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.
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.
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.
By means of contact-density chain-growth simulations, we investigate a simple lattice model of a flexible polymer interacting with an attractive substrate. The contact density is a function of the numbers of monomer-s...
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By means of contact-density chain-growth simulations, we investigate a simple lattice model of a flexible polymer interacting with an attractive substrate. The contact density is a function of the numbers of monomer-substrate and monomer-monomer contacts. These contact numbers represent natural order parameters and allow for a comprising statistical study of the conformational space accessible to the polymer in dependence of external parameters such as the attraction strength of the substrate and the temperature. Since the contact density is independent of the energy scales associated to the interactions, its logarithm is an unbiased measure for the entropy of the conformational space. By setting explicit energy scales, the thus defined, highly general microcontact entropy can easily be related to the microcanonical entropy of the corresponding hybrid polymer-substrate system. (C) 2010 Published by Elsevier B. V.
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.
computersimulationstudies in condensed-matterphysics VII provides a broad overview of recentdevelopments. Presented at the recentworkshop, it contains the invited and contributed papers which describe new physica...
ISBN:
(纸本)9783642792953
computersimulationstudies in condensed-matterphysics VII provides a broad overview of recentdevelopments. Presented at the recentworkshop, it contains the invited and contributed papers which describe new physical results, simulational techniques and ways of interpreting simulational data. Both classical and quantum systems are discussed.
computersimulationstudies in condensed-matterphysics VI provides a broad overview of recentdevelopments in this field. Based on the last workshop, it presents invited and contributed papers which describe new phys...
ISBN:
(纸本)9783642784507
computersimulationstudies in condensed-matterphysics VI provides a broad overview of recentdevelopments in this field. Based on the last workshop, it presents invited and contributed papers which describe new physical results, simulational techniques and ways of interpreting simulational data. Both classical and quantum systems are discussed.
computersimulationstudies in condensed-matterphysics VIprovides a broad overview of recentdevelopments in thisfield. Based on the last workshop, it presents invited andcontributed papers which describe new physic...
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ISBN:
(数字)9783642784484
ISBN:
(纸本)9783642784507
computersimulationstudies in condensed-matterphysics VI
provides a broad overview of recentdevelopments in this
field. Based on the last workshop, it presents invited and
contributed papers which describe new physical results,
simulational techniques and ways of interpreting
simulational data. Both classical and quantum systems are
discussed.
The canonical technique for Monte Carlo simulations in statistical physics is importance sampling via a suitably constructed Markov chain. While such approaches are quite successful, they are not particularly well sui...
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The canonical technique for Monte Carlo simulations in statistical physics is importance sampling via a suitably constructed Markov chain. While such approaches are quite successful, they are not particularly well suited for parallelization as the chain dynamics is sequential, and if replicated chains are used to increase statistics each of them relaxes into equilibrium with an intrinsic time constant that cannot be reduced by parallel work. Population annealing is a sequential Monte Carlo method that simulates an ensemble of system replica under a cooling protocol. The population element makes it naturally well suited for massively parallel simulations, and bias can be systematically reduced by increasing the population size. We present an implementation of population annealing on graphics processing units and discuss its behavior for different systems undergoing continuous and first-order phase transitions.
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