Genetic fitting techniques for precision ultracold spectroscopy

We present development of a genetic algorithm for fitting potential energy curves of diatomic molecules to experimental data. Our approach does not involve any functional form for fitting, which makes it a general fitting procedure. In particular, it takes in a guess potential, perhaps from an $ab
initio$ calculation, along with experimental measurements of vibrational binding energies, rotational constants, and their experimental uncertainties. The fitting procedure is able to modify the guess potential until it converges to better than 1% uncertainty, as measured by ${\bar{\chi }}^2$. We present the details of this technique along with a comparison of potentials calculated by our genetic algorithm and the state of the art fitting techniques based on inverted perturbation approach for the $X{}^1{\mathrm{\Sigma }}^{+}$ and $C{}^1{\mathrm{\Sigma }}^{+}$ potentials of lithium-rubidium.