中国科学技术大学学报 ›› 2020, Vol. 50 ›› Issue (6): 811-818.DOI: 10.3969/j.issn.0253-2778.2020.06.013

• 论著 • 上一篇    下一篇

一种基于哈密顿矩阵的电子波函数演化算法

王涛,张国桢,杨丽,江俊   

  • 收稿日期:2020-03-10 修回日期:2020-06-20 接受日期:2020-06-20 出版日期:2020-06-30 发布日期:2020-06-20
  • 通讯作者: 杨丽
  • 作者简介:王涛,男,1991年生,硕士生. 研究方向: 理论与计算化学. E-mail: wto42@mail.ustc.edu.cn
  • 基金资助:
    国家自然科学基金青年科学基金(21803063)资助.

A Hamiltonian matrix based algorithm for simulating evolution of electronic wave functions

WANG Tao, ZHANG Guozhen, YANG Li, JIANG Jun   

  • Received:2020-03-10 Revised:2020-06-20 Accepted:2020-06-20 Online:2020-06-30 Published:2020-06-20

摘要: 电子的运动与演化是贯穿许多物理化学过程的主线,而对这一过程的精确模拟和分析是发展有效的电子调控方法和应用的关键.传统方法,如TDHF(time-dependent Hartree-Fock)、TDDFT(time-dependent density functional theory)等,在模拟小尺度体系内的电子演化时表现优异,然而,在模拟大尺度体系时计算复杂度偏高,成本较大.在一些大尺度体系内,原子核位置相对固定,并且微扰对整体相互作用的哈密顿量影响较小.为此提出了一种简单有效的基于哈密顿矩阵的电子波函数演化方法,这一方法能处理远远大于TDDFT计算尺度的大体系.通过将该方法应用于四个不同的体系进行测试分析,验证了这一方法在处理大体系时的可行性,并为相关的电子调控应用提供了新的思路.

关键词: 电子演化, TDHF, TDDFT, 大尺度体系, 演化算法

Abstract: Accurate simulation and analysis of electronic motion and evolution are the key to developing efficient electron modulation methods for practical applications.Some traditional methods, such as TDHF(time-dependent Hartree-Fock) and TDDFT (time-dependent density functional theory), work well when dealing with small scale systems. However, they are not suitable enough for large scale systems, in terms of computational complexity and costs.Considering that in some large systems the relative position of atoms are quite stable, and perturbations have limited effect on inner interaction Hamiltonian, a simple yet effective method is proposed capable of quickly simulating the evolution of electronic wave function based on Hamiltonian matrix. The method is applied in four different systems and the results demonstrate the applicability of this algorithm to treat the charge evolution behavior in large systems, providing a new perspective for the development of electron modulation.

Key words: electron evolution, TDHF, TDDFT, large scale system, evolutionary algorithm

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