Journal
NATURE
Volume 606, Issue 7913, Pages 276-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41586-022-04750-w
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Funding
- Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [279384907 - SFB 1245]
- research programme of the Netherlands Organization for Scientific Research (NWO)
- US Department of Energy, Office of Science, Office of Nuclear Physics [DE-AC52-06NA25396]
- Laboratory Directed Research and Development programme of Los Alamos National Laboratory [20190617PRD1, 20190021DR]
- US Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Scientific Discovery through Advanced Computing (SciDAC) programme
- Max Planck Society
- Swedish Research Council [2020-03330]
- National Science Foundation [PHY-2010970, OAC-2117997]
- Bundesministerium fur Bildung und Forschung (BMBF, German Federal Ministry of Education and Research) [05P19VTFC1]
- Helmholtz Graduate School for Hadron and Ion Research (HGS-HIRe)
- national supercomputer Hawk at the High Performance Computing Center Stuttgart (HLRS) [44189]
- SuperMUC-NG at Leibniz Supercomputing Centre Munich [pn29ba]
- US Department of Energy National Nuclear Security Administration [89233218CNA000001]
- National Energy Research Scientific Computing Center (NERSC) - US Department of Energy, Office of Science [DE-AC02-05CH11231]
- US National Science Foundation
- French Centre National de Recherche Scientifique (CNRS)
- Italian Istituto Nazionale della Fisica Nucleare (INFN)
- Dutch Nikhef
- IN2P3 - DSM/CEA
- GSI
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Studying dense matter is crucial for understanding high-energy astrophysical phenomena, and data from heavy-ion collision experiments provide valuable insights in addition to astrophysical observations. By combining data from various sources, including heavy-ion collisions and microscopic nuclear theory calculations, researchers found significant improvements in their understanding of dense matter and its consistency with observations.
Interpreting high-energy, astrophysical phenomena, 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 probed only in astrophysical observations, but also in terrestrial heavy-ion collision experiments. Here we use Bayesian inference to combine data from astrophysical multi-messenger observations of neutron stars(1-9) and from heavy-ion collisions of gold nuclei at relativistic energies(10,11) with microscopic nuclear theory calculations(12-17) to improve our understanding of dense matter. We find that the inclusion of heavy-ion collision data indicates an increase in the pressure in dense matter relative to previous analyses, shifting neutron-star radii towards larger values, consistent with recent observations by the Neutron Star Interior Composition Explorer mission(5-8,18). Our findings 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.
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