Towards Exascale Astrophysics of Mergers and Supernovae (TEAMS)
Andrew W. Steiner, University of Tennessee, Knoxville (Principal Investigator)
Anthony Mezzacappa, University of Tennessee, Knoxville (co-Investigator)
Sanjay Reddy, University of Washington (co-Investigator)
Rebecca Surman, University of Notre Dame (co-Investigator)
This award will support the University of Tennessee at Knoxville's component of the
SciDAC4 project "Towards Exascale Astrophysics of Mergers and Supernovae" (TEAMS).
The TEAMS Project is a multi-laboratory and multi-university effort in computational
nuclear astrophysics, which plans to dramatically improve our understanding of the
rapid neutron capture process (r-process) that led to the synthesis of most of the
elements heavier than iron. The r-process requires a neutron-rich environment that acts
on very short time scales, suggesting an association with cataclysmic events such as
core-collapse supernovae or neutron-star mergers. A central goal of the project is
the calculation of the various observable signals of such events, including the
fluxes of photons, neutrinos and gravitational waves, and nucleosynthesis signatures.
Simulations of different astrophysics r-process scenarios have similar computational
toolkit requirements, these being magnetohydrodynamics, thermonuclear kinetics, the
equation of state of nuclear matter, and radiation transport of neutrinos. TEAMS plans to
restructure existing astrophysical application codes to take full advantage of current and
anticipated future supercomputers, and develop new open-source frameworks for nuclear
astrophysics simulations that have greater physical fidelity; this will be feasible
on the next generation of high performance supercomputers. At UTK, TEAMS members will
develop equations of state and neutrino interactions that are essential aspects
of supernova and merger simulations, and improve the treatment of general relativity
in the simulation codes. This award will also support subcontracts to the University
of Washington and the University of Notre Dame, to improve the modeling of neutrino
interactions in hot and dense matter, and develop the more extensive nuclear reaction
networks needed for accurate predictions of r-process nucleosynthesis abundances.
