Simulation of Spin Chains with Off-Diagonal Coupling Using the Inchworm Method

IF 5.7 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation Pub Date : 2024-10-18 DOI:10.1021/acs.jctc.4c00864

Yixiao Sun, Geshuo Wang, Zhenning Cai

引用次数: 0

Abstract

We study the dynamical simulation of an open quantum spin chain with nearest neighboring coupling, where each spin in the chain is associated with a harmonic bath. This is an extension of our previous work (Wang, G.; Cai, Z. J. Chem. Theory Comput. 2023, 19, 8523–8540) by generalizing the application of the inchworm method and the technique of modular path integrals from diagonally coupled cases to off-diagonally coupled cases. Additionally, to reduce computational and memory cost in long time simulation, we apply tensor-train representation to efficiently represent the reduced density matrix of the spin chains, and employ the transfer tensor method (TTM) to avoid exponential growth of computational cost with respect to time. Abundant numerical experiments are performed to validate our method.

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使用 Inchworm 方法模拟具有非对角耦合的自旋链

我们研究了具有近邻耦合的开放量子自旋链的动力学模拟，链中的每个自旋都与谐波浴相关。这是对我们以前的工作（Wang, G.; Cai, Z. J. Chem. Theory Comput.此外，为了降低长时间模拟的计算和内存成本，我们采用张量-列车表示法来有效表示自旋链的还原密度矩阵，并采用转移张量法 (TTM) 来避免计算成本随时间呈指数增长。我们进行了大量的数值实验来验证我们的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Chemical Theory and Computation 化学-物理：原子、分子和化学物理

CiteScore

9.90

自引率

16.40%

发文量

568

审稿时长

1 months

期刊介绍： The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.