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Consistent inference of neutron star bulk and crust properties and nuclear observables using an Energy-Density Functional approach.

ORAL

Abstract

We have entered the era of multi-messenger nuclear astrophysics; bringing a host of astrophysical observations and nuclear experimental data to collectively measure the properties of neutron star matter and the nuclear force in neutron-rich systems. In order to combine disparate data sets with meaningful uncertainty quantification, over the past decade statistical inference techniques employing ensembles of models have been increasingly employed. In order to minimize systematic model uncertainty, where possible the same underlying model should be used to construct both neutron star and nuclear models. We present an example of such an approach, using an Energy-Density Functional to model bulk properties of neutron stars such as the maximum mass, radii, tidal deformabilities and moments of inertia, crust properties of neutron stars, and nuclear properties including nuclear masses, neutron skins and dipole polarizabilities. We demonstrate how different observables constrain nuclear matter in different density ranges, and discuss some of the remaining model uncertainties.

Publication: "Constraining the Nuclear Symmetry Energy with Multimessenger Resonant Shattering Flares", Physical Review Letters, Volume 130, Issue 11, article id.112701<br>"From neutron skins and neutron matter to the neutron star crust",Physics Letters B, Volume 834, article id. 137481<br>"Ensembles of unified crust and core equations of state in a nuclear-multimessenger astrophysics environment", The European Physical Journal A, Volume 58, Issue 4, article id.69<br>"Bayesian inference of neutron star bulk and crust properties and nuclear observables", in prep.

Presenters

  • William G Newton

    Texas A&M University–Commerce

Authors

  • William G Newton

    Texas A&M University–Commerce

  • Rebecca Preston

    Texas A&M University–Commerce

  • Lauren E Balliet

    Texas A&M University–Commerce

  • Brianna T Douglas

    Texas A&M University–Commerce

  • Thomas B Head

    Florida International University