Stochastic potential switching algorithm for Monte Carlo simulations of complex systems
Stochastic potential switching algorithm for Monte Carlo simulations of complex systems
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DOI：
10.1063/1.1925273
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发表时间：
2005-06-01
影响因子：
4.4
通讯作者：
Mak, CH
中科院分区：
文献类型：
--
作者：
Mak, CH
本文介绍了一种新的蒙特卡罗方法的基础上，一种新的随机电位开关算法。该算法使一个系统的平衡性能与潜在的V计算使用Monte Carlo模拟的一个系统可能不太复杂的随机改变的电位（V）在波浪线。通过适当地选择随机开关和转移概率，它表明，详细的平衡，可以严格保持相对于原始的潜力V。一个简单的一维例子说明了该方法的有效性。然后，该方法推广到多维系统的任何添加剂的潜力，提供了一个框架，设计更有效的算法来模拟复杂的系统。一个近临界的Lennard-Jones流体与超过20000个粒子被用来说明该方法。与大都会方法相比，新算法产生了更小的动态标度指数，并将采样效率提高了一个数量级以上。(c)2005年美国物理学会。
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 (V) over tilde. 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. (c) 2005 American Institute of Physics.