Learning spin liquids on a honeycomb lattice with artificial neural networks
Abstract Machine learning methods provide a new perspective on the study of many-body system in condensed matter physics and there is only limited understanding of their representational properties and limitations in quantum spin liquid systems. In this work, we investigate the ability of the machin...
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Autores principales: | Chang-Xiao Li, Sheng Yang, Jing-Bo Xu |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/d62a9389027543848943424de4bd2cde |
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