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Found 2 papers, 1 papers with code
Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning
For 35 years, {\it ab initio} molecular dynamics (AIMD) has been the method of choice for modeling complex atomistic phenomena from first principles.
Computational Physics
Deep Density: circumventing the Kohn-Sham equations via symmetry preserving neural networks
By directly targeting at the self-consistent electron density, we demonstrate that the adapted network architecture, called the Deep Density, can effectively represent the electron density as the linear combination of contributions from many local clusters.
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