Kumara Sastry

Genetic programming for multi-timescale modeling

Sastry, K. Johnson, D. D., Goldberg, D. E., Bellon, P. (2005). Physical Review B, 72, 085438. [Selected for the August 29, 2005 issue of Virtual Journal of Nanoscale Science & Technology as frontier research].

Abstract:

A bottleneck for multi-timescale thermally-activated dynamics is the computation of the potential energy surface (PES). We explore the use of genetic programming (GP) to symbolically regress a mapping of the saddle-point barriers from only a few calculated points via molecular dynamics, thereby avoiding explicit calculation of all barriers. The GP-regressed barrier function enables use of kinetic Monte Carlo (KMC) to simulate real-time kinetics (seconds to hours) based upon realistic atomic interactions. To illustrate the concept, we apply a GP regression to vacancy-assisted migration on a surface of a concentrated binary alloy (from both quantum and empirical potentials) and predict the diffusion barriers within ~0.1% error from 3% (or less) of the barriers. We discuss the significant reduction in CPU time (4 to 7 orders of magnitude), the efficacy of GP over standard regression, e.g., polynomial, and the independence of the method on the type of potential.

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