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Searching for globally optimal functional forms for interatomic potentials using genetic programming with parallel tempering
Author(s) -
Slepoy A.,
Peters M. D.,
Thompson A. P.
Publication year - 2007
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.20710
Subject(s) - parallel tempering , computer science , force field (fiction) , genetic programming , monte carlo method , massively parallel , molecular dynamics , statistical physics , energy functional , field (mathematics) , density functional theory , computational chemistry , hybrid monte carlo , mathematics , artificial intelligence , physics , chemistry , parallel computing , quantum mechanics , bayesian probability , statistics , markov chain monte carlo , pure mathematics
Molecular dynamics and other molecular simulation methods rely on a potential energy function, based only on the relative coordinates of the atomic nuclei. Such a function, called a force field, approximately represents the electronic structure interactions of a condensed matter system. Developing such approximate functions and fitting their parameters remains an arduous, time‐consuming process, relying on expert physical intuition. To address this problem, a functional programming methodology was developed that may enable automated discovery of entirely new force‐field functional forms, while simultaneously fitting parameter values. The method uses a combination of genetic programming, Metropolis Monte Carlo importance sampling and parallel tempering, to efficiently search a large space of candidate functional forms and parameters. The methodology was tested using a nontrivial problem with a well‐defined globally optimal solution: a small set of atomic configurations was generated and the energy of each configuration was calculated using the Lennard‐Jones pair potential. Starting with a population of random functions, our fully automated, massively parallel implementation of the method reproducibly discovered the original Lennard‐Jones pair potential by searching for several hours on 100 processors, sampling only a minuscule portion of the total search space. This result indicates that, with further improvement, the method may be suitable for unsupervised development of more accurate force fields with completely new functional forms. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007