Statistics – Computation
Scientific paper
Jun 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006aas...208.0208m&link_type=abstract
American Astronomical Society Meeting 208, #2.08; Bulletin of the American Astronomical Society, Vol. 38, p.79
Statistics
Computation
1
Scientific paper
Unarguably, it is now realized that multidimensional, multigroup, radiation-hydrodynamic models are indispensable elements of realistic models of stellar-core collapse, core-collapse supernovae, and proto-neutron star instabilities. We present here a two-dimensional, multigroup algorithm for modeling neutrino-radiation-hydrodynamic flows present in core-collapse supernovae. It uses a staggered-mesh approach, which belongs in the same class as the ZEUS family of algorithms (Stone and Norman 1992). However, its extends previous work in several important ways: First, the algorithm incorporates multi-species, multigroup radiation hydrodynamics in a flux-limited diffusion approximation and is capable of modeling pair-coupled neutrino radiation-hydrodynamics. This treatment of transport includes effects of Pauli blocking in the collision integrals, which gives rise to non-linearities in the discretized diffusion equation. The non-linear diffusion and collision-integral portions of the code are implicitly time evolved. The algorithm employs Newton-Krylov methods together with sparse-approximate-inverse preconditioners to find a fast parallel solution of the non-linear implicit equations. Second, the effects of deleptonization are included through the inclusion of an electron conservation equation that describes the evolution of the electron number density in the hydrodynamic flow. Finally, the hydrodynamic algorithm has been extended to accommodate a realistic, complex equation of state that can be non-convex. The algorithm is designed for straightforward implementation on large-scale, state-of-the-art, parallel-computing architectures.We gratefully acknowledge the support of the U.S. Dept. of Energy, through SciDAC Award DE-FC02- 01ER41185, by which this work was funded. We are also grateful to the National Energy Research Scientific Computing Center (NERSC) for computational support.
Myra Eric Stephen
Swesty Frank Douglas
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