Computational models of stellar collapse and core-collapse supernovae
Core-collapse supernovae are among Nature's most energetic events. They mark the end of massive star evolution and pollute the interstellar medium with the life-enabling ashes of thermonuclear burning. Despite their importance for the evolution of galaxies and life in the universe, the details...
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Published in | Journal of physics. Conference series Vol. 180; no. 1; p. 012022 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Bristol
IOP Publishing
01.07.2009
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Subjects | |
Online Access | Get full text |
ISSN | 1742-6596 1742-6588 1742-6596 |
DOI | 10.1088/1742-6596/180/1/012022 |
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Summary: | Core-collapse supernovae are among Nature's most energetic events. They mark the end of massive star evolution and pollute the interstellar medium with the life-enabling ashes of thermonuclear burning. Despite their importance for the evolution of galaxies and life in the universe, the details of the core-collapse supernova explosion mechanism remain in the dark and pose a daunting computational challenge. We outline the multi-dimensional, multi-scale, and multi-physics nature of the core-collapse supernova problem and discuss computational strategies and requirements for its solution. Specifically, we highlight the axisymmetric (2D) radiation-MHD code VULCAN/2D and present results obtained from the first full-2D angle-dependent neutrino radiation-hydrodynamics simulations of the post-core-bounce supernova evolution. We then go on to discuss the new code Zelmani which is based on the open-source HPC Cactus framework and provides a scalable AMR approach for 3D fully general-relativistic modeling of stellar collapse, core-collapse supernovae and black hole formation on current and future massively-parallel HPC systems. We show Zelmani's scaling properties to more than 16,000 compute cores and discuss first 3D general-relativistic core-collapse results. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 1742-6596 1742-6588 1742-6596 |
DOI: | 10.1088/1742-6596/180/1/012022 |