Abstract
After decades, the theoretical study of core-collapse supernova explosions is moving from parameterized, spherically symmetric models to increasingly realistic multidimensional simulations. However, obtaining nucleosynthesis yields based on such multidimensional core-collapse supernova simulations is not straightforward. Frequently, tracer particles are employed. Tracer particles may be tracked in situ during the simulation, but often they are reconstructed in a post-processing step based on the information saved during the hydrodynamic simulation. Reconstruction can be done in a number of ways, and here we compare the approaches of backward and forward integration of the equations of motion to the results based on inline particle trajectories. We find that both methods agree reasonably well with the inline results for isotopes for which a large number of particles contribute. However, for rarer isotopes that are produced only by a small number of particle trajectories, deviations can be large. For our setup, we find that backward integration leads to better agreement with the inline particles by more accurately reproducing the conditions following freeze-out from nuclear statistical equilibrium, because the establishment of nuclear statistical equilibrium erases the need for detailed trajectories at earlier times. Based on our results, if inline tracers are unavailable, we recommend backward reconstruction to the point when nuclear statistical equilibrium was last applied, with an interval between simulation snapshots of at most 1 ms for nucleosynthesis post-processing.
Original language | English |
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Article number | 34 |
Journal | Astrophysical Journal |
Volume | 950 |
Issue number | 1 |
DOIs | |
State | Published - Jun 1 2023 |
Funding
This research was supported by the U.S. Department of Energy Offices of Nuclear Physics and Advanced Scientific Computing Research; the NASA Astrophysics Theory Program (grant NNH11AQ72I); and the National Science Foundation PetaApps Program (grants OCI-0749242, OCI-0749204, and OCI-0749248), Nuclear Theory Program (PHY-1913531, PHY-1516197) and Stellar Astronomy and Astrophysics program (AST-0653376). A.S. acknowledges funding by the European Union's Framework Programme for Research and Innovation Horizon Europe under Marie Sklodowska-Curie grant agreement No. 101065891. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231. This research used resources of the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory. Research at Oak Ridge National Laboratory is supported under contract DE-AC05-00OR22725 from the Office of Science of the U.S. Department of Energy to UT-Battelle, LLC. This research made use of numpy (van der Walt et al. 2011) and matplotlib (Hunter 2007). We thank the referee for helpful comments and suggestions to improve the manuscript. This research was supported by the U.S. Department of Energy Offices of Nuclear Physics and Advanced Scientific Computing Research; the NASA Astrophysics Theory Program (grant NNH11AQ72I); and the National Science Foundation PetaApps Program (grants OCI-0749242, OCI-0749204, and OCI-0749248), Nuclear Theory Program (PHY-1913531, PHY-1516197) and Stellar Astronomy and Astrophysics program (AST-0653376). A.S. acknowledges funding by the European Union's Framework Programme for Research and Innovation Horizon Europe under Marie Sklodowska-Curie grant agreement No. 101065891. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231. This research used resources of the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory. Research at Oak Ridge National Laboratory is supported under contract DE-AC05-00OR22725 from the Office of Science of the U.S. Department of Energy to UT-Battelle, LLC. This research made use of numpy (van der Walt et al. ) and matplotlib (Hunter ). We thank the referee for helpful comments and suggestions to improve the manuscript.
Funders | Funder number |
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European Union's Framework Programme for Research and Innovation Horizon Europe | 101065891 |
National Science Foundation PetaApps Program | PHY-1913531, OCI-0749204, OCI-0749248, PHY-1516197, AST-0653376, OCI-0749242 |
Nuclear Physics and Advanced Scientific Computing Research | |
U.S. Department of Energy | |
National Aeronautics and Space Administration | NNH11AQ72I |
Office of Science | |
Oak Ridge National Laboratory | |
Lawrence Berkeley National Laboratory | DE-AC05-00OR22725, DE-AC02-05CH11231 |