Generalization properties of neural network approximations to frustrated magnet ground states

Neural quantum states (NQS) attract a lot of attention due to their potential to serve as a very expressive variational ansatz for quantum many-body systems. Here we study the main factors governing the applicability of NQS to frustrated magnets by training neural networks to approximate ground stat...

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Detalles Bibliográficos
Autores principales: Westerhout, Tom, Astrakhantsev, Nikita, Tikhonov, Konstantin S., Katsnelson, Mikhail I., Bagrov, Andrey A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7101385/
https://www.ncbi.nlm.nih.gov/pubmed/32221284
http://dx.doi.org/10.1038/s41467-020-15402-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7101385/
https://www.ncbi.nlm.nih.gov/pubmed/32221284
http://dx.doi.org/10.1038/s41467-020-15402-w

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