Department of Computational Biology, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA.
J Chem Phys. 2009 Dec 7;131(21):214110. doi: 10.1063/1.3269674.
We demonstrate a nondynamical Monte Carlo method to compute free energies and generate equilibrium ensembles of dense fluids. In this method, based on step-by-step polymer growth algorithms, an ensemble of n+1 particles is obtained from an ensemble of n particles by generating configurations of the n+1st particle. A statistically rigorous resampling scheme is utilized to remove configurations with low weights and to avoid a combinatorial explosion; the free energy is obtained from the sum of the weights. In addition to the free energy, the method generates an equilibrium ensemble of the full system. We consider two different system sizes for a Lennard-Jones fluid and compare the results with conventional Monte Carlo methods.
我们展示了一种非动力蒙特卡罗方法，用于计算自由能并生成密集流体的平衡系综。在这种方法中，基于逐步聚合物生长算法，通过生成第 n+1 个粒子的构型，从 n 个粒子的系综中获得 n+1 个粒子的系综。利用严格的统计重采样方案来去除权重较低的构型，以避免组合爆炸；自由能是从权重的总和中得到的。除了自由能，该方法还生成了整个系统的平衡系综。我们考虑了两种不同的 Lennard-Jones 流体系统大小，并将结果与传统的蒙特卡罗方法进行了比较。
