Preface thirty one years ago, because of the dramatic increase in the power and utility of computersimulations, the University of Georgia formed the first institutional unit devoted to the application of simulations ...
Preface thirty one years ago, because of the dramatic increase in the power and utility of computersimulations, the University of Georgia formed the first institutional unit devoted to the application of simulations in research and teaching: the Center for simulational physics. then, as the international simulations community expanded further, we sensed the need for a meeting place for both experienced simulators and newcomers to discuss inventive algorithms and recent results in an environment that promoted lively discussion. As a consequence, the Center for simulational physics established an annual workshop series on recentdevelopments in computersimulationstudies in condensedmatterphysics. this year's highly interactive workshop was the 30th in the series marking our efforts to promote high quality research in simulational physics. the continued interest shown by the scientific community amply demonstrates the useful purpose that these meetings have served. the latest workshop was held at the University of Georgia from February 20-24, 2017 and served to mark three decades of successful and highly interactive workshops. these Proceedings provide a 'status report' on a number of important topics. this on-line 'volume' is published withthe goal of timely dissemination of the material to a wider audience. these Proceedings contain both invited papers and contributed presentations on problems in both classical and quantum condensedmatterphysics. the day prior to the workshop we co-hosted, together with Riken, Japan, a Tutorial on the simulations management tool OACIS, and the Proceedings begins with an overview of the tutorial material. the workshop topics, as usual, ranged from hard and soft condensedmatter to biologically inspired problems and purely methodological advances. While familiar topics like phase transitions were still on display, the trends in biophysics, dynamical behavior and complex systems demonstrated the continuing progression in the foc
thirty years ago, because of the dramatic increase in the power and utility of computersimulations, the University of Georgia formed the first institutional unit devoted to the application of simulations in research ...
thirty years ago, because of the dramatic increase in the power and utility of computersimulations, the University of Georgia formed the first institutional unit devoted to the application of simulations in research and teaching: the Center for simulational physics. then, as the international simulations community expanded further, we sensed the need for a meeting place for both experienced simulators and newcomers to discuss inventive algorithms and recent results in an environment that promoted lively discussion. As a consequence, the Center for simulational physics established an annual workshop series on recentdevelopments in computersimulationstudies in condensedmatterphysics. this year's highly interactive workshop was the 29th in the series marking our efforts to promote high quality research in simulational physics. the continued interest shown by the scientific community amply demonstrates the useful purpose that these meetings have served. the latest workshop was held at the University of Georgia from February 22-26, 2016. It served to mark the 30th Anniversary of the founding of the Center for simulational physics. In addition, during this workshop we celebrated the 60th birthday of our esteemed colleague Prof. H.-Bernd Schuttler. Bernd has not only contributed to the understanding of strongly correlated electron system, but has made seminal contributions to systems biology through the introduction of modern methods of computational physics. these Proceedings provide a 'status report' on a number of important topics. this on-line 'volume' is published withthe goal of timely dissemination of the material to a wider audience. this program was supported in part by the President's Venture Fund through the generous gifts of the University of Georgia Partners and other donors. We also wish to offer thanks to the Office of the Vice-President for Research, the Franklin College of Arts and Sciences, and the IBM Corporation for partial support of this year's
this year’s workshop includes contributions which deal with several different aspects of the rapidly developing area of computersimulations in condensedmatterphysics. the invited talks are reported in rather long ...
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Coarse-grained solvent-free simulation models enabling the study of self-assembling fluid lipid bilayers have been the goal of much recent modeling efforts, since their realization appeared to be quite intricate. this...
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ISBN:
(纸本)9783540856245
Coarse-grained solvent-free simulation models enabling the study of self-assembling fluid lipid bilayers have been the goal of much recent modeling efforts, since their realization appeared to be quite intricate. this contribution reviews some of the challenges faced along the way, presents a surprisingly simple solution, and illustrates its capacity by means of three examples of biological interest.
Rare-event simulations can be limited by the wide range of time scales they must often probe. Using accelerated molecular dynamics in the framework of hyperdynamics, we overcome this limitation by identifying and cons...
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ISBN:
(纸本)9783540856245
Rare-event simulations can be limited by the wide range of time scales they must often probe. Using accelerated molecular dynamics in the framework of hyperdynamics, we overcome this limitation by identifying and consolidating groups of shallow minima into coarse states [1]. the method ensures a correct, equilibrium sampling of the fast processes while enabling the simulation to be run on the time scale of the slow events. We demonstrate the method in accelerated molecular-dynamics simulations of the diffusion of Co clusters on Cu(001) [2].
We present a computersimulation model that is strictly causal and local in Einstein's sense, does not rely on concepts of quantum theory but. can nevertheless reproduce the results of quantum theory for the singl...
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ISBN:
(纸本)9783540856245
We present a computersimulation model that is strictly causal and local in Einstein's sense, does not rely on concepts of quantum theory but. can nevertheless reproduce the results of quantum theory for the single-spin expectation values and two-spin correlations in an Einstem-Podolsky-Rosen-Bohm experiment.
We consider an individual-based two-dimensional spatial model with nearest-neighbor preemptive competition to study front propagation between an invader and a resident species. In particular, we investigate the asympt...
ISBN:
(纸本)9783540856245
We consider an individual-based two-dimensional spatial model with nearest-neighbor preemptive competition to study front propagation between an invader and a resident species. In particular, we investigate the asymptotic front. velocity and compare it, with mean-field predictions.
the Wang-Landau algorithm is an entropic sampling method that incoroporates an update factor ln f(i), which introduces a self-avoidance tendency into the random walk. Continued sampling at constant ln f(i) leads to a ...
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the Wang-Landau algorithm is an entropic sampling method that incoroporates an update factor ln f(i), which introduces a self-avoidance tendency into the random walk. Continued sampling at constant ln f(i) leads to a steady state estimate of the density of states ln g(i) (E). We find numerically that the difference between ln g(i) (E) and the true density of states ln g (E) is proportional to the update factor.
Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type o...
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Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type of machine learning algorithm that can provide a reproducible way to apply pattern recognition heuristics to underspecified problems. Here we use the open-source TensorFlow machine learning library and apply it to the problem of identifying which hypothetical observation sequences from a computersimulation are "equilibrated" and which are not. We generate training populations and test populations of observation sequences with embedded linear and exponential correlations. We train a twoneuron artificial network to distinguish the correlated and uncorrelated sequences. We find that this simple network is good enough for > 98% accuracy in identifying exponentially-decaying energy trajectories from molecular simulations.
Nature often arranges atoms in the shape of perfect crystals, but sometimes she creates defects and multiple domains. the optimal crystal shape at zero kelvin can be found via the Wulff construction, which can be only...
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Nature often arranges atoms in the shape of perfect crystals, but sometimes she creates defects and multiple domains. the optimal crystal shape at zero kelvin can be found via the Wulff construction, which can be only be carried out analytically for those trivial cases where next nearest neighbour interactions can be neglected. For our system of interest - videlicit the HCP non-Bravais case, numerical simulation is needed. this system is of relevance because we are modeling helium crystals. We have modeled two adjacent crystallites with different orientations in contact creating twist or tilt grain boundaries, and calculated the surface energy of the interface. Experience gained from several aspects of this project have a wider applications, including the condensedmattersimulation application to sample construction for multi-domain crystals, and a visualization one for representation in the presence of grain boundaries. the optimization of sample shapes into their groundstates is also related to wavefront optimization in multimirror telescopes.
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