Radial basis function approach in nuclear mass predictions

Abstract

The radial basis function (RBF) approach is applied in predicting nuclear masses for 8 widely used nuclear mass models, ranging from macroscopic-microscopic to microscopic types. A significantly improved accuracy in computing nuclear masses is obtained, and the corresponding rms deviations with respect to the known masses is reduced by up to 78%. Moreover, strong correlations are found between a target nucleus and the reference nuclei within about three unit in distance, which play critical roles in improving nuclear mass predictions. Based on the latest Weizsäcker-Skyrme mass model, the RBF approach can achieve an accuracy comparable with the extrapolation method used in atomic mass evaluation. In addition, the necessity of new high-precision experimental data to improve the mass predictions with the RBF approach is emphasized as well.

18 pages, 8 figures

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• Sensitivity study of \emph{r}-process abundances to nuclear masses
• Toward precision mass measurements of neutron-rich nuclei relevant to $r$-process nucleosynthesis
• Systematic calculations of $\alpha$-decay half-lives with an improved empirical formula
• Correlations between neutrons and protons near Fermi surface and $Q_{\alpha }$ of super-heavy nuclei
• Principal components of nuclear mass models
• Correlating charge radius with quadrupole deformation and $B(E2)$ in atomic nuclei
• Modification of the Nuclear Landscape in the Inverse Problem Framework using the Generalized Bethe-Weizsäcker Mass Formula
• Nuclear mass predictions based on deep neural network and finite-range droplet model (2012)
• Influence of binding energies of electrons on nuclear mass predictions
• Impact of the nuclear mass uncertainties on the r process