Literature DB >> 20365093

Event-chain Monte Carlo algorithms for hard-sphere systems.

Etienne P Bernard1, Werner Krauth, David B Wilson.   

Abstract

In this paper we present the event-chain algorithms, which are fast Markov-chain Monte Carlo methods for hard spheres and related systems. In a single move of these rejection-free methods, an arbitrarily long chain of particles is displaced, and long-range coherent motion can be induced. Numerical simulations show that event-chain algorithms clearly outperform the conventional Metropolis method. Irreversible versions of the algorithms, which violate detailed balance, improve the speed of the method even further. We also compare our method with a recent implementations of the molecular-dynamics algorithm.

Mesh:

Year:  2009        PMID: 20365093     DOI: 10.1103/PhysRevE.80.056704

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  5 in total

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Authors:  John Russo; Hajime Tanaka
Journal:  Proc Natl Acad Sci U S A       Date:  2015-05-18       Impact factor: 11.205

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Authors:  Isabella Petrelli; Pasquale Digregorio; Leticia F Cugliandolo; Giuseppe Gonnella; Antonio Suma
Journal:  Eur Phys J E Soft Matter       Date:  2018-10-25       Impact factor: 1.890

3.  Entropy-controlled cross-linking in linker-mediated vitrimers.

Authors:  Qun-Li Lei; Xiuyang Xia; Juan Yang; Massimo Pica Ciamarra; Ran Ni
Journal:  Proc Natl Acad Sci U S A       Date:  2020-10-21       Impact factor: 11.205

4.  Acceleration of Convergence to Equilibrium in Markov Chains by Breaking Detailed Balance.

Authors:  Marcus Kaiser; Robert L Jack; Johannes Zimmer
Journal:  J Stat Phys       Date:  2017-05-18       Impact factor: 1.548

5.  Spatiotemporal blocking of the bouncy particle sampler for efficient inference in state-space models.

Authors:  Jacob Vorstrup Goldman; Sumeetpal S Singh
Journal:  Stat Comput       Date:  2021-09-01       Impact factor: 2.559

  5 in total

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