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Size Consistent Excited States via Algorithmic Transformations between Variational Principles.

作者信息

Shea Jacqueline A R, Neuscamman Eric

机构信息

Department of Chemistry, University of California , Berkeley, California 94720, United States.

Chemical Science Division, Lawrence Berkeley National Laboratory , Berkeley, California 94720, United States.

出版信息

J Chem Theory Comput. 2017 Dec 12;13(12):6078-6088. doi: 10.1021/acs.jctc.7b00923. Epub 2017 Nov 30.

DOI:10.1021/acs.jctc.7b00923
PMID:29140699
Abstract

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.

摘要

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