Efficient systematic scheme to construct second-principles lattice-dynamical models

TL;DR

This paper introduces an efficient, systematic method for constructing second-principles lattice-dynamical models from first-principles data, enabling accurate and computationally light simulations of complex materials.

Contribution

The authors develop a fast, automatic scheme for building and selecting simplified yet accurate lattice-dynamical models using polynomial interatomic potentials and cross-validation.

Findings

Method efficiently fits models via matrix diagonalization.

Automatically selects relevant interactions for accuracy.

Successfully applied to complex SrTiO3 with non-trivial features.

Abstract

We start from the polynomic interatomic potentials introduced by Wojde{\l} et al. [J. Phys. Condens. Matt. 25, 305401(2013)] and take advantage of one of their key features -- namely, the linear dependence of the energy on the potential's adjustable parameters -- to devise a scheme for the construction of first-principles-based ({\em second-principles}) models for large-scale lattice-dynamical simulations. Our method presents the following convenient features. The parameters of the model are computed in a very fast and efficient way, as it is possible to recast the fit to a training set of first-principles data into a simple matrix diagonalization problem. Our method selects automatically the interactions that are most relevant to reproduce the training-set data, by choosing from a pool that includes virtually all possible coupling terms, and produces a family of models of increasing complexity and accuracy. We work with practical and convenient cross-validation criteria linked to the physical properties that will be relevant in future simulations based on the new model, and which greatly facilitate the task of identifying a potential that is simultaneously simple (thus computationally light), very accurate, and predictive. We also discuss practical ways to guarantee that our energy models are bounded from below, with a minimal impact on their accuracy. Finally, we demonstrate our scheme with an application to ferroelastic perovskite SrTiO$_{3}$, which features many non-trivial lattice-dynamical features (e.g., a phase transition driven by soft phonons, competing structural instabilities, highly anharmonic dynamics) and provides a very demanding test.