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Size Consistent Excited States via Algorithmic Transformations between Variational Principles

delete2017-11-30
delete39
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OA
AI
J
Jacqueline A. R. Shea
E
Eric Neuscamman *
DOI:10.1021/acs.jctc.7b00923delete
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摘要

摘要

En 中文
We demonstrate that a broad class of excited state variational principles is not size consistent. In light of this difficulty, we develop and test an approach to excited state optimization that transforms between variational principles to achieve state selectivity, size consistency, and compatibility with quantum Monte Carlo. To complement our formal analysis, we provide numerical examples that confirm these properties and demonstrate how they contribute to a more black box approach to excited states in quantum Monte Carlo.
Keyword:
MOLECULAR-ORBITAL METHODS
WAVE-FUNCTIONS
MONTE-CARLO
QUANTUM-CHEMISTRY
OPTIMIZATION
FUNCTIONALS
MODEL

期刊

Journal of Chemical Theory and Computation 封面图
Journal of Chemical Theory and Computation
IF:
5.5
论文数:
1.1W
被引数:
5.4W

机构

University of California System 封面图
University of California System
学者数:
37.7W
论文数: 33.8W
被引数: 6.6K
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