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Machine-learning iterative calculation of entropy for physical systems
Characterizing the entropy of a system is a crucial, and often computationally costly, step in understanding its thermodynamics. It plays a key role in the study of phase transitions, pattern formation, protein folding, and more. Current methods for entropy estimation suffer from a high computationa...
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| Publicado en: | Proc Natl Acad Sci U S A |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
National Academy of Sciences
2020
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7720104/ https://ncbi.nlm.nih.gov/pubmed/33214150 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.2017042117 |
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