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Published November 2019 | Published
Journal Article Open

Equation of state effects in the core collapse of a 20−M_⊙ star

Abstract

Uncertainties in our knowledge of the properties of dense matter near and above nuclear saturation density are among the main sources of variations in multimessenger signatures predicted for core-collapse supernovae (CCSNe) and the properties of neutron stars (NSs). We construct 97 new finite-temperature equations of state (EOSs) of dense matter that obey current experimental, observational, and theoretical constraints and discuss how systematic variations in the EOS parameters affect the properties of cold nonrotating NSs and the core collapse of a 20−M_⊙ progenitor star. The core collapse of the 20−M_⊙ progenitor star is simulated in spherical symmetry using the general-relativistic radiation-hydrodynamics code GR1D where neutrino interactions are computed for each EOS using the NuLib library. We conclude that the effective mass of nucleons at densities above nuclear saturation density is the largest source of uncertainty in the CCSN neutrino signal and dynamics even though it plays a subdominant role in most properties of cold NS matter. Meanwhile, changes in other observables affect the properties of cold NSs, while having little effect in CCSNe. To strengthen our conclusions, we perform six octant three-dimensional CCSN simulations varying the effective mass of nucleons at nuclear saturation density. We conclude that neutrino heating and, thus, the likelihood of explosion is significantly increased for EOSs where the effective mass of nucleons at nuclear saturation density is large.

Additional Information

© 2019 American Physical Society. Received 6 June 2019; published 7 November 2019. We acknowledge helpful discussions with H. Nagakura, I. Tews, C. Constantinou, M. Prakash, C. J. Horowitz, S. Couch, MK.L. Warren, and H. Yasin. This research was funded by the National Science Foundation under Award No. AST-1333520, CAREER Grants No. PHY-1151197, No. PHY-1404569, and No. OAC-1550514, and by the Sherman Fairchild Foundation. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a US Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this paper. E.O.C. acknowledges support from the Swedish Research Council (Project No. 2018-04575).

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August 19, 2023
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