The Nature of Dense Matter from Multi-Messenger Observations of Neutron Stars
Andrew Steiner ( University of Tennessee)
April 19, 2018
Abstract: Constructing the most complete picture of the neutron star interior is (currently) only possible through the combined analysis of several data sets. Our research group uses Bayesian inference to combine neutron star observations, nuclear experiments, and nuclear theory. In this talk, I will begin by describing some of the methodology before presenting our predictions for neutron star tidal deformabilities and their relationship to GW170817. I will then go beyond the bulk thermodynamics of dense matter and show how our work is beginning to constrain the proton-to-neutron ratio and the nature of superfluidity in dense matter. Finally, I will describe how our results can be used as the input for more accurate simulations of neutron star mergers.