Enzo: An adaptive mesh refinement code for astrophysics

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 TaskerStephen Skory, Christine M. Simpson, Oliver Hahn, Jeffrey S. Oishi, Geoffrey C. So, Fen Zhao, Renyue Cen, Yuan Li

Research output: Contribution to journalArticlepeer-review


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 one, two, and three 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.

Original languageEnglish (US)
Article number19
JournalAstrophysical Journal, Supplement Series
Issue number2
StatePublished - Apr 2014
Externally publishedYes


  • hydrodynamics methods
  • numerical
  • words

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science


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