A sparse representation for potential energy surface

Abstract

We propose a simple scheme to estimate potential energy surface (PES) with which the accuracy can be easily controlled and improved up to the level of the density functional theory (DFT) calculations. It is based on a model selection within the framework of linear regression using the least absolute shrinkage and selection operator (LASSO) technique. Basis functions are selected from a systematic large set of candidate functions. The sparsity of PES significantly reduces the computational demands for evaluation of the energy and the force in molecular dynamics simulations without losing the accuracy. The usefulness of the scheme is well demonstrated for describing elemental metals of Na and Mg.