Vincent Mark A, Silva Arnaldo F, Popelier Paul L A
Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN, UK.
School of Chemistry, The University of Manchester, Manchester, M13 9PL, UK.
J Comput Chem. 2019 Dec 15;40(32):2793-2800. doi: 10.1002/jcc.26037. Epub 2019 Aug 2.
Recently, the quantum topological energy partitioning method called interacting quantum atoms (IQA) has been extended to MPn (n = 2, 3, 4) wave functions. This enables the extraction of chemical insight related to dynamic electron correlation. The large computational expense of the IQA-MPn approach is compensated by the advantages that IQA offers compared to older nontopological energy decomposition schemes. This expense is problematic in the construction of a machine learning training set to create kriging models for topological atoms. However, the algorithm presented here markedly accelerates the calculation of atomically partitioned electron correlation energies. Then again, the algorithm cannot calculate pairwise interatomic energies because it applies analytical integrals over whole space (rather than over atomic volumes). However, these pairwise energies are not needed in the quantum topological force field FFLUX, which only uses the energy of an atom interacting with all remaining atoms of the system that it is part of. Thus, it is now feasible to generate accurate and sizeable training sets at MPn level of theory. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.
最近,一种名为相互作用量子原子(IQA)的量子拓扑能量划分方法已扩展到MPn(n = 2、3、4)波函数。这使得与动态电子相关性相关的化学见解得以提取。与旧的非拓扑能量分解方案相比,IQA提供的优势弥补了IQA-MPn方法巨大的计算成本。在构建用于创建拓扑原子克里金模型的机器学习训练集时,这种成本是个问题。然而,这里提出的算法显著加速了原子划分电子相关能的计算。再者,该算法无法计算成对原子间能量,因为它应用的是整个空间上的解析积分(而非原子体积上的积分)。然而,在量子拓扑力场FFLUX中并不需要这些成对能量,该力场仅使用原子与它所属系统中所有其余原子相互作用的能量。因此,现在在MPn理论水平上生成准确且规模可观的训练集是可行的。© 2019作者。《计算化学杂志》由威利期刊公司出版。