Web: http://arxiv.org/abs/2201.11188

Jan. 28, 2022, 2:10 a.m. | Minoru Kusaba, Chang Liu, Ryo Yoshida

cs.LG updates on arXiv.org arxiv.org

The prediction of energetically stable crystal structures formed by a given
chemical composition is a central problem in solid-state physics. In principle,
the crystalline state of assembled atoms can be determined by optimizing the
energy surface, which in turn can be evaluated using first-principles
calculations. However, performing the iterative gradient descent on the
potential energy surface using first-principles calculations is prohibitively
expensive for complex systems, such as those with many atoms per unit cell.
Here, we present a unique methodology …

arxiv learning machine machine learning prediction

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