A New Genetic Algorithm to be Used in the Direct Fit of Potential Energy Curves to ab initio and Spectroscopic Data



We propose a two-step genetic algorithm (GA) to fit potential energy curves to both ab initio and spectroscopic data. In the first step, the GA is applied to fit only the ab initio points; the parameters of the potential so obtained are then used in the second-step GA optimization, where both ab initio and spectroscopic data are included in the fitting procedure. We have tested this methodology for the extended-Rydberg function, but it can be applied to other functions providing they are sufficiently flexible to fit the data. The results for NaLi and Ar2 diatomic molecules show that the present method provides an efficient way to obtain diatomic potentials with spectroscopic accuracy.


Evolutionary Optimization


Journal of Physics B: Atomic, Molecular & Optical Physics, Vol. 41, #8, June 2008

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