Interplay of astrophysics and nuclear physics in determining the properties of neutron stars
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1.
California Institute of Technology
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2.
Canadian Institute for Theoretical Astrophysics
Abstract
Neutron star properties depend on both nuclear physics and astrophysical processes, and thus observations of neutron stars offer constraints on both large-scale astrophysics and the behavior of cold, dense matter. In this study, we use astronomical data to jointly infer the universal equation of state of dense matter along with two distinct astrophysical populations: Galactic neutron stars observed electromagnetically and merging neutron stars in binaries observed with gravitational waves. We place constraints on neutron star properties and quantify the extent to which they are attributable to macrophysics or microphysics. We confirm previous results indicating that the Galactic and merging neutron stars have distinct mass distributions. The inferred maximum mass of both Galactic neutron stars, πpop,EM=2.0β’5^(+0.11)_(−0.06)β’πβ (median and 90% symmetric credible interval), and merging neutron star binaries, πpop,GW =1.8β’5^(+0.39)_(−0.16)β’πβ, are consistent with the maximum mass of nonrotating neutron stars set by nuclear physics, πTOV =2.2β’8^(+0.41)_(−0.21)β’πβ. The radius of a 1.4β’πβ neutron star is 12.2^(+0.8)_(−0.9) km, consistent with, though ∼20% tighter than, previous results using an identical equation of state model. Even though observed Galactic and merging neutron stars originate from populations with distinct properties, there is currently no evidence that astrophysical processes cannot produce neutron stars up to the maximum value imposed by nuclear physics.
Copyright and License
© 2025 American Physical Society.
Acknowledgement
We thank Will Farr for helpful discussions on hierarchical inference of subpopulations. We are also grateful to Reed Essick for useful discussions on population modeling with our dataset. We also thank Sylvia Biscoveanu for helpful comments on the manuscript. J. G. would like to gratefully acknowledge the support from the National Science Foundation through the Grant No. NSF PHY-2207758. I. L. and K. C. acknowledge support from the Department of Energy under Award No. DE-SC0023101, the Sloan Foundation, and by a grant from the Simons Foundation (Grant No. MP-SCMPS-00001470). P. L. is supported by the Natural Sciences & Engineering Research Council of Canada (NSERC). Research at Perimeter Institute is supported in part by the Government of Canada through the Department of Innovation, Science and Economic Development and by the Province of Ontario through the Ministry of Colleges and Universities. The authors are grateful for computational resources provided by the LIGO Laboratory and supported by National Science Foundation Grants No. PHY-0757058 and No. PHY-0823459. This material is based upon work supported by NSF’s LIGO Laboratory which is a major facility fully funded by the National Science Foundation.
Software References
BILBY [65,66], DYNESTY [67], SCIPY [101], NUMPY [102], MATPLOTLIB [103], LWP [104]
Data Availability
The data supporting this study’s findings are available within the article.
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Additional details
- National Science Foundation
- PHY-2207758
- United States Department of Energy
- DE-SC0023101
- Alfred P. Sloan Foundation
- Simons Foundation
- MP-SCMPS-00001470
- Natural Sciences and Engineering Research Council
- Perimeter Institute
- Government of Canada
- Innovation, Science and Economic Development Canada
- Ministry of Colleges and Universities
- National Science Foundation
- PHY-0757058
- National Science Foundation
- PHY-0823459
- Accepted
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2024-11-27Accepted
- Caltech groups
- Astronomy Department, LIGO
- Publication Status
- Published