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Bypassing the Kohn-Sham equations with machine learning
- Source :
- Nature Communications, Vol 8, Iss 1, Pp 1-10 (2017)
- Publication Year :
- 2017
- Publisher :
- Nature Portfolio, 2017.
-
Abstract
- Machine learning allows electronic structure calculations to access larger system sizes and, in dynamical simulations, longer time scales. Here, the authors perform such a simulation using a machine-learned density functional that avoids direct solution of the Kohn-Sham equations.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 8
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.5eb66063f9824f3e9aa4606612d626ee
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-017-00839-3