Above-barrier heavy-ion fusion cross-sections using the relativistic mean-field approach: case of spherical colliding nuclei

TL;DR

This study investigates how nuclear matter density from the Relativistic Mean Field approach affects heavy-ion fusion cross-section calculations, comparing results with Hartree-Fock densities and experimental data.

Contribution

It introduces the use of RMF-derived nuclear densities in the double folding potential and fusion cross-section calculations, providing a novel comparison with HF densities.

Findings

RMF and HF densities yield similar agreement with experimental data.

Friction strength correlates strongly between RMF and HF density-based models.

Nuclear density choice impacts fusion cross-section calculations.

Abstract

The double folding (DF) approach is one of the widely used methods for finding nucleus-nucleus interaction potential. In the present work, the influence of the nuclear matter density on the DF potential and on the Coulomb barrier parameters is studied systematically for collisions of spherical nuclei. The value of the parameter $B_Z=Z_P Z_T/(A_P^{1/3}+A_T^{1/3})$ (estimating the Coulomb barrier height) varies in these calculations from 10 MeV up to 150 MeV. The novel feature of this study is that the nuclear densities came from the Relativistic Mean Field approach (RMF). For the nucleon-nucleon effective interaction, the M3Y forces with the finite range exchange term and density dependence are employed. The above barrier fusion cross sections are calculated within the framework of the trajectory model with surface friction. Results are compared with the previous study in which the nuclear density came from the Hartree-Fock (HF) calculations and with the high precision experimental data. This comparison demonstrates that i) agreement between the theoretical and experimental cross sections obtained with RMF and HF densities is of the same quality and ii) the values of the only adjustable parameter (friction strength) obtained with RMF and HF densities strongly correlate.