Teaching spin symmetry while learning neural network wave functions: Quantum chemistry

Yongle Li; Yuhao Chen; Xiao He

doi:10.1038/s43588-024-00727-z

Teaching spin symmetry while learning neural network wave functions: Quantum chemistry

Yongle Li, Yuhao Chen, Xiao He

School of Chemistry and Molecular Engineering

Shanghai University

Research output: Contribution to journal › Comment/debate

Abstract

By developing an efficient spin symmetry penalty, a recent study has substantially accelerated the calculation of accurate energies with correct spin states in variational Monte Carlo for both ground and excited states of quantum many-particle systems.

Original language	English
Pages (from-to)	884-885
Number of pages	2
Journal	Nature Computational Science
Volume	4
Issue number	12
DOIs	https://doi.org/10.1038/s43588-024-00727-z
State	Published - Dec 2024

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title = "Teaching spin symmetry while learning neural network wave functions: Quantum chemistry",

abstract = "By developing an efficient spin symmetry penalty, a recent study has substantially accelerated the calculation of accurate energies with correct spin states in variational Monte Carlo for both ground and excited states of quantum many-particle systems.",

author = "Yongle Li and Yuhao Chen and Xiao He",

note = "Publisher Copyright: {\textcopyright} Springer Nature America, Inc. 2024.",

year = "2024",

month = dec,

doi = "10.1038/s43588-024-00727-z",

language = "英语",

volume = "4",

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journal = "Nature Computational Science",

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T1 - Teaching spin symmetry while learning neural network wave functions

T2 - Quantum chemistry

AU - Li, Yongle

AU - Chen, Yuhao

AU - He, Xiao

N1 - Publisher Copyright: © Springer Nature America, Inc. 2024.

PY - 2024/12

Y1 - 2024/12

N2 - By developing an efficient spin symmetry penalty, a recent study has substantially accelerated the calculation of accurate energies with correct spin states in variational Monte Carlo for both ground and excited states of quantum many-particle systems.

AB - By developing an efficient spin symmetry penalty, a recent study has substantially accelerated the calculation of accurate energies with correct spin states in variational Monte Carlo for both ground and excited states of quantum many-particle systems.

UR - https://www.scopus.com/pages/publications/85211500930

U2 - 10.1038/s43588-024-00727-z

DO - 10.1038/s43588-024-00727-z

M3 - 评论/辩论

AN - SCOPUS:85211500930

SN - 2662-8457

VL - 4

SP - 884

EP - 885

JO - Nature Computational Science

JF - Nature Computational Science

IS - 12

ER -

Teaching spin symmetry while learning neural network wave functions: Quantum chemistry

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