Constraining Neutron-Star Matter with Microscopic and Macroscopic Collisions

ORAL

Abstract

Neutron stars contain the largest reservoirs of degenerate fermions, reaching the highest densities we can observe in the cosmos, and probe matter under conditions that cannot be recreated in terrestrial experiments. Interpreting high-energy, astrophysical phenomena involving neutron stars, such as supernova explosions or neutron-star collisions, requires a robust understanding of matter at supranuclear densities. However, our knowledge about dense matter explored in the cores of neutron stars remains limited. Fortunately, dense matter is not only probed in astrophysical observations, but also in terrestrial heavy-ion collision experiments. 

 In this talk, I will show how to use Bayesian inference to combine data from astrophysical multi-messenger observations of neutron stars and from heavy-ion collisions of gold nuclei at relativistic energies with microscopic nuclear theory calculations to improve our understanding of dense matter. I will show that constraints from heavy-ion collision experiments show a remarkable consistency with multi-messenger observations and provide complementary information on nuclear matter at intermediate densities. This work combines nuclear theory, nuclear experiment, and astrophysical observations, and shows how joint analyses can shed light on the properties of neutron-rich supranuclear matter over the density range probed in neutron stars.

LA-UR-21-32199

*This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -- Project-ID 279384907 -- SFB 1245, the research program of the Netherlands Organization for Scientific Research (NWO), by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, under contract No. DE-AC52-06NA25396, by the Laboratory Directed Research and Development program of Los Alamos National Laboratory under project numbers 20190617PRD1 and 20190021DR, by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Scientific Discovery through Advanced Computing (SciDAC) program, by the Max Planck Society, by the Swedish Research Council (Reg. no. 2020-03330), by the National Science Foundation with grant numbers PHY-2010970 and OAC-2117997, by the French-German Collaboration Agreement between IN2P3 - DSM/CEA and GSI, by the Bundesministerium für Bildung und Forschung (BMBF, German Federal Ministry of Education and Research

Publication: S. Huth et al., arXiv:2107.06229

Presenters

  • Ingo Tews

    • Los Alamos National Laboratory

Authors

  • Ingo Tews

    • Los Alamos National Laboratory