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Gibbs free-energy estimates from direct path-sampling computations

机译:直接路径采样计算得出的吉布斯自由能估计

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We have implemented a path-sampling scheme enabling a direct estimation of Gibbs free energy.This scheme consists of a Monte Carlo sampling of constant-pressure Langevin paths,followed by an ensemble averaging carried out over the Markov chain of paths.In practice,we sample an umbrella path ensemble,which requires to rigorously define a statistical weight for the paths,equivalent of the Boltzmann weight.This statistical weight is a function of an effective work related to the path.The umbrella ensemble is chosen so that its work histogram overlaps with the histograms corresponding to the ensembles of forward and backward paths.We have finally investigated the relations between numerical efficiency and overlapping properties of the various work histograms.This analysis yields a built-in criterion for diagnosing the convergence during a single-run simulation.
机译:我们实施了一种路径采样方案,可以直接估算吉布斯自由能。该方案包括恒压Langevin路径的蒙特卡洛采样,然后是对路径的马尔可夫链进行的总体平均。对伞形路径集合进行抽样,这需要严格定义路径的统计权重,相当于玻尔兹曼权重。此统计权重是与路径相关的有效功的函数。选择伞形集合以使其工作直方图重叠最后,我们研究了各种工作直方图的数值效率与重叠特性之间的关系,该分析为单次运行仿真中的收敛性诊断提供了内置标准。

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