the sedimentation timescale. This suggests that the composition gradients as inferred from sedimentation models, which do not fully account for the anisotropic character of the weakly collisional environment, might not be very robust. Our results emphasize the subtleties involved in understanding the gas dynamics of the ICM and argue for the need of a comprehensive approach to address the issue of Helium sedimentation beyond current models.« less

  1. Cosmology and astrophysics from relaxed galaxy clusters - III. Thermodynamic profiles and scaling relations

    NASA Astrophysics Data System (ADS)

    Mantz, A. B.; Allen, S. W.; Morris, R. G.; Schmidt, R. W.

    2016-03-01

    This is the third in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Our sample comprises 40 clusters identified as being dynamically relaxed and hot (I.e. massive) in Papers I and II of this series. Here we consider the thermodynamics of the intracluster medium, in particular the profiles of density, temperature and related quantities, as well as integrated measurements of gas mass, average temperature, total luminosity and centre-excluded luminosity. We fit power-law scaling relations of each of these quantities as a function of redshift and cluster mass, which can be measured precisely and with minimal bias for these relaxed clusters using hydrostatic arguments. For the thermodynamic profiles, we jointly model the density and temperature and their intrinsic scatter as a function of radius, thus also capturing the behaviour of the gas pressure and entropy. For the integrated quantities, we also jointly fit a multidimensional intrinsic covariance. Our results reinforce the view that simple hydrodynamical models provide a good description of relaxed clusters outside their centres, but that additional heating and cooling processes are important in the inner regions (radii r ≲ 0.5 r2500 ≈ 0.15 r500). The thermodynamic profiles remain regular, with small intrinsic scatter, down to the smallest radii where deprojection is straightforward (˜20 kpc); within this radius, even the most relaxed systems show clear departures from spherical symmetry. Our results suggest that heating and cooling are continuously regulated in a tight feedback loop, allowing the cluster atmosphere to remain stratified on these scales.

  2. Self-Adaptive Prediction of Cloud Resource Demands Using Ensemble Model and Subtractive-Fuzzy Clustering Based Fuzzy Neural Network

    PubMed Central

    Chen, Zhijia; Zhu, Yuanchang; Di, Yanqiang; Feng, Shaochong

    2015-01-01

    In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper proposes a self-adaptive prediction method using ensemble model and subtractive-fuzzy clustering based fuzzy neural network (ESFCFNN). We analyze the characters of user preferences and demands. Then the architecture of the prediction model is constructed. We adopt some base predictors to compose the ensemble model. Then the structure and learning algorithm of fuzzy neural network is researched. To obtain the number of fuzzy rules and the initial value of the premise and consequent parameters, this paper proposes the fuzzy c-means combined with subtractive clustering algorithm, that is, the subtractive-fuzzy clustering. Finally, we adopt different criteria to evaluate the proposed method. The experiment results show that the method is accurate and effective in predicting the resource demands. PMID:25691896

  3. Surface properties for α-cluster nuclear matter

    NASA Astrophysics Data System (ADS)

    Castro, J. J.; Soto, J. R.; Yépez, E.

    2013-03-01

    We introduce a new microscopic model for α-cluster matter, which simulates the properties of ordinary nuclear matter and α-clustering in a curved surface of a large but finite nucleus. The model is based on a nested icosahedral fullerene-like multiple-shell structure, where each vertex is occupied by a microscopic α-particle. The novel aspect of this model is that it allows a consistent description of nuclear surface properties from microscopic parameters to be made without using the leptodermous expansion. In particular, we show that the calculated surface energy is in excellent agreement with the corresponding coefficient of the Bethe-Weizäcker semi-empirical mass formula. We discuss the properties of the surface α-cluster state, which resembles an ultra cold bosonic quantum gas trapped in an optical lattice. By comparing the surface and interior states we are able to estimate the α preformation probability. Possible extensions of this model to study nuclear dynamics through surface vibrations and departures from approximate sphericity are mentioned.

  4. Dark energy domination in the Virgocentric flow

    NASA Astrophysics Data System (ADS)

    Chernin, A. D.; Karachentsev, I. D.; Nasonova, O. G.; Teerikorpi, P.; Valtonen, M. J.; Dolgachev, V. P.; Domozhilova, L. M.; Byrd, G. G.

    2010-09-01

    Context. The standard ΛCDM cosmological model implies that all celestial bodies are embedded in a perfectly uniform dark energy background, represented by Einstein's cosmological constant, and experience its repulsive antigravity action. Aims: Can dark energy have strong dynamical effects on small cosmic scales as well as globally? Continuing our efforts to clarify this question, we now focus on the Virgo Cluster and the flow of expansion around it. Methods: We interpret the Hubble diagram from a new database of velocities and distances of galaxies in the cluster and its environment, using a nonlinear analytical model, which incorporates the antigravity force in terms of Newtonian mechanics. The key parameter is the zero-gravity radius, the distance at which gravity and antigravity are in balance. Results: 1. The interplay between the gravity of the cluster and the antigravity of the dark energy background determines the kinematical structure of the system and controls its evolution. 2. The gravity dominates the quasi-stationary bound cluster, while the antigravity controls the Virgocentric flow, bringing order and regularity to the flow, which reaches linearity and the global Hubble rate at distances ⪆15 Mpc. 3. The cluster and the flow form a system similar to the Local Group and its outflow. In the velocity-distance diagram, the cluster-flow structure reproduces the group-flow structure with a scaling factor of about 10; the zero-gravity radius for the cluster system is also 10 times larger. Conclusions: The phase and dynamical similarity of the systems on the scales of 1-30 Mpc suggests that a two-component pattern may be universal for groups and clusters: a quasi-stationary bound central component and an expanding outflow around it, caused by the nonlinear gravity-antigravity interplay with the dark energy dominating in the flow component.

  5. Star Count Density Profiles and Structural Parameters of 26 Galactic Globular Clusters

    NASA Astrophysics Data System (ADS)

    Miocchi, P.; Lanzoni, B.; Ferraro, F. R.; Dalessandro, E.; Vesperini, E.; Pasquato, M.; Beccari, G.; Pallanca, C.; Sanna, N.

    2013-09-01

    We used an appropriate combination of high-resolution Hubble Space Telescope observations and wide-field, ground-based data to derive the radial stellar density profiles of 26 Galactic globular clusters from resolved star counts (which can be all freely downloaded on-line). With respect to surface brightness (SB) profiles (which can be biased by the presence of sparse, bright stars), star counts are considered to be the most robust and reliable tool to derive cluster structural parameters. For each system, a detailed comparison with both King and Wilson models has been performed and the most relevant best-fit parameters have been obtained. This collection of data represents the largest homogeneous catalog collected so far of star count profiles and structural parameters derived therefrom. The analysis of the data of our catalog has shown that (1) the presence of the central cusps previously detected in the SB profiles of NGC 1851, M13, and M62 is not confirmed; (2) the majority of clusters in our sample are fit equally well by the King and the Wilson models; (3) we confirm the known relationship between cluster size (as measured by the effective radius) and galactocentric distance; (4) the ratio between the core and the effective radii shows a bimodal distribution, with a peak at ~0.3 for about 80% of the clusters and a secondary peak at ~0.6 for the remaining 20%. Interestingly, the main peak turns out to be in agreement with that expected from simulations of cluster dynamical evolution and the ratio between these two radii correlates well with an empirical dynamical-age indicator recently defined from the observed shape of blue straggler star radial distribution, thus suggesting that no exotic mechanisms of energy generation are needed in the cores of the analyzed clusters.

  6. The effect of gas dynamics on semi-analytic modelling of cluster galaxies

    NASA Astrophysics Data System (ADS)

    Saro, A.; De Lucia, G.; Dolag, K.; Borgani, S.

    2008-12-01

    We study the degree to which non-radiative gas dynamics affect the merger histories of haloes along with subsequent predictions from a semi-analytic model (SAM) of galaxy formation. To this aim, we use a sample of dark matter only and non-radiative smooth particle hydrodynamics (SPH) simulations of four massive clusters. The presence of gas-dynamical processes (e.g. ram pressure from the hot intra-cluster atmosphere) makes haloes more fragile in the runs which include gas. This results in a 25 per cent decrease in the total number of subhaloes at z = 0. The impact on the galaxy population predicted by SAMs is complicated by the presence of `orphan' galaxies, i.e. galaxies whose parent substructures are reduced below the resolution limit of the simulation. In the model employed in our study, these galaxies survive (unaffected by the tidal stripping process) for a residual merging time that is computed using a variation of the Chandrasekhar formula. Due to ram-pressure stripping, haloes in gas simulations tend to be less massive than their counterparts in the dark matter simulations. The resulting merging times for satellite galaxies are then longer in these simulations. On the other hand, the presence of gas influences the orbits of haloes making them on average more circular and therefore reducing the estimated merging times with respect to the dark matter only simulation. This effect is particularly significant for the most massive satellites and is (at least in part) responsible for the fact that brightest cluster galaxies in runs with gas have stellar masses which are about 25 per cent larger than those obtained from dark matter only simulations. Our results show that gas dynamics has only a marginal impact on the statistical properties of the galaxy population, but that its impact on the orbits and merging times of haloes strongly influences the assembly of the most massive galaxies.

  7. Computational Design of Clusters for Catalysis

    NASA Astrophysics Data System (ADS)

    Jimenez-Izal, Elisa; Alexandrova, Anastassia N.

    2018-04-01

    When small clusters are studied in chemical physics or physical chemistry, one perhaps thinks of the fundamental aspects of cluster electronic structure, or precision spectroscopy in ultracold molecular beams. However, small clusters are also of interest in catalysis, where the cold ground state or an isolated cluster may not even be the right starting point. Instead, the big question is: What happens to cluster-based catalysts under real conditions of catalysis, such as high temperature and coverage with reagents? Myriads of metastable cluster states become accessible, the entire system is dynamic, and catalysis may be driven by rare sites present only under those conditions. Activity, selectivity, and stability are highly dependent on size, composition, shape, support, and environment. To probe and master cluster catalysis, sophisticated tools are being developed for precision synthesis, operando measurements, and multiscale modeling. This review intends to tell the messy story of clusters in catalysis.

  8. Periodic Methods for Controlling a Satellite in Formation

    DTIC Science & Technology

    2002-03-01

    5 5. Clohessy - Wiltshire Reference Frame................................................................... 10 6...techniques to study relative position errors within a satellite cluster [19, 24]. The dynamics were based on Clohessy - Wiltshire equations with near...dynamics model by solving the time periodic, linearized system using Floquet Theory. More accurate than the Clohessy - Wiltshire solutions used in previous

  9. Cluster Analysis of Atmospheric Dynamics and Pollution Transport in a Coastal Area

    NASA Astrophysics Data System (ADS)

    Sokolov, Anton; Dmitriev, Egor; Maksimovich, Elena; Delbarre, Hervé; Augustin, Patrick; Gengembre, Cyril; Fourmentin, Marc; Locoge, Nadine

    2016-11-01

    Summertime atmospheric dynamics in the coastal zone of the industrialized Dunkerque agglomeration in northern France was characterized by a cluster analysis of back trajectories in the context of pollution transport. The MESO-NH atmospheric model was used to simulate the local dynamics at multiple scales with horizontal resolution down to 500 m, and for the online calculation of the Lagrangian backward trajectories with 30-min temporal resolution. Airmass transport was performed along six principal pathways obtained by the weighted k-means clustering technique. Four of these centroids corresponded to a range of wind speeds over the English Channel: two for wind directions from the north-east and two from the south-west. Another pathway corresponded to a south-westerly continental transport. The backward trajectories of the largest and most dispersed sixth cluster contained low wind speeds, including sea-breeze circulations. Based on analyses of meteorological data and pollution measurements, the principal atmospheric pathways were related to local air-contamination events. Continuous air quality and meteorological data were collected during the Benzene-Toluene-Ethylbenzene-Xylene 2006 campaign. The sites of the pollution measurements served as the endpoints for the backward trajectories. Pollutant transport pathways corresponding to the highest air contamination were defined.

  10. Classical plasma dynamics of Mie-oscillations in atomic clusters

    NASA Astrophysics Data System (ADS)

    Kull, H.-J.; El-Khawaldeh, A.

    2018-04-01

    Mie plasmons are of basic importance for the absorption of laser light by atomic clusters. In this work we first review the classical Rayleigh-theory of a dielectric sphere in an external electric field and Thomson’s plum-pudding model applied to atomic clusters. Both approaches allow for elementary discussions of Mie oscillations, however, they also indicate deficiencies in describing the damping mechanisms by electrons crossing the cluster surface. Nonlinear oscillator models have been widely studied to gain an understanding of damping and absorption by outer ionization of the cluster. In the present work, we attempt to address the issue of plasmon relaxation in atomic clusters in more detail based on classical particle simulations. In particular, we wish to study the role of thermal motion on plasmon relaxation, thereby extending nonlinear models of collective single-electron motion. Our simulations are particularly adopted to the regime of classical kinetics in weakly coupled plasmas and to cluster sizes extending the Debye-screening length. It will be illustrated how surface scattering leads to the relaxation of Mie oscillations in the presence of thermal motion and of electron spill-out at the cluster surface. This work is intended to give, from a classical perspective, further insight into recent work on plasmon relaxation in quantum plasmas [1].

  11. Droplet localization in the random XXZ model and its manifestations

    NASA Astrophysics Data System (ADS)

    Elgart, A.; Klein, A.; Stolz, G.

    2018-01-01

    We examine many-body localization properties for the eigenstates that lie in the droplet sector of the random-field spin- \\frac 1 2 XXZ chain. These states satisfy a basic single cluster localization property (SCLP), derived in Elgart et al (2018 J. Funct. Anal. (in press)). This leads to many consequences, including dynamical exponential clustering, non-spreading of information under the time evolution, and a zero velocity Lieb-Robinson bound. Since SCLP is only applicable to the droplet sector, our definitions and proofs do not rely on knowledge of the spectral and dynamical characteristics of the model outside this regime. Rather, to allow for a possible mobility transition, we adapt the notion of restricting the Hamiltonian to an energy window from the single particle setting to the many body context.

  12. Double blue straggler sequences in globular clusters: The case of NGC 362

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

    Dalessandro, E.; Ferraro, F. R.; Massari, D.

    2013-12-01

    We used high-quality images acquired with the Wide Field Camera 3 on board the Hubble Space Telescope to probe the blue straggler star (BSS) population of the galactic globular cluster NGC 362. We have found two distinct sequences of BSSs: this is the second case, after M30, where such a feature has been observed. Indeed, the BSS location, their extension in magnitude and color, and their radial distribution within the cluster nicely resemble those observed in M30, thus suggesting that the same interpretative scenario can be applied: the red BSS sub-population is generated by mass-transfer binaries, the blue one bymore » collisions. The discovery of four new W UMa stars, three of which lie along the red BSS sequence, further supports this scenario. We also found that the inner portion of the density profile deviates from a King model and is well reproduced by either a mild power law (α ∼ –0.2) or a double King profile. This feature supports the hypothesis that the cluster is currently undergoing the core-collapse phase. Moreover, the BSS radial distribution shows a central peak and monotonically decreases outward without any evidence of an external rising branch. This evidence is a further indication of the advanced dynamical age of NGC 362; in fact, together with M30, NGC 362 belongs to the family of dynamically old clusters (Family III) in the 'dynamical clock' classification proposed by Ferraro et al. The observational evidence presented here strengthens the possible connection between the existence of a double BSS sequence and a quite advanced dynamical status of the parent cluster.« less

  13. A novel look at energy equipartition in globular clusters

    NASA Astrophysics Data System (ADS)

    Bianchini, P.; van de Ven, G.; Norris, M. A.; Schinnerer, E.; Varri, A. L.

    2016-06-01

    Two-body interactions play a major role in shaping the structural and dynamical properties of globular clusters (GCs) over their long-term evolution. In particular, GCs evolve towards a state of partial energy equipartition that induces a mass dependence in their kinematics. By using a set of Monte Carlo cluster simulations evolved in quasi-isolation, we show that the stellar mass dependence of the velocity dispersion σ(m) can be described by an exponential function σ2 ∝ exp (-m/meq), with the parameter meq quantifying the degree of partial energy equipartition of the systems. This simple parametrization successfully captures the behaviour of the velocity dispersion at lower as well as higher stellar masses, that is, the regime where the system is expected to approach full equipartition. We find a tight correlation between the degree of equipartition reached by a GC and its dynamical state, indicating that clusters that are more than about 20 core relaxation times old, have reached a maximum degree of equipartition. This equipartition-dynamical state relation can be used as a tool to characterize the relaxation condition of a cluster with a kinematic measure of the meq parameter. Vice versa, the mass dependence of the kinematics can be predicted knowing the relaxation time solely on the basis of photometric measurements. Moreover, any deviations from this tight relation could be used as a probe of a peculiar dynamical history of a cluster. Finally, our novel approach is important for the interpretation of state-of-the-art Hubble Space Telescope proper motion data, for which the mass dependence of kinematics can now be measured, and for the application of modelling techniques which take into consideration multimass components and mass segregation.

  14. Principles and Algorithms for Natural and Engineered Systems

    DTIC Science & Technology

    2014-12-16

    Toolbox for MATLAB into C/C++. The target for the calibration is a 2D black and white checkerboard pattern. In a typical set of calibration images...errors the dynamic clusters typically contain entangled trajectories i.e. links form between two different dynamic clusters (see Figures 8 and 9). To...all dynamic clusters is L, and the average number of trajectories a given dynamic cluster are entangled with for its entire length is known as the

  15. Matter and charge distributions of 6He and 5,6,7,9Li within the dynamic-correlation model

    NASA Astrophysics Data System (ADS)

    Tomaselli, M.; Hjorth-Jensen, M.; Fritzsche, S.; Egelhof, P.; Neumaier, S. R.; Mutterer, M.; Kühl, T.; Dax, A.; Wang, H.

    2000-12-01

    The matter and the charge distributions of the 6He and 5,6,7,9Li isotopes are investigated within the dynamic-correlation model (DCM) which describes the ground states of light nuclei in terms of microscopic correlated clusters: the valence particles and the intrinsic vacuum states. The amplitudes of these mixed-mode wave functions are calculated in the framework of nonperturbative solutions of the equation of motion method (EOMM). The matter and charge mean square radii are in good agreement with experimental results. The calculated matter distribution of the 6He nucleus is characterized by a halo structure less pronounced than that calculated by the three cluster models. The charge distribution of 6Li reproduces well the electron scattering data. Good agreement with experimental data has been also achieved for the proton scattering cross sections of p-6He at an energy of 0.7 GeV/nucleon.

  16. Dynamical cluster approximation plus semiclassical approximation study for a Mott insulator and d-wave pairing

    NASA Astrophysics Data System (ADS)

    Kim, SungKun; Lee, Hunpyo

    2017-06-01

    Via a dynamical cluster approximation with N c = 4 in combination with a semiclassical approximation (DCA+SCA), we study the doped two-dimensional Hubbard model. We obtain a plaquette antiferromagnetic (AF) Mott insulator, a plaquette AF ordered metal, a pseudogap (or d-wave superconductor) and a paramagnetic metal by tuning the doping concentration. These features are similar to the behaviors observed in copper-oxide superconductors and are in qualitative agreement with the results calculated by the cluster dynamical mean field theory with the continuous-time quantum Monte Carlo (CDMFT+CTQMC) approach. The results of our DCA+SCA differ from those of the CDMFT+CTQMC approach in that the d-wave superconducting order parameters are shown even in the high doped region, unlike the results of the CDMFT+CTQMC approach. We think that the strong plaquette AF orderings in the dynamical cluster approximation (DCA) with N c = 4 suppress superconducting states with increasing doping up to strongly doped region, because frozen dynamical fluctuations in a semiclassical approximation (SCA) approach are unable to destroy those orderings. Our calculation with short-range spatial fluctuations is initial research, because the SCA can manage long-range spatial fluctuations in feasible computational times beyond the CDMFT+CTQMC tool. We believe that our future DCA+SCA calculations should supply information on the fully momentum-resolved physical properties, which could be compared with the results measured by angle-resolved photoemission spectroscopy experiments.

  17. Force Field Development and Molecular Dynamics of [NiFe] Hydrogenase

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

    Smith, Dayle MA; Xiong, Yijia; Straatsma, TP

    2012-05-09

    Classical molecular force-field parameters describing the structure and motion of metal clusters in [NiFe] hydrogenase enzymes can be used to compare the dynamics and thermodynamics of [NiFe] under different oxidation, protonation, and ligation circumstances. Using density functional theory (DFT) calculations of small model clusters representative of the active site and the proximal, medial, and distal Fe/S metal centers and their attached protein side chains, we have calculated classical force-field parameters for [NiFe] in reduced and oxidized states, including internal coordinates, force constants, and atom-centered charges. Derived force constants revealed that cysteinate ligands bound to the metal ions are more flexiblemore » in the Ni-B active site, which has a bridging hydroxide ligand, than in the Ni-C active site, which has a bridging hydride. Ten nanosecond all-atom, explicit-solvent MD simulations of [NiFe] hydrogenase in oxidized and reduced catalytic states established the stability of the derived force-field parameters in terms of C{alpha} and metal cluster fluctuations. Average active site structures from the protein MD simulations are consistent with [NiFe] structures from the Protein Data Bank, suggesting that the derived force-field parameters are transferrable to other hydrogenases beyond the structure used for testing. A comparison of experimental H{sub 2}-production rates demonstrated a relationship between cysteinate side chain rotation and activity, justifying the use of a fully dynamic model of [NiFe] metal cluster motion.« less

  18. 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.

  19. Molecular dynamics study of Al and Ni 3Al sputtering by Al clusters bombardment

    NASA Astrophysics Data System (ADS)

    Zhurkin, Eugeni E.; Kolesnikov, Anton S.

    2002-06-01

    The sputtering of Al and Ni 3Al (1 0 0) surfaces induced by impact of Al ions and Al N clusters ( N=2,4,6,9,13,55) with energies of 100 and 500 eV/atom is studied at atomic scale by means of classical molecular dynamics (MD). The MD code we used implements many-body tight binding potential splined to ZBL at short distances. Special attention has been paid to model dense cascades: we used quite big computation cells with lateral periodic and damped boundary conditions. In addition, long simulation times (10-25 ps) and representative statistics (up to 1000 runs per each case) were considered. The total sputtering yields, energy and time spectrums of sputtered particles, as well as preferential sputtering of compound target were analyzed, both in the linear and non-linear regimes. The significant "cluster enhancement" of sputtering yield was found for cluster sizes N⩾13. In parallel, we estimated collision cascade features depending on cluster size in order to interpret the nature of observed non-linear effects.

  20. Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.

    PubMed

    Makeneni, Spandana; Thieker, David F; Woods, Robert J

    2018-03-26

    In this work, we developed a computational protocol that employs multiple molecular docking experiments, followed by pose clustering, molecular dynamic simulations (10 ns), and energy rescoring to produce reliable 3D models of antibody-carbohydrate complexes. The protocol was applied to 10 antibody-carbohydrate co-complexes and three unliganded (apo) antibodies. Pose clustering significantly reduced the number of potential poses. For each system, 15 or fewer clusters out of 100 initial poses were generated and chosen for further analysis. Molecular dynamics (MD) simulations allowed the docked poses to either converge or disperse, and rescoring increased the likelihood that the best-ranked pose was an acceptable pose. This approach is amenable to automation and can be a valuable aid in determining the structure of antibody-carbohydrate complexes provided there is no major side chain rearrangement or backbone conformational change in the H3 loop of the CDR regions. Further, the basic protocol of docking a small ligand to a known binding site, clustering the results, and performing MD with a suitable force field is applicable to any protein ligand system.

  1. Breaking the Vainshtein screening in clusters of galaxies

    NASA Astrophysics Data System (ADS)

    Salzano, Vincenzo; Mota, David F.; Capozziello, Salvatore; Donahue, Megan

    2017-02-01

    In this work we will test an alternative model of gravity belonging to the large family of Galileon models. It is characterized by an intrinsic breaking of the Vainshtein mechanism inside large astrophysical objects, thus having possibly detectable observational signatures. We will compare theoretical predictions from this model with the observed total mass profile for a sample of clusters of galaxies. The profiles are derived using two complementary tools: x-ray hot intracluster gas dynamics, and strong and weak gravitational lensing. We find that a dependence with the dynamical internal status of each cluster is possible; for those clusters which are very close to be relaxed, and thus less perturbed by possible astrophysical local processes, the Galileon model gives a quite good fit to both x-ray and lensing observations. Both masses and concentrations for the dark matter halos are consistent with earlier results found in numerical simulations and in the literature, and no compelling statistical evidence for a deviation from general relativity is detectable from the present observational state. Actually, the characteristic Galileon parameter ϒ is always consistent with zero, and only an upper limit (≲0.086 at 1 σ , ≲0.16 at 2 σ , and ≲0.23 at 3 σ ) can be established. Some interesting distinctive deviations might be operative, but the statistical validity of the results is far from strong, and better data would be needed in order to either confirm or reject a potential tension with general relativity.

  2. Photonuclear reaction as a probe for α -clustering nuclei in the quasi-deuteron region

    NASA Astrophysics Data System (ADS)

    Huang, B. S.; Ma, Y. G.; He, W. B.

    2017-03-01

    Photon-nuclear reaction in a transport model frame, namely an extended quantum molecular dynamics model, has been realized at the photon energy of 70-140 MeV in the quasi-deuteron regime. For an important application, we pay a special focus on photonuclear reactions of 12C(γ ,n p )10B where 12C is considered as different configurations including α clustering. Obvious differences for some observables have been observed among different configurations, which can be attributed to spatial-momentum correlation of a neutron-proton pair inside nucleus, and therefore it gives us a sensitive probe to distinguish the different configurations including α clustering with the help of the photonuclear reaction mechanism.

  3. A "First Principles" Potential Energy Surface for Liquid Water from VRT Spectroscopy of Water Clusters

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

    Goldman, N; Leforestier, C; Saykally, R J

    We present results of gas phase cluster and liquid water simulations from the recently determined VRT(ASP-W)III water dimer potential energy surface. VRT(ASP-W)III is shown to not only be a model of high ''spectroscopic'' accuracy for the water dimer, but also makes accurate predictions of vibrational ground-state properties for clusters up through the hexamer. Results of ambient liquid water simulations from VRT(ASP-W)III are compared to those from ab initio Molecular Dynamics, other potentials of ''spectroscopic'' accuracy, and to experiment. The results herein represent the first time that a ''spectroscopic'' potential surface is able to correctly model condensed phase properties of water.

  4. Clustering in light nuclei and their effects on fusion and pre - equilibrium processes.

    NASA Astrophysics Data System (ADS)

    Gramegna, Fabiana; Cicerchia, Magda; Fabris, Daniela; Marchi, Tommaso; Cinausero, Marco; Degerlier, Meltem; Mabiala, Justin; Mantovani, Giorgia; Morelli, Luca; D'Agostino, Michela; Bruno, Mauro; Barlini, Sandro; Bini, Maurizio; Pasquali, Gabriele; Piantelli, Silvia; Casini, Giovanni; Pastore, Giuseppe; Gruyer, Diego; Ottanelli, Pietro; Valdré, Simone; Gelli, Nicla; Olmi, Alessandro; Poggi, Giacomo; Vardaci, Emanuele; Lombardo, Ivano; Dell'Aquila, Daniele; Leoni, Silvia; Cieplicka-Orynczak, Natalya; Fornal, Bogdan; Mengoni, Daniele; Collazuol, Gianmaria; Caciolli, Antonio; Colonna, Maria; Ono, Akira; Baiocco, Giorgio

    2017-11-01

    The study of nuclear cluster states bound by valence neutrons is a field of recent large interest. In particular, it is important to study the pre-formation of α-clusters in α-conjugate nuclei and the dynamical condensation of clusters during nuclear reactions [1-5]. The NUCL-EX collaboration has recently initiated an experimental campaign of exclusive measurements of fusion-evaporation reactions with light nuclei as interacting partners. In collisions involving light systems, the low expected multiplicity of fragments increases the probability of achieving a quasi-complete reconstruction of the event. In particular the formation and decay modes of an excited 24Mg system have been studied through two different reactions, 12C (95 MeV)+ 12C and 14N (80.7 MeV)+ 10B, which have been used to produce fused systems with nearly the same mass and excitation energy ( 60 MeV). In particular, even the de-excitation of the Hoyle state in 12C have been studied, both in peripheral (projectiles de-excitation) and in central collisions (six α-particles channel). Moreover, a research campaign studying pre-equilibrium emission of light charged particles and cluster properties of light and medium-mass nuclei has been carried out. For this purpose, a comparative study of the three nuclear systems 18O+28Si, 16O+30Si and 19F+27Al has been recently studied using the GARFIELD+RCo 4π setup [6]. The experimental data are compared with the predictions of simulated events generated with the statistical models (GEMINI++ and HFl) and through dynamical models like Stochastic Mean Field (SMF) and Antisymmetrized Molecular Dynamics (AMD) and filtered with a software replica of our apparatus in order to take into account the experimental conditions.

  5. 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.

  6. Changes in tropical precipitation cluster size distributions under global warming

    NASA Astrophysics Data System (ADS)

    Neelin, J. D.; Quinn, K. M.

    2016-12-01

    The total amount of precipitation integrated across a tropical storm or other precipitation feature (contiguous clusters of precipitation exceeding a minimum rain rate) is a useful measure of the aggregate size of the disturbance. To establish baseline behavior in current climate, the probability distribution of cluster sizes from multiple satellite retrievals and National Center for Environmental Prediction (NCEP) reanalysis is compared to those from Coupled Model Intercomparison Project (CMIP5) models and the Geophysical Fluid Dynamics Laboratory high-resolution atmospheric model (HIRAM-360 and -180). With the caveat that a minimum rain rate threshold is important in the models (which tend to overproduce low rain rates), the models agree well with observations in leading properties. In particular, scale-free power law ranges in which the probability drops slowly with increasing cluster size are well modeled, followed by a rapid drop in probability of the largest clusters above a cutoff scale. Under the RCP 8.5 global warming scenario, the models indicate substantial increases in probability (up to an order of magnitude) of the largest clusters by the end of century. For models with continuous time series of high resolution output, there is substantial spread on when these probability increases for the largest precipitation clusters should be detectable, ranging from detectable within the observational period to statistically significant trends emerging only in the second half of the century. Examination of NCEP reanalysis and SSMI/SSMIS series of satellite retrievals from 1979 to present does not yield reliable evidence of trends at this time. The results suggest improvements in inter-satellite calibration of the SSMI/SSMIS retrievals could aid future detection.

  7. Analyzing gene expression time-courses based on multi-resolution shape mixture model.

    PubMed

    Li, Ying; He, Ye; Zhang, Yu

    2016-11-01

    Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Role of string-like collective atomic motion on diffusion and structural relaxation in glass forming Cu-Zr alloys

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

    Zhang, Hao; Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Alberta T6G 2V4; Zhong, Cheng

    2015-04-28

    We investigate Cu-Zr liquid alloys using molecular dynamics simulation and well-accepted embedded atom method potentials over a wide range of chemical composition and temperature as model metallic glass-forming (GF) liquids. As with other types of GF materials, the dynamics of these complex liquids are characterized by “dynamic heterogeneity” in the form of transient polymeric clusters of highly mobile atoms that are composed in turn of atomic clusters exhibiting string-like cooperative motion. In accordance with the string model of relaxation, an extension of the Adam-Gibbs (AG) model, changes in the activation free energy ΔG{sub a} with temperature of both the Cumore » and Zr diffusion coefficients D, and the alpha structural relaxation time τ{sub α} can be described to a good approximation by changes in the average string length, L. In particular, we confirm that the strings are a concrete realization of the abstract “cooperatively rearranging regions” of AG. We also find coexisting clusters of relatively “immobile” atoms that exhibit predominantly icosahedral local packing rather than the low symmetry packing of “mobile” atoms. These two distinct types of dynamic heterogeneity are then associated with different fluid structural states. Glass-forming liquids are thus analogous to polycrystalline materials where the icosahedrally packed regions correspond to crystal grains, and the strings reside in the relatively disordered grain boundary-like regions exterior to these locally well-ordered regions. A dynamic equilibrium between localized (“immobile”) and wandering (“mobile”) particles exists in the liquid so that the dynamic heterogeneity can be considered to be type of self-assembly process. We also characterize changes in the local atomic free volume in the course of string-like atomic motion to better understand the initiation and propagation of these fluid excitations.« less

  9. 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.

  10. 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.

  11. Clustering of brain tumor cells: a first step for understanding tumor recurrence

    NASA Astrophysics Data System (ADS)

    Khain, Evgeniy; Nowicki, M. O.; Chiocca, E. A.; Lawler, S. E.; Schneider-Mizell, C. M.; Sander, L. M.

    2012-02-01

    Glioblastoma tumors are highly invasive; therefore the overall prognosis of patients remains poor, despite major improvements in treatment techniques. Cancer cells detach from the inner tumor core and actively migrate away [1]; eventually these invasive cells might form clusters, which can develop to recurrent tumors. In vitro experiments in collagen gel [1] followed the clustering dynamics of different glioma cell lines. Based on the experimental data, we formulated a stochastic model for cell dynamics, which identified two mechanisms of clustering. First, there is a critical value of the strength of adhesion; above the threshold, large clusters grow from a homogeneous suspension of cells; below it, the system remains homogeneous, similarly to the ordinary phase separation. Second, when cells form a cluster, there is evidence that their proliferation rate increases. We confirmed the theoretical predictions in a separate cell migration experiment on a substrate and found that both mechanisms are crucial for cluster formation and growth [2]. In addition to their medical importance, these phenomena present exciting examples of pattern formation and collective cell behavior in intrinsically non-equilibrium systems [3]. [4pt] [1] A. M. Stein et al, Biophys. J., 92, 356 (2007). [0pt] [2] E. Khain et al, EPL 88, 28006 (2009). [0pt] [3] E. Khain et al, Phys. Rev. E. 83, 031920 (2011).

  12. 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.

  13. Activity of a social dynamics model

    NASA Astrophysics Data System (ADS)

    Reia, Sandro M.; Neves, Ubiraci P. C.

    2015-10-01

    Axelrod's model was proposed to study interactions between agents and the formation of cultural domains. It presents a transition from a monocultural to a multicultural steady state which has been studied in the literature by evaluation of the relative size of the largest cluster. In this article, we propose new measurements based on the concept of activity per agent to study the Axelrod's model on the square lattice. We show that the variance of system activity can be used to indicate the critical points of the transition. Furthermore the frequency distribution of the system activity is able to show a coexistence of phases typical of a first order phase transition. Finally, we verify a power law dependence between cluster activity and cluster size for multicultural steady state configurations at the critical point.

  14. Structural transition in sputter-deposited amorphous germanium films by aging at ambient temperature

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

    Okugawa, M.; Nakamura, R., E-mail: nakamura@mtr.osakafu-u.ac.jp; Numakura, H.

    The structure of amorphous Ge (a-Ge) films prepared by sputter-deposition and the effects of aging at ambient temperature and pressure were studied by pair-distribution-function (PDF) analysis from electron scattering and molecular dynamics simulations. The PDFs of the as-deposited and aged samples for 3–13 months showed that the major peaks for Ge-Ge bonds decrease in intensity and broaden with aging for up to 7 months. In the PDFs of a-Ge of molecular dynamics simulation obtained by quenching liquid at different rates, the major peak intensities of a slowly cooled model are higher than those of a rapidly cooled model. Analyses onmore » short- and medium-range configurations show that the slowly cooled model includes a certain amount of medium-range ordered (MRO) clusters, while the rapidly cooled model includes liquid-like configurations rather than MRO clusters. The similarity between experimental and computational PDFs implies that as-deposited films are similar in structure to the slowly cooled model, whereas the fully aged films are similar to the rapidly cooled model. It is assumed that as they undergo room-temperature aging, the MRO clusters disintegrate and transform into liquid-like regions in the same matrix. This transition in local configurations is discussed in terms of instability and the non-equilibrium of nanoclusters produced by a vapor-deposition process.« less

  15. Long-range correlations improve understanding of the influence of network structure on contact dynamics.

    PubMed

    Peyrard, N; Dieckmann, U; Franc, A

    2008-05-01

    Models of infectious diseases are characterized by a phase transition between extinction and persistence. A challenge in contemporary epidemiology is to understand how the geometry of a host's interaction network influences disease dynamics close to the critical point of such a transition. Here we address this challenge with the help of moment closures. Traditional moment closures, however, do not provide satisfactory predictions close to such critical points. We therefore introduce a new method for incorporating longer-range correlations into existing closures. Our method is technically simple, remains computationally tractable and significantly improves the approximation's performance. Our extended closures thus provide an innovative tool for quantifying the influence of interaction networks on spatially or socially structured disease dynamics. In particular, we examine the effects of a network's clustering coefficient, as well as of new geometrical measures, such as a network's square clustering coefficients. We compare the relative performance of different closures from the literature, with or without our long-range extension. In this way, we demonstrate that the normalized version of the Bethe approximation-extended to incorporate long-range correlations according to our method-is an especially good candidate for studying influences of network structure. Our numerical results highlight the importance of the clustering coefficient and the square clustering coefficient for predicting disease dynamics at low and intermediate values of transmission rate, and demonstrate the significance of path redundancy for disease persistence.

  16. Viscoelasticity promotes collective swimming of sperm

    NASA Astrophysics Data System (ADS)

    Tung, Chih-Kuan; Harvey, Benedict B.; Fiore, Alyssa G.; Ardon, Florencia; Suarez, Susan S.; Wu, Mingming

    From flocking birds to swarming insects, interactions of organisms large and small lead to the emergence of collective dynamics. Here, we report striking collective swimming of bovine sperm, with sperm orienting in the same direction within each cluster, enabled by the viscoelasticity of the fluid. A long-chain polyacrylamide solution was used as a model viscoelastic fluid such that its rheology can be fine-tuned to mimic that of bovine cervical mucus. In viscoelastic fluid, sperm formed dynamic clusters, and the cluster size increased with elasticity of the polyacrylamide solution. In contrast, sperm swam randomly and individually in Newtonian fluids of similar viscosity. Analysis of the fluid motion surrounding individual swimming sperm indicated that sperm-fluid interaction is facilitated by the elastic component of the fluid. We note that almost all biological fluids (e.g. mucus and blood) are viscoelastic in nature, this finding highlights the importance of fluid elasticity in biological function. We will discuss what the orientation fluctuation within a cluster reveals about the interaction strength. Supported by NIH Grant 1R01HD070038.

  17. Phase synchronization of bursting neurons in clustered small-world networks

    NASA Astrophysics Data System (ADS)

    Batista, C. A. S.; Lameu, E. L.; Batista, A. M.; Lopes, S. R.; Pereira, T.; Zamora-López, G.; Kurths, J.; Viana, R. L.

    2012-07-01

    We investigate the collective dynamics of bursting neurons on clustered networks. The clustered network model is composed of subnetworks, each of them presenting the so-called small-world property. This model can also be regarded as a network of networks. In each subnetwork a neuron is connected to other ones with regular as well as random connections, the latter with a given intracluster probability. Moreover, in a given subnetwork each neuron has an intercluster probability to be connected to the other subnetworks. The local neuron dynamics has two time scales (fast and slow) and is modeled by a two-dimensional map. In such small-world network the neuron parameters are chosen to be slightly different such that, if the coupling strength is large enough, there may be synchronization of the bursting (slow) activity. We give bounds for the critical coupling strength to obtain global burst synchronization in terms of the network structure, that is, the probabilities of intracluster and intercluster connections. We find that, as the heterogeneity in the network is reduced, the network global synchronizability is improved. We show that the transitions to global synchrony may be abrupt or smooth depending on the intercluster probability.

  18. Modeling ecohydrological dynamics of smallholder strategies for food production in dryland agricultural systems

    NASA Astrophysics Data System (ADS)

    Gower, Drew B.; Dell'Angelo, Jampel; McCord, Paul F.; Caylor, Kelly K.; Evans, Tom P.

    2016-11-01

    In dryland environments, characterized by low and frequently variable rainfall, smallholder farmers must take crop water sensitivity into account along with other characteristics like seed availability and market price when deciding what to plant. In this paper we use the results of surveys conducted among smallholders located near Mount Kenya to identify clusters of farmers devoting different fractions of their land to subsistence and market crops. Additionally, we explore the tradeoffs between water-insensitive but low-value subsistence crops and a water-sensitive but high-value market crop using a numerical model that simulates soil moisture dynamics and crop production over multiple growing seasons. The cluster analysis shows that most farmers prefer to plant either only subsistence crops or only market crops, with a minority choosing to plant substantial fractions of both. The model output suggests that the value a farmer places on a successful growing season, a measure of risk aversion, plays a large role in whether the farmer chooses a subsistence or market crop strategy. Furthermore, access to irrigation, makes market crops more appealing, even to very risk-averse farmers. We then conclude that the observed clustering may result from different levels of risk aversion and access to irrigation.

  19. Two-temperature model in molecular dynamics simulations of cascades in Ni-based alloys

    DOE PAGES

    Zarkadoula, Eva; Samolyuk, German; Weber, William J.

    2017-01-03

    In high-energy irradiation events, energy from the fast moving ion is transferred to the system via nuclear and electronic energy loss mechanisms. The nuclear energy loss results in the creation of point defects and clusters, while the energy transferred to the electrons results in the creation of high electronic temperatures, which can affect the damage evolution. In this paper, we perform molecular dynamics simulations of 30 keV and 50 keV Ni ion cascades in nickel-based alloys without and with the electronic effects taken into account. We compare the results of classical molecular dynamics (MD) simulations, where the electronic effects aremore » ignored, with results from simulations that include the electronic stopping only, as well as simulations where both the electronic stopping and the electron-phonon coupling are incorporated, as described by the two temperature model (2T-MD). Finally, our results indicate that the 2T-MD leads to a smaller amount of damage, more isolated defects and smaller defect clusters.« less

  20. Numerical studies from quantum to macroscopic scales of carbon nanoparticules in hydrogen plasma

    NASA Astrophysics Data System (ADS)

    Lombardi, Guillaume; Ngandjong, Alain; Mezei, Zsolt; Mougenot, Jonathan; Michau, Armelle; Hassouni, Khaled; Seydou, Mahamadou; Maurel, François

    2016-09-01

    Dusty plasmas take part in large scientific domains from Universe Science to nanomaterial synthesis processes. They are often generated by growth from molecular precursor. This growth leads to the formation of larger clusters which induce solid germs nucleation. Particle formed are described by an aerosol dynamic taking into account coagulation, molecular deposition and transport processes. These processes are controlled by the elementary particle. So there is a strong coupling between particle dynamics and plasma discharge equilibrium. This study is focused on the development of a multiscale physic and numeric model of hydrogen plasmas and carbon particles around three essential coupled axes to describe the various physical phenomena: (i) Macro/mesoscopic fluid modeling describing in an auto-coherent way, characteristics of the plasma, molecular clusters and aerosol behavior; (ii) the classic molecular dynamics offering a description to the scale molecular of the chains of chemical reactions and the phenomena of aggregation; (iii) the quantum chemistry to establish the activation barriers of the different processes driving the nanopoarticule formation.

  1. Dynamical evolution of globular-cluster systems in clusters of galaxies

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

    Muzzio, J.C.

    1987-04-01

    The dynamical processes that affect globular-cluster systems in clusters of galaxies are analyzed. Two-body and impulsive approximations are utilized to study dynamical friction, drag force, tidal stripping, tidal radii, globular-cluster swapping, tidal accretion, and galactic cannibalism. The evolution of galaxies and the collision of galaxies are simulated numerically; the steps involved in the simulation are described. The simulated data are compared with observations. Consideration is given to the number of galaxies, halo extension, location of the galaxies, distribution of the missing mass, nonequilibrium initial conditions, mass dependence, massive central galaxies, globular-cluster distribution, and lost globular clusters. 116 references.

  2. Dynamics, Chemical Abundances, and ages of Globular Clusters in the Virgo Cluster of Galaxies

    NASA Astrophysics Data System (ADS)

    Guhathakurta, Puragra; NGVS Collaboration

    2018-01-01

    We present a study of the dynamics, metallicities, and ages of globular clusters (GCs) in the Next Generation Virgo cluster Survey (NGVS), a deep, multi-band (u, g, r, i, z, and Ks), wide-field (104 deg2) imaging survey carried out using the 3.6-m Canada-France-Hawaii Telescope and MegaCam imager. GC candidates were selected from the NGVS survey using photometric and image morphology criteria and these were followed up with deep, medium-resolution, multi-object spectroscopy using the Keck II 10-m telescope and DEIMOS spectrograph. The primary spectroscopic targets were candidate GC satellites of dwarf elliptical (dE) and ultra-diffuse galaxies (UDGs) in the Virgo cluster. While many objects were confirmed as GC satellites of Virgo dEs and UDGs, many turned out to be non-satellites based on their radial velocity and/or positional mismatch any identifiable Virgo cluster galaxy. We have used a combination of spectral characteristics (e.g., presence of absorption vs. emission lines), new Gaussian mixture modeling of radial velocity and sky position data, and a new extreme deconvolution analysis of ugrizKs photometry and image morphology, to classify all the objects in our sample into: (1) GC satellites of dE galaxies, (2) GC satellites of UDGs, (3) intra-cluster GCs (ICGCs) in the Virgo cluster, (4) GCs in the outer halo of the central cluster galaxy M87, (5) foreground Milky Way stars, and (6) distant background galaxies. We use these data to study the dynamics and dark matter content of dE and UDGs in the Virgo cluster, place important constraints on the nature of dE nuclei, and study the origin of ICGCs versus GCs in the remote M87 halo.We are grateful for financial support from the NSF and NASA/STScI.

  3. A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models

    PubMed Central

    Rolls, David A.; Wang, Peng; McBryde, Emma; Pattison, Philippa; Robins, Garry

    2015-01-01

    We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random graph models (ERGMs) and extensions of the configuration model. We use three kinds of empirical contact networks, chosen to provide both variety and realistic patterns of human contact: a highly clustered network, a bipartite network and a snowball sampled network of a “hidden population”. In the case of the snowball sampled network we present a novel method for fitting an edge-triangle model. In our results, ERGMs consistently capture clustering as well or better than configuration-type models, but the latter models better capture the node degree distribution. Despite the additional computational requirements to fit ERGMs to empirical networks, the use of ERGMs provides only a slight improvement in the ability of the models to recreate epidemic features of the empirical network in simulated SIR epidemics. Generally, SIR epidemic results from using configuration-type models fall between those from a random network model (i.e., an Erdős-Rényi model) and an ERGM. The addition of subgraphs of size four to edge-triangle type models does improve agreement with the empirical network for smaller densities in clustered networks. Additional subgraphs do not make a noticeable difference in our example, although we would expect the ability to model cliques to be helpful for contact networks exhibiting household structure. PMID:26555701

  4. Application of dynamic topic models to toxicogenomics data.

    PubMed

    Lee, Mikyung; Liu, Zhichao; Huang, Ruili; Tong, Weida

    2016-10-06

    All biological processes are inherently dynamic. Biological systems evolve transiently or sustainably according to sequential time points after perturbation by environment insults, drugs and chemicals. Investigating the temporal behavior of molecular events has been an important subject to understand the underlying mechanisms governing the biological system in response to, such as, drug treatment. The intrinsic complexity of time series data requires appropriate computational algorithms for data interpretation. In this study, we propose, for the first time, the application of dynamic topic models (DTM) for analyzing time-series gene expression data. A large time-series toxicogenomics dataset was studied. It contains over 3144 microarrays of gene expression data corresponding to rat livers treated with 131 compounds (most are drugs) at two doses (control and high dose) in a repeated schedule containing four separate time points (4-, 8-, 15- and 29-day). We analyzed, with DTM, the topics (consisting of a set of genes) and their biological interpretations over these four time points. We identified hidden patterns embedded in this time-series gene expression profiles. From the topic distribution for compound-time condition, a number of drugs were successfully clustered by their shared mode-of-action such as PPARɑ agonists and COX inhibitors. The biological meaning underlying each topic was interpreted using diverse sources of information such as functional analysis of the pathways and therapeutic uses of the drugs. Additionally, we found that sample clusters produced by DTM are much more coherent in terms of functional categories when compared to traditional clustering algorithms. We demonstrated that DTM, a text mining technique, can be a powerful computational approach for clustering time-series gene expression profiles with the probabilistic representation of their dynamic features along sequential time frames. The method offers an alternative way for uncovering hidden patterns embedded in time series gene expression profiles to gain enhanced understanding of dynamic behavior of gene regulation in the biological system.

  5. Encapsulating urban traffic rhythms into road networks.

    PubMed

    Wang, Junjie; Wei, Dong; He, Kun; Gong, Hang; Wang, Pu

    2014-02-20

    Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.

  6. Encapsulating Urban Traffic Rhythms into Road Networks

    PubMed Central

    Wang, Junjie; Wei, Dong; He, Kun; Gong, Hang; Wang, Pu

    2014-01-01

    Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution. PMID:24553203

  7. Salmonella enterica Pulsed-Field Gel Electrophoresis Clusters, Minnesota, USA, 2001–2007

    PubMed Central

    Hedberg, Craig W.; Meyer, Stephanie; Boxrud, David J.; Smith, Kirk E.

    2010-01-01

    We determined characteristics of Salmonella enterica pulsed-field gel electrophoresis clusters that predict their being solved (i.e., that result in identification of a confirmed outbreak). Clusters were investigated by the Minnesota Department of Health by using a dynamic iterative model. During 2001–2007, a total of 43 (12.5%) of 344 clusters were solved. Clusters of >4 isolates were more likely to be solved than clusters of 2 isolates. Clusters in which the first 3 case isolates were received at the Minnesota Department of Health within 7 days were more likely to be solved than were clusters in which the first 3 case isolates were received over a period >14 days. If resources do not permit investigation of all S. enterica pulsed-field gel electrophoresis clusters, investigation of clusters of >4 cases and clusters in which the first 3 case isolates were received at a public health laboratory within 7 days may improve outbreak investigations. PMID:21029524

  8. Alignment and integration of complex networks by hypergraph-based spectral clustering

    NASA Astrophysics Data System (ADS)

    Michoel, Tom; Nachtergaele, Bruno

    2012-11-01

    Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

  9. Alignment and integration of complex networks by hypergraph-based spectral clustering.

    PubMed

    Michoel, Tom; Nachtergaele, Bruno

    2012-11-01

    Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

  10. Cooling rate dependence of structural order in Al90Sm10 metallic glass

    NASA Astrophysics Data System (ADS)

    Sun, Yang; Zhang, Yue; Zhang, Feng; Ye, Zhuo; Ding, Zejun; Wang, Cai-Zhuang; Ho, Kai-Ming

    2016-07-01

    The atomic structure of Al90Sm10 metallic glass is studied using molecular dynamics simulations. By performing a long sub-Tg annealing, we developed a glass model closer to the experiments than the models prepared by continuous cooling. Using the cluster alignment method, we found that "3661" cluster is the dominating short-range order in the glass samples. The connection and arrangement of "3661" clusters, which define the medium-range order in the system, are enhanced significantly in the sub-Tg annealed sample as compared with the fast cooled glass samples. Unlike some strong binary glass formers such as Cu64.5Zr35.5, the clusters representing the short-range order do not form an interconnected interpenetrating network in Al90Sm10, which has only marginal glass formability.

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

    DOE PAGES

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

    2017-12-20

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

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

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

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

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

  13. Dynamical organization towards consensus in the Axelrod model on complex networks

    NASA Astrophysics Data System (ADS)

    Guerra, Beniamino; Poncela, Julia; Gómez-Gardeñes, Jesús; Latora, Vito; Moreno, Yamir

    2010-05-01

    We analyze the dynamics toward cultural consensus in the Axelrod model on scale-free networks. By looking at the microscopic dynamics of the model, we are able to show how culture traits spread across different cultural features. We compare the diffusion at the level of cultural features to the growth of cultural consensus at the global level, finding important differences between these two processes. In particular, we show that even when most of the cultural features have reached macroscopic consensus, there are still no signals of globalization. Finally, we analyze the topology of consensus clusters both for global culture and at the feature level of representation.

  14. On the effects of cluster density and concentration on the horizontal branch morphology - The origin of the blue tails

    NASA Technical Reports Server (NTRS)

    Fusi Pecci, F.; Ferraro, F. R.; Bellazzini, M.; Djorgovski, S.; Piotto, G.; Buonanno, R.

    1993-01-01

    Possible relationships between horizontal branch (HB) morphology in Galactic globular clusters and the cluster structure and dynamical evolution are investigated. New HB observables are defined and determined using a theoretical framework deduced from HB models. Data for 53 Galactic globular clusters are used to obtain correlations between the observables. It is found that the net length of the HB and the presence and extent of blue tails in particular are correlated with the cluster density and concentrations, in the sense of more concentrated or denser clusters having bluer and longer HB morphologies. This effect is especially strong for the intermediate metallicity clusters. Thus, the cluster environment can affect the stellar evolution leading to the HB and therefore the HB morphology. This result is interpreted in terms of an enhanced mass removal from the HB progenitors.

  15. Coulomb explosion of hydrogen clusters irradiated by an ultrashort intense laser pulse

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

    Li Hongyu; Liu Jiansheng; Wang Cheng

    The explosion dynamics of hydrogen clusters driven by an ultrashort intense laser pulse has been analyzed analytically and numerically by employing a simplified Coulomb explosion model. The dependence of average and maximum proton kinetic energy on cluster size, pulse duration, and laser intensity has been investigated respectively. The existence of an optimum cluster size allows the proton energy to reach the maximum when the cluster size matches with the intensity and the duration of the laser pulse. In order to explain our experimental results such as the measured proton energy spectrum and the saturation effect of proton energy, the effectsmore » of cluster size distribution as well as the laser intensity distribution on the focus spot should be considered. A good agreement between them is obtained.« less

  16. Coulomb explosion of hydrogen clusters irradiated by an ultrashort intense laser pulse

    NASA Astrophysics Data System (ADS)

    Li, Hongyu; Liu, Jiansheng; Wang, Cheng; Ni, Guoquan; Li, Ruxin; Xu, Zhizhan

    2006-08-01

    The explosion dynamics of hydrogen clusters driven by an ultrashort intense laser pulse has been analyzed analytically and numerically by employing a simplified Coulomb explosion model. The dependence of average and maximum proton kinetic energy on cluster size, pulse duration, and laser intensity has been investigated respectively. The existence of an optimum cluster size allows the proton energy to reach the maximum when the cluster size matches with the intensity and the duration of the laser pulse. In order to explain our experimental results such as the measured proton energy spectrum and the saturation effect of proton energy, the effects of cluster size distribution as well as the laser intensity distribution on the focus spot should be considered. A good agreement between them is obtained.

  17. Cluster analysis of word frequency dynamics

    NASA Astrophysics Data System (ADS)

    Maslennikova, Yu S.; Bochkarev, V. V.; Belashova, I. A.

    2015-01-01

    This paper describes the analysis and modelling of word usage frequency time series. During one of previous studies, an assumption was put forward that all word usage frequencies have uniform dynamics approaching the shape of a Gaussian function. This assumption can be checked using the frequency dictionaries of the Google Books Ngram database. This database includes 5.2 million books published between 1500 and 2008. The corpus contains over 500 billion words in American English, British English, French, German, Spanish, Russian, Hebrew, and Chinese. We clustered time series of word usage frequencies using a Kohonen neural network. The similarity between input vectors was estimated using several algorithms. As a result of the neural network training procedure, more than ten different forms of time series were found. They describe the dynamics of word usage frequencies from birth to death of individual words. Different groups of word forms were found to have different dynamics of word usage frequency variations.

  18. Prediction of line failure fault based on weighted fuzzy dynamic clustering and improved relational analysis

    NASA Astrophysics Data System (ADS)

    Meng, Xiaocheng; Che, Renfei; Gao, Shi; He, Juntao

    2018-04-01

    With the advent of large data age, power system research has entered a new stage. At present, the main application of large data in the power system is the early warning analysis of the power equipment, that is, by collecting the relevant historical fault data information, the system security is improved by predicting the early warning and failure rate of different kinds of equipment under certain relational factors. In this paper, a method of line failure rate warning is proposed. Firstly, fuzzy dynamic clustering is carried out based on the collected historical information. Considering the imbalance between the attributes, the coefficient of variation is given to the corresponding weights. And then use the weighted fuzzy clustering to deal with the data more effectively. Then, by analyzing the basic idea and basic properties of the relational analysis model theory, the gray relational model is improved by combining the slope and the Deng model. And the incremental composition and composition of the two sequences are also considered to the gray relational model to obtain the gray relational degree between the various samples. The failure rate is predicted according to the principle of weighting. Finally, the concrete process is expounded by an example, and the validity and superiority of the proposed method are verified.

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

    NASA Astrophysics Data System (ADS)

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

    2018-06-01

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

  20. Wettability behavior of water droplet on organic-polluted fused quartz surfaces of pillar-type nanostructures applying molecular dynamics simulation

    NASA Astrophysics Data System (ADS)

    Chen, Jiaxuan; Chen, Wenyang; Xie, Yajing; Wang, Zhiguo; Qin, Jianbo

    2017-02-01

    Molecular dynamics (MD) is applied to research the wettability behaviors of different scale of water clusters absorbed on organic-polluted fused quartz (FQ) surface and different surface structures. The wettability of water clusters is studied under the effect of organic pollutant. With the combined influence of pillar height and interval, the stair-step Wenzel-Cassie transition critical line is obtained by analyzing stable state of water clusters on different surface structures. The results also show that when interval of pillars and the height of pillars keep constant respectively, the changing rules are exactly the opposite and these are termed as the "waterfall" rules. The substrate models of water clusters at Cassie-Baxter state which are at the vicinity of critical line are chosen to analyze the relationship of HI (refers to the pillar height/interval) ratio and scale of water cluster. The study has found that there is a critical changing threshold in the wettability changing process. When the HI ratio keeps constant, the wettability decreases first and then increase as the size of cluster increases; on the contrary, when the size of cluster keeps constant, the wettability decreases and then increase with the decrease of HI ratio, but when the size of water cluster is close to the threshold the HI ratio has little effect on the wettability.

  1. Cross-entropy clustering framework for catchment classification

    NASA Astrophysics Data System (ADS)

    Tongal, Hakan; Sivakumar, Bellie

    2017-09-01

    There is an increasing interest in catchment classification and regionalization in hydrology, as they are useful for identification of appropriate model complexity and transfer of information from gauged catchments to ungauged ones, among others. This study introduces a nonlinear cross-entropy clustering (CEC) method for classification of catchments. The method specifically considers embedding dimension (m), sample entropy (SampEn), and coefficient of variation (CV) to represent dimensionality, complexity, and variability of the time series, respectively. The method is applied to daily streamflow time series from 217 gauging stations across Australia. The results suggest that a combination of linear and nonlinear parameters (i.e. m, SampEn, and CV), representing different aspects of the underlying dynamics of streamflows, could be useful for determining distinct patterns of flow generation mechanisms within a nonlinear clustering framework. For the 217 streamflow time series, nine hydrologically homogeneous clusters that have distinct patterns of flow regime characteristics and specific dominant hydrological attributes with different climatic features are obtained. Comparison of the results with those obtained using the widely employed k-means clustering method (which results in five clusters, with the loss of some information about the features of the clusters) suggests the superiority of the cross-entropy clustering method. The outcomes from this study provide a useful guideline for employing the nonlinear dynamic approaches based on hydrologic signatures and for gaining an improved understanding of streamflow variability at a large scale.

  2. Dynamics of photoprocesses induced by femtosecond infrared radiation in free molecules and clusters of iron pentacarbonyl

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

    Kompanets, V. O.; Lokhman, V. N.; Poydashev, D. G., E-mail: poydashev@isan.troitsk.ru

    2016-04-15

    The dynamics of photoprocesses induced by femtosecond infrared radiation in free Fe(CO){sub 5} molecules and their clusters owing to the resonant excitation of vibrations of CO bonds in the 5-μm range has been studied. The technique of infrared excitation and photoionization probing (λ = 400 nm) by femtosecond pulses has been used in combination with time-of-flight mass spectrometry. It has been found that an infrared pulse selectively excites vibrations of CO bonds in free molecules, which results in a decrease in the yield of the Fe(CO){sub 5}{sup +} molecular ion. Subsequent relaxation processes have been analyzed and the results havemore » been interpreted. The time of the energy transfer from excited vibrations to other vibrations of the molecule owing to intramolecular relaxation has been measured. The dynamics of dissociation of [Fe(CO){sub 5}]{sub n} clusters irradiated by femtosecond infrared radiation has been studied. The time dependence of the yield of free molecules has been measured under different infrared laser excitation conditions. We have proposed a model that well describes the results of the experiment and makes it possible, in particular, to calculate the profile of variation of the temperature of clusters within the “evaporation ensemble” concept. The intramolecular and intracluster vibrational relaxation rates in [Fe(CO){sub 5}]{sub n} clusters have been estimated.« less

  3. Étude statistique et dynamique de la propagation d'épidémies dans un réseau de petit mondeStatistical and dynamical study of the epidemics propagation in a small world network

    NASA Astrophysics Data System (ADS)

    Zekri, Nouredine; Clerc, Jean Pierre

    We study numerically in this work the statistical and dynamical properties of the clusters in a one dimensional small world model. The parameters chosen correspond to a realistic network of children of school age where a disease like measles can propagate. Extensive results on the statistical behavior of the clusters around the percolation threshold, as well as the evoltion with time, are discussed. To cite this article: N. Zekri, J.P. Clerc, C. R. Physique 3 (2002) 741-747.

  4. Mass segregation phenomena using the Hamiltonian Mean Field model

    NASA Astrophysics Data System (ADS)

    Steiner, J. R.; Zolacir, T. O.

    2018-02-01

    Mass segregation problem is thought to be entangled with the dynamical evolution of young stellar clusters (Olczak, 2011 [1]). This is a common sense in the astrophysical community. In this work, the Hamiltonian Mean Field (HMF) model with different masses is studied. A mass segregation phenomenon (MSP) arises from this study as a dynamical feature. The MSP in the HMF model is a consequence of the Landau damping (LD) and it appears in systems that the interactions belongs to a long range regime. Actually HMF is a toy model known to show up the main characteristics of astrophysical systems due to the mean field character of the potential and for different masses, as stellar and galaxies clusters, also exhibits MSP. It is in this sense that computational simulations focusing in what happens over the mass distribution in the phase space are performed for this system. What happens through the violent relaxation period and what stands for the quasi-stationary states (QSS) of this dynamics is analyzed. The results obtained support the fact that MSP is observed already in the violent relaxation time and is maintained during the QSS. Some structures in the mass distribution function are observed. As a result of this study the mass distribution is determined by the system dynamics and is independent of the dimensionality of the system. MSP occurs in a one dimensional system as a result of the long range forces that acts in the system. In this approach MSP emerges as a dynamical feature. We also show that for HMF with different masses, the dynamical time scale is N.

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

    PubMed

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

    2017-01-01

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

  6. Dynamical heterogeneity in a glass-forming ideal gas.

    PubMed

    Charbonneau, Patrick; Das, Chinmay; Frenkel, Daan

    2008-07-01

    We conduct a numerical study of the dynamical behavior of a system of three-dimensional "crosses," particles that consist of three mutually perpendicular line segments of length sigma rigidly joined at their midpoints. In an earlier study [W. van Ketel, Phys. Rev. Lett. 94, 135703 (2005)] we showed that this model has the structural properties of an ideal gas, yet the dynamical properties of a strong glass former. In the present paper we report an extensive study of the dynamical heterogeneities that appear in this system in the regime where glassy behavior sets in. On the one hand, we find that the propensity of a particle to diffuse is determined by the structure of its local environment. The local density around mobile particles is significantly less than the average density, but there is little clustering of mobile particles, and the clusters observed tend to be small. On the other hand, dynamical susceptibility results indicate that a large dynamical length scale develops even at moderate densities. This suggests that propensity and other mobility measures are an incomplete measure of the dynamical length scales in this system.

  7. Mechanism of cell alignment in groups of Myxococcus xanthus bacteria

    NASA Astrophysics Data System (ADS)

    Balgam, Rajesh; Igoshin, Oleg

    2015-03-01

    Myxococcus xanthus is a model for studying self-organization in bacteria. These flexible cylindrical bacteria move along. In groups, M. xanthus cells align themselves into dynamic cell clusters but the mechanism underlying their formation is unknown. It has been shown that steric interactions can cause alignment in self-propelled hard rods but it is not clear how flexibility and reversals affect the alignment and cluster formation. We have investigated cell alignment process using our biophysical model of M. xanthus cell in an agent-based simulation framework under realistic cell flexibility values. We observed that flexible model cells can form aligned cell clusters when reversals are suppressed but these clusters disappeared when reversals frequency becomes similar to the observed value. However, M. xanthus cells follow slime (polysaccharide gel like material) trails left by other cells and we show that implementing this into our model rescues cell clustering for reversing cells. Our results show that slime following along with periodic cell reversals act as positive feedback to reinforce existing slime trails and recruit more cells. Furthermore, we have observed that mechanical cell alignment combined with slime following is sufficient to explain the distinct clustering patterns of reversing and non-reversing cells as observed in recent experiments. This work is supported by NSF MCB 0845919 and 1411780.

  8. Biophysical controls on cluster dynamics and architectural differentiation of microbial biofilms in contrasting flow environments

    PubMed Central

    Hödl, Iris; Mari, Lorenzo; Bertuzzo, Enrico; Suweis, Samir; Besemer, Katharina; Rinaldo, Andrea; Battin, Tom J

    2014-01-01

    Ecology, with a traditional focus on plants and animals, seeks to understand the mechanisms underlying structure and dynamics of communities. In microbial ecology, the focus is changing from planktonic communities to attached biofilms that dominate microbial life in numerous systems. Therefore, interest in the structure and function of biofilms is on the rise. Biofilms can form reproducible physical structures (i.e. architecture) at the millimetre-scale, which are central to their functioning. However, the spatial dynamics of the clusters conferring physical structure to biofilms remains often elusive. By experimenting with complex microbial communities forming biofilms in contrasting hydrodynamic microenvironments in stream mesocosms, we show that morphogenesis results in ‘ripple-like’ and ‘star-like’ architectures – as they have also been reported from monospecies bacterial biofilms, for instance. To explore the potential contribution of demographic processes to these architectures, we propose a size-structured population model to simulate the dynamics of biofilm growth and cluster size distribution. Our findings establish that basic physical and demographic processes are key forces that shape apparently universal biofilm architectures as they occur in diverse microbial but also in single-species bacterial biofilms. PMID:23879839

  9. Clustering mechanism of oxocarboxylic acids involving hydration reaction: Implications for the atmospheric models

    NASA Astrophysics Data System (ADS)

    Liu, Ling; Kupiainen-Määttä, Oona; Zhang, Haijie; Li, Hao; Zhong, Jie; Kurtén, Theo; Vehkamäki, Hanna; Zhang, Shaowen; Zhang, Yunhong; Ge, Maofa; Zhang, Xiuhui; Li, Zesheng

    2018-06-01

    The formation of atmospheric aerosol particles from condensable gases is a dominant source of particulate matter in the boundary layer, but the mechanism is still ambiguous. During the clustering process, precursors with different reactivities can induce various chemical reactions in addition to the formation of hydrogen bonds. However, the clustering mechanism involving chemical reactions is rarely considered in most of the nucleation process models. Oxocarboxylic acids are common compositions of secondary organic aerosol, but the role of oxocarboxylic acids in secondary organic aerosol formation is still not fully understood. In this paper, glyoxylic acid, the simplest and the most abundant atmospheric oxocarboxylic acid, has been selected as a representative example of oxocarboxylic acids in order to study the clustering mechanism involving hydration reactions using density functional theory combined with the Atmospheric Clusters Dynamic Code. The hydration reaction of glyoxylic acid can occur either in the gas phase or during the clustering process. Under atmospheric conditions, the total conversion ratio of glyoxylic acid to its hydration reaction product (2,2-dihydroxyacetic acid) in both gas phase and clusters can be up to 85%, and the product can further participate in the clustering process. The differences in cluster structures and properties induced by the hydration reaction lead to significant differences in cluster formation rates and pathways at relatively low temperatures.

  10. Tidal stripping stellar substructures around four metal-poor globular clusters in the galactic bulge

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

    Chun, Sang-Hyun; Kang, Minhee; Jung, DooSeok

    2015-01-01

    We investigate the spatial density configuration of stars around four metal-poor globular clusters (NGC 6266, NGC 6626, NGC 6642, and NGC 6723) in the Galactic bulge region using wide-field deep J, H, and K imaging data obtained with the Wide Field Camera near-infrared array on the United Kingdom Infrared Telescope. A statistical weighted filtering algorithm for the stars on the color–magnitude diagram is applied in order to sort cluster member candidates from the field star contamination. In two-dimensional isodensity contour maps of the clusters, we find that all four of the globular clusters exhibit strong evidence of tidally stripped stellarmore » features beyond the tidal radius in the form of tidal tails or small density lobes/chunks. The orientations of the extended stellar substructures are likely to be associated with the effect of dynamic interaction with the Galaxy and the cluster's space motion. The observed radial density profiles of the four globular clusters also describe the extended substructures; they depart from theoretical King and Wilson models and have an overdensity feature with a break in the slope of the profile at the outer region of clusters. The observed results could imply that four globular clusters in the Galactic bulge region have experienced strong environmental effects such as tidal forces or bulge/disk shocks of the Galaxy during the dynamical evolution of globular clusters. These observational results provide further details which add to our understanding of the evolution of clusters in the Galactic bulge region as well as the formation of the Galaxy.« less

  11. Clustered multistate models with observation level random effects, mover-stayer effects and dynamic covariates: modelling transition intensities and sojourn times in a study of psoriatic arthritis.

    PubMed

    Yiu, Sean; Farewell, Vernon T; Tom, Brian D M

    2018-02-01

    In psoriatic arthritis, it is important to understand the joint activity (represented by swelling and pain) and damage processes because both are related to severe physical disability. The paper aims to provide a comprehensive investigation into both processes occurring over time, in particular their relationship, by specifying a joint multistate model at the individual hand joint level, which also accounts for many of their important features. As there are multiple hand joints, such an analysis will be based on the use of clustered multistate models. Here we consider an observation level random-effects structure with dynamic covariates and allow for the possibility that a subpopulation of patients is at minimal risk of damage. Such an analysis is found to provide further understanding of the activity-damage relationship beyond that provided by previous analyses. Consideration is also given to the modelling of mean sojourn times and jump probabilities. In particular, a novel model parameterization which allows easily interpretable covariate effects to act on these quantities is proposed.

  12. 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

  13. On the accuracy of the MB-pol many-body potential for water: Interaction energies, vibrational frequencies, and classical thermodynamic and dynamical properties from clusters to liquid water and ice

    NASA Astrophysics Data System (ADS)

    Reddy, Sandeep K.; Straight, Shelby C.; Bajaj, Pushp; Huy Pham, C.; Riera, Marc; Moberg, Daniel R.; Morales, Miguel A.; Knight, Chris; Götz, Andreas W.; Paesani, Francesco

    2016-11-01

    The MB-pol many-body potential has recently emerged as an accurate molecular model for water simulations from the gas to the condensed phase. In this study, the accuracy of MB-pol is systematically assessed across the three phases of water through extensive comparisons with experimental data and high-level ab initio calculations. Individual many-body contributions to the interaction energies as well as vibrational spectra of water clusters calculated with MB-pol are in excellent agreement with reference data obtained at the coupled cluster level. Several structural, thermodynamic, and dynamical properties of the liquid phase at atmospheric pressure are investigated through classical molecular dynamics simulations as a function of temperature. The structural properties of the liquid phase are in nearly quantitative agreement with X-ray diffraction data available over the temperature range from 268 to 368 K. The analysis of other thermodynamic and dynamical quantities emphasizes the importance of explicitly including nuclear quantum effects in the simulations, especially at low temperature, for a physically correct description of the properties of liquid water. Furthermore, both densities and lattice energies of several ice phases are also correctly reproduced by MB-pol. Following a recent study of DFT models for water, a score is assigned to each computed property, which demonstrates the high and, in many respects, unprecedented accuracy of MB-pol in representing all three phases of water.

  14. Perspective: Size selected clusters for catalysis and electrochemistry

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

    Halder, Avik; Curtiss, Larry A.; Fortunelli, Alessandro

    We report that size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this Perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition,more » cluster-support interactions and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modelling based on density functional theory sampling of local minima and energy barriers or ab initio Molecular Dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Lastly, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.« less

  15. Perspective: Size selected clusters for catalysis and electrochemistry

    DOE PAGES

    Halder, Avik; Curtiss, Larry A.; Fortunelli, Alessandro; ...

    2018-03-15

    We report that size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this Perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition,more » cluster-support interactions and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modelling based on density functional theory sampling of local minima and energy barriers or ab initio Molecular Dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Lastly, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.« less

  16. Perspective: Size selected clusters for catalysis and electrochemistry

    NASA Astrophysics Data System (ADS)

    Halder, Avik; Curtiss, Larry A.; Fortunelli, Alessandro; Vajda, Stefan

    2018-03-01

    Size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization, and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition, cluster-support interactions, and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modeling based on density functional theory sampling of local minima and energy barriers or ab initio molecular dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Finally, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.

  17. Dynamical Competition of IC-Industry Clustering from Taiwan to China

    NASA Astrophysics Data System (ADS)

    Tsai, Bi-Huei; Tsai, Kuo-Hui

    2009-08-01

    Most studies employ qualitative approach to explore the industrial clusters; however, few research has objectively quantified the evolutions of industry clustering. The purpose of this paper is to quantitatively analyze clustering among IC design, IC manufacturing as well as IC packaging and testing industries by using the foreign direct investment (FDI) data. The Lotka-Volterra system equations are first adopted here to capture the competition or cooperation among such three industries, thus explaining their clustering inclinations. The results indicate that the evolution of FDI into China for IC design industry significantly inspire the subsequent FDI of IC manufacturing as well as IC packaging and testing industries. Since IC design industry lie in the upstream stage of IC production, the middle-stream IC manufacturing and downstream IC packing and testing enterprises tend to cluster together with IC design firms, in order to sustain a steady business. Finally, Taiwan IC industry's FDI amount into China is predicted to cumulatively increase, which supports the industrial clustering tendency for Taiwan IC industry. Particularly, the FDI prediction of Lotka-Volterra model performs superior to that of the conventional Bass model after the forecast accuracy of these two models are compared. The prediction ability is dramatically improved as the industrial mutualism among each IC production stage is taken into account.

  18. A molecular dynamics study of water nucleation using the TIP4P/2005 model

    NASA Astrophysics Data System (ADS)

    Pérez, Alejandro; Rubio, Angel

    2011-12-01

    Extensive molecular dynamics simulations were conducted using the TIP4P/2005 water model of Abascal and Vega [J. Chem. Phys. 123, 234505 (2005)] to investigate its condensation from supersaturated vapor to liquid at 330 K. The mean first passage time method [J. Wedekind, R. Strey, and D. Reguera, J. Chem. Phys. 126, 134103 (2007); L. S. Bartell and D. T. Wu, 125, 194503 (2006)] was used to analyze the influence of finite size effects, thermostats, and charged species on the nucleation dynamics. We find that the Nosé-Hoover thermostat and the one proposed by Bussi et al. [J. Chem. Phys. 126, 014101 (2007)] give essentially the same averages. We identify the maximum thermostat coupling time to guarantee proper thermostating for these simulations. The presence of charged species has a dramatic impact on the dynamics, inducing a marked change towards a pure growth regime, which highlights the importance of ions in the formation of liquid droplets in the atmosphere. It was found a small but noticeable sign preference at intermediate cluster sizes (between 5 and 30 water molecules) corresponding mostly to the formation of the second solvation shell around the ion. The TIP4P/2005 water model predicts that anions induce faster formation of water clusters than cations of the same magnitude of charge.

  19. Spheroidal Populated Star Systems

    NASA Astrophysics Data System (ADS)

    Angeletti, Lucio; Giannone, Pietro

    2008-10-01

    Globular clusters and low-ellipticity early-type galaxies can be treated as systems populated by a large number of stars and whose structures can be schematized as spherically symmetric. Their studies profit from the synthesis of stellar populations. The computation of synthetic models makes use of various contributions from star evolution and stellar dynamics. In the first sections of the paper we present a short review of our results on the occurrence of galactic winds in star systems ranging from globular clusters to elliptical galaxies, and the dynamical evolution of a typical massive globular cluster. In the subsequent sections we describe our approach to the problem of the stellar populations in elliptical galaxies. The projected radial behaviours of spectro-photometric indices for a sample of eleven galaxies are compared with preliminary model results. The best agreement between observation and theory shows that our galaxies share a certain degree of heterogeneity. The gas energy dissipation varies from moderate to large, the metal yield ranges from solar to significantly oversolar, the dispersion of velocities is isotropic in most of the cases and anisotropic in the remaining instances.

  20. An Overview of the History of Cluster Conferences

    NASA Astrophysics Data System (ADS)

    Horiuchi, H.

    2017-06-01

    An overview is given on the historical development of the cluster conference series which started at Bohum in 1969. I start with the discussion of the philosophy of Karl Wildermuth and then I make a review on the main subjects and topics in cluster conferences. Since the cluster dynamics is a main nuclear dynamics together with the mean-field dynamics, we see that development of the cluster conference has been along with the rises of many new subjects in nuclear physics itself. Examples of them include superheavy nuclei, nuclear astrophysics, neutron-rich nuclei, cluster-gas states and ab initio calculations. Finally I discuss that more activities in and attention to cluster physics are seen in recent days.

  1. HIFLUGCS: X-ray luminosity-dynamical mass relation and its implications for mass calibrations with the SPIDERS and 4MOST surveys

    NASA Astrophysics Data System (ADS)

    Zhang, Yu-Ying; Reiprich, Thomas H.; Schneider, Peter; Clerc, Nicolas; Merloni, Andrea; Schwope, Axel; Borm, Katharina; Andernach, Heinz; Caretta, César A.; Wu, Xiang-Ping

    2017-03-01

    We present the relation of X-ray luminosity versus dynamical mass for 63 nearby clusters of galaxies in a flux-limited sample, the HIghest X-ray FLUx Galaxy Cluster Sample (HIFLUGCS, consisting of 64 clusters). The luminosity measurements are obtained based on 1.3 Ms of clean XMM-Newton data and ROSAT pointed observations. The masses are estimated using optical spectroscopic redshifts of 13647 cluster galaxies in total. We classify clusters into disturbed and undisturbed based on a combination of the X-ray luminosity concentration and the offset between the brightest cluster galaxy and X-ray flux-weighted center. Given sufficient numbers (I.e., ≥45) of member galaxies when the dynamical masses are computed, the luminosity versus mass relations agree between the disturbed and undisturbed clusters. The cool-core clusters still dominate the scatter in the luminosity versus mass relation even when a core-corrected X-ray luminosity is used, which indicates that the scatter of this scaling relation mainly reflects the structure formation history of the clusters. As shown by the clusters with only few spectroscopically confirmed members, the dynamical masses can be underestimated and thus lead to a biased scaling relation. To investigate the potential of spectroscopic surveys to follow up high-redshift galaxy clusters or groups observed in X-ray surveys for the identifications and mass calibrations, we carried out Monte Carlo resampling of the cluster galaxy redshifts and calibrated the uncertainties of the redshift and dynamical mass estimates when only reduced numbers of galaxy redshifts per cluster are available. The resampling considers the SPIDERS and 4MOST configurations, designed for the follow-up of the eROSITA clusters, and was carried out for each cluster in the sample at the actual cluster redshift as well as at the assigned input cluster redshifts of 0.2, 0.4, 0.6, and 0.8. To follow up very distant clusters or groups, we also carried out the mass calibration based on the resampling with only ten redshifts per cluster, and redshift calibration based on the resampling with only five and ten redshifts per cluster, respectively. Our results demonstrate the power of combining upcoming X-ray and optical spectroscopic surveys for mass calibration of clusters. The scatter in the dynamical mass estimates for the clusters with at least ten members is within 50%.

  2. Combining symmetry collective states with coupled-cluster theory: Lessons from the Agassi model Hamiltonian

    NASA Astrophysics Data System (ADS)

    Hermes, Matthew R.; Dukelsky, Jorge; Scuseria, Gustavo E.

    2017-06-01

    The failures of single-reference coupled-cluster theory for strongly correlated many-body systems is flagged at the mean-field level by the spontaneous breaking of one or more physical symmetries of the Hamiltonian. Restoring the symmetry of the mean-field determinant by projection reveals that coupled-cluster theory fails because it factorizes high-order excitation amplitudes incorrectly. However, symmetry-projected mean-field wave functions do not account sufficiently for dynamic (or weak) correlation. Here we pursue a merger of symmetry projection and coupled-cluster theory, following previous work along these lines that utilized the simple Lipkin model system as a test bed [J. Chem. Phys. 146, 054110 (2017), 10.1063/1.4974989]. We generalize the concept of a symmetry-projected mean-field wave function to the concept of a symmetry projected state, in which the factorization of high-order excitation amplitudes in terms of low-order ones is guided by symmetry projection and is not exponential, and combine them with coupled-cluster theory in order to model the ground state of the Agassi Hamiltonian. This model has two separate channels of correlation and two separate physical symmetries which are broken under strong correlation. We show how the combination of symmetry collective states and coupled-cluster theory is effective in obtaining correlation energies and order parameters of the Agassi model throughout its phase diagram.

  3. An improved fast multipole method for electrostatic potential calculations in a class of coarse-grained molecular simulations

    NASA Astrophysics Data System (ADS)

    Poursina, Mohammad; Anderson, Kurt S.

    2014-08-01

    This paper presents a novel algorithm to approximate the long-range electrostatic potential field in the Cartesian coordinates applicable to 3D coarse-grained simulations of biopolymers. In such models, coarse-grained clusters are formed via treating groups of atoms as rigid and/or flexible bodies connected together via kinematic joints. Therefore, multibody dynamic techniques are used to form and solve the equations of motion of such coarse-grained systems. In this article, the approximations for the potential fields due to the interaction between a highly negatively/positively charged pseudo-atom and charged particles, as well as the interaction between clusters of charged particles, are presented. These approximations are expressed in terms of physical and geometrical properties of the bodies such as the entire charge, the location of the center of charge, and the pseudo-inertia tensor about the center of charge of the clusters. Further, a novel substructuring scheme is introduced to implement the presented far-field potential evaluations in a binary tree framework as opposed to the existing quadtree and octree strategies of implementing fast multipole method. Using the presented Lagrangian grids, the electrostatic potential is recursively calculated via sweeping two passes: assembly and disassembly. In the assembly pass, adjacent charged bodies are combined together to form new clusters. Then, the potential field of each cluster due to its interaction with faraway resulting clusters is recursively calculated in the disassembly pass. The method is highly compatible with multibody dynamic schemes to model coarse-grained biopolymers. Since the proposed method takes advantage of constant physical and geometrical properties of rigid clusters, improvement in the overall computational cost is observed comparing to the tradition application of fast multipole method.

  4. Mass profile and dynamical status of the z ~ 0.8 galaxy cluster LCDCS 0504

    NASA Astrophysics Data System (ADS)

    Guennou, L.; Biviano, A.; Adami, C.; Limousin, M.; Lima Neto, G. B.; Mamon, G. A.; Ulmer, M. P.; Gavazzi, R.; Cypriano, E. S.; Durret, F.; Clowe, D.; LeBrun, V.; Allam, S.; Basa, S.; Benoist, C.; Cappi, A.; Halliday, C.; Ilbert, O.; Johnston, D.; Jullo, E.; Just, D.; Kubo, J. M.; Márquez, I.; Marshall, P.; Martinet, N.; Maurogordato, S.; Mazure, A.; Murphy, K. J.; Plana, H.; Rostagni, F.; Russeil, D.; Schirmer, M.; Schrabback, T.; Slezak, E.; Tucker, D.; Zaritsky, D.; Ziegler, B.

    2014-06-01

    Context. Constraints on the mass distribution in high-redshift clusters of galaxies are currently not very strong. Aims: We aim to constrain the mass profile, M(r), and dynamical status of the z ~ 0.8 LCDCS 0504 cluster of galaxies that is characterized by prominent giant gravitational arcs near its center. Methods: Our analysis is based on deep X-ray, optical, and infrared imaging as well as optical spectroscopy, collected with various instruments, which we complemented with archival data. We modeled the mass distribution of the cluster with three different mass density profiles, whose parameters were constrained by the strong lensing features of the inner cluster region, by the X-ray emission from the intracluster medium, and by the kinematics of 71 cluster members. Results: We obtain consistent M(r) determinations from three methods based on kinematics (dispersion-kurtosis, caustics, and MAMPOSSt), out to the cluster virial radius, ≃1.3 Mpc and beyond. The mass profile inferred by the strong lensing analysis in the central cluster region is slightly higher than, but still consistent with, the kinematics estimate. On the other hand, the X-ray based M(r) is significantly lower than the kinematics and strong lensing estimates. Theoretical predictions from ΛCDM cosmology for the concentration-mass relation agree with our observational results, when taking into account the uncertainties in the observational and theoretical estimates. There appears to be a central deficit in the intracluster gas mass fraction compared with nearby clusters. Conclusions: Despite the relaxed appearance of this cluster, the determinations of its mass profile by different probes show substantial discrepancies, the origin of which remains to be determined. The extension of a dynamical analysis similar to that of other clusters of the DAFT/FADA survey with multiwavelength data of sufficient quality will allow shedding light on the possible systematics that affect the determination of mass profiles of high-z clusters, which is possibly related to our incomplete understanding of intracluster baryon physics. Table 2 is available in electronic form at http://www.aanda.org

  5. Capturing the 3D Motion of an Infalling Galaxy via Fluid Dynamics

    NASA Astrophysics Data System (ADS)

    Su, Yuanyuan; Kraft, Ralph P.; Nulsen, Paul E. J.; Roediger, Elke; Forman, William R.; Churazov, Eugene; Randall, Scott W.; Jones, Christine; Machacek, Marie E.

    2017-01-01

    The Fornax Cluster is the nearest (≤slant 20 Mpc) galaxy cluster in the southern sky. NGC 1404 is a bright elliptical galaxy falling through the intracluster medium (ICM) of the Fornax Cluster. The sharp leading edge of NGC 1404 forms a classical “cold front” that separates 0.6 keV dense interstellar medium and 1.5 keV diffuse ICM. We measure the angular pressure variation along the cold front using a very deep (670 ks) Chandra X-ray observation. We are taking the classical approach—using stagnation pressure to determine a substructure’s speed—to the next level by not only deriving a general speed but also directionality, which yields the complete velocity field as well as the distance of the substructure directly from the pressure distribution. We find a hydrodynamic model consistent with the pressure jump along NGC 1404's atmosphere measured in multiple directions. The best-fit model gives an inclination of 33° and a Mach number of 1.3 for the infall of NGC 1404, in agreement with complementary measurements of the motion of NGC 1404. Our study demonstrates the successful treatment of a highly ionized ICM as ideal fluid flow, in support of the hypothesis that magnetic pressure is not dynamically important over most of the virial region of galaxy clusters.

  6. Homogeneous SPC/E water nucleation in large molecular dynamics simulations.

    PubMed

    Angélil, Raymond; Diemand, Jürg; Tanaka, Kyoko K; Tanaka, Hidekazu

    2015-08-14

    We perform direct large molecular dynamics simulations of homogeneous SPC/E water nucleation, using up to ∼ 4 ⋅ 10(6) molecules. Our large system sizes allow us to measure extremely low and accurate nucleation rates, down to ∼ 10(19) cm(-3) s(-1), helping close the gap between experimentally measured rates ∼ 10(17) cm(-3) s(-1). We are also able to precisely measure size distributions, sticking efficiencies, cluster temperatures, and cluster internal densities. We introduce a new functional form to implement the Yasuoka-Matsumoto nucleation rate measurement technique (threshold method). Comparison to nucleation models shows that classical nucleation theory over-estimates nucleation rates by a few orders of magnitude. The semi-phenomenological nucleation model does better, under-predicting rates by at worst a factor of 24. Unlike what has been observed in Lennard-Jones simulations, post-critical clusters have temperatures consistent with the run average temperature. Also, we observe that post-critical clusters have densities very slightly higher, ∼ 5%, than bulk liquid. We re-calibrate a Hale-type J vs. S scaling relation using both experimental and simulation data, finding remarkable consistency in over 30 orders of magnitude in the nucleation rate range and 180 K in the temperature range.

  7. Analytical Tools for Investigating and Modeling Agent-Based Systems

    DTIC Science & Technology

    2005-06-01

    of Black Holes Cluster 10 : Juan M. Maldacena (1924), Journal of High Energy Physics Field theory models for tachyon and gauge field string dy...namics; Super-Poincare Invariant Superstring Field The- ory; Level Four Approximation to the Tachyon Potential in Superstring Field Theory; SO(32) Spinors

  8. Investigation of nucleation kinetics in H2SO4 vapor through modeling of gas phase kinetics coupled with particle dynamics

    NASA Astrophysics Data System (ADS)

    Carlsson, Philip T. M.; Zeuch, Thomas

    2018-03-01

    We have developed a new model utilizing our existing kinetic gas phase models to simulate experimental particle size distributions emerging in dry supersaturated H2SO4 vapor homogeneously produced by rapid oxidation of SO2 through stabilized Criegee-Intermediates from 2-butene ozonolysis. We use a sectional method for simulating the particle dynamics. The particle treatment in the model is based on first principles and takes into account the transition from the kinetic to the diffusion-limited regime. It captures the temporal evolution of size distributions at the end of the ozonolysis experiment well, noting a slight underrepresentation of coagulation effects for larger particle sizes. The model correctly predicts the shape and the modes of the experimentally observed particle size distributions. The predicted modes show an extremely high sensitivity to the H2SO4 evaporation rates of the initially formed H2SO4 clusters (dimer to pentamer), which were arbitrarily restricted to decrease exponentially with increasing cluster size. In future, the analysis presented in this work can be extended to allow a direct validation of quantum chemically predicted stabilities of small H2SO4 clusters, which are believed to initiate a significant fraction of atmospheric new particle formation events. We discuss the prospects and possible limitations of the here presented approach.

  9. Predictive Multiple Model Switching Control with the Self-Organizing Map

    NASA Technical Reports Server (NTRS)

    Motter, Mark A.

    2000-01-01

    A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.

  10. Theoretical modeling of magnesium ion imprints in the Raman scattering of water.

    PubMed

    Kapitán, Josef; Dracínský, Martin; Kaminský, Jakub; Benda, Ladislav; Bour, Petr

    2010-03-18

    Hydration envelopes of metallic ions significantly influence their chemical properties and biological functioning. Previous computational studies, nuclear magnetic resonance (NMR), and vibrational spectra indicated a strong affinity of the Mg(2+) cation to water. We find it interesting that, although monatomic ions do not vibrate themselves, they cause notable changes in the water Raman signal. Therefore, in this study, we used a combination of Raman spectroscopy and computer modeling to analyze the magnesium hydration shell and origin of the signal. In the measured spectra of several salts (LiCl, NaCl, KCl, MgCl(2), CaCl(2), MgBr(2), and MgI(2) water solutions), only the spectroscopic imprint of the hydrated Mg(2+) cation could clearly be identified as an exceptionally distinct peak at approximately 355 cm(-1). The assignment of this band to the Mg-O stretching motion could be confirmed on the basis of several models involving quantum chemical computations on metal/water clusters. Minor Raman spectral features could also be explained. Ab initio and Fourier transform (FT) techniques coupled with the Car-Parrinello molecular dynamics were adapted to provide the spectra from dynamical trajectories. The results suggest that even in concentrated solutions magnesium preferentially forms a [Mg(H(2)O)(6)](2+) complex of a nearly octahedral symmetry; nevertheless, the Raman signal is primarily associated with the relatively strong metal-H(2)O bond. Partially covalent character of the Mg-O bond was confirmed by a natural bond orbital analysis. Computations on hydrated chlorine anion did not provide a specific signal. The FT techniques gave good spectral profiles in the high-frequency region, whereas the lowest-wavenumber vibrations were better reproduced by the cluster models. Both dynamical and cluster computational models provided a useful link between spectral shapes and specific ion-water interactions.

  11. Kinematics and dynamics of the MKW/AWM poor clusters

    NASA Technical Reports Server (NTRS)

    Beers, Timothy C.; Kriessler, Jeffrey R.; Bird, Christina M.; Huchra, John P.

    1995-01-01

    We report 472 new redshifts for 416 galaxies in the regions of the 23 poor clusters of galaxies originally identified by Morgan, Kayser, and White (MKW), and Albert, White, and Morgan (AWM). Eighteen of the poor clusters now have 10 or more available redshifts within 1.5/h Mpc of the central galaxy; 11 clusters have at least 20 available redshifts. Based on the 21 clusters for which we have sufficient velocity information, the median velocity scale is 336 km/s, a factor of 2 smaller than found for rich clusters. Several of the poor clusters exhibit complex velocity distributions due to the presence of nearby clumps of galaxies. We check on the velocity of the dominant galaxy in each poor cluster relative to the remaining cluster members. Significantly high relative velocities of the dominant galaxy are found in only 4 of 21 poor clusters, 3 of which we suspect are due to contamination of the parent velocity distribution. Several statistical tests indicate that the D/cD galaxies are at the kinematic centers of the parent poor cluster velocity distributions. Mass-to-light ratios for 13 of the 15 poor clusters for which we have the required data are in the range 50 less than or = M/L(sub B(0)) less than or = 200 solar mass/solar luminosity. The complex nature of the regions surrounding many of the poor clusters suggests that these groupings may represent an early epoch of cluster formation. For example, the poor clusters MKW7 and MKWS are shown to be gravitationally bound and likely to merge to form a richer cluster within the next several Gyrs. Eight of the nine other poor clusters for which simple two-body dynamical models can be carried out are consistent with being bound to other clumps in their vicinity. Additional complex systems with more than two gravitationally bound clumps are observed among the poor clusters.

  12. A Study Of Anomalous Stars and Binary Populations Within Open Clusters: Tests Of Theoretical Models

    NASA Astrophysics Data System (ADS)

    Geller, Aaron M.; Mathieu, Robert D.; Braden, Ella; Latham, David W.

    2008-08-01

    ``Anomalous'' stars, such as blue stragglers and more recently sub- subgiants, have been an enduring challenge for stellar evolution theory. Recently it has become clear that in star clusters these systems are closely linked to the binary star populations. Furthermore, through advances in N-body modeling, we have come to realize that stellar dynamical processes play a central role in the formation of such anomalous stars. Indeed, these stars trace the interface between the classical fields of stellar evolution and stellar dynamics. We propose a thesis study to directly probe this interface through high-precision radial-velocity measurements of the anomalous stars and the binary populations in four open clusters. We have selected NGC 188 (7 Gyr), M67 (NGC 2682; 4 Gyr), NGC 6819 (2.4 Gyr), and M35 (NGC 2168; 150 Myr), as these span a wide range in age, are rich enough to provide statistically significant conclusions, and already have an extensive base of kinematic, spectroscopic, and photometric observations from the WIYN Open Cluster Study. Our proposed observations will define the spectroscopic hard binary populations (fraction, frequency distributions of orbital parameters, mass ratios) for orbital periods approaching the hard-soft boundary. These observations will also provide a comprehensive survey for anomalous stars, including secure establishment of their cluster membership. These data will allow us to perform the first detailed comparison to predictions from open cluster simulations of the binary populations among normal and anomalous stars, and thereby to constrain the evolutionary paths from one to the other.

  13. A Study Of Anomalous Stars and Binary Populations Within Open Clusters: Tests Of Theoretical Models

    NASA Astrophysics Data System (ADS)

    Geller, Aaron M.; Mathieu, Robert D.; Gosnell, Natalie; Latham, David W.

    2009-02-01

    ``Anomalous'' stars, such as blue stragglers and more recently sub- subgiants, have been an enduring challenge for stellar evolution theory. Recently it has become clear that in star clusters these systems are closely linked to the binary star populations. Furthermore, through advances in N-body modeling, we have come to realize that stellar dynamical processes play a central role in the formation of such anomalous stars. Indeed, these stars trace the interface between the classical fields of stellar evolution and stellar dynamics. We propose a thesis study to directly probe this interface through high-precision radial-velocity measurements of the anomalous stars and the binary populations in four open clusters. We have selected NGC 188 (7 Gyr), M67 (NGC 2682; 4 Gyr), NGC 6819 (2.4 Gyr), and M35 (NGC 2168; 150 Myr), as these span a wide range in age, are rich enough to provide statistically significant conclusions, and already have an extensive base of kinematic, spectroscopic, and photometric observations from the WIYN Open Cluster Study. Our proposed observations will define the spectroscopic hard binary populations (fraction, frequency distributions of orbital parameters, mass ratios) for orbital periods approaching the hard-soft boundary. These observations will also provide a comprehensive survey for anomalous stars, including secure establishment of their cluster membership. These data will allow us to perform the first detailed comparison to predictions from open cluster simulations of the binary populations among normal and anomalous stars, and thereby to constrain the evolutionary paths from one to the other.

  14. A Study Of Anomalous Stars and Binary Populations Within Open Clusters: Tests Of Theoretical Models

    NASA Astrophysics Data System (ADS)

    Geller, Aaron M.; Mathieu, Robert D.; Braden, Ella; Latham, David W.

    2008-02-01

    ``Anomalous'' stars, such as blue stragglers and more recently sub- subgiants, have been an enduring challenge for stellar evolution theory. Recently it has become clear that in star clusters these systems are closely linked to the binary star populations. Furthermore, through advances in N-body modeling, we have come to realize that stellar dynamical processes play a central role in the formation of such anomalous stars. Indeed, these stars trace the interface between the classical fields of stellar evolution and stellar dynamics. We propose a thesis study to directly probe this interface through high-precision radial-velocity measurements of the anomalous stars and the binary populations in four open clusters. We have selected NGC 188 (7 Gyr), M67 (NGC 2682; 4 Gyr), NGC 6819 (2.4 Gyr), and M35 (NGC 2168; 150 Myr), as these span a wide range in age, are rich enough to provide statistically significant conclusions, and already have an extensive base of kinematic, spectroscopic, and photometric observations from the WIYN Open Cluster Study. Our proposed observations will define the spectroscopic hard binary populations (fraction, frequency distributions of orbital parameters, mass ratios) for orbital periods approaching the hard-soft boundary. These observations will also provide a comprehensive survey for anomalous stars, including secure establishment of their cluster membership. These data will allow us to perform the first detailed comparison to predictions from open cluster simulations of the binary populations among normal and anomalous stars, and thereby to constrain the evolutionary paths from one to the other.

  15. Pattern selection and super-patterns in the bounded confidence model

    DOE PAGES

    Ben-Naim, E.; Scheel, A.

    2015-10-26

    We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes ofmore » the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. Furthermore, the spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.« less

  16. Visualization of T Cell-Regulated Monocyte Clusters Mediating Keratinocyte Death in Acquired Cutaneous Immunity.

    PubMed

    Liu, Zheng; Yang, Fei; Zheng, Hao; Fan, Zhan; Qiao, Sha; Liu, Lei; Tao, Juan; Luo, Qingming; Zhang, Zhihong

    2018-06-01

    It remains unclear how monocytes are mobilized to amplify inflammatory reactions in T cell-mediated adaptive immunity. Here, we investigate dynamic cellular events in the cascade of inflammatory responses through intravital imaging of a multicolor-labeled murine contact hypersensitivity model. We found that monocytes formed clusters around hair follicles in the contact hypersensitivity model. In this process, effector T cells encountered dendritic cells under regions of monocyte clusters and secreted IFN-γ, which mobilizes CCR2-dependent monocyte interstitial migration and CXCR2-dependent monocyte cluster formation. We showed that hair follicles shaped the inflammatory microenvironment for communication among the monocytes, keratinocytes, and effector T cells. After disrupting the T cell-mobilized monocyte clusters through CXCR2 antagonization, monocyte activation and keratinocyte apoptosis were significantly inhibited. Our study provides a new perspective on effector T cell-regulated monocyte behavior, which amplifies the inflammatory reaction in acquired cutaneous immunity. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Pattern selection and super-patterns in the bounded confidence model

    NASA Astrophysics Data System (ADS)

    Ben-Naim, E.; Scheel, A.

    2015-10-01

    We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.

  18. Formation and emission mechanisms of Ag nanoclusters in the Ar matrix assembly cluster source

    NASA Astrophysics Data System (ADS)

    Zhao, Junlei; Cao, Lu; Palmer, Richard E.; Nordlund, Kai; Djurabekova, Flyura

    2017-11-01

    In this paper, we study the mechanisms of growth of Ag nanoclusters in a solid Ar matrix and the emission of these nanoclusters from the matrix by a combination of experimental and theoretical methods. The molecular dynamics simulations show that the cluster growth mechanism can be described as "thermal spike-enhanced clustering" in multiple sequential ion impact events. We further show that experimentally observed large sputtered metal clusters cannot be formed by direct sputtering of Ag mixed in the Ar. Instead, we describe the mechanism of emission of the metal nanocluster that, at first, is formed in the cryogenic matrix due to multiple ion impacts, and then is emitted as a result of the simultaneous effects of interface boiling and spring force. We also develop an analytical model describing this size-dependent cluster emission. The model bridges the atomistic simulations and experimental time and length scales, and allows increasing the controllability of fast generation of nanoclusters in experiments with a high production rate.

  19. Explicitly Representing the Solvation Shell in Continuum Solvent Calculations

    PubMed Central

    Svendsen, Hallvard F.; Merz, Kenneth M.

    2009-01-01

    A method is presented to explicitly represent the first solvation shell in continuum solvation calculations. Initial solvation shell geometries were generated with classical molecular dynamics simulations. Clusters consisting of solute and 5 solvent molecules were fully relaxed in quantum mechanical calculations. The free energy of solvation of the solute was calculated from the free energy of formation of the cluster and the solvation free energy of the cluster calculated with continuum solvation models. The method has been implemented with two continuum solvation models, a Poisson-Boltzmann model and the IEF-PCM model. Calculations were carried out for a set of 60 ionic species. Implemented with the Poisson-Boltzmann model the method gave an unsigned average error of 2.1 kcal/mol and a RMSD of 2.6 kcal/mol for anions, for cations the unsigned average error was 2.8 kcal/mol and the RMSD 3.9 kcal/mol. Similar results were obtained with the IEF-PCM model. PMID:19425558

  20. Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism

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

    Li, Zhen; Bian, Xin; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu

    2015-12-28

    The Mori-Zwanzig formalism for coarse-graining a complex dynamical system typically introduces memory effects. The Markovian assumption of delta-correlated fluctuating forces is often employed to simplify the formulation of coarse-grained (CG) models and numerical implementations. However, when the time scales of a system are not clearly separated, the memory effects become strong and the Markovian assumption becomes inaccurate. To this end, we incorporate memory effects into CG modeling by preserving non-Markovian interactions between CG variables, and the memory kernel is evaluated directly from microscopic dynamics. For a specific example, molecular dynamics (MD) simulations of star polymer melts are performed while themore » corresponding CG system is defined by grouping many bonded atoms into single clusters. Then, the effective interactions between CG clusters as well as the memory kernel are obtained from the MD simulations. The constructed CG force field with a memory kernel leads to a non-Markovian dissipative particle dynamics (NM-DPD). Quantitative comparisons between the CG models with Markovian and non-Markovian approximations indicate that including the memory effects using NM-DPD yields similar results as the Markovian-based DPD if the system has clear time scale separation. However, for systems with small separation of time scales, NM-DPD can reproduce correct short-time properties that are related to how the system responds to high-frequency disturbances, which cannot be captured by the Markovian-based DPD model.« less

  1. 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.

  2. The Evolution of the Globular Cluster System in a Triaxial Galaxy: Can a Galactic Nucleus Form by Globular Cluster Capture?

    NASA Astrophysics Data System (ADS)

    Capuzzo-Dolcetta, Roberto

    1993-10-01

    Among the possible phenomena inducing evolution of the globular cluster system in an elliptical galaxy, dynamical friction due to field stars and tidal disruption caused by a central nucleus is of crucial importance. The aim of this paper is the study of the evolution of the globular cluster system in a triaxial galaxy in the presence of these phenomena. In particular, the possibility is examined that some galactic nuclei have been formed by frictionally decayed globular clusters moving in a triaxial potential. We find that the initial rapid growth of the nucleus, due mainly to massive clusters on box orbits falling in a short time scale into the galactic center, is later slowed by tidal disruption induced by the nucleus itself on less massive clusters in the way described by Ostriker, Binney, and Saha. The efficiency of dynamical friction is such to carry to the center of the galaxy enough globular cluster mass available to form a compact nucleus, but the actual modes and results of cluster-cluster encounters in the central potential well are complicated phenomena which remains to be investigated. The mass of the resulting nucleus is determined by the mutual feedback of the described processes, together with the initial spatial, velocity, and mass distributions of the globular cluster family. The effect on the system mass function is studied, showing the development of a low- and high-mass turnover even with an initially flat mass function. Moreover, in this paper is discussed the possibility that the globular cluster fall to the galactic center has been a cause of primordial violent galactic activity. An application of the model to M31 is presented.

  3. Differential dynamic microscopy of weakly scattering and polydisperse protein-rich clusters

    NASA Astrophysics Data System (ADS)

    Safari, Mohammad S.; Vorontsova, Maria A.; Poling-Skutvik, Ryan; Vekilov, Peter G.; Conrad, Jacinta C.

    2015-10-01

    Nanoparticle dynamics impact a wide range of biological transport processes and applications in nanomedicine and natural resource engineering. Differential dynamic microscopy (DDM) was recently developed to quantify the dynamics of submicron particles in solutions from fluctuations of intensity in optical micrographs. Differential dynamic microscopy is well established for monodisperse particle populations, but has not been applied to solutions containing weakly scattering polydisperse biological nanoparticles. Here we use bright-field DDM (BDDM) to measure the dynamics of protein-rich liquid clusters, whose size ranges from tens to hundreds of nanometers and whose total volume fraction is less than 10-5. With solutions of two proteins, hemoglobin A and lysozyme, we evaluate the cluster diffusion coefficients from the dependence of the diffusive relaxation time on the scattering wave vector. We establish that for weakly scattering populations, an optimal thickness of the sample chamber exists at which the BDDM signal is maximized at the smallest sample volume. The average cluster diffusion coefficient measured using BDDM is consistently lower than that obtained from dynamic light scattering at a scattering angle of 90∘. This apparent discrepancy is due to Mie scattering from the polydisperse cluster population, in which larger clusters preferentially scatter more light in the forward direction.

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

    PubMed

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

    2014-09-01

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

  5. Starburst clusters in the Galactic center

    NASA Astrophysics Data System (ADS)

    Habibi, Maryam

    2014-09-01

    The central region of the Galaxy is the most active site of star formation in the Milky Way, where massive stars have formed very recently and are still forming today. The rich population of massive stars in the Galactic center provide a unique opportunity to study massive stars in their birth environment and probe their initial mass function, which is the spectrum of stellar masses at their birth. The Arches cluster is the youngest among the three massive clusters in the Galactic center, providing a collection of high-mass stars and a very dense core which makes this cluster an excellent site to address questions about massive star formation, the stellar mass function and the dynamical evolution of massive clusters in the Galactic center. In this thesis, I perform an observational study of the Arches cluster using K_{s}-band imaging obtained with NAOS/CONICA at the VLT combined with Subaru/Cisco J-band data to gain a full understanding of the cluster mass distribution out to its tidal radius for the first time. Since the light from the Galactic center reaches us through the Galactic disc, the extinction correction is crucial when studying this region. I use a Bayesian method to construct a realistic extinction map of the cluster. It is shown in this study that the determination of the mass of the most massive star in the Arches cluster, which had been used in previous studies to establish an upper mass limit for the star formation process in the Milky Way, strongly depends on the assumed slope of the extinction law. Assuming the two regimes of widely used infrared extinction laws, I show that the difference can reach up to 30% for individually derived stellar masses and Δ A_{Ks}˜ 1 magnitude in acquired K_{s}-band extinction, while the present-day mass function slope changes by ˜ 0.17 dex. The present-day mass function slope derived assuming the more recent extinction law, which suggests a steeper wavelength dependence for the infrared extinction law, reveals an overpopulation of massive stars in the core (r<0.2 pc) with a flat slope of α_{Nishi}=-1.50 ±0.35 in comparison to the Salpeter slope of α=-2.3. The slope of the mass function increases to α_{Nishi}=-2.21 ±0.27 in the intermediate annulus (0.2

  6. Inferring HIV-1 Transmission Dynamics in Germany From Recently Transmitted Viruses.

    PubMed

    Pouran Yousef, Kaveh; Meixenberger, Karolin; Smith, Maureen R; Somogyi, Sybille; Gromöller, Silvana; Schmidt, Daniel; Gunsenheimer-Bartmeyer, Barbara; Hamouda, Osamah; Kücherer, Claudia; von Kleist, Max

    2016-11-01

    Although HIV continues to spread globally, novel intervention strategies such as treatment as prevention (TasP) may bring the epidemic to a halt. However, their effective implementation requires a profound understanding of the underlying transmission dynamics. We analyzed parameters of the German HIV epidemic based on phylogenetic clustering of viral sequences from recently infected seroconverters with known infection dates. Viral baseline and follow-up pol sequences (n = 1943) from 1159 drug-naïve individuals were selected from a nationwide long-term observational study initiated in 1997. Putative transmission clusters were computed based on a maximum likelihood phylogeny. Using individual follow-up sequences, we optimized our clustering threshold to maximize the likelihood of co-clustering individuals connected by direct transmission. The sizes of putative transmission clusters scaled inversely with their abundance and their distribution exhibited a heavy tail. Clusters based on the optimal clustering threshold were significantly more likely to contain members of the same or bordering German federal states. Interinfection times between co-clustered individuals were significantly shorter (26 weeks; interquartile range: 13-83) than in a null model. Viral intraindividual evolution may be used to select criteria that maximize co-clustering of transmission pairs in the absence of strong adaptive selection pressure. Interinfection times of co-clustered individuals may then be an indicator of the typical time to onward transmission. Our analysis suggests that onward transmission may have occurred early after infection, when individuals are typically unaware of their serological status. The latter argues that TasP should be combined with HIV testing campaigns to reduce the possibility of transmission before TasP initiation.

  7. Tropical forest carbon balance: effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass

    NASA Astrophysics Data System (ADS)

    Di Vittorio, Alan V.; Negrón-Juárez, Robinson I.; Higuchi, Niro; Chambers, Jeffrey Q.

    2014-03-01

    Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949-54) reported that Central Amazon plots missed 9-17% of tree mortality, and here we address ‘why’ by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies.

  8. Requirements for efficient cell-type proportioning: regulatory timescales, stochasticity and lateral inhibition

    NASA Astrophysics Data System (ADS)

    Pfeuty, B.; Kaneko, K.

    2016-04-01

    The proper functioning of multicellular organisms requires the robust establishment of precise proportions between distinct cell types. This developmental differentiation process typically involves intracellular regulatory and stochastic mechanisms to generate cell-fate diversity as well as intercellular signaling mechanisms to coordinate cell-fate decisions at tissue level. We thus surmise that key insights about the developmental regulation of cell-type proportion can be captured by the modeling study of clustering dynamics in population of inhibitory-coupled noisy bistable systems. This general class of dynamical system is shown to exhibit a very stable two-cluster state, but also metastability, collective oscillations or noise-induced state hopping, which can prevent from timely and reliably reaching a robust and well-proportioned clustered state. To circumvent these obstacles or to avoid fine-tuning, we highlight a general strategy based on dual-time positive feedback loops, such as mediated through transcriptional versus epigenetic mechanisms, which improves proportion regulation by coordinating early and flexible lineage priming with late and firm commitment. This result sheds new light on the respective and cooperative roles of multiple regulatory feedback, stochasticity and lateral inhibition in developmental dynamics.

  9. Measurement of high-dynamic range x-ray Thomson scattering spectra for the characterization of nano-plasmas at LCLS

    DOE PAGES

    MacDonald, M. J.; Gorkhover, T.; Bachmann, B.; ...

    2016-08-08

    Atomic clusters can serve as ideal model systems for exploring ultrafast (~100 fs) laser-driven ionization dynamics of dense matter on the nanometer scale. Resonant absorption of optical laser pulses enables heating to temperatures on the order of 1 keV at near solid density conditions. To date, direct probing of transient states of such nano plasmas was limited to coherent x-ray imaging. Here we present the first measurement of spectrally-resolved incoherent x-ray scattering from clusters, enabling measurements of transient temperature, densities and ionization. Single shot x-ray Thomson scatterings signals were recorded at 120 Hz using a crystal spectrometer in combination withmore » a single-photon counting and energy-dispersive pnCCD. A precise pump laser collimation scheme enabled recording near background-free scattering spectra from Ar clusters with an unprecedented dynamic range of more than 3 orders of magnitude. As a result, such measurements are important for understanding collective effects in laser-matter interactions on femtosecond timescales, opening new routes for the development of schemes for their ultrafast control.« less

  10. Measurement of high-dynamic range x-ray Thomson scattering spectra for the characterization of nano-plasmas at LCLS

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

    MacDonald, M. J., E-mail: macdonm@umich.edu; SLAC National Accelerator Laboratory, Menlo Park, California 94025; Gorkhover, T.

    2016-11-15

    Atomic clusters can serve as ideal model systems for exploring ultrafast (∼100 fs) laser-driven ionization dynamics of dense matter on the nanometer scale. Resonant absorption of optical laser pulses enables heating to temperatures on the order of 1 keV at near solid density conditions. To date, direct probing of transient states of such nano-plasmas was limited to coherent x-ray imaging. Here we present the first measurement of spectrally resolved incoherent x-ray scattering from clusters, enabling measurements of transient temperature, densities, and ionization. Single shot x-ray Thomson scattering signals were recorded at 120 Hz using a crystal spectrometer in combination withmore » a single-photon counting and energy-dispersive pnCCD. A precise pump laser collimation scheme enabled recording near background-free scattering spectra from Ar clusters with an unprecedented dynamic range of more than 3 orders of magnitude. Such measurements are important for understanding collective effects in laser-matter interactions on femtosecond time scales, opening new routes for the development of schemes for their ultrafast control.« less

  11. Molecular dynamics simulations of the surface tension and structure of salt solutions and clusters.

    PubMed

    Sun, Lu; Li, Xin; Hede, Thomas; Tu, Yaoquan; Leck, Caroline; Ågren, Hans

    2012-03-15

    Sodium halides, which are abundant in sea salt aerosols, affect the optical properties of aerosols and are active in heterogeneous reactions that cause ozone depletion and acid rain problems. Interfacial properties, including surface tension and halide anion distributions, are crucial issues in the study of the aerosols. We present results from molecular dynamics simulations of water solutions and clusters containing sodium halides with the interatomic interactions described by a conventional force field. The simulations reproduce experimental observations that sodium halides increase the surface tension with respect to pure water and that iodide anions reach the outermost layer of water clusters or solutions. It is found that the van der Waals interactions have an impact on the distribution of the halide anions and that a conventional force field with optimized parameters can model the surface tension of the salt solutions with reasonable accuracy. © 2012 American Chemical Society

  12. Cooling rate dependence of structural order in Al 90Sm 10 metallic glass

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

    Sun, Yang; Zhang, Yue; Zhang, Feng

    2016-07-07

    Here, the atomic structure of Al 90Sm 10 metallic glass is studied using molecular dynamics simulations. By performing a long sub-T g annealing, we developed a glass model closer to the experiments than the models prepared by continuous cooling. Using the cluster alignment method, we found that “3661” cluster is the dominating short-range order in the glass samples. The connection and arrangement of “3661” clusters, which define the medium-range order in the system, are enhanced significantly in the sub-T g annealed sample as compared with the fast cooled glass samples. Unlike some strong binary glass formers such as Cu 64.5Zrmore » 35.5, the clusters representing the short-range order do not form an interconnected interpenetrating network in Al 90Sm 10, which has only marginal glass formability.« less

  13. Cooling rate dependence of structural order in Al{sub 90}Sm{sub 10} metallic glass

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

    Sun, Yang; Ames Laboratory, US Department of Energy, Ames, Iowa 50011; Zhang, Yue

    2016-07-07

    The atomic structure of Al{sub 90}Sm{sub 10} metallic glass is studied using molecular dynamics simulations. By performing a long sub-T{sub g} annealing, we developed a glass model closer to the experiments than the models prepared by continuous cooling. Using the cluster alignment method, we found that “3661” cluster is the dominating short-range order in the glass samples. The connection and arrangement of “3661” clusters, which define the medium-range order in the system, are enhanced significantly in the sub-T{sub g} annealed sample as compared with the fast cooled glass samples. Unlike some strong binary glass formers such as Cu{sub 64.5}Zr{sub 35.5},more » the clusters representing the short-range order do not form an interconnected interpenetrating network in Al{sub 90}Sm{sub 10,} which has only marginal glass formability.« less

  14. Different mechanisms of cluster explosion within a unified smooth particle hydrodynamics Thomas-Fermi approach: Optical and short-wavelength regimes compared

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

    Rusek, Marian; Orlowski, Arkadiusz

    2005-04-01

    The dynamics of small ({<=}55 atoms) argon clusters ionized by an intense femtosecond laser pulse is studied using a time-dependent Thomas-Fermi model. The resulting Bloch-like hydrodynamic equations are solved numerically using the smooth particle hydrodynamics method without the necessity of grid simulations. As follows from recent experiments, absorption of radiation and subsequent ionization of clusters observed in the short-wavelength laser frequency regime (98 nm) differs considerably from that in the optical spectral range (800 nm). Our theoretical approach provides a unified framework for treating these very different frequency regimes and allows for a deeper understanding of the underlying cluster explosionmore » mechanisms. The results of our analysis following from extensive numerical simulations presented in this paper are compared both with experimental findings and with predictions of other theoretical models.« less

  15. Bayesian nonparametric clustering in phylogenetics: modeling antigenic evolution in influenza.

    PubMed

    Cybis, Gabriela B; Sinsheimer, Janet S; Bedford, Trevor; Rambaut, Andrew; Lemey, Philippe; Suchard, Marc A

    2018-01-30

    Influenza is responsible for up to 500,000 deaths every year, and antigenic variability represents much of its epidemiological burden. To visualize antigenic differences across many viral strains, antigenic cartography methods use multidimensional scaling on binding assay data to map influenza antigenicity onto a low-dimensional space. Analysis of such assay data ideally leads to natural clustering of influenza strains of similar antigenicity that correlate with sequence evolution. To understand the dynamics of these antigenic groups, we present a framework that jointly models genetic and antigenic evolution by combining multidimensional scaling of binding assay data, Bayesian phylogenetic machinery and nonparametric clustering methods. We propose a phylogenetic Chinese restaurant process that extends the current process to incorporate the phylogenetic dependency structure between strains in the modeling of antigenic clusters. With this method, we are able to use the genetic information to better understand the evolution of antigenicity throughout epidemics, as shown in applications of this model to H1N1 influenza. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  16. Structure and Dynamics of Ionic Block Copolymer Melts: Computational Study

    DOE PAGES

    Aryal, Dipak; Agrawal, Anupriya; Perahia, Dvora; ...

    2017-09-06

    Structure and dynamics of melts of copolymers with an ABCBA topology, where C is an ionizable block, have been studied by fully atomistic molecular dynamics (MD) simulations. Introducing an ionizable block for functionality adds a significant element to the coupled set of interactions that determine the structure and dynamics of the macromolecule. The polymer consists of a randomly sulfonated polystyrene C block tethered to a flexible poly(ethylene-r-propylene) bridge B and end-capped with poly(tert-butylstyrene) A. The chemical structure and topology of these polymers constitute a model for incorporation of ionic blocks within a framework that provides tactility and mechanical stability. Heremore » in this paper we resolve the structure and dynamics of a structured polymer on the nanoscale constrained by ionic clusters. We find that the melts form intertwined networks of the A and C blocks independent of the degree of sulfonation of the C block with no long-range order. The cluster cohesiveness and morphology affect both macroscopic translational motion and segmental dynamics of all the blocks.« less

  17. Structure and Dynamics of Ionic Block Copolymer Melts: Computational Study

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

    Aryal, Dipak; Agrawal, Anupriya; Perahia, Dvora

    Structure and dynamics of melts of copolymers with an ABCBA topology, where C is an ionizable block, have been studied by fully atomistic molecular dynamics (MD) simulations. Introducing an ionizable block for functionality adds a significant element to the coupled set of interactions that determine the structure and dynamics of the macromolecule. The polymer consists of a randomly sulfonated polystyrene C block tethered to a flexible poly(ethylene-r-propylene) bridge B and end-capped with poly(tert-butylstyrene) A. The chemical structure and topology of these polymers constitute a model for incorporation of ionic blocks within a framework that provides tactility and mechanical stability. Heremore » in this paper we resolve the structure and dynamics of a structured polymer on the nanoscale constrained by ionic clusters. We find that the melts form intertwined networks of the A and C blocks independent of the degree of sulfonation of the C block with no long-range order. The cluster cohesiveness and morphology affect both macroscopic translational motion and segmental dynamics of all the blocks.« less

  18. Clustering effects in ionic polymers: Molecular dynamics simulations.

    PubMed

    Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S

    2015-08-01

    Ionic clusters control the structure, dynamics, and transport in soft matter. Incorporating a small fraction of ionizable groups in polymers substantially reduces the mobility of the macromolecules in melts. These ionic groups often associate into random clusters in melts, where the distribution and morphology of the clusters impact the transport in these materials. Here, using molecular dynamic simulations we demonstrate a clear correlation between cluster size and morphology with the polymer mobility in melts of sulfonated polystyrene. We show that in low dielectric media ladderlike clusters that are lower in energy compared with spherical assemblies are formed. Reducing the electrostatic interactions by enhancing the dielectric constant leads to morphological transformation from ladderlike clusters to globular assemblies. Decrease in electrostatic interaction significantly enhances the mobility of the polymer.

  19. An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

    PubMed Central

    Mustapha, Ibrahim; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A.; Sali, Aduwati; Mohamad, Hafizal

    2015-01-01

    It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach. PMID:26287191

  20. An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

    PubMed

    Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

    2015-08-13

    It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

  1. Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

    NASA Astrophysics Data System (ADS)

    Chen, Yu-Zhong; Lai, Ying-Cheng

    2018-03-01

    Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

  2. Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics.

    PubMed

    Chen, Yu-Zhong; Lai, Ying-Cheng

    2018-03-01

    Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

  3. Parallel FEM Simulation of Electromechanics in the Heart

    NASA Astrophysics Data System (ADS)

    Xia, Henian; Wong, Kwai; Zhao, Xiaopeng

    2011-11-01

    Cardiovascular disease is the leading cause of death in America. Computer simulation of complicated dynamics of the heart could provide valuable quantitative guidance for diagnosis and treatment of heart problems. In this paper, we present an integrated numerical model which encompasses the interaction of cardiac electrophysiology, electromechanics, and mechanoelectrical feedback. The model is solved by finite element method on a Linux cluster and the Cray XT5 supercomputer, kraken. Dynamical influences between the effects of electromechanics coupling and mechanic-electric feedback are shown.

  4. Inferring time-varying network topologies from gene expression data.

    PubMed

    Rao, Arvind; Hero, Alfred O; States, David J; Engel, James Douglas

    2007-01-01

    Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.

  5. Dynamic gene expression analysis in a H1N1 influenza virus mouse pneumonia model.

    PubMed

    Bao, Yanyan; Gao, Yingjie; Shi, Yujing; Cui, Xiaolan

    2017-06-01

    H1N1, a major pathogenic subtype of influenza A virus, causes a respiratory infection in humans and livestock that can range from a mild infection to more severe pneumonia associated with acute respiratory distress syndrome. Understanding the dynamic changes in the genome and the related functional changes induced by H1N1 influenza virus infection is essential to elucidating the pathogenesis of this virus and thereby determining strategies to prevent future outbreaks. In this study, we filtered the significantly expressed genes in mouse pneumonia using mRNA microarray analysis. Using STC analysis, seven significant gene clusters were revealed, and using STC-GO analysis, we explored the significant functions of these seven gene clusters. The results revealed GOs related to H1N1 virus-induced inflammatory and immune functions, including innate immune response, inflammatory response, specific immune response, and cellular response to interferon-beta. Furthermore, the dynamic regulation relationships of the key genes in mouse pneumonia were revealed by dynamic gene network analysis, and the most important genes were filtered, including Dhx58, Cxcl10, Cxcl11, Zbp1, Ifit1, Ifih1, Trim25, Mx2, Oas2, Cd274, Irgm1, and Irf7. These results suggested that during mouse pneumonia, changes in the expression of gene clusters and the complex interactions among genes lead to significant changes in function. Dynamic gene expression analysis revealed key genes that performed important functions. These results are a prelude to advancements in mouse H1N1 influenza virus infection biology, as well as the use of mice as a model organism for human H1N1 influenza virus infection studies.

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

    Morscher, Meagan; Pattabiraman, Bharath; Rodriguez, Carl

    Our current understanding of the stellar initial mass function and massive star evolution suggests that young globular clusters (GCs) may have formed hundreds to thousands of stellar-mass black holes (BHs), the remnants of stars with initial masses from ∼20-100 M {sub ☉}. Birth kicks from supernova explosions may eject some BHs from their birth clusters, but most should be retained. Using a Monte Carlo method we investigate the long-term dynamical evolution of GCs containing large numbers of stellar BHs. We describe numerical results for 42 models, covering a broad range of realistic initial conditions, including up to 1.6 × 10{supmore » 6} stars. In almost all models we find that significant numbers of BHs (up to ∼10{sup 3}) are retained all the way to the present. This is in contrast to previous theoretical expectations that most BHs should be ejected dynamically within a few gigayears The main reason for this difference is that core collapse driven by BHs (through the Spitzer {sup m}ass segregation instability{sup )} is easily reverted through three-body processes, and involves only a small number of the most massive BHs, while lower-mass BHs remain well-mixed with ordinary stars far from the central cusp. Thus the rapid segregation of stellar BHs does not lead to a long-term physical separation of most BHs into a dynamically decoupled inner core, as often assumed previously. Combined with the recent detections of several BH X-ray binary candidates in Galactic GCs, our results suggest that stellar BHs could still be present in large numbers in many GCs today, and that they may play a significant role in shaping the long-term dynamical evolution and the present-day dynamical structure of many clusters.« less

  7. Luminosity segregation in galaxy clusters as an indication of dynamical evolution

    NASA Technical Reports Server (NTRS)

    Baier, F. W.; Schmidt, K.-H.

    1993-01-01

    Theoretical models describing the dynamical evolution of self-gravitating systems predict a spatial mass segregation for more evolved systems, with the more massive objects concentrated toward the center of the configuration. From the observational point of view, however, the existence of mass segregation in galaxy clusters seems to be a matter of controversy. A special problem in this connection is the formation of cD galaxies in the centers of galaxy clusters. The most promising scenarios of their formation are galaxy cannibalism (merger scenario) and growing by cooling flows. It seems to be plausible to consider the swallowing of smaller systems by a dominant galaxy as an important process in the evolution of a cD galaxy. The stage of the evolution of the dominant galaxy should be reflected by the surrounding galaxy population, especially by possible mass segregation effects. Assuming that mass segregation is tantamount to luminosity segregation we analyzed luminosity segregation in roughly 40 cD galaxy clusters. Obviously there are three different groups of clusters: (1) clusters with luminosity segregation, (2) clusters without luminosity segregation, and (3) such objects exhibiting a phenomenon which we call antisegregation in luminosity, i.e. a deficiency of bright galaxies in the central regions of clusters. This result is interpreted in the sense of different degrees of mass segregation and as an indication for different evolution stages of these clusters. The clusters are arranged in the three segregation classes 2, 1, and 0 (S2 = strong mass segregation, S1 = moderate mass segregation, S0 = weak or absent mass segregation). We assume that a galaxy cluster starts its dynamical evolution after virialization without any radial mass segregation. Energy exchange during encounters of cluster members as well as merger processes between cluster galaxies lead to an increasing radial mass segregation in the cluster (S1). If a certain degree of segregation (S2) has been established, an essential number of slow-moving and relative massive cluster members in the center will be cannibalized by the initial brightest cluster galaxy. This process should lead to the growing of the predominate galaxy, which is accompanied by a diminution of the mass segregation (transition to S1 and S0, respectively) in the neighborhood of the central very massive galaxy. An increase of the areal density of brighter galaxies towards the outer cluster regions (antisegregation of luminosity), i.e. an extreme low degree of mass segregation was estimated for a substantial percentage of cD clusters. This result favors the cannibalism scenario for the formation of cD galaxies.

  8. Quantum cluster variational method and message passing algorithms revisited

    NASA Astrophysics Data System (ADS)

    Domínguez, E.; Mulet, Roberto

    2018-02-01

    We present a general framework to study quantum disordered systems in the context of the Kikuchi's cluster variational method (CVM). The method relies in the solution of message passing-like equations for single instances or in the iterative solution of complex population dynamic algorithms for an average case scenario. We first show how a standard application of the Kikuchi's CVM can be easily translated to message passing equations for specific instances of the disordered system. We then present an "ad hoc" extension of these equations to a population dynamic algorithm representing an average case scenario. At the Bethe level, these equations are equivalent to the dynamic population equations that can be derived from a proper cavity ansatz. However, at the plaquette approximation, the interpretation is more subtle and we discuss it taking also into account previous results in classical disordered models. Moreover, we develop a formalism to properly deal with the average case scenario using a replica-symmetric ansatz within this CVM for quantum disordered systems. Finally, we present and discuss numerical solutions of the different approximations for the quantum transverse Ising model and the quantum random field Ising model in two-dimensional lattices.

  9. Vapor condensation onto a non-volatile liquid drop

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

    Inci, Levent; Bowles, Richard K., E-mail: richard.bowles@usask.ca

    2013-12-07

    Molecular dynamics simulations of miscible and partially miscible binary Lennard–Jones mixtures are used to study the dynamics and thermodynamics of vapor condensation onto a non-volatile liquid drop in the canonical ensemble. When the system volume is large, the driving force for condensation is low and only a submonolayer of the solvent is adsorbed onto the liquid drop. A small degree of mixing of the solvent phase into the core of the particles occurs for the miscible system. At smaller volumes, complete film formation is observed and the dynamics of film growth are dominated by cluster-cluster coalescence. Mixing into the coremore » of the droplet is also observed for partially miscible systems below an onset volume suggesting the presence of a solubility transition. We also develop a non-volatile liquid drop model, based on the capillarity approximations, that exhibits a solubility transition between small and large drops for partially miscible mixtures and has a hysteresis loop similar to the one observed in the deliquescence of small soluble salt particles. The properties of the model are compared to our simulation results and the model is used to study the formulation of classical nucleation theory for systems with low free energy barriers.« less

  10. Ferromagnetic clusters induced by a nonmagnetic random disorder in diluted magnetic semiconductors

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

    Bui, Dinh-Hoi; Physics Department, Hue University’s College of Education, 34 Le Loi, Hue; Phan, Van-Nham, E-mail: phanvannham@dtu.edu.vn

    In this work, we analyze the nonmagnetic random disorder leading to a formation of ferromagnetic clusters in diluted magnetic semiconductors. The nonmagnetic random disorder arises from randomness in the host lattice. Including the disorder to the Kondo lattice model with random distribution of magnetic dopants, the ferromagnetic–paramagnetic transition in the system is investigated in the framework of dynamical mean-field theory. At a certain low temperature one finds a fraction of ferromagnetic sites transiting to the paramagnetic state. Enlarging the nonmagnetic random disorder strength, the paramagnetic regimes expand resulting in the formation of the ferromagnetic clusters.

  11. Clustering Timber Harvests and the Effects of Dynamic Forest Management Policy on Forest Fragmentation

    Treesearch

    Eric J. Gustafson

    1998-01-01

    To integrate multiple uses (mature forest and commodity production) better on forested lands, timber management strategies that cluster harvests have been proposed. One such approach clusters harvest activity in space and time, and rotates timber production zones across the landscape with a long temporal period (dynamic zoning). Dynamic zoning has...

  12. Density-based clustering of small peptide conformations sampled from a molecular dynamics simulation.

    PubMed

    Kim, Minkyoung; Choi, Seung-Hoon; Kim, Junhyoung; Choi, Kihang; Shin, Jae-Min; Kang, Sang-Kee; Choi, Yun-Jaie; Jung, Dong Hyun

    2009-11-01

    This study describes the application of a density-based algorithm to clustering small peptide conformations after a molecular dynamics simulation. We propose a clustering method for small peptide conformations that enables adjacent clusters to be separated more clearly on the basis of neighbor density. Neighbor density means the number of neighboring conformations, so if a conformation has too few neighboring conformations, then it is considered as noise or an outlier and is excluded from the list of cluster members. With this approach, we can easily identify clusters in which the members are densely crowded in the conformational space, and we can safely avoid misclustering individual clusters linked by noise or outliers. Consideration of neighbor density significantly improves the efficiency of clustering of small peptide conformations sampled from molecular dynamics simulations and can be used for predicting peptide structures.

  13. Model Selection for Monitoring CO2 Plume during Sequestration

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

    2014-12-31

    The model selection method developed as part of this project mainly includes four steps: (1) assessing the connectivity/dynamic characteristics of a large prior ensemble of models, (2) model clustering using multidimensional scaling coupled with k-mean clustering, (3) model selection using the Bayes' rule in the reduced model space, (4) model expansion using iterative resampling of the posterior models. The fourth step expresses one of the advantages of the method: it provides a built-in means of quantifying the uncertainty in predictions made with the selected models. In our application to plume monitoring, by expanding the posterior space of models, the finalmore » ensemble of representations of geological model can be used to assess the uncertainty in predicting the future displacement of the CO2 plume. The software implementation of this approach is attached here.« less

  14. Dynamically allocated virtual clustering management system

    NASA Astrophysics Data System (ADS)

    Marcus, Kelvin; Cannata, Jess

    2013-05-01

    The U.S Army Research Laboratory (ARL) has built a "Wireless Emulation Lab" to support research in wireless mobile networks. In our current experimentation environment, our researchers need the capability to run clusters of heterogeneous nodes to model emulated wireless tactical networks where each node could contain a different operating system, application set, and physical hardware. To complicate matters, most experiments require the researcher to have root privileges. Our previous solution of using a single shared cluster of statically deployed virtual machines did not sufficiently separate each user's experiment due to undesirable network crosstalk, thus only one experiment could be run at a time. In addition, the cluster did not make efficient use of our servers and physical networks. To address these concerns, we created the Dynamically Allocated Virtual Clustering management system (DAVC). This system leverages existing open-source software to create private clusters of nodes that are either virtual or physical machines. These clusters can be utilized for software development, experimentation, and integration with existing hardware and software. The system uses the Grid Engine job scheduler to efficiently allocate virtual machines to idle systems and networks. The system deploys stateless nodes via network booting. The system uses 802.1Q Virtual LANs (VLANs) to prevent experimentation crosstalk and to allow for complex, private networks eliminating the need to map each virtual machine to a specific switch port. The system monitors the health of the clusters and the underlying physical servers and it maintains cluster usage statistics for historical trends. Users can start private clusters of heterogeneous nodes with root privileges for the duration of the experiment. Users also control when to shutdown their clusters.

  15. 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

  16. Fuzzy C-mean clustering on kinetic parameter estimation with generalized linear least square algorithm in SPECT

    NASA Astrophysics Data System (ADS)

    Choi, Hon-Chit; Wen, Lingfeng; Eberl, Stefan; Feng, Dagan

    2006-03-01

    Dynamic Single Photon Emission Computed Tomography (SPECT) has the potential to quantitatively estimate physiological parameters by fitting compartment models to the tracer kinetics. The generalized linear least square method (GLLS) is an efficient method to estimate unbiased kinetic parameters and parametric images. However, due to the low sensitivity of SPECT, noisy data can cause voxel-wise parameter estimation by GLLS to fail. Fuzzy C-Mean (FCM) clustering and modified FCM, which also utilizes information from the immediate neighboring voxels, are proposed to improve the voxel-wise parameter estimation of GLLS. Monte Carlo simulations were performed to generate dynamic SPECT data with different noise levels and processed by general and modified FCM clustering. Parametric images were estimated by Logan and Yokoi graphical analysis and GLLS. The influx rate (K I), volume of distribution (V d) were estimated for the cerebellum, thalamus and frontal cortex. Our results show that (1) FCM reduces the bias and improves the reliability of parameter estimates for noisy data, (2) GLLS provides estimates of micro parameters (K I-k 4) as well as macro parameters, such as volume of distribution (Vd) and binding potential (BP I & BP II) and (3) FCM clustering incorporating neighboring voxel information does not improve the parameter estimates, but improves noise in the parametric images. These findings indicated that it is desirable for pre-segmentation with traditional FCM clustering to generate voxel-wise parametric images with GLLS from dynamic SPECT data.

  17. Cluster dynamics modeling and experimental investigation of the effect of injected interstitials

    NASA Astrophysics Data System (ADS)

    Michaut, B.; Jourdan, T.; Malaplate, J.; Renault-Laborne, A.; Sefta, F.; Décamps, B.

    2017-12-01

    The effect of injected interstitials on loop and cavity microstructures is investigated experimentally and numerically for 304L austenitic stainless steel irradiated at 450 °C with 10 MeV Fe5+ ions up to about 100 dpa. A cluster dynamics model is parametrized on experimental results obtained by transmission electron microscopy (TEM) in a region where injected interstitials can be safely neglected. It is then used to model the damage profile and study the impact of self-ion injection. Results are compared to TEM observations on cross-sections of specimens. It is shown that injected interstitials have a significant effect on cavity density and mean size, even in the sink-dominated regime. To quantitatively match the experimental data in the self-ions injected area, a variation of some parameters is necessary. We propose that the fraction of freely migrating species may vary as a function of depth. Finally, we show that simple rate theory considerations do not seem to be valid for these experimental conditions.

  18. Computationally-efficient stochastic cluster dynamics method for modeling damage accumulation in irradiated materials

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

    Hoang, Tuan L.; Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, CA 94550; Marian, Jaime, E-mail: jmarian@ucla.edu

    2015-11-01

    An improved version of a recently developed stochastic cluster dynamics (SCD) method (Marian and Bulatov, 2012) [6] is introduced as an alternative to rate theory (RT) methods for solving coupled ordinary differential equation (ODE) systems for irradiation damage simulations. SCD circumvents by design the curse of dimensionality of the variable space that renders traditional ODE-based RT approaches inefficient when handling complex defect population comprised of multiple (more than two) defect species. Several improvements introduced here enable efficient and accurate simulations of irradiated materials up to realistic (high) damage doses characteristic of next-generation nuclear systems. The first improvement is a proceduremore » for efficiently updating the defect reaction-network and event selection in the context of a dynamically expanding reaction-network. Next is a novel implementation of the τ-leaping method that speeds up SCD simulations by advancing the state of the reaction network in large time increments when appropriate. Lastly, a volume rescaling procedure is introduced to control the computational complexity of the expanding reaction-network through occasional reductions of the defect population while maintaining accurate statistics. The enhanced SCD method is then applied to model defect cluster accumulation in iron thin films subjected to triple ion-beam (Fe{sup 3+}, He{sup +} and H{sup +}) irradiations, for which standard RT or spatially-resolved kinetic Monte Carlo simulations are prohibitively expensive.« less

  19. Computationally-efficient stochastic cluster dynamics method for modeling damage accumulation in irradiated materials

    NASA Astrophysics Data System (ADS)

    Hoang, Tuan L.; Marian, Jaime; Bulatov, Vasily V.; Hosemann, Peter

    2015-11-01

    An improved version of a recently developed stochastic cluster dynamics (SCD) method (Marian and Bulatov, 2012) [6] is introduced as an alternative to rate theory (RT) methods for solving coupled ordinary differential equation (ODE) systems for irradiation damage simulations. SCD circumvents by design the curse of dimensionality of the variable space that renders traditional ODE-based RT approaches inefficient when handling complex defect population comprised of multiple (more than two) defect species. Several improvements introduced here enable efficient and accurate simulations of irradiated materials up to realistic (high) damage doses characteristic of next-generation nuclear systems. The first improvement is a procedure for efficiently updating the defect reaction-network and event selection in the context of a dynamically expanding reaction-network. Next is a novel implementation of the τ-leaping method that speeds up SCD simulations by advancing the state of the reaction network in large time increments when appropriate. Lastly, a volume rescaling procedure is introduced to control the computational complexity of the expanding reaction-network through occasional reductions of the defect population while maintaining accurate statistics. The enhanced SCD method is then applied to model defect cluster accumulation in iron thin films subjected to triple ion-beam (Fe3+, He+ and H+) irradiations, for which standard RT or spatially-resolved kinetic Monte Carlo simulations are prohibitively expensive.

  20. CSDMS2.0: Computational Infrastructure for Community Surface Dynamics Modeling

    NASA Astrophysics Data System (ADS)

    Syvitski, J. P.; Hutton, E.; Peckham, S. D.; Overeem, I.; Kettner, A.

    2012-12-01

    The Community Surface Dynamic Modeling System (CSDMS) is an NSF-supported, international and community-driven program that seeks to transform the science and practice of earth-surface dynamics modeling. CSDMS integrates a diverse community of more than 850 geoscientists representing 360 international institutions (academic, government, industry) from 60 countries and is supported by a CSDMS Interagency Committee (22 Federal agencies), and a CSDMS Industrial Consortia (18 companies). CSDMS presently distributes more 200 Open Source models and modeling tools, access to high performance computing clusters in support of developing and running models, and a suite of products for education and knowledge transfer. CSDMS software architecture employs frameworks and services that convert stand-alone models into flexible "plug-and-play" components to be assembled into larger applications. CSDMS2.0 will support model applications within a web browser, on a wider variety of computational platforms, and on other high performance computing clusters to ensure robustness and sustainability of the framework. Conversion of stand-alone models into "plug-and-play" components will employ automated wrapping tools. Methods for quantifying model uncertainty are being adapted as part of the modeling framework. Benchmarking data is being incorporated into the CSDMS modeling framework to support model inter-comparison. Finally, a robust mechanism for ingesting and utilizing semantic mediation databases is being developed within the Modeling Framework. Six new community initiatives are being pursued: 1) an earth - ecosystem modeling initiative to capture ecosystem dynamics and ensuing interactions with landscapes, 2) a geodynamics initiative to investigate the interplay among climate, geomorphology, and tectonic processes, 3) an Anthropocene modeling initiative, to incorporate mechanistic models of human influences, 4) a coastal vulnerability modeling initiative, with emphasis on deltas and their multiple threats and stressors, 5) a continental margin modeling initiative, to capture extreme oceanic and atmospheric events generating turbidity currents in the Gulf of Mexico, and 6) a CZO Focus Research Group, to develop compatibility between CSDMS architecture and protocols and Critical Zone Observatory-developed models and data.

  1. Cluster Morphology-Polymer Dynamics Correlations in Sulfonated Polystyrene Melts: Computational Study

    DOE PAGES

    Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S.

    2016-04-11

    Reaching exceptionally long times up to 500 ns in equilibrium and nonequilibrium molecular dynamics simulations studies, we have attained a fundamental molecular understanding of the correlation of ionomer clusters structure and multiscale dynamics, providing new insight into one critical, long-standing challenge in ionic polymer physics. The cluster structure in melts of sulfonated polystyrene with Na + and Mg 2+ counterions are resolved and correlated with the dynamics on multiple length and time scales extracted from measurements of the dynamic structure factor and shear rheology. We find that as the morphology of the ionic clusters changes from ladderlike for Na +more » to disordered structures for Mg 2+, the dynamic structure factor is affected on the length scale corresponding to the ionic clusters. Lastly, rheology studies show that the viscosity for Mg 2+ melts is higher than for Na + ones for all shear rates, which is well correlated with the larger ionic clusters’ size for the Mg 2+ melts.« less

  2. Modeling the coupled return-spread high frequency dynamics of large tick assets

    NASA Astrophysics Data System (ADS)

    Curato, Gianbiagio; Lillo, Fabrizio

    2015-01-01

    Large tick assets, i.e. assets where one tick movement is a significant fraction of the price and bid-ask spread is almost always equal to one tick, display a dynamics in which price changes and spread are strongly coupled. We present an approach based on the hidden Markov model, also known in econometrics as the Markov switching model, for the dynamics of price changes, where the latent Markov process is described by the transitions between spreads. We then use a finite Markov mixture of logit regressions on past squared price changes to describe temporal dependencies in the dynamics of price changes. The model can thus be seen as a double chain Markov model. We show that the model describes the shape of the price change distribution at different time scales, volatility clustering, and the anomalous decrease of kurtosis. We calibrate our models based on Nasdaq stocks and we show that this model reproduces remarkably well the statistical properties of real data.

  3. A dynamic scheduling algorithm for singe-arm two-cluster tools with flexible processing times

    NASA Astrophysics Data System (ADS)

    Li, Xin; Fung, Richard Y. K.

    2018-02-01

    This article presents a dynamic algorithm for job scheduling in two-cluster tools producing multi-type wafers with flexible processing times. Flexible processing times mean that the actual times for processing wafers should be within given time intervals. The objective of the work is to minimize the completion time of the newly inserted wafer. To deal with this issue, a two-cluster tool is decomposed into three reduced single-cluster tools (RCTs) in a series based on a decomposition approach proposed in this article. For each single-cluster tool, a dynamic scheduling algorithm based on temporal constraints is developed to schedule the newly inserted wafer. Three experiments have been carried out to test the dynamic scheduling algorithm proposed, comparing with the results the 'earliest starting time' heuristic (EST) adopted in previous literature. The results show that the dynamic algorithm proposed in this article is effective and practical.

  4. Features of globular cluster's dynamics with an intermediate-mass black hole

    NASA Astrophysics Data System (ADS)

    Ryabova, Marina V.; Gorban, Alena S.; Shchekinov, Yuri A.; Vasiliev, Evgenii O.

    2018-02-01

    In this paper, we address the question of how a central intermediate-mass black hole (IMBH) in a globular cluster (GC) affects dynamics, core collapse, and formation of the binary population. It is shown that the central IMBH forms a binary system that affects dynamics of stars in the cluster significantly. The presence of an intermediate-mass black hole with mass ≥ 1.0-1.7%of the total stellar mass in the cluster inhibits the formation of binary stars population.

  5. Topological ordering in liquid UO 2

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

    Benmore, C. J.; Skinner, L. B.; Lee, B.

    2015-12-10

    A molecular dynamics model of liquid UO2 that is in good agreement with recent high-energy x-ray diffraction data has been analyzed using the Bhatia–Thornton formalism. A pre-peak appears in the topological structure factor S NN(Q) at Q = 1.85(1)Å-1 which is not present in the more common, element specific Faber–Ziman partial structure factors. A radical Voronoi tessellation of the 3D molecular dynamics model shows the presence of a wide distribution of clusters, consistent with presence of highly mobile oxygen atoms. However, 4-fold Voronoi polyhedra (n 4) are found to dominate the structure and the majority of clusters can be describedmore » by the distribution n 3 ≤ n 4 ≥ n 5. It is argued that an open network of 4-fold Voronoi polyhedra could explain the origin of the pre-peak in S NN(Q) and the topological ordering observed in liquid UO2.« less

  6. Calculations of Helium Bubble Evolution in the PISCES Experiments with Cluster Dynamics

    NASA Astrophysics Data System (ADS)

    Blondel, Sophie; Younkin, Timothy; Wirth, Brian; Lasa, Ane; Green, David; Canik, John; Drobny, Jon; Curreli, Davide

    2017-10-01

    Plasma surface interactions in fusion tokamak reactors involve an inherently multiscale, highly non-equilibrium set of phenomena, for which current models are inadequate to predict the divertor response to and feedback on the plasma. In this presentation, we describe the latest code developments of Xolotl, a spatially-dependent reaction diffusion cluster dynamics code to simulate the divertor surface response to fusion-relevant plasma exposure. Xolotl is part of a code-coupling effort to model both plasma and material simultaneously; the first benchmark for this effort is the series of PISCES linear device experiments. We will discuss the processes leading to surface morphology changes, which further affect erosion, as well as how Xolotl has been updated in order to communicate with other codes. Furthermore, we will show results of the sub-surface evolution of helium bubbles in tungsten as well as the material surface displacement under these conditions.

  7. Ab Initio Molecular Dynamics Studies of Pb m Sb n ( m + n ≤ 9) Alloy Clusters

    NASA Astrophysics Data System (ADS)

    Song, Bingyi; Xu, Baoqiang; Yang, Bin; Jiang, Wenlong; Chen, Xiumin; Xu, Na; Liu, Dachun; Dai, Yongnian

    2017-10-01

    Structure, stability, and dynamics of Pb m Sb n ( m + n ≤ 9) clusters were investigated using ab initio molecular dynamics. Size dependence of binding energies, the second-order energy difference of clusters, dissociation energy, HOMO-LUMO gaps, Mayer bond order, and the diffusion coefficient of Pb m Sb n clusters were discussed. Results suggest that Pb3Sb2, Pb4Sb2, and Pb5Sb4 ( n = 2 or 4) clusters have higher stability than other clusters, which is consistent with previous findings. In case of Pb-Sb alloy, the dynamics results show that Pb4Sb2 (Pb-22.71 wt pct Sb) can exist in gas phase at 1073 K (800 °C), which reasonably explains the azeotropic phenomenon, and the calculated values are in agreement with the experimental results (Pb-22 wt pct Sb).

  8. Clustering effects in ionic polymers: Molecular dynamics simulations

    DOE PAGES

    Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S.

    2015-08-18

    Ionic clusters control the structure, dynamics, and transport in soft matter. Incorporating a small fraction of ionizable groups in polymers substantially reduces the mobility of the macromolecules in melts. Furthermore, these ionic groups often associate into random clusters in melts, where the distribution and morphology of the clusters impact the transport in these materials. Here, using molecular dynamic simulations we demonstrate a clear correlation between cluster size and morphology with the polymer mobility in melts of sulfonated polystyrene. We show that in low dielectric media ladderlike clusters that are lower in energy compared with spherical assemblies are formed. Reducing themore » electrostatic interactions by enhancing the dielectric constant leads to morphological transformation from ladderlike clusters to globular assemblies. Finally, decrease in electrostatic interaction significantly enhances the mobility of the polymer.« less

  9. Cosmology and astrophysics from relaxed galaxy clusters - V. Consistency with cold dark matter structure formation

    NASA Astrophysics Data System (ADS)

    Mantz, A. B.; Allen, S. W.; Morris, R. G.

    2016-10-01

    This is the fifth in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Our sample comprises 40 clusters identified as being dynamically relaxed and hot in Papers I and II of this series. Here we use constraints on cluster mass profiles from X-ray data to test some of the basic predictions of cosmological structure formation in the cold dark matter (CDM) paradigm. We present constraints on the concentration-mass relation for massive clusters, finding a power-law mass dependence with a slope of κm = -0.16 ± 0.07, in agreement with CDM predictions. For this relaxed sample, the relation is consistent with a constant as a function of redshift (power-law slope with 1 + z of κζ = -0.17 ± 0.26), with an intrinsic scatter of σln c = 0.16 ± 0.03. We investigate the shape of cluster mass profiles over the radial range probed by the data (typically ˜50 kpc-1 Mpc), and test for departures from the simple Navarro-Frenk-White (NFW) form, for which the logarithmic slope of the density profile tends to -1 at small radii. Specifically, we consider as alternatives the generalized NFW (GNFW) and Einasto parametrizations. For the GNFW model, we find an average value of (minus) the logarithmic inner slope of β = 1.02 ± 0.08, with an intrinsic scatter of σβ = 0.22 ± 0.07, while in the Einasto case we constrain the average shape parameter to be α = 0.29 ± 0.04 with an intrinsic scatter of σα = 0.12 ± 0.04. Our results are thus consistent with the simple NFW model on average, but we clearly detect the presence of intrinsic, cluster-to-cluster scatter about the average.

  10. Cosmology and astrophysics from relaxed galaxy clusters – V. Consistency with cold dark matter structure formation

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

    Mantz, A. B.; Allen, S. W.; Morris, R. G.

    This is the fifth in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Our sample comprises 40 clusters identified as being dynamically relaxed and hot in Papers I and II of this series. Here we use constraints on cluster mass profiles from X-ray data to test some of the basic predictions of cosmological structure formation in the cold dark matter (CDM) paradigm. In addition, we present constraints on the concentration–mass relation for massive clusters, finding a power-law mass dependence with a slope of κ m = –0.16 ± 0.07, in agreement with CDMmore » predictions. For this relaxed sample, the relation is consistent with a constant as a function of redshift (power-law slope with 1 + z of κ ζ = –0.17 ± 0.26), with an intrinsic scatter of σln c = 0.16 ± 0.03. We investigate the shape of cluster mass profiles over the radial range probed by the data (typically ~50 kpc–1 Mpc), and test for departures from the simple Navarro–Frenk–White (NFW) form, for which the logarithmic slope of the density profile tends to –1 at small radii. Specifically, we consider as alternatives the generalized NFW (GNFW) and Einasto parametrizations. For the GNFW model, we find an average value of (minus) the logarithmic inner slope of β = 1.02 ± 0.08, with an intrinsic scatter of σ β = 0.22 ± 0.07, while in the Einasto case we constrain the average shape parameter to be α = 0.29 ± 0.04 with an intrinsic scatter of σ α = 0.12 ± 0.04. Our results are thus consistent with the simple NFW model on average, but we clearly detect the presence of intrinsic, cluster-to-cluster scatter about the average.« less

  11. STAR COUNT DENSITY PROFILES AND STRUCTURAL PARAMETERS OF 26 GALACTIC GLOBULAR CLUSTERS

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

    Miocchi, P.; Lanzoni, B.; Ferraro, F. R.

    We used an appropriate combination of high-resolution Hubble Space Telescope observations and wide-field, ground-based data to derive the radial stellar density profiles of 26 Galactic globular clusters from resolved star counts (which can be all freely downloaded on-line). With respect to surface brightness (SB) profiles (which can be biased by the presence of sparse, bright stars), star counts are considered to be the most robust and reliable tool to derive cluster structural parameters. For each system, a detailed comparison with both King and Wilson models has been performed and the most relevant best-fit parameters have been obtained. This collection ofmore » data represents the largest homogeneous catalog collected so far of star count profiles and structural parameters derived therefrom. The analysis of the data of our catalog has shown that (1) the presence of the central cusps previously detected in the SB profiles of NGC 1851, M13, and M62 is not confirmed; (2) the majority of clusters in our sample are fit equally well by the King and the Wilson models; (3) we confirm the known relationship between cluster size (as measured by the effective radius) and galactocentric distance; (4) the ratio between the core and the effective radii shows a bimodal distribution, with a peak at {approx}0.3 for about 80% of the clusters and a secondary peak at {approx}0.6 for the remaining 20%. Interestingly, the main peak turns out to be in agreement with that expected from simulations of cluster dynamical evolution and the ratio between these two radii correlates well with an empirical dynamical-age indicator recently defined from the observed shape of blue straggler star radial distribution, thus suggesting that no exotic mechanisms of energy generation are needed in the cores of the analyzed clusters.« less

  12. Investigating the internal structure of galaxies and clusters through strong gravitational lensing

    NASA Astrophysics Data System (ADS)

    Jigish Gandhi, Pratik; Grillo, Claudio; Bonamigo, Mario

    2018-01-01

    Gravitational lensing studies have radically improved our understanding of the internal structure of galaxies and cluster-scale systems. In particular, the combination of strong lensing and stellar dynamics or stellar population synthesis models have made it possible to characterize numerous fundamental properties of the galaxies as well as dark matter halos and subhalos with unprecedented robustness and accuracy. Here we demonstrate the usefulness and accuracy of strong lensing as a probe for characterising the properties of cluster members as well as dark matter halos, to show that such characterisation carried out via lensing analyses alone is as viable as those carried out through a combination of spectroscopy and lensing analyses.Our study uses focuses on the early-type galaxy cluster MACS J1149.5+2223 at redshift 0.54 in the Hubble Frontier Fields (HFF) program, where the first magnified and spatially resolved multiple images of supernova (SN) “Refsdal” and its late-type host galaxy at redshift 1.489 were detected. The Refsdal system is unique in being the first ever multiply-imaged supernova, with it’s first four images appearing in an Einstein Cross configuration around one of the cluster members in 2015. In our lensing analyses we use HST data of the multiply-imaged SN Refsdal to constrain the dynamical masses, velocity dispersions, and virial radii of individual galaxies and dark matter halos in the MACS J1149.5+2223 cluster. For our lensing models we select a sample of 300 cluster members within approximately 500 kpc from the BCG, and a set of reliable multiple images associated with 18 distinct knots in the SN host spiral galaxy, as well as multiple images of the supernova itself. Our results provide accurate measurements of the masses, velocity dispersions, and radii of the cluster’s dark matter halo as well as three chosen members galaxies, in strong agreement with those obtained by Grillo et al 2015, demonstrating the usefulness of strong lensing in characterising the properties of cluster-scale systems.

  13. Cosmology and astrophysics from relaxed galaxy clusters – V. Consistency with cold dark matter structure formation

    DOE PAGES

    Mantz, A. B.; Allen, S. W.; Morris, R. G.

    2016-07-15

    This is the fifth in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Our sample comprises 40 clusters identified as being dynamically relaxed and hot in Papers I and II of this series. Here we use constraints on cluster mass profiles from X-ray data to test some of the basic predictions of cosmological structure formation in the cold dark matter (CDM) paradigm. In addition, we present constraints on the concentration–mass relation for massive clusters, finding a power-law mass dependence with a slope of κ m = –0.16 ± 0.07, in agreement with CDMmore » predictions. For this relaxed sample, the relation is consistent with a constant as a function of redshift (power-law slope with 1 + z of κ ζ = –0.17 ± 0.26), with an intrinsic scatter of σln c = 0.16 ± 0.03. We investigate the shape of cluster mass profiles over the radial range probed by the data (typically ~50 kpc–1 Mpc), and test for departures from the simple Navarro–Frenk–White (NFW) form, for which the logarithmic slope of the density profile tends to –1 at small radii. Specifically, we consider as alternatives the generalized NFW (GNFW) and Einasto parametrizations. For the GNFW model, we find an average value of (minus) the logarithmic inner slope of β = 1.02 ± 0.08, with an intrinsic scatter of σ β = 0.22 ± 0.07, while in the Einasto case we constrain the average shape parameter to be α = 0.29 ± 0.04 with an intrinsic scatter of σ α = 0.12 ± 0.04. Our results are thus consistent with the simple NFW model on average, but we clearly detect the presence of intrinsic, cluster-to-cluster scatter about the average.« less

  14. Communication: Diverse nanoscale cluster dynamics: Diffusion of 2D epitaxial clusters

    NASA Astrophysics Data System (ADS)

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

    2017-11-01

    The dynamics of nanoscale clusters can be distinct from macroscale behavior described by continuum formalisms. For diffusion of 2D clusters of N atoms in homoepitaxial systems mediated by edge atom hopping, macroscale theory predicts simple monotonic size scaling of the diffusion coefficient, DN ˜ N-β, with β = 3/2. However, modeling for nanoclusters on metal(100) surfaces reveals that slow nucleation-mediated diffusion displaying weak size scaling β < 1 occurs for "perfect" sizes Np = L2 and L(L+1) for integer L = 3,4,… (with unique square or near-square ground state shapes), and also for Np+3, Np+4,…. In contrast, fast facile nucleation-free diffusion displaying strong size scaling β ≈ 2.5 occurs for sizes Np+1 and Np+2. DN versus N oscillates strongly between the slowest branch (for Np+3) and the fastest branch (for Np+1). All branches merge for N = O(102), but macroscale behavior is only achieved for much larger N = O(103). This analysis reveals the unprecedented diversity of behavior on the nanoscale.

  15. Structural origin of fractional Stokes-Einstein relation in glass-forming liquids

    NASA Astrophysics Data System (ADS)

    Pan, Shaopeng; Wu, Z. W.; Wang, W. H.; Li, M. Z.; Xu, Limei

    2017-01-01

    In many glass-forming liquids, fractional Stokes-Einstein relation (SER) is observed above the glass transition temperature. However, the origin of such phenomenon remains elusive. Using molecular dynamics simulations, we investigate the break- down of SER and the onset of fractional SER in a model of metallic glass-forming liquid. We find that SER breaks down when the size of the largest cluster consisting of trapped atoms starts to increase sharply at which the largest cluster spans half of the simulations box along one direction, and the fractional SER starts to follows when the largest cluster percolates the entire system and forms 3-dimentional network structures. Further analysis based on the percolation theory also confirms that percolation occurs at the onset of the fractional SER. Our results directly link the breakdown of the SER with structure inhomogeneity and onset of the fraction SER with percolation of largest clusters, thus provide a possible picture for the break- down of SER and onset of fractional SER in glass-forming liquids, which is is important for the understanding of the dynamic properties in glass-forming liquids.

  16. CLASH-VLT: DISSECTING THE FRONTIER FIELDS GALAXY CLUSTER MACS J0416.1-2403 WITH ∼800 SPECTRA OF MEMBER GALAXIES

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

    Balestra, I.; Sartoris, B.; Girardi, M.

    2016-06-01

    We present VIMOS-Very Large Telescope (VLT) spectroscopy of the Frontier Fields cluster MACS J0416.1-2403 ( z  = 0.397). Taken as part of the CLASH-VLT survey, the large spectroscopic campaign provided more than 4000 reliable redshifts over ∼600 arcmin{sup 2}, including ∼800 cluster member galaxies. The unprecedented sample of cluster members at this redshift allows us to perform a highly detailed dynamical and structural analysis of the cluster out to ∼2.2 r {sub 200} (∼4 Mpc). Our analysis of substructures reveals a complex system composed of a main massive cluster ( M {sub 200} ∼ 0.9 × 10{sup 15} M {sub ⊙} and σ{sub V,r200} ∼ 1000 km s{supmore » −1}) presenting two major features: (i) a bimodal velocity distribution, showing two central peaks separated by Δ V {sub rf} ∼ 1100 km s{sup −1} with comparable galaxy content and velocity dispersion, and (ii) a projected elongation of the main substructures along the NE–SW direction, with a prominent sub-clump ∼600 kpc SW of the center and an isolated BCG approximately halfway between the center and the SW clump. We also detect a low-mass structure at z  ∼ 0.390, ∼10′ south of the cluster center, projected at ∼3 Mpc, with a relative line-of-sight velocity of Δ V{sub rf} ∼ −1700 km s{sup −1}. The cluster mass profile that we obtain through our dynamical analysis deviates significantly from the “universal” NFW, being best fit by a Softened Isothermal Sphere model instead. The mass profile measured from the galaxy dynamics is found to be in relatively good agreement with those obtained from strong and weak lensing, as well as with that from the X-rays, despite the clearly unrelaxed nature of the cluster. Our results reveal an overall complex dynamical state of this massive cluster and support the hypothesis that the two main subclusters are being observed in a pre-collisional phase, in agreement with recent findings from radio and deep X-ray data. In this article, we also release the entire redshift catalog of 4386 sources in the field of this cluster, which includes 60 identified Chandra X-ray sources and 105 JVLA radio sources.« less

  17. N-body simulations of star clusters

    NASA Astrophysics Data System (ADS)

    Engle, Kimberly Anne

    1999-10-01

    We investigate the structure and evolution of underfilling (i.e. non-Roche-lobe-filling) King model globular star clusters using N-body simulations. We model clusters with various underfilling factors and mass distributions to determine their evolutionary tracks and lifetimes. These models include a self-consistent galactic tidal field, mass loss due to stellar evolution, ejection, and evaporation, and binary evolution. We find that a star cluster that initially does not fill its Roche lobe can live many times longer than one that does initially fill its Roche lobe. After a few relaxation times, the cluster expands to fill its Roche lobe. We also find that the choice of initial mass function significantly affects the lifetime of the cluster. These simulations were performed on the GRAPE-4 (GRAvity PipE) special-purpose hardware with the stellar dynamics package ``Starlab.'' The GRAPE-4 system is a massively-parallel computer designed to calculate the force (and its first time derivative) due to N particles. Starlab's integrator ``kira'' employs a 4th- order Hermite scheme with hierarchical (block) time steps to evolve the stellar system. We discuss, in some detail, the design of the GRAPE-4 system and the manner in which the Hermite integration scheme with block time steps is implemented in the hardware.

  18. On the accuracy of the MB-pol many-body potential for water: Interaction energies, vibrational frequencies, and classical thermodynamic and dynamical properties from clusters to liquid water and ice

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

    Reddy, Sandeep K.; Straight, Shelby C.; Bajaj, Pushp

    The MB-pol many-body potential has recently emerged as an accurate molecular model for water simulations from the gas to the condensed phase. In this study, the accuracy of MB-pol is systematically assessed across the three phases of water through extensive comparisons with experimental data and high-level ab initio calculations. Individual many-body contributions to the interaction energies as well as vibrational spectra of water clusters calculated with MB-pol are in excellent agreement with reference data obtained at the coupled cluster level. Several structural, thermodynamic, and dynamical properties of the liquid phase at atmospheric pressure are investigated through classical molecular dynamics simulationsmore » as a function of temperature. The structural properties of the liquid phase are in nearly quantitative agreement with X-ray diffraction data available over the temperature range from 268 to 368 K. The analysis of other thermodynamic and dynamical quantities emphasizes the importance of explicitly including nuclear quantum effects in the simulations, especially at low temperature, for a physically correct description of the properties of liquid water. Furthermore, both densities and lattice energies of several ice phases are also correctly reproduced by MB-pol. Following a recent study of DFT models for water, a score is assigned to each computed property, which demonstrates the high and, in many respects, unprecedented accuracy of MB-pol in representing all three phases of water. Published by AIP Publishing.« less

  19. Human Guidance Behavior Decomposition and Modeling

    NASA Astrophysics Data System (ADS)

    Feit, Andrew James

    Trained humans are capable of high performance, adaptable, and robust first-person dynamic motion guidance behavior. This behavior is exhibited in a wide variety of activities such as driving, piloting aircraft, skiing, biking, and many others. Human performance in such activities far exceeds the current capability of autonomous systems in terms of adaptability to new tasks, real-time motion planning, robustness, and trading safety for performance. The present work investigates the structure of human dynamic motion guidance that enables these performance qualities. This work uses a first-person experimental framework that presents a driving task to the subject, measuring control inputs, vehicle motion, and operator visual gaze movement. The resulting data is decomposed into subspace segment clusters that form primitive elements of action-perception interactive behavior. Subspace clusters are defined by both agent-environment system dynamic constraints and operator control strategies. A key contribution of this work is to define transitions between subspace cluster segments, or subgoals, as points where the set of active constraints, either system or operator defined, changes. This definition provides necessary conditions to determine transition points for a given task-environment scenario that allow a solution trajectory to be planned from known behavior elements. In addition, human gaze behavior during this task contains predictive behavior elements, indicating that the identified control modes are internally modeled. Based on these ideas, a generative, autonomous guidance framework is introduced that efficiently generates optimal dynamic motion behavior in new tasks. The new subgoal planning algorithm is shown to generate solutions to certain tasks more quickly than existing approaches currently used in robotics.

  20. Microbial community development in a dynamic gut model is reproducible, colon region specific, and selective for Bacteroidetes and Clostridium cluster IX.

    PubMed

    Van den Abbeele, Pieter; Grootaert, Charlotte; Marzorati, Massimo; Possemiers, Sam; Verstraete, Willy; Gérard, Philippe; Rabot, Sylvie; Bruneau, Aurélia; El Aidy, Sahar; Derrien, Muriel; Zoetendal, Erwin; Kleerebezem, Michiel; Smidt, Hauke; Van de Wiele, Tom

    2010-08-01

    Dynamic, multicompartment in vitro gastrointestinal simulators are often used to monitor gut microbial dynamics and activity. These reactors need to harbor a microbial community that is stable upon inoculation, colon region specific, and relevant to in vivo conditions. Together with the reproducibility of the colonization process, these criteria are often overlooked when the modulatory properties from different treatments are compared. We therefore investigated the microbial colonization process in two identical simulators of the human intestinal microbial ecosystem (SHIME), simultaneously inoculated with the same human fecal microbiota with a high-resolution phylogenetic microarray: the human intestinal tract chip (HITChip). Following inoculation of the in vitro colon compartments, microbial community composition reached steady state after 2 weeks, whereas 3 weeks were required to reach functional stability. This dynamic colonization process was reproducible in both SHIME units and resulted in highly diverse microbial communities which were colon region specific, with the proximal regions harboring saccharolytic microbes (e.g., Bacteroides spp. and Eubacterium spp.) and the distal regions harboring mucin-degrading microbes (e.g., Akkermansia spp.). Importantly, the shift from an in vivo to an in vitro environment resulted in an increased Bacteroidetes/Firmicutes ratio, whereas Clostridium cluster IX (propionate producers) was enriched compared to clusters IV and XIVa (butyrate producers). This was supported by proportionally higher in vitro propionate concentrations. In conclusion, high-resolution analysis of in vitro-cultured gut microbiota offers new insight on the microbial colonization process and indicates the importance of digestive parameters that may be crucial in the development of new in vitro models.

  1. On the accuracy of the MB-pol many-body potential for water: Interaction energies, vibrational frequencies, and classical thermodynamic and dynamical properties from clusters to liquid water and ice [How good is the MB-pol many-body potential for water?

    DOE PAGES

    Reddy, Sandeep K.; Straight, Shelby C.; Bajaj, Pushp; ...

    2016-11-17

    The MB-pol many-body potential has recently emerged as an accurate molecular model for water simulations from the gas to the condensed phase. Here, the accuracy of MB-pol is systematically assessed across the three phases of water through extensive comparisons with experimental data and high-level ab initio calculations. Individual many-body contributions to the interaction energies as well as vibrational spectra of water clusters calculated with MB-pol are in excellent agreement with reference data obtained at the coupled cluster level. We investigate several structural, thermodynamic, and dynamical properties of the liquid phase at atmospheric pressure through classical molecular dynamics simulations as amore » function of temperature. Furthermore, the structural properties of the liquid phase are in nearly quantitative agreement with X-ray diffraction data available over the temperature range from 268 to 368 K. The analysis of other thermodynamic and dynamical quantities emphasizes the importance of explicitly including nuclear quantum effects in the simulations, especially at low temperature, for a physically correct description of the properties of liquid water. Furthermore, both densities and lattice energies of several ice phases are also correctly reproduced by MB-pol. Following a recent study of DFT models for water, a score is assigned to each computed property, which demonstrates the high and, in many respects, unprecedented accuracy of MB-pol in representing all three phases of water.« less

  2. On the accuracy of the MB-pol many-body potential for water: Interaction energies, vibrational frequencies, and classical thermodynamic and dynamical properties from clusters to liquid water and ice [How good is the MB-pol many-body potential for water?

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

    Reddy, Sandeep K.; Straight, Shelby C.; Bajaj, Pushp

    The MB-pol many-body potential has recently emerged as an accurate molecular model for water simulations from the gas to the condensed phase. Here, the accuracy of MB-pol is systematically assessed across the three phases of water through extensive comparisons with experimental data and high-level ab initio calculations. Individual many-body contributions to the interaction energies as well as vibrational spectra of water clusters calculated with MB-pol are in excellent agreement with reference data obtained at the coupled cluster level. We investigate several structural, thermodynamic, and dynamical properties of the liquid phase at atmospheric pressure through classical molecular dynamics simulations as amore » function of temperature. Furthermore, the structural properties of the liquid phase are in nearly quantitative agreement with X-ray diffraction data available over the temperature range from 268 to 368 K. The analysis of other thermodynamic and dynamical quantities emphasizes the importance of explicitly including nuclear quantum effects in the simulations, especially at low temperature, for a physically correct description of the properties of liquid water. Furthermore, both densities and lattice energies of several ice phases are also correctly reproduced by MB-pol. Following a recent study of DFT models for water, a score is assigned to each computed property, which demonstrates the high and, in many respects, unprecedented accuracy of MB-pol in representing all three phases of water.« less

  3. Molecular dynamics simulations and docking studies on 3D models of the heterodimeric and homodimeric 5-HT(2A) receptor subtype.

    PubMed

    Bruno, Agostino; Beato, Claudia; Costantino, Gabriele

    2011-04-01

    G-protein coupled receptors may exist as functional homodimers, heterodimers and even as higher aggregates. In this work, we investigate the 5-HT(2A) receptor, which is a known target for antipsychotic drugs. Recently, 5-HT(2A) has been shown to form functional homodimers and heterodimers with the mGluR2 receptor. The objective of this study is to build up 3D models of the 5-HT(2A)/mGluR2 heterodimer and of the 5-HT(2A)-5-HT(2A) homodimer, and to evaluate the impact of the dimerization interface on the shape of the 5-HT(2A) binding pocket by using molecular dynamics simulations and docking studies. The heterodimer, homodimer and monomeric 5-HT(2A) receptors were simulated by molecular dynamics for 40 ns each. The trajectories were clustered and representative structures of six clusters for each system were generated. Inspection of the these representative structures clearly indicate an effect of the dimerization interface on the topology of the binding pocket. Docking studies allowed to generate receiver operating characteristic curves for a set of 5-HT(2A) ligands, indicating that different complexes prefer different classes of 5-HT(2A) ligands. This study clearly indicates that the presence of a dimerization interface must explicitly be considered when studying G-protein coupled receptors known to exist as dimers. Molecular dynamics simulation and cluster analysis are appropriate tools to study the phenomenon.

  4. Individualization as Driving Force of Clustering Phenomena in Humans

    PubMed Central

    Mäs, Michael; Flache, Andreas; Helbing, Dirk

    2010-01-01

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

  5. A Computational Algorithm for Functional Clustering of Proteome Dynamics During Development

    PubMed Central

    Wang, Yaqun; Wang, Ningtao; Hao, Han; Guo, Yunqian; Zhen, Yan; Shi, Jisen; Wu, Rongling

    2014-01-01

    Phenotypic traits, such as seed development, are a consequence of complex biochemical interactions among genes, proteins and metabolites, but the underlying mechanisms that operate in a coordinated and sequential manner remain elusive. Here, we address this issue by developing a computational algorithm to monitor proteome changes during the course of trait development. The algorithm is built within the mixture-model framework in which each mixture component is modeled by a specific group of proteins that display a similar temporal pattern of expression in trait development. A nonparametric approach based on Legendre orthogonal polynomials was used to fit dynamic changes of protein expression, increasing the power and flexibility of protein clustering. By analyzing a dataset of proteomic dynamics during early embryogenesis of the Chinese fir, the algorithm has successfully identified several distinct types of proteins that coordinate with each other to determine seed development in this forest tree commercially and environmentally important to China. The algorithm will find its immediate applications for the characterization of mechanistic underpinnings for any other biological processes in which protein abundance plays a key role. PMID:24955031

  6. Time-Dependent Thomas-Fermi Approach for Electron Dynamics in Metal Clusters

    NASA Astrophysics Data System (ADS)

    Domps, A.; Reinhard, P.-G.; Suraud, E.

    1998-06-01

    We propose a time-dependent Thomas-Fermi approach to the (nonlinear) dynamics of many-fermion systems. The approach relies on a hydrodynamical picture describing the system in terms of collective flow. We investigate in particular an application to electron dynamics in metal clusters. We make extensive comparisons with fully fledged quantal dynamical calculations and find overall good agreement. The approach thus provides a reliable and inexpensive scheme to study the electronic response of large metal clusters.

  7. Self-organized Criticality in Hierarchical Brain Network

    NASA Astrophysics Data System (ADS)

    Yang, Qiu-Ying; Zhang, Ying-Yue; Chen, Tian-Lun

    2008-11-01

    It is shown that the cortical brain network of the macaque displays a hierarchically clustered organization and the neuron network shows small-world properties. Now the two factors will be considered in our model and the dynamical behavior of the model will be studied. We study the characters of the model and find that the distribution of avalanche size of the model follows power-law behavior.

  8. Collective Flows of 16O+16O Collisions with α-Clustering Configurations

    NASA Astrophysics Data System (ADS)

    Guo, Chen-Chen; He, Wan-Bing; Ma, Yu-Gang

    2017-08-01

    The main purpose of the present paper is to discuss whether or not the collective flows in heavy-ion collision at Fermi energy can be taken as a tool to investigate the cluster configuration in light nuclei. In practice, within an Extended Quantum Molecular Dynamics model, four $\\alpha$-clustering (linear chain, kite, square, and tetrahedron) configurations of $^{16}$O are employed in the initialization, $^{16}$O+$^{16}$O around Fermi energy (40 - 60 MeV$/$nucleon) with impact parameter 1 - 3 fm are simulated, the directed and elliptic flows are analyzed. It is found that collective flows are influenced by the different $\\alpha$-clustering configurations, and the directed flow of free protons is more sensitive to the initial cluster configuration than the elliptic flow. Nuclear reaction at Fermi energy can be taken a useful way to study cluster configuration in light nuclei.

  9. Cluster correlation and fragment emission in 12C+12C at 95 MeV/nucleon

    NASA Astrophysics Data System (ADS)

    Tian, G.; Chen, Z.; Han, R.; Shi, F.; Luo, F.; Sun, Q.; Song, L.; Zhang, X.; Xiao, G. Q.; Wada, R.; Ono, A.

    2018-03-01

    The impact of cluster correlations has been studied in the intermediate mass fragment (IMF) emission in 12C+12C at 95 MeV/nucleon, using antisymmetrized molecular dynamics (AMD) model simulations. In AMD, the cluster correlation is introduced as a process to form light clusters with A ≤4 in the final states of a collision induced by the nucleon-nucleon residual interaction. Correlations between light clusters are also considered to form light nuclei with A ≤9 . This version of AMD, combined with GEMINI to calculate the decay of primary fragments, reproduces the experimental energy spectra of IMFs well overall with reasonable reproduction of light charged particles when we carefully analyze the excitation energies of primary fragments produced by AMD and their secondary decays. The results indicate that the cluster correlation plays a crucial role for producing fragments at relatively low excitation energies in the intermediate-energy heavy-ion collisions.

  10. From Points to Patterns - Functional Relations between Groundwater Connectivity and Catchment-scale Streamflow Response

    NASA Astrophysics Data System (ADS)

    Rinderer, M.; McGlynn, B. L.; van Meerveld, I. H. J.

    2016-12-01

    Groundwater measurements can help us to improve our understanding of runoff generation at the catchment-scale but typically only provide point-scale data. These measurements, therefore, need to be interpolated or upscaled in order to obtain information about catchment scale groundwater dynamics. Our approach used data from 51 spatially distributed groundwater monitoring sites in a Swiss pre-alpine catchment and time series clustering to define six groundwater response clusters. Each of the clusters was characterized by distinctly different site characteristics (i.e., Topographic Wetness Index and curvature), which allowed us to assign all unmonitored locations to one of these clusters. Time series modeling and the definition of response thresholds (i.e., the depth of more transmissive soil layers) allowed us to derive maps of the spatial distribution of active (i.e., responding) locations across the catchment at 15 min time intervals. Connectivity between all active locations and the stream network was determined using a graph theory approach. The extent of the active and connected areas differed during events and suggests that not all active locations directly contributed to streamflow. Gate keeper sites prevented connectivity of upslope locations to the channel network. Streamflow dynamics at the catchment outlet were correlated to catchment average connectivity dynamics. In a sensitivity analysis we tested six different groundwater levels for a site to be considered "active", which showed that the definition of the threshold did not significantly influence the conclusions drawn from our analysis. This study is the first one to derive patterns of groundwater dynamics based on empirical data (rather than interpolation) and provides insight into the spatio-temporal evolution of the active and connected runoff source areas at the catchment-scale that is critical to understanding the dynamics of water quantity and quality in streams.

  11. Formation and organization of protein domains in the immunological synapse

    NASA Astrophysics Data System (ADS)

    Carlson, Andreas; Mahadevan, L.

    2014-11-01

    The cellular basis for the adaptive immune response during antigen recognition relies on a specialized protein interface known as the immunological synapse. Here, we propose a minimal mathematical model for the dynamics of the IS that encompass membrane mechanics, hydrodynamics and protein kinetics. Simple scaling laws describe the dynamics of protein clusters as a function of membrane stiffness, rigidity of the adhesive proteins, and fluid flow in the synaptic cleft. Numerical simulations complement the scaling laws by quantifying the nucleation, growth and stabilization of proteins domains on the size of the cell. Direct comparison with experiment suggests that passive dynamics suffices to describe the short-time formation and organization of protein clusters, while the stabilization and long time dynamics of the synapse is likely determined by active cytoskeleton processes triggered by receptor binding. Our study reveals that the fluid flow generated by the interplay between membrane deformation and protein binding kinetics can assist immune cells in regulating protein sorting.

  12. Young star clusters in nearby molecular clouds

    NASA Astrophysics Data System (ADS)

    Getman, K. V.; Kuhn, M. A.; Feigelson, E. D.; Broos, P. S.; Bate, M. R.; Garmire, G. P.

    2018-06-01

    The SFiNCs (Star Formation in Nearby Clouds) project is an X-ray/infrared study of the young stellar populations in 22 star-forming regions with distances ≲ 1 kpc designed to extend our earlier MYStIX (Massive Young Star-Forming Complex Study in Infrared and X-ray) survey of more distant clusters. Our central goal is to give empirical constraints on cluster formation mechanisms. Using parametric mixture models applied homogeneously to the catalogue of SFiNCs young stars, we identify 52 SFiNCs clusters and 19 unclustered stellar structures. The procedure gives cluster properties including location, population, morphology, association with molecular clouds, absorption, age (AgeJX), and infrared spectral energy distribution (SED) slope. Absorption, SED slope, and AgeJX are age indicators. SFiNCs clusters are examined individually, and collectively with MYStIX clusters, to give the following results. (1) SFiNCs is dominated by smaller, younger, and more heavily obscured clusters than MYStIX. (2) SFiNCs cloud-associated clusters have the high ellipticities aligned with their host molecular filaments indicating morphology inherited from their parental clouds. (3) The effect of cluster expansion is evident from the radius-age, radius-absorption, and radius-SED correlations. Core radii increase dramatically from ˜0.08 to ˜0.9 pc over the age range 1-3.5 Myr. Inferred gas removal time-scales are longer than 1 Myr. (4) Rich, spatially distributed stellar populations are present in SFiNCs clouds representing early generations of star formation. An appendix compares the performance of the mixture models and non-parametric minimum spanning tree to identify clusters. This work is a foundation for future SFiNCs/MYStIX studies including disc longevity, age gradients, and dynamical modelling.

  13. Collective firm bankruptcies and phase transition in rating dynamics

    NASA Astrophysics Data System (ADS)

    Sieczka, P.; Hołyst, J. A.

    2009-10-01

    We present a simple model of firm rating evolution. We consider two sources of defaults: individual dynamics of economic development and Potts-like interactions between firms. We show that such a defined model leads to phase transition, which results in collective defaults. The existence of the collective phase depends on the mean interaction strength. For small interaction strength parameters, there are many independent bankruptcies of individual companies. For large parameters, there are giant collective defaults of firm clusters. In the case when the individual firm dynamics favors dumping of rating changes, there is an optimal strength of the firm's interactions from the systemic risk point of view. in here

  14. TethysCluster: A comprehensive approach for harnessing cloud resources for hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Nelson, J.; Jones, N.; Ames, D. P.

    2015-12-01

    Advances in water resources modeling are improving the information that can be supplied to support decisions affecting the safety and sustainability of society. However, as water resources models become more sophisticated and data-intensive they require more computational power to run. Purchasing and maintaining the computing facilities needed to support certain modeling tasks has been cost-prohibitive for many organizations. With the advent of the cloud, the computing resources needed to address this challenge are now available and cost-effective, yet there still remains a significant technical barrier to leverage these resources. This barrier inhibits many decision makers and even trained engineers from taking advantage of the best science and tools available. Here we present the Python tools TethysCluster and CondorPy, that have been developed to lower the barrier to model computation in the cloud by providing (1) programmatic access to dynamically scalable computing resources, (2) a batch scheduling system to queue and dispatch the jobs to the computing resources, (3) data management for job inputs and outputs, and (4) the ability to dynamically create, submit, and monitor computing jobs. These Python tools leverage the open source, computing-resource management, and job management software, HTCondor, to offer a flexible and scalable distributed-computing environment. While TethysCluster and CondorPy can be used independently to provision computing resources and perform large modeling tasks, they have also been integrated into Tethys Platform, a development platform for water resources web apps, to enable computing support for modeling workflows and decision-support systems deployed as web apps.

  15. A Smoluchowski model of crystallization dynamics of small colloidal clusters

    NASA Astrophysics Data System (ADS)

    Beltran-Villegas, Daniel J.; Sehgal, Ray M.; Maroudas, Dimitrios; Ford, David M.; Bevan, Michael A.

    2011-10-01

    We investigate the dynamics of colloidal crystallization in a 32-particle system at a fixed value of interparticle depletion attraction that produces coexisting fluid and solid phases. Free energy landscapes (FELs) and diffusivity landscapes (DLs) are obtained as coefficients of 1D Smoluchowski equations using as order parameters either the radius of gyration or the average crystallinity. FELs and DLs are estimated by fitting the Smoluchowski equations to Brownian dynamics (BD) simulations using either linear fits to locally initiated trajectories or global fits to unbiased trajectories using Bayesian inference. The resulting FELs are compared to Monte Carlo Umbrella Sampling results. The accuracy of the FELs and DLs for modeling colloidal crystallization dynamics is evaluated by comparing mean first-passage times from BD simulations with analytical predictions using the FEL and DL models. While the 1D models accurately capture dynamics near the free energy minimum fluid and crystal configurations, predictions near the transition region are not quantitatively accurate. A preliminary investigation of ensemble averaged 2D order parameter trajectories suggests that 2D models are required to capture crystallization dynamics in the transition region.

  16. Quantitative comparison of alternative methods for coarse-graining biological networks

    PubMed Central

    Bowman, Gregory R.; Meng, Luming; Huang, Xuhui

    2013-01-01

    Markov models and master equations are a powerful means of modeling dynamic processes like protein conformational changes. However, these models are often difficult to understand because of the enormous number of components and connections between them. Therefore, a variety of methods have been developed to facilitate understanding by coarse-graining these complex models. Here, we employ Bayesian model comparison to determine which of these coarse-graining methods provides the models that are most faithful to the original set of states. We find that the Bayesian agglomerative clustering engine and the hierarchical Nyström expansion graph (HNEG) typically provide the best performance. Surprisingly, the original Perron cluster cluster analysis (PCCA) method often provides the next best results, outperforming the newer PCCA+ method and the most probable paths algorithm. We also show that the differences between the models are qualitatively significant, rather than being minor shifts in the boundaries between states. The performance of the methods correlates well with the entropy of the resulting coarse-grainings, suggesting that finding states with more similar populations (i.e., avoiding low population states that may just be noise) gives better results. PMID:24089717

  17. Dynamics of multi-frequency oscillator ensembles with resonant coupling

    NASA Astrophysics Data System (ADS)

    Lück, S.; Pikovsky, A.

    2011-07-01

    We study dynamics of populations of resonantly coupled oscillators having different frequencies. Starting from the coupled van der Pol equations we derive the Kuramoto-type phase model for the situation, where the natural frequencies of two interacting subpopulations are in relation 2:1. Depending on the parameter of coupling, ensembles can demonstrate fully synchronous clusters, partial synchrony (only one subpopulation synchronizes), or asynchrony in both subpopulations. Theoretical description of the dynamics based on the Watanabe-Strogatz approach is developed.

  18. Modeling the polydomain-monodomain transition of liquid crystal elastomers.

    PubMed

    Whitmer, Jonathan K; Roberts, Tyler F; Shekhar, Raj; Abbott, Nicholas L; de Pablo, Juan J

    2013-02-01

    We study the mechanism of the polydomain-monodomain transition in liquid crystalline elastomers at the molecular scale. A coarse-grained model is proposed in which mesogens are described as ellipsoidal particles. Molecular dynamics simulations are used to examine the transition from a polydomain state to a monodomain state in the presence of uniaxial strain. Our model demonstrates soft elasticity, similar to that exhibited by side-chain elastomers in the literature. By analyzing the growth dynamics of nematic domains during uniaxial extension, we provide direct evidence that at a molecular level the polydomain-monodomain transition proceeds through cluster rotation and domain growth.

  19. Fast trimers in a one-dimensional extended Fermi-Hubbard model

    NASA Astrophysics Data System (ADS)

    Dhar, A.; Törmä, P.; Kinnunen, J. J.

    2018-04-01

    We consider a one-dimensional two-component extended Fermi-Hubbard model with nearest-neighbor interactions and mass imbalance between the two species. We study the binding energy of trimers, various observables for detecting them, and expansion dynamics. We generalize the definition of the trimer gap to include the formation of different types of clusters originating from nearest-neighbor interactions. Expansion dynamics reveal rapidly propagating trimers, with speeds exceeding doublon propagation in the strongly interacting regime. We present a simple model for understanding this unique feature of the movement of the trimers, and we discuss the potential for experimental realization.

  20. A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data.

    PubMed

    Manzi, Alessandro; Dario, Paolo; Cavallo, Filippo

    2017-05-11

    Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

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