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Title: Implications for Post-processing Nucleosynthesis of Core-collapse Supernova Models with Lagrangian Particles

In this paper, we investigate core-collapse supernova (CCSN) nucleosynthesis with self-consistent, axisymmetric (2D) simulations performed using the neutrino hydrodynamics code Chimera. Computational costs have traditionally constrained the evolution of the nuclear composition within multidimensional CCSN models to, at best, a 14-species α-network capable of tracking only $$(\alpha ,\gamma )$$ reactions from 4He to 60Zn. Such a simplified network limits the ability to accurately evolve detailed composition and neutronization or calculate the nuclear energy generation rate. Lagrangian tracer particles are commonly used to extend the nuclear network evolution by incorporating more realistic networks into post-processing nucleosynthesis calculations. However, limitations such as poor spatial resolution of the tracer particles; inconsistent thermodynamic evolution, including misestimation of expansion timescales; and uncertain determination of the multidimensional mass cut at the end of the simulation impose uncertainties inherent to this approach. Finally, we present a detailed analysis of the impact of such uncertainties for four self-consistent axisymmetric CCSN models initiated from solar-metallicity, nonrotating progenitors of 12, 15, 20, and 25 $${M}_{\odot }$$ and evolved with the smaller α-network to more than 1 s after the launch of an explosion.
Authors:
ORCiD logo [1] ; ORCiD logo [2] ;  [3] ;  [3] ; ORCiD logo [4] ; ORCiD logo [5]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Nuclear Science Division; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Center for Computational Sciences
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Physics Division; Univ. of Tennessee, Knoxville, TN (United States). Dept. of Physics and Astronomy
  3. Univ. of Tennessee, Knoxville, TN (United States). Dept. of Physics and Astronomy
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Physics Division. Joint Inst. for Computational Sciences; Univ. of Tennessee, Knoxville, TN (United States). Dept. of Physics and Astronomy
  5. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Center for Computational Sciences. Physics Division; Univ. of Tennessee, Knoxville, TN (United States). Dept. of Physics and Astronomy
Publication Date:
Grant/Contract Number:
AC05-00OR22725; AC02-05CH11231; NNH11AQ72I; PHY-1516197; TG-MCA08X010
Type:
Accepted Manuscript
Journal Name:
The Astrophysical Journal (Online)
Additional Journal Information:
Journal Name: The Astrophysical Journal (Online); Journal Volume: 843; Journal Issue: 1; Journal ID: ISSN 1538-4357
Publisher:
Institute of Physics (IOP)
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Nuclear Physics (NP) (SC-26); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); National Aeronautic and Space Administration (NASA); National Science Foundation (NSF)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; numerical methods; nuclear reactions; nucleosynthesis; abundances; stars; supernovae
OSTI Identifier:
1376490
Alternate Identifier(s):
OSTI ID: 1471037

Harris, J. Austin, Hix, W. Raphael, Chertkow, Merek A., Lee, C. T., Lentz, Eric J., and Messer, O. E. Bronson. Implications for Post-processing Nucleosynthesis of Core-collapse Supernova Models with Lagrangian Particles. United States: N. p., Web. doi:10.3847/1538-4357/aa76de.
Harris, J. Austin, Hix, W. Raphael, Chertkow, Merek A., Lee, C. T., Lentz, Eric J., & Messer, O. E. Bronson. Implications for Post-processing Nucleosynthesis of Core-collapse Supernova Models with Lagrangian Particles. United States. doi:10.3847/1538-4357/aa76de.
Harris, J. Austin, Hix, W. Raphael, Chertkow, Merek A., Lee, C. T., Lentz, Eric J., and Messer, O. E. Bronson. 2017. "Implications for Post-processing Nucleosynthesis of Core-collapse Supernova Models with Lagrangian Particles". United States. doi:10.3847/1538-4357/aa76de. https://www.osti.gov/servlets/purl/1376490.
@article{osti_1376490,
title = {Implications for Post-processing Nucleosynthesis of Core-collapse Supernova Models with Lagrangian Particles},
author = {Harris, J. Austin and Hix, W. Raphael and Chertkow, Merek A. and Lee, C. T. and Lentz, Eric J. and Messer, O. E. Bronson},
abstractNote = {In this paper, we investigate core-collapse supernova (CCSN) nucleosynthesis with self-consistent, axisymmetric (2D) simulations performed using the neutrino hydrodynamics code Chimera. Computational costs have traditionally constrained the evolution of the nuclear composition within multidimensional CCSN models to, at best, a 14-species α-network capable of tracking only $(\alpha ,\gamma )$ reactions from 4He to 60Zn. Such a simplified network limits the ability to accurately evolve detailed composition and neutronization or calculate the nuclear energy generation rate. Lagrangian tracer particles are commonly used to extend the nuclear network evolution by incorporating more realistic networks into post-processing nucleosynthesis calculations. However, limitations such as poor spatial resolution of the tracer particles; inconsistent thermodynamic evolution, including misestimation of expansion timescales; and uncertain determination of the multidimensional mass cut at the end of the simulation impose uncertainties inherent to this approach. Finally, we present a detailed analysis of the impact of such uncertainties for four self-consistent axisymmetric CCSN models initiated from solar-metallicity, nonrotating progenitors of 12, 15, 20, and 25 ${M}_{\odot }$ and evolved with the smaller α-network to more than 1 s after the launch of an explosion.},
doi = {10.3847/1538-4357/aa76de},
journal = {The Astrophysical Journal (Online)},
number = 1,
volume = 843,
place = {United States},
year = {2017},
month = {6}
}