Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions
Machine learning models can accurately predict atomistic chemical properties but do not provide access to the molecular electronic structure. Here the authors use a deep learning approach to predict the quantum mechanical wavefunction at high efficiency from which other ground-state properties can b...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2019-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-019-12875-2 |
| Summary: | Machine learning models can accurately predict atomistic chemical properties but do not provide access to the molecular electronic structure. Here the authors use a deep learning approach to predict the quantum mechanical wavefunction at high efficiency from which other ground-state properties can be derived. |
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| ISSN: | 2041-1723 |