Bayesian inference of finite-nuclei observables based on the KIDS model

TL;DR

This paper employs Bayesian analysis within the KIDS nuclear model to constrain nuclear matter parameters using experimental data, revealing how including higher-order parameters affects the posterior distributions and correlations.

Contribution

It introduces a Bayesian framework that incorporates higher-order nuclear parameters, providing more comprehensive constraints on nuclear matter properties from experimental data.

Findings

Broadening of posterior PDFs when including higher-order parameters

Robust constraints of L<90 MeV and K_0<270 MeV

Quantification of consistency between different experimental constraints

Abstract

Bayesian analyses on both isoscalar and isovector nuclear interaction parameters are carried out based on the Korea-IBS-Daegu-SKKU (KIDS) model under the constraints of nuclear structure data of $^{208}$Pb and $^{120}$Sn. Under the constraint of the neutron-skin thickness, it is found that incorporating the curvature parameter $K_{sym}$ of nuclear symmetry energy as an independent variable significantly broadens the posterior probability distribution function (PDF) of the slope parameter $L$, and affects the related correlations. Typically, the anticorrelation between $L$ and the symmetry energy at saturation density disappears, while a positive correlation between $L$ and $K_{sym}$ is observed. Under the constraint of the isoscalar giant monopole resonance (ISGMR), incorporating the skewness parameter as an independent variable also significantly broadens the posterior PDF of the nuclear matter incompressibility $K_0$. Even with the broad uncertainties of higher-order parameters of the equation of state (EOS), robust constraints of $L<90$ MeV and $K_0<270$ MeV are obtained. Our study quantifies the consistency between the constraints on $L$ from the neutron-skin data of PREXII and isovector giant dipole resonance (IVGDR) data, and the constraints on $K_0$ from the data of ISGMR in $^{208}$Pb and $^{120}$Sn.