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Bypassing the Kohn-Sham equations with machine learning

Authors :
Felix Brockherde
Leslie Vogt
Li Li
Mark E. Tuckerman
Kieron Burke
Klaus-Robert Müller
Source :
Nature Communications, Vol 8, Iss 1, Pp 1-10 (2017)
Publication Year :
2017
Publisher :
Nature Portfolio, 2017.

Abstract

Machine learning allows electronic structure calculations to access larger system sizes and, in dynamical simulations, longer time scales. Here, the authors perform such a simulation using a machine-learned density functional that avoids direct solution of the Kohn-Sham equations.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
8
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.5eb66063f9824f3e9aa4606612d626ee
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-017-00839-3