Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons

TLDR

We introduce a class of interatomic potential models that can be automatically generated from quantum‑mechanical data of atomic energies and forces. The models have no fixed functional form, can capture complex energy landscapes, are systematically improvable with additional data, and are applied to bulk crystals to compute high‑temperature properties. Using these potentials to run long molecular dynamics trajectories reduces computational cost by orders of magnitude.

Abstract

We introduce a class of interatomic potential models that can be automatically generated from data consisting of the energies and forces experienced by atoms, as derived from quantum mechanical calculations. The models do not have a fixed functional form and hence are capable of modeling complex potential energy landscapes. They are systematically improvable with more data. We apply the method to bulk crystals, and test it by calculating properties at high temperatures. Using the interatomic potential to generate the long molecular dynamics trajectories required for such calculations saves orders of magnitude in computational cost.