Inverse renormalization group based on image super-resolution using deep convolutional networks

The inverse renormalization group is studied based on the image super-resolution using the deep convolutional neural networks. We consider the improved correlation configuration instead of spin configuration for the spin models, such as the two-dimensional Ising and three-state Potts models. We prop...

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Detalles Bibliográficos
Autores principales: Shiina, Kenta, Mori, Hiroyuki, Tomita, Yusuke, Lee, Hwee Kuan, Okabe, Yutaka
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/PMC8099887/
https://www.ncbi.nlm.nih.gov/pubmed/33953229
http://dx.doi.org/10.1038/s41598-021-88605-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8099887/
https://www.ncbi.nlm.nih.gov/pubmed/33953229
http://dx.doi.org/10.1038/s41598-021-88605-w

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