Welcome to the AstroBEAR Wiki
AstroBEAR is a parallelized hydrodynamic/MHD simulation code suitable for a variety of astrophysical problems. Derived from the BearCLAW package written by Sorin Mitran, AstroBEAR is designed for 2D and 3D adaptive mesh refinement (AMR), multiphysics simulations. Users write their own project modules by specifying initial conditions and continual processes (such as an inflow condition). In addition, AstroBEAR comes with a number of pre-built physical phenomena such as clumps and winds that can be loaded into a user module.
Capabilites - Listing of AstroBEAR's capabilities
AstroBEAR introduction video - Introductory video on AstroBEAR and its capabilities
AstroBEAR YouTube Channel - A movie listing of simulations performed with AstroBEAR can also be checked out here
- Download — Instructions for downloading AstroBEAR.
- User Guide — Information on using AstroBEAR
- FAQ — Frequently asked questions about AstroBEAR
- Developer Guide — The portal to information on AstroBEAR's algorithms and source code.
- Development — Information about ongoing development
Publications and External Links
- Publications using AstroBear — A list of publications using AstroBEAR
- Image Gallery — Selected images produced by AstroBEAR simulations.
- Collaborators & Projects — How AstroBEAR is currently being employed, and by whom.
- External Links and Literature — Links to some of the concepts and technologies used by AstroBEAR.
- Member Pages — Current Members' Pages.
Financial support for AstroBEAR is currently provided by the Department of Energy grant DE-SC0001063, DE-SC0020432, and DE-SC0020434, the National Science Foundation grants AST-1515648 and AST-1813298, and the Space Telescope Science Institute grant HST-AR-14563.001-A.
We are also supported by the computational and visualization resources in the Center for Integrated Research Computing (CIRC) at the University of Rochester and the computational resources of the Texas Advanced Computing Center (TACC) at The University of Texas at Austin, provided through allocation TG-AST120060 from the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562.