Application of robust estimation methods to simple models of nucleon separation energies

Abstract

Some works have recently shown the usefulness of simple models of nucleon separation energies in terms of neutron and proton numbers. However, the customary use of least squares in the process of parameter estimation turns out to be extremely sensible to the accuracy of the model and the extent and quality of data (e.g. highly vulnerable to the sample size or the possible existence of undesired errors in the experimental values). We will show how robust estimation by global optimization instead of least squares estimation improves on both the stability of the estimated parameters and the extrapolation to unknown energies. Comparison against recently determined experimental data will show a level of agreement comparable to the predictions made by the best and much more complex models.