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Fornax: A Flexible Code for Multiphysics Astrophysical Simulations

2018/06/30 by M. Aaron Skinner, Joshua C. Dolence, Adam Burrows +2 · 1 citation
Physics and Astronomy · #Code (set theory) #Gamma-ray bursts and supernovae #Moment (physics) #Multiphysics #Neutrino #Neutrino Physics Research #Particle physics theoretical and experimental studies #Radiation #Range (aeronautics) #Suite #astro-ph.HE #astro-ph.IM #astro-ph.SR #physics.comp-ph

paper · pdf · doi:10.3847/1538-4365/ab007f

Accepted to the Astrophysical Journal Supplement Series; A few more textual and reference updates; As before, one additional code test included

openalex created_date 2018/06/29 · arxiv created 2019/02/07 · openalex publication_date 2019/02/28 · arxiv updated 2019/03/06 · openalex updated_date 2026/08/06

Abstract

Abstract This paper describes the design and implementation of our new multigroup, multidimensional radiation hydrodynamics code F ornax and provides a suite of code tests to validate its application in a wide range of physical regimes. Instead of focusing exclusively on tests of neutrino radiation hydrodynamics relevant to the core-collapse supernova problem for which F ornax is primarily intended, we present here classical and rigorous demonstrations of code performance relevant to a broad range of multidimensional hydrodynamic and multigroup radiation hydrodynamic problems. Our code solves the comoving-frame radiation moment equations using the M 1 closure, utilizes conservative high-order reconstruction, employs semi-explicit matter and radiation transport via a high-order time stepping scheme, and is suitable for application to a wide range of astrophysical problems. To this end, we first describe the philosophy, algorithms, and methodologies of F ornax and then perform numerous stringent code tests that collectively and vigorously exercise the code, demonstrate the excellent numerical fidelity with which it captures the many physical effects of radiation hydrodynamics, and show excellent strong scaling well above 100,000 MPI tasks.

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