Accelerating the weighted histogram analysis method by direct inversion in the iterative subspace.
Accelerating the weighted histogram analysis method by direct inversion in the iterative subspace.
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DOI：
10.1080/08927022.2015.1110583
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发表时间：
2016
影响因子：
2.1
通讯作者：
Pettitt BM
中科院分区：
文献类型：
--
作者：
Zhang C;Lai CL;Pettitt BM
用于自由能计算的加权直方图分析方法(WHAM)是以最小误差产生自由能差的有价值的工具。在给出多次模拟的情况下，WHAM从分布中得到的态密度的最优统计估计值与可以计算自由能差的最优统计估计值重叠。WHAM方程通常采用迭代方法求解。在这项工作中，我们使用了一种著名的线性代数算法，该算法允许更快地收敛到解。我们发现，在迭代子空间中使用直接逆方法可以改善WHAM和与之密切相关的多重Bennett接受率(MBAR)方法的迭代解的计算复杂性。我们给出了晶格模型、简单液体和蛋白质水溶液的例子。
The weighted histogram analysis method (WHAM) for free energy calculations is a valuable tool to produce free energy differences with the minimal errors. Given multiple simulations, WHAM obtains from the distribution overlaps the optimal statistical estimator of the density of states, from which the free energy differences can be computed. The WHAM equations are often solved by an iterative procedure. In this work, we use a well-known linear algebra algorithm which allows for more rapid convergence to the solution. We find that the computational complexity of the iterative solution to WHAM and the closely-related multiple Bennett acceptance ratio (MBAR) method can be improved by using the method of direct inversion in the iterative subspace. We give examples from a lattice model, a simple liquid and an aqueous protein solution.