The multigrid POTFIT (MGPF) method: grid representations of potentials for quantum dynamics of large systems.
The multigrid POTFIT (MGPF) method: grid representations of potentials for quantum dynamics of large systems.
复制标题
多重网格 POTFIT (MGPF) 方法：大型系统量子动力学势的网格表示。
作者：
D. Peláez;H. Meyer
本文提出了一种新的多网格POTFIT方法(MGPF)。MGPF是一种基于网格的算法，它将一般的势能面转换为乘积形式，即一维函数的乘积和。为了从量子动力学的多组态依赖时间的哈特里方法中获益，这种形式是必要的。MGPF回避了POTFIT中存在的与维度相关的问题[A.Jäck和H.-D.Meyer，J.Chem]。太棒了。104,7974(1996)]，允许对大约12维的系统进行量子动力学研究。MGPF需要定义细网格和粗网格，后者是前者的子集。MGPF近似依赖于一系列基本的POTFIT网格计算，这些网格比精细网格小，大于或等于粗网格。这一方面使MGPF的精确度略低于POTFIT，但速度比POTFIT快几个数量级，内存需求比POTFIT少几个数量级。此外，与POTFIT一样，MGPF是可变的，并且提供了一种有效的差错控制。
In this article, a new method, multigrid POTFIT (MGPF), is presented. MGPF is a grid-based algorithm which transforms a general potential energy surface into product form, that is, a sum of products of one-dimensional functions. This form is necessary to profit from the computationally advantageous multiconfiguration time-dependent Hartree method for quantum dynamics. MGPF circumvents the dimensionality related issues present in POTFIT [A. Jäckle and H.-D. Meyer, J. Chem. Phys. 104, 7974 (1996)], allowing quantum dynamical studies of systems up to about 12 dimensions. MGPF requires the definition of a fine grid and a coarse grid, the latter being a subset of the former. The MGPF approximation relies on a series of underlying POTFIT calculations on grids which are smaller than the fine one and larger than or equal to the coarse one. This aspect makes MGPF a bit less accurate than POTFIT but orders of magnitude faster and orders of magnitude less memory demanding than POTFIT. Moreover, like POTFIT, MGPF is variational and provides an efficient error control.
DOI：
10.1063/1.4729536
发表时间：
2012
期刊：
The Journal of chemical physics
影响因子：
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作者：
K. Sadri;D. Lauvergnat;F. Gatti ;H.-D. Meyer
通讯作者：
H.-D. Meyer