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20 April 2024 |
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Enzo: An Adaptive Mesh Refinement Code for Astrophysics | | Enzo Collaboration
; Greg L. Bryan
; Michael L. Norman
; Brian W. O'Shea
; Tom Abel
; John H. Wise
; Matthew J. Turk
; Daniel R. Reynolds
; David C. Collins
; Peng Wang
; Samuel W. Skillman
; Britton Smith
; Robert P. Harkness
; James Bordner
; Ji-hoon Kim
; Michael Kuhlen
; Hao Xu
; Nathan Goldbaum
; Cameron Hummels
; Alexei G. Kritsuk
; Elizabeth Tasker
; Stephen Skory
; Christine M. Simpson
; Oliver Hahn
; Jeffrey S. Oishi
; Geoffrey C So
; Fen Zhao
; Renyue Cen
; Yuan Li
; | | Date: |
Mon, 8 Jul 2013 20:42:32 GMT (1826kb) | | Abstract: | This paper describes the open-source code Enzo, which uses block-structured
adaptive mesh refinement to provide high spatial and temporal resolution for
modeling astrophysical fluid flows. The code is Cartesian, can be run in 1, 2,
and 3 dimensions, and supports a wide variety of physics including
hydrodynamics, ideal and non-ideal magnetohydrodynamics, N-body dynamics (and,
more broadly, self-gravity of fluids and particles), primordial gas chemistry,
optically-thin radiative cooling of primordial and metal-enriched plasmas (as
well as some optically-thick cooling models), radiation transport, cosmological
expansion, and models for star formation and feedback in a cosmological
context. In addition to explaining the algorithms implemented, we present
solutions for a wide range of test problems, demonstrate the code’s parallel
performance, and discuss the Enzo collaboration’s code development methodology. | | Source: | arXiv, 1307.2265 | | Services: | Forum | Review | PDF | Favorites | |
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