A Pareto Approach to Parameter Optimization of Empirical Interatomic Potentials

Eugene Ragasa
Seminar

The traditional process of selecting an optimal parameterization of an empirical potential is generally approached as a multiple-objective optimization problem. An initial guess is made of the potential parameters and gradient methods are used to minimize a weighted function of the errors between the predicted and target parameter values. Here, we discuss an approach centered around the Pareto surface, which represents the set of all "optimal" parameterizations, calculated from the differences of the predicted values of physical properties of interest with respect to reference values. The methodology is illustrated with example results for a Buckingham potential for MgO to generate a Pareto surface. This uses the approach in an iterative process to identify an ensemble of parameterizations and illustrates the choices in tradeoffs of fidelity that need to be made in simulating competing material properties.