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We propose a novel approach called Self-Learning Hybrid Monte Carlo (SLHMC) which is a general method to make use of machine learning potentials to accelerate the statistical sampling of first-principles density-functional-theory (DFT) simulations.
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2009
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2018
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2019
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M. Shiga, PIMD: An Open Source Software for Parallel Molecular Simulation, Version 2.2.1 (2019), https://ccse.jaea.go.jp/ja/download/pimd/index.en.html
2019
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