ENZO: AN ADAPTIVE MESH REFINEMENT CODE FOR ASTROPHYSICS

By Corey Brummel-Smith, Greg L. Bryan, Iryna Butsky, L. Corlies, A. Emerick, John C. Forbes, Y. Fujimoto, N. Goldbaum, P. Grete, Cameron Hummels and 45 more. 2013

620 citations recorded by the source corpus.

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.

Subfields: Astronomy and Astrophysics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/9c9eda1ce16fb5cbaf52262ec38ad551c4f96327

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In Astronomy and Astrophysics

  1. P. Hopkins
  2. L. Hernquist
  3. Volker Springel
  4. C. Faucher-Giguére
  5. E. Quataert
  6. D. Keres̆
  7. James S. Bullock
  8. P. Torrey

In Statistical and Nonlinear Physics

  1. Ralf Klessen
  2. S. Garrison-Kimmel
  3. S. Glover
  4. James S. Bullock
  5. P. Hopkins
  6. C. Faucher-Giguére
  7. M. Boylan-Kolchin
  8. A. Ferrara

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