Weighing the Likelihoods of Equations of State with Gravitational Wave Observations

In the age of gravitational waves, multi-messenger Neutron Star observations can provide insights to the extreme matter within them. With this aim, we have streamlined a Bayesian Hierarchical Inference scheme previously used for nonparametric equation of state (EOS) inference. The hierarchical inference takes in EOS realizations and constrains their posterior probability by weighting them according to the likelihood of gravitational-wave observations of compact binary coalescences, to a 90% credible interval. We implement an analysis using a set of EOS realizations generated by a Gaussian process, exploring the space of all causal and thermodynamically stable pressure-density functions, including those with first-order phase transitions. Using the inference code, we probe the speed of sound within the core and compare with the conformal limit.