Semi-agnostic Equation of State models for Bayesian inference with Neutron Star observations

Dense and neutron rich matter is partly out of the reach of nuclear laboratories on Earth but comprises the deepest shells of the highly compact astrophysical objects that are Neutron Stars. An entire field of nuclear astrophysics, which includes multi-messenger astronomy, is devoted to exploring dense matter by observing Neutron Stars from their birth in core collapse supernovae to their deaths in mergers. Radio, X-ray and gravitational wave detections of neutron star’s astrophysical features have already partly constrained the neutron)rich and dense matter. However, large uncertainties remain and additional and more precise measurements of the mass, radius and tidal deformability of neutron stars are necessary.

In practice, informing dense matter using astrophysical measurements relies on Bayesian inference techniques that require equation of state priors. Using the publicly available code CUTER (Crust Unified Tool for Equation of state Reconstruction) we present new semi agnostic equation of state models. We first present the meta-modeling approach used for the low density equation of state, and present the experimental and theoretical nuclear physics data used to inform it up to nuclear saturation density. We then discuss the use of piecewise polytropes for the high density equation of state parametrization, and propose a subsitution relying on non parametric representations for the agnostic approach relevant in the deepest shells of the neutron star.