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Stochastic Potential Switching Algorithm for Monte Carlo Simulations of Complex Systems

C. H. Mak
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Abstract

This paper describes a new Monte Carlo method based on a novel stochastic potential switching algorithm. This algorithm enables the equilibrium properties of a system with potential $V$ to be computed using a Monte Carlo simulation for a system with a possibly less complex stochastically altered potential $\tilde V$. By proper choices of the stochastic switching and transition probabilities, it is shown that detailed balance can be strictly maintained with respect to the original potential $V$. The validity of the method is illustrated with a simple one-dimensional example. The method is then generalized to multidimensional systems with any additive potential, providing a framework for the design of more efficient algorithms to simulate complex systems. A near-critical Lennard-Jones fluid with more than 20000 particles is used to illustrate the method. The new algorithm produced a much smaller dynamic scaling exponent compared to the Metropolis method and improved sampling efficiency by over an order of magnitude.

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BibTeXRIS

C. H. Mak. 2006-02-14. Stochastic Potential Switching Algorithm for Monte Carlo Simulations of Complex Systems. https://arxiv.org/abs/cond-mat/0602325

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