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Machine-learned approximations to Density Functional Theory Hamiltonians
Large scale Density Functional Theory (DFT) based electronic structure calculations are highly time consuming and scale poorly with system size. While semi-empirical approximations to DFT result in a reduction in computational time versus ab initio DFT, creating such approximations involves signific...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group
2017
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309850/ https://www.ncbi.nlm.nih.gov/pubmed/28198471 http://dx.doi.org/10.1038/srep42669 |