Dergi makalesi Açık Erişim

Multimessenger and multiphysics Bayesian inference for the GW170817 binary neutron star merger

2020    Guven, H.; Bozkurt, K.; Khan, E.; Margueron, J.

The tidal deformability probability distribution extracted from GW170817 alone, or including multimessenger information, is confronted by additional constraints from astrophysical and nuclear physics within a semiagnostic approach for the dense matter equation of state. We use Bayesian statistics to combine together low-density nuclear physics data, such as the ab initio predictions based on chiral effective field theory interactions or the isoscalar giant monopole resonance, and astrophysical constraints from neutron stars, such as the maximum mass of neutron stars or the probability distribution function of the tidal deformability (Lambda) over tilde obtained from the GW170817 event. The so-called posterior probability distribution functions are marginalized over several nuclear empirical parameters (L-sym, K-sym, Q(sat), and Q(sym)), as well as over observational quantities such as the 1.4M(circle dot) radius R-1.4 and the pressure at twice the saturation density P(2n(sat)). The correlations between L-sym and K-sym and between K-sat and Q(sat) are also further analyzed. Tension is found between the posteriors: The first one is localized in the tidal deformability probability distribution itself, depending whether multimessenger analysis is included, and the second one is between the observational data and the nuclear physics inputs. These tensions impact the predictions for L-sym, K-sym, and R-1.4 with centroids which differ by 2-3 sigma. Implications for the nuclear equation of state are also discussed.