Bayesian analysis of neutron-star properties with parameterized equations of state: the role of the likelihood functions
Jin-Liang Jiang · Christian Ecker · Luciano Rezzolla
We have investigated the systematic differences introduced when performing a Bayesian-inference analysis of the equation of state of neutron stars employing either variable- or constant-likelihood functions. The former have the advantage that it retains the full information on the distributions of the measurements, making an exhaustive usage of the data. The latter, on the other hand, have the advantage of a much simpler implementation and reduced computational costs. In both approaches, the EOSs have identical priors and have been built using the sound-speed parameterization method so as to satisfy the constraints from X-ray and gravitational-waves observations, as well as those from Chiral Effective Theory and perturbative QCD. In all cases, the two approaches lead to very similar results and the -confidence levels are essentially overlapping. Some differences do appear, but in regions where the probability density is extremely small and are mostly due to the sharp cutoff set on the binary tidal deformability employed in the constant-likelihood analysis. Our analysis has also produced two additional results. First, a clear inverse correlation between the normalized central number density of a maximally massive star, , and the radius of a maximally massive star, . Second, and most importantly, it has confirmed the relation between the chirp mass and the binary tidal deformability . The importance of this result is that it relates a quantity that is measured very accurately, , with a quantity that contains important information on the micro-physics, . Hence, once is measured in future detections, our relation has the potential of setting tight constraints on .