NetKet: A machine learning toolkit for many-body quantum systems

NetKet: A machine learning toolkit for many-body quantum systems

We introduce NetKet, a comprehensive open source framework for the study of many-body quantum systems using machine learning techniques. The framework is built around a general and flexible implementation of neural-network quantum states, which are used as a variational ansatz for quantum wavefuncti...

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Bibliographic Details
Main Authors: Giuseppe Carleo, Kenny Choo, Damian Hofmann, James E.T. Smith, Tom Westerhout, Fabien Alet, Emily J. Davis, Stavros Efthymiou, Ivan Glasser, Sheng-Hsuan Lin, Marta Mauri, Guglielmo Mazzola, Christian B. Mendl, Evert van Nieuwenburg, Ossian O’Reilly, Hugo Théveniaut, Giacomo Torlai, Filippo Vicentini, Alexander Wietek
Format: Article
Language:English
Published: Elsevier 2019-07-01
Series:SoftwareX
Online Access:http://www.sciencedirect.com/science/article/pii/S2352711019300974

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http://www.sciencedirect.com/science/article/pii/S2352711019300974

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