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 potentials using active learning as implemented in the MLIP package, focusing on the efficient ways to automatically 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/.

Automated summary

This paper focuses on the technology of constructing machine-learning interatomic potentials through active learning in the MLIP package, addressing efficient methods for automatically sampling training sets, the impact of expanding training sets on prediction errors, and cost-effective setup of ab initio calculations. The MLIP package can be downloaded at https://mlip.skoltech.ru/download/.