AT2017gfo: Bayesian inference and model selection of multicomponent kilonovae and constraints on the neutron star equation of state. Issue 2 (12th May 2021) - Breschi, Matteo; Perego, Albino; Bernuzzi, Sebastiano; Del Pozzo, Walter; Nedora, Vsevolod; Radice, David; Vescovi, Diego
ABSTRACT: The joint detection of the gravitational wave GW170817, of the short γ-ray burst GRB170817A and of the kilonova AT2017gfo, generated by the the binary neutron star (NS) merger observed on 2017 August 17, is a milestone in multimessenger astronomy and provides new constraints on the NS equation of state. We perform Bayesian inference and model selection on AT2017gfo using semi-analytical, multicomponents models that also account for non-spherical ejecta. Observational data favour anisotropic geometries to spherically symmetric profiles, with a log-Bayes' factor of ∼10 4, and favour multicomponent models against single-component ones. The best-fitting model is an anisotropic three-component composed of dynamical ejecta plus neutrino and viscous winds. Using the dynamical ejecta parameters inferred from the best-fitting model and numerical–relativity relations connecting the ejecta properties to the binary properties, we constrain the binary mass ratio to q < 1.54 and the reduced tidal parameter to $120\lt \tilde{Λ }\lt 1110$ . Finally, we combine the predictions from AT2017gfo with those from GW170817, constraining the radius of a NS of 1.4 M⊙ to 12.2 ± 0.5 km (1σ level). This prediction could be further strengthened by improving kilonova models with numerical-relativity information.