Bulletin of the American Physical Society
2024 Fall Meeting of the APS Division of Nuclear Physics
Sunday–Thursday, October 6–10, 2024; Boston, Massachusetts
Session L06: Mini-Symposium: Nuclear Data in the Cosmos
2:00 PM–3:48 PM,
Wednesday, October 9, 2024
Hilton Boston Park Plaza
Room: Copley & Kenmore, Lobby Level
Chair: Matthew Mumpower, Los Alamos National Laboratory (LANL)
Abstract: L06.00001 : pynucastro: A python library for connecting nuclear data to astrophysical simulations*
2:00 PM–2:36 PM
Presenter:
Michael Zingale
(Stony Brook University)
Author:
Michael Zingale
(Stony Brook University)
Collaboration:
pynucastro developers
nuclear reactions. During most of their lives, this change is slow
and the energy released from reactions in their interior is radiated
through their surface. At late stages of their evolution, or when
interacting with binary companions, the energy release can be fast
and drive stellar explosions. Modeling reacting stellar flows
requires coupling a hydrodynamic simulation code with a nuclear
reaction network, with attention to modern supercomputer programming
models.
Often in simulations, we would like to explore how our results are
sensitive to the details of the nuclear physics: the size of the
network, rates used, screening formulations, etc. To aid in this
exploration, we've created a python library, pynucastro, that can
interface with nuclear data resources and allow for interactive
exploration of rates and networks, as well as output C++ or python
code corresponding to the righthand side of the system of ordinary
differential equations that needs to be evolved to model the
reactions. This framework makes it easy to produce new networks and
adapt to updates in reaction rates of other nuclear physics.
We describe the features of pynucastro, including the libraries of
rates it currently uses, and show how to export a network to be used
with GPU acceleration in our simulation code, Castro. Example
simulations of Type Ia supernovae, X-ray bursts, and massive star
convection leading up to core-collapse will be shown. All of the
code is fully open source and follows a community development model.
*The work at Stony Brook was supported by DOE/Office of NuclearPhysics grant DE-FG02-87ER40317. This research used resources of theNational Energy Research Scientific Computing Center, a DOE Office ofScience User Facility supported by the Office of Science of theUS Department of Energy under Contract No. DE-AC02-05CH11231.This research used resources of the Oak Ridge Leadership ComputingFacility at the Oak Ridge National Laboratory, which is supported bythe Office of Science of the U.S. Department of Energy under ContractNo. DE-AC05-00OR22725, awarded through the DOE INCITE program.
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