The MLIP package: Moment Tensor Potentials with MPI and Active Learning

The subject of this paper is the technology (the "how") of constructing machine-learning interatomic potentials, rather than science (the "what" and "why") of atomistic simulations using machine-learning potentials. Namely, we illustrate how to construct moment tensor p...

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Bibliographic Details
Published inarXiv.org
Main Authors Novikov, Ivan S, Gubaev, Konstantin, Podryabinkin, Evgeny V, Shapeev, Alexander V
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 16.07.2020
Subjects
Active learning
Machine learning
Mathematical analysis
Tensors
Training
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ISSN2331-8422

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Summary:The subject of this paper is the technology (the "how") of constructing machine-learning interatomic potentials, rather than science (the "what" and "why") of atomistic simulations using machine-learning potentials. Namely, we illustrate how to construct moment tensor potentials using active learning as implemented in the MLIP package, focusing on the efficient ways to sample configurations for the training set, how expanding the training set changes the error of predictions, how to set up ab initio calculations in a cost-effective manner, etc. The MLIP package (short for Machine-Learning Interatomic Potentials) is available at https://mlip.skoltech.ru/download/.
Bibliography:content type line 50
SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
ISSN:2331-8422