1301.2407 (Tuncay Bayram et al.)

Systematics on ground-state energies of nuclei within the neural
networks    [PDF]

Tuncay Bayram, Serkan Akkoyun, S. Okan Kara

One of the fundamental ground-state properties of nuclei is binding energy. In this study, we have employed artificial neural networks (ANNs) to obtain binding energies based on the data calculated from Hartree-Fock-Bogolibov (HFB) method with the two SLy4 and SKP Skyrme forces. Also, ANNs have been employed to obtain two-neutron and two-proton separation energies of nuclei. Statistical modeling of nuclear data using ANNs has been seen as to be successful in this study. Such a statistical model can be possible tool for searching in systematics of nuclei beyond existing experimental nuclear data.

View original: http://arxiv.org/abs/1301.2407