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arXiv · 1306.1812

Orbital-free Bond Breaking via Machine Learning

John C. Snyder·Matthias Rupp·Katja Hansen·Leo Blooston·Klaus-Robert Müller·Kieron Burke
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Abstract

Machine learning is used to approximate the kinetic energy of one dimensional diatomics as a functional of the electron density. The functional can accurately dissociate a diatomic, and can be systematically improved with training. Highly accurate self-consistent densities and molecular forces are found, indicating the possibility for ab-initio molecular dynamics simulations.

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John C. Snyder, Matthias Rupp, Katja Hansen, Leo Blooston, Klaus-Robert Müller, Kieron Burke. 2013-06-07. Orbital-free Bond Breaking via Machine Learning. https://doi.org/10.1063/1.4834075

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