Nakayama Akira, Seki Nanami, Taketsugu Tetsuya
Division of Chemistry, Graduate School of Science, Hokkaido University, Sapporo 060-0810, Japan.
J Chem Phys. 2009 Jan 14;130(2):024107. doi: 10.1063/1.3055910.
An approach is developed to enhance sampling for ab initio Monte Carlo and ab initio path integral Monte Carlo calculations of molecular clusters by utilizing an approximate potential as a guide to move in the configuration space more efficiently. The interpolated potential energy obtained by the moving least-squares method is used as an approximate potential, and this scheme is applied to a water molecule and small protonated water clusters (H(3)O(+), H(5)O(2)(+)). It is found that the statistical errors are reduced by almost a factor of 3 in most calculations, which translates into a reduction in the computational cost by an order of magnitude. We also provide an automatic scheme where the ab initio data obtained during the simulation is added to the reference data set of interpolation dynamically, which further speeds up the convergence.
开发了一种方法,通过利用近似势作为在构型空间中更有效移动的指南,来增强分子簇的从头算蒙特卡罗和从头算路径积分蒙特卡罗计算的采样。通过移动最小二乘法获得的插值势能用作近似势,并将该方案应用于水分子和小的质子化水簇(H(3)O(+)、H(5)O(2)(+))。发现在大多数计算中统计误差几乎降低了3倍,这意味着计算成本降低了一个数量级。我们还提供了一种自动方案,其中在模拟过程中获得的从头算数据会动态添加到插值的参考数据集中,这进一步加快了收敛速度。