Title: Genetic fitting techniques for precision ultracold spectroscopy,
Abstract: 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 $X \ ^1\Sigma^+$ and $C \ ^1\Sigma^+$
potentials of lithium-rubidium.