Searching for Globally Optimal Functional Forms for Inter-Atomic Potentials Using Parallel Tempering and Genetic Programming
| dc.creator | Slepoy, A. | |
| dc.creator | Thompson, A. P. | |
| dc.creator | Peters, M. D. | |
| dc.date | 2006-08-18 | |
| dc.date.accessioned | 2026-07-07T07:20:01Z | |
| dc.date.available | 2026-07-07T07:20:01Z | |
| dc.description | We develop a Genetic Programming-based methodology that enables discovery of novel functional forms for classical inter-atomic force-fields, used in molecular dynamics simulations. Unlike previous efforts in the field, that fit only the parameters to the fixed functional forms, we instead use a novel algorithm to search the space of many possible functional forms. While a follow-on practical procedure will use experimental and {\it ab inito} data to find an optimal functional form for a forcefield, we first validate the approach using a manufactured solution. This validation has the advantage of a well-defined metric of success. We manufactured a training set of atomic coordinate data with an associated set of global energies using the well-known Lennard-Jones inter-atomic potential. We performed an automatic functional form fitting procedure starting with a population of random functions, using a genetic programming functional formulation, and a parallel tempering Metropolis-based optimization algorithm. Our massively-parallel method independently discovered the Lennard-Jones function after searching for several hours on 100 processors and covering a miniscule portion of the configuration space. We find that the method is suitable for unsupervised discovery of functional forms for inter-atomic potentials/force-fields. We also find that our parallel tempering Metropolis-based approach significantly improves the optimization convergence time, and takes good advantage of the parallel cluster architecture. | |
| dc.identifier | https://arxiv.org/abs/cs/0608078 | |
| dc.identifier | http://arxiv.org/abs/cs/0608078 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/114841 | |
| dc.subject | Neural and Evolutionary Computing | |
| dc.subject | Artificial Intelligence | |
| dc.title | Searching for Globally Optimal Functional Forms for Inter-Atomic Potentials Using Parallel Tempering and Genetic Programming | |
| dc.type | text |