Constructing exact representations of quantum many-body systems with deep neural networks
Significant improvements in numerical methods for quantum systems often come from finding new ways of representing quantum states that can be optimized and simulated more efficiently. Here the authors demonstrate a method to calculate exact neural network representations of many-body ground states.
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2018
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/39fa743f78674be2a91326e970938e4f |
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| Sumario: | Significant improvements in numerical methods for quantum systems often come from finding new ways of representing quantum states that can be optimized and simulated more efficiently. Here the authors demonstrate a method to calculate exact neural network representations of many-body ground states. |
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