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Deep learning on the 2-dimensional Ising model to extract the crossover region with a variational autoencoder
The 2-dimensional Ising model on a square lattice is investigated with a variational autoencoder in the non-vanishing field case for the purpose of extracting the crossover region between the ferromagnetic and paramagnetic phases. The encoded latent variable space is found to provide suitable metric...
Gorde:
| Argitaratua izan da: | Sci Rep |
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| Egile Nagusiak: | , , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
Nature Publishing Group UK
2020
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7400542/ https://ncbi.nlm.nih.gov/pubmed/32747725 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-69848-5 |
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