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Bootstrap Embedding for Molecules
Author(s) -
HongZhou Ye,
Nathan D. Ricke,
Henry K. Tran,
Troy Van Voorhis
Publication year - 2019
Publication title -
journal of chemical theory and computation
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/acs.jctc.9b00529
Subject(s) - embedding , quantum entanglement , scaling , fragment (logic) , fragmentation (computing) , molecule , statistical physics , computer science , fragment molecular orbital , localized molecular orbitals , physics , algorithm , quantum , quantum mechanics , molecular orbital , mathematics , artificial intelligence , linear combination of atomic orbitals , geometry , operating system
Fragment embedding is one way to circumvent the high computational scaling of accurate electron correlation methods. The challenge of applying fragment embedding to molecular systems primarily lies in the strong entanglement and correlation that prevent accurate fragmentation across chemical bonds. Recently, Schmidt decomposition has been shown effective for embedding fragments that are strongly coupled to a bath in several model systems. In this work, we extend a recently developed quantum embedding scheme, bootstrap embedding (BE), to molecular systems. The resulting method utilizes the matching conditions naturally arising from using overlapping fragments to optimize the embedding. Numerical simulation suggests that the accuracy of the embedding improves rapidly with fragment size for small molecules, whereas larger fragments that include orbitals from different atoms may be needed for larger molecules. BE scales linearly with system size (apart from an integral transform) and hence can potentially be useful for large-scale calculations.

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