Heuristic machinery for thermodynamic studies of SU(N) fermions with neural networks

The power of machine learning (ML) provides the possibility of analyzing experimental measurements with a high sensitivity. However, it still remains challenging to probe the subtle effects directly related to physical observables and to understand physics behind from ordinary experimental data usin...

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Detalles Bibliográficos
Autores principales: Zhao, Entong, Lee, Jeongwon, He, Chengdong, Ren, Zejian, Hajiyev, Elnur, Liu, Junwei, Jo, Gyu-Boong
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/PMC8012572/
https://www.ncbi.nlm.nih.gov/pubmed/33790292
http://dx.doi.org/10.1038/s41467-021-22270-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012572/
https://www.ncbi.nlm.nih.gov/pubmed/33790292
http://dx.doi.org/10.1038/s41467-021-22270-5

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