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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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| Опубликовано в: : | Nat Commun |
|---|---|
| Главные авторы: | , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Nature Publishing Group UK
2021
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8012572/ https://ncbi.nlm.nih.gov/pubmed/33790292 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-021-22270-5 |
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