Efficient representation of quantum many-body states with deep neural networks

One of the challenges in studies of quantum many-body physics is finding an efficient way to record the large system wavefunctions. Here the authors present an analysis of the capabilities of recently-proposed neural network representations for storing physically accessible quantum states.

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Detalles Bibliográficos
Autores principales:	Xun Gao, Lu-Ming Duan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/9f9c6842ec6b445d8d8f8a8a52fa8155
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spelling	oai:doaj.org-article:9f9c6842ec6b445d8d8f8a8a52fa81552021-12-02T14:40:56ZEfficient representation of quantum many-body states with deep neural networks10.1038/s41467-017-00705-22041-1723https://doaj.org/article/9f9c6842ec6b445d8d8f8a8a52fa81552017-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-017-00705-2https://doaj.org/toc/2041-1723One of the challenges in studies of quantum many-body physics is finding an efficient way to record the large system wavefunctions. Here the authors present an analysis of the capabilities of recently-proposed neural network representations for storing physically accessible quantum states.Xun GaoLu-Ming DuanNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-6 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Xun Gao Lu-Ming Duan Efficient representation of quantum many-body states with deep neural networks
description	One of the challenges in studies of quantum many-body physics is finding an efficient way to record the large system wavefunctions. Here the authors present an analysis of the capabilities of recently-proposed neural network representations for storing physically accessible quantum states.
format	article
author	Xun Gao Lu-Ming Duan
author_facet	Xun Gao Lu-Ming Duan
author_sort	Xun Gao
title	Efficient representation of quantum many-body states with deep neural networks
title_short	Efficient representation of quantum many-body states with deep neural networks
title_full	Efficient representation of quantum many-body states with deep neural networks
title_fullStr	Efficient representation of quantum many-body states with deep neural networks
title_full_unstemmed	Efficient representation of quantum many-body states with deep neural networks
title_sort	efficient representation of quantum many-body states with deep neural networks
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/9f9c6842ec6b445d8d8f8a8a52fa8155
work_keys_str_mv	AT xungao efficientrepresentationofquantummanybodystateswithdeepneuralnetworks AT lumingduan efficientrepresentationofquantummanybodystateswithdeepneuralnetworks
_version_	1718390070189228032

Efficient representation of quantum many-body states with deep neural networks

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