Monte Carlo techniques in statistical physics

Details Monte Carlo techniques in statistical physics Monte Carlo techniques in statistical physics

Nov 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006smpr.confe..18m&link_type=abstract

Proceedings of the International conference on Statistical Mechanics of Plasticity and Related Instabilities. August 29-Septembe

Physics

Condensed Matter

Statistical Mechanics

Scientific paper

In this paper we shall briefly review a few Markov Chain Monte Carlo methods for simulating closed systems described by canonical ensembles. We cover both Boltzmann and non-Boltzmann sampling techniques. The Metropolis algorithm is a typical example of Boltzmann Monte Carlo method. We discuss the time-symmetry of the Markov chain generated by Metropolis like algo- rithms that obey detailed balance. The non-Boltzmann Monte Carlo techniques reviewed include the multicanonical and Wang-Landau sampling. We list what we consider as milestones in the historical development of Monte Carlo methods in statistical physics. We dedicate this article to Prof. Dr. G. Ananthakrishna and wish him the very best in the coming years

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