Bypassing the Kohn-Sham equations with machine learning

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.

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Autores principales:	Felix Brockherde, Leslie Vogt, Li Li, Mark E. Tuckerman, Kieron Burke, Klaus-Robert Müller
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/5eb66063f9824f3e9aa4606612d626ee
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spelling	oai:doaj.org-article:5eb66063f9824f3e9aa4606612d626ee2021-12-02T15:36:59ZBypassing the Kohn-Sham equations with machine learning10.1038/s41467-017-00839-32041-1723https://doaj.org/article/5eb66063f9824f3e9aa4606612d626ee2017-10-01T00:00:00Zhttps://doi.org/10.1038/s41467-017-00839-3https://doaj.org/toc/2041-1723Machine 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.Felix BrockherdeLeslie VogtLi LiMark E. TuckermanKieron BurkeKlaus-Robert MüllerNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Felix Brockherde Leslie Vogt Li Li Mark E. Tuckerman Kieron Burke Klaus-Robert Müller Bypassing the Kohn-Sham equations with machine learning
description	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.
format	article
author	Felix Brockherde Leslie Vogt Li Li Mark E. Tuckerman Kieron Burke Klaus-Robert Müller
author_facet	Felix Brockherde Leslie Vogt Li Li Mark E. Tuckerman Kieron Burke Klaus-Robert Müller
author_sort	Felix Brockherde
title	Bypassing the Kohn-Sham equations with machine learning
title_short	Bypassing the Kohn-Sham equations with machine learning
title_full	Bypassing the Kohn-Sham equations with machine learning
title_fullStr	Bypassing the Kohn-Sham equations with machine learning
title_full_unstemmed	Bypassing the Kohn-Sham equations with machine learning
title_sort	bypassing the kohn-sham equations with machine learning
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/5eb66063f9824f3e9aa4606612d626ee
work_keys_str_mv	AT felixbrockherde bypassingthekohnshamequationswithmachinelearning AT leslievogt bypassingthekohnshamequationswithmachinelearning AT lili bypassingthekohnshamequationswithmachinelearning AT marketuckerman bypassingthekohnshamequationswithmachinelearning AT kieronburke bypassingthekohnshamequationswithmachinelearning AT klausrobertmuller bypassingthekohnshamequationswithmachinelearning
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Bypassing the Kohn-Sham equations with machine learning

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