Enzo 2.0

We are proud to announce the public release of Enzo version 2.0. Enzo is a parallel code for astrophysical and cosmological simulations utilizing adaptive mesh refinement. Enzo 2.0 features many new physics capabilities including ideal MHD, radiation transport (ray tracing and flux limited diffusion), star particle class, metallicity-dependent cooling, and several new hydro solvers. More importantly, we have introduced new software tools to make using and developing Enzo easier. We have adopted distributed version control using Mercurial which supports the growing Enzo developer community. The documentation has been made more accessible and is now distributed with the source code. We have more than doubled the number of test problems and example problems (as well as the number of developers!) In addition, we have added solution testing to the nightly regression tests.

Enzo 2.0 is the product of developments made at UC San Diego, Stanford, Princeton, Columbia, MSU, CU Boulder, CITA, McMaster??, SMU, and UC Berkeley.

Enzo 2.0 now lives at http://enzo.googlecode.com/ to reflect its multi-institutional provenance. Prospective users are also encouraged to view online lectures from the 2010 Enzo Users' Workshop at http://lca.ucsd.edu/workshops/enzo2010.

Enzo development is supported by grants AST-0808184 and OCI-0832662 from the National Science Foundation.


Enzo Project Page

This is the development site for Enzo, an adaptive mesh refinement (AMR), grid-based hybrid code (hydro + N-Body) which is designed to do simulations of cosmological structure formation. Links to documentation and downloads for all versions of Enzo from 1.0 on are available.

Enzo development is supported by grants AST-0808184 and OCI-0832662 from the National Science Foundation.




Compiling Help


Mailing Lists

Enzo Users

enzo-users-l@lists.ucsd.edu is the community forum (archive).

Enzo Developers

enzo-l@lists.ucsd.edu is a private list for the core Enzo developers (restricted archive).

Regression Tests

The Enzo trunk and select branches are checked out of Subversion and tested continuously using lcatest on ppcluster.ucsd.edu:

For questions or suggestions related to the Enzo regression testing or lcatest, please contact James Bordner at jobordner at ucsd.edu.

Citing Enzo

If you use Enzo for a scientific publication, we ask that you cite the code in the following way in the acknowledgments of your paper:

Computations described in this work were performed using the Enzo code developed by the Laboratory for Computational Astrophysics at the University of California in San Diego (http://lca.ucsd.edu).