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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...
Autores principales: | Walker, Nicholas, Tam, Ka-Ming, Jarrell, Mark |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400542/ https://www.ncbi.nlm.nih.gov/pubmed/32747725 http://dx.doi.org/10.1038/s41598-020-69848-5 |
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