On the Binding Energy Predictions of RMF Model with DEFNE Interaction Parameters

BAYRAM T., AKKOYUN S.

1st International Underground Resources and Energy Conference, Yozgat, Turkey, 6 - 08 November 2016, pp.43

  • Publication Type: Conference Paper / Summary Text
  • City: Yozgat
  • Country: Turkey
  • Page Numbers: pp.43
  • Karadeniz Technical University Affiliated: No

Abstract

We have improved new nuclear interaction parameters for non-linear Relativistic Mean
Field (RMF) model by using artificial neural networks (ANN), recently. It is called DEFNE. One can expect that DEFNE interaction parameter set within the framework of RMF model can predicts various ground-state nuclear properties of nuclei such as binding energy, nuclear charge radii, deformation parameters and quadrupole moments successfully. Because of this reason, we have calculated binding energy of about 200 even-even nuclei by using RMF model with DEFNE interaction parameter set. The results have been found as in agreement with the available experimental data. Furthermore, our results have been compared with those of other non-linear RMF interaction parameter set and discussed in detail.