Hybridizing agnostic and relativistic mean-field models of the dense matter equation of state for neutron star inference.

Relativistic mean-field models of the nuclear equation of state are postulated to effectively represent matter inside of neutron stars. However, because mean-field models are phenomenological, it is generally not clear in what conditions such models are valid, and where other models of dense matter may be required. In this talk, I will discuss how model-agnostic methods can be combined with relativistic mean-field models of the nuclear equation of state to perform robust astrophysical inference of neutron star properties. In addition, I will discuss how hybrid informed-agnostic inference can be leveraged to effectively constrain properties of nuclear models using astrophysics, while incorporating uncertainty in composition of matter at high densities.