Correlator convolutional neural networks as an interpretable architecture for image-like quantum matter data

Image-like data from quantum systems promises to offer greater insight into the physics of correlated quantum matter. However, the traditional framework of condensed matter physics lacks principled approaches for analyzing such data. Machine learning models are a powerful theoretical tool for analyz...

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Detalles Bibliográficos
Autores principales: Miles, Cole, Bohrdt, Annabelle, Wu, Ruihan, Chiu, Christie, Xu, Muqing, Ji, Geoffrey, Greiner, Markus, Weinberger, Kilian Q., Demler, Eugene, Kim, Eun-Ah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8222395/
https://www.ncbi.nlm.nih.gov/pubmed/34162847
http://dx.doi.org/10.1038/s41467-021-23952-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8222395/
https://www.ncbi.nlm.nih.gov/pubmed/34162847
http://dx.doi.org/10.1038/s41467-021-23952-w

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