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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Auteurs principaux: | , |
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Format: | article |
Langue: | EN |
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Nature Portfolio
2017
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Sujets: | |
Accès en ligne: | https://doaj.org/article/9f9c6842ec6b445d8d8f8a8a52fa8155 |
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