相互关联。

IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL
Francesco A Evangelista
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引用次数: 0

摘要

量化量子多体态的相关性和复杂性是推进理论和计算化学、物理学和量子信息科学的核心。这项工作引入了一个新的框架,相互关联,基于两体简化密度矩阵累积量的Frobenius范数平方。通过对累积范数的系统划分,相互关联量化了相互作用子系统之间的非加性关联。为了评估相互关联识别轨道相互作用的能力,我们对包括H10、N2和对苯在内的模型系统进行了基准研究,并对轨道相互信息进行了形式和数值比较。通过最大化相互关联的非线性代价函数得到的最大相关轨道,也被认为是识别无关基的相关划分。该研究表明,互相关是一种广泛适用的度量,在主动空间选择和电子状态解释中很有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mutual Correlation.

Quantifying correlation and complexity in quantum many-body states is central to advancing theoretical and computational chemistry, physics, and quantum information science. This work introduces a novel framework, mutual correlation, based on the Frobenius norm squared of the two-body reduced density matrix cumulant. Through systematic partitioning of the cumulant norm, mutual correlation quantifies nonadditive correlations among interacting subsystems. To assess the ability of mutual correlation to identify orbital interactions, we performed benchmark studies on model systems, including H10, N2, and p-benzyne, and performed a formal and numerical comparison with orbital mutual information. Maximally correlated orbitals, obtained by maximizing a nonlinear cost function of the mutual correlation, are also considered to identify a basis-independent partitioning of correlation. This study suggests that mutual correlation is a broadly applicable metric, useful in active space selection and the interpretation of electronic states.

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来源期刊
Journal of Chemical Theory and Computation
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Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere.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.
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