Bayesian inference of nuclear symmetry energy from measured and imagined neutron skin thickness in $^{116,118,120,122,124,130,132}$Sn, $^{208}$Pb, and $^{48}$Ca
Jun Xu, Wen-Jie Xie, and Bao-An Li

TL;DR
This study uses Bayesian inference within the Skyrme-Hartree-Fock model to estimate the nuclear symmetry energy slope parameter from both measured and simulated neutron skin thickness data across various nuclei, comparing results with neutron star observations.
Contribution
It introduces a Bayesian framework to infer the symmetry energy slope parameter from imagined and experimental neutron skin data, providing insights into nuclear matter properties and their relation to neutron star observations.
Findings
Neutron skin data for Sn isotopes constrains L to about 45.5 MeV.
Imagined neutron skin measurements can refine L estimates.
Comparison with neutron star data shows consistency within uncertainties.
Abstract
The neutron skin thickness in heavy nuclei has been known as one of the most sensitive terrestrial probes of the nuclear symmetry energy around of the saturation density of nuclear matter. Existing neutron skin data mostly from hadronic observables suffer from large uncertainties and their extraction from experiments are often strongly model dependent. While waiting eagerly for the promised model-independent and high-precision neutron skin data for Pb and Ca from the parity-violating electron scattering experiments (PREX-II and CREX at JLab as well as MREX at MESA), within the Bayesian statistical framework using the Skyrme-Hartree-Fock model we infer the posterior probability distribution functions (PDFs) of the slope parameter of the nuclear symmetry energy at from imagined Pb, 0.20, and…
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