Bayesian reconstruction of nuclear matter parameters from the equation of state of neutron star matter

TL;DR

This paper employs Bayesian methods to infer nuclear matter parameters from neutron star matter equations of state, revealing significant uncertainties and correlations among parameters.

Contribution

It introduces a Bayesian framework to reconstruct NMPs from EoS data, accounting for prior constraints and analyzing uncertainties and correlations.

Findings

Median NMPs deviate from true values

Uncertainties are mainly due to parameter correlations

EoS remains stable despite variations in nuclear matter parameters

Abstract

The nuclear matter parameters (NMPs), those underlie in the construction of the equation of state (EoS) of neutron star matter, are not directly accessible. The Bayesian approach is applied to reconstruct the posterior distributions of NMPs from the EoS of neutron star matter. The constraints on lower-order parameters as imposed by the finite nuclei observables are incorporated through appropriately chosen prior distributions. The calculations are performed with two sets of pseudo data on the EoS whose true models are known. The median values of second or higher order NMPs show sizeable deviations from their true values and associated uncertainties are also larger. The sources of these uncertainties are intrinsic in nature, identified as (i) the correlations among various NMPs and (ii) the variations in the EoS of symmetric nuclear matter, symmetry energy, and the neutron-proton asymmetry in such a way that the neutron star matter EoS remain almost unaffected.