Markov Chain Monte Carlo Methods in Statistical Physics
نویسندگان
چکیده
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 algorithms 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.
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