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Monte Carlo with Absorbing Markov Chains: Fast Local Algorithms for Slow Dynamics

M. A. Novotny
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Abstract

A class of Monte Carlo algorithms which incorporate absorbing Markov chains is presented. In a particular limit, the lowest-order of these algorithms reduces to the $n$-fold way algorithm. These algorithms are applied to study the escape from the metastable state in the two-dimensional square-lattice nearest-neighbor Ising ferromagnet in an unfavorable applied field, and the agreement with theoretical predictions is very good. It is demonstrated that the higher-order algorithms can be many orders of magnitude faster than either the traditional Monte Carlo or $n$-fold way algorithms.

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M. A. Novotny. 1995-06-29. Monte Carlo with Absorbing Markov Chains: Fast Local Algorithms for Slow Dynamics. https://doi.org/10.1103/physrevlett.74.1

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