Stochastic Potential Switching Algorithm for Monte Carlo Simulations of Complex Systems

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dc.creatorMak, C. H.
dc.date2006-02-14
dc.date.accessioned2026-07-07T07:01:42Z
dc.date.available2026-07-07T07:01:42Z
dc.descriptionThis 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.
dc.description7 pages, 5 figures
dc.identifierhttps://arxiv.org/abs/cond-mat/0602325
dc.identifierhttp://arxiv.org/abs/cond-mat/0602325
dc.identifierJOURNAL OF CHEMICAL PHYSICS 122 (21): Art. No. 214110 JUN 1 2005
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/108354
dc.subjectStatistical Mechanics
dc.titleStochastic Potential Switching Algorithm for Monte Carlo Simulations of Complex Systems
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