Fitting of interatomic potentials without forces: a parallel particle swarm optimization algorithm
Materials Science
2016-08-01 v1
Abstract
We present a methodology for fitting interatomic potentials to ab initio data, using the particle swarm optimization (PSO) algorithm, needing only a set of positions and energies as input. The prediction error of energies associated with the fitted parameters can be close to 1 meV/atom or lower, for reference energies having a standard deviation of about 0.5 eV/atom. We tested our method by fitting a Sutton-Chen potential for copper from \emph{ab initio} data, which is able to recover structural and dynamical properties, and obtain a better agreement of the predicted melting point versus the experimental value, as compared to the prediction of the standard Sutton-Chen parameters.
Cite
@article{arxiv.1401.7688,
title = {Fitting of interatomic potentials without forces: a parallel particle swarm optimization algorithm},
author = {Diego González and Sergio Davis},
journal= {arXiv preprint arXiv:1401.7688},
year = {2016}
}