Chelli Riccardo
Dipartimento di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy and European Laboratory for Nonlinear Spectroscopy (LENS), Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy.
J Chem Theory Comput. 2010 Jul 13;6(7):1935-50. doi: 10.1021/ct100105z.
In serial generalized-ensemble simulations, the sampling of a collective coordinate of a system is enhanced through non-Boltzmann weighting schemes. A popular version of such methods is certainly the simulated tempering technique, which is based on a random walk in temperature ensembles to explore the phase space more thoroughly. The most critical aspect of serial generalized-ensemble methods with respect to their parallel counterparts, such as replica exchange, is the difficulty of weight determination. Here we propose an adaptive approach to update the weights on the fly during the simulation. The algorithm is based on generalized forms of the Bennett acceptance ratio and of the free energy perturbation. It does not require intensive communication between processors and, therefore, is prone to be used in distributed computing environments with modest computational cost. We illustrate the method in a series of molecular dynamics simulations of a model system and compare its performances to two recent approaches, one based on adaptive Bayesian-weighted histogram analysis and the other based on initial estimates of weight factors obtained by potential energy averages.
在串行广义系综模拟中，通过非玻尔兹曼加权方案增强了系统集体坐标的采样。这类方法中一种流行的版本无疑是模拟回火技术，它基于温度系综中的随机游走，以更全面地探索相空间。与并行广义系综方法（如副本交换）相比，串行广义系综方法最关键的方面是权重确定的困难。在此，我们提出一种自适应方法，在模拟过程中实时更新权重。该算法基于贝内特接受率和自由能微扰的广义形式。它不需要处理器之间进行密集通信，因此易于在具有适度计算成本的分布式计算环境中使用。我们在一个模型系统的一系列分子动力学模拟中说明了该方法，并将其性能与最近的两种方法进行比较，一种基于自适应贝叶斯加权直方图分析，另一种基于通过势能平均值获得的权重因子初始估计。
