Wednesday, July 10, 2013

1307.2265 (The Enzo Collaboration et al.)

Enzo: An Adaptive Mesh Refinement Code for Astrophysics    [PDF]

The 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
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.
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