Machine learning quantum phases of matter beyond the fermion sign problem
Abstract State-of-the-art machine learning techniques promise to become a powerful tool in statistical mechanics via their capacity to distinguish different phases of matter in an automated way. Here we demonstrate that convolutional neural networks (CNN) can be optimized for quantum many-fermion sy...
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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2017
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/2436c67e977c43d480a0a608687695d2 |
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