AsterX is a GPU-accelerated GRMHD code for dynamical spacetimes, written in C++. It is built on the CarpetX driver, which is designed for use with the Einstein Toolkit. CarpetX itself is based on AMReX, a software framework for block-structured adaptive mesh refinement (AMR).
- Heavily derived from the GRMHD code Spritz
- Solves the GRMHD equations in 3D Cartesian coordinates on dynamical spacetimes using high-resolution shock-capturing (HRSC) schemes
- Based on the flux-conservative Valencia formulation
- Directly evolves the staggered vector potential
AsterX– Core GRMHD moduleAsterMasks– Provides masking functionalityAsterSeeds– Initial data moduleAsterUtils– Utility functionsCon2PrimFactory– Conservative-to-primitive variable recovery routinesEOSX– Equation of state driverFishboneMoncriefIDX– Initial data for Fishbone–Moncrief disksID_TabEOS_HydroQuantities– Initializes hydrodynamic quantities for tabulated EOSReconX– Reconstruction scheme moduleTOVSolverX– Modified version of the TOVSolver thorn from the Einstein Toolkit
- Instructions for downloading and building AsterX with the Einstein Toolkit are available here.
- Simfactory files for various clusters and setup instructions can be found here.
- Example Jupyter notebooks and plotting scripts are available here.
- CarpetX – Next-generation driver for the Einstein Toolkit
- SpacetimeX – Modules for spacetime evolution
- BNSTools – Utilities supporting BNS merger simulations
- nuX – Modules for an upcoming neutrino transport code
- Kalinani et al. (2024) – Introduction to the AsterX code
- Ji et al. (2025) – Subcycling algorithm and spacetime solver in CarpetX
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Using CarpetX: A Guide for Early Adopters
Seminar by Erik Schnetter providing an overview of CarpetX capabilities. -
Tutorial: GPUs and the Einstein Toolkit
Tutorial by Lorenzo Ennoggi, Jay Kalinani, and Federico Lopez Armengol during the North American Einstein Toolkit Workshop 2022. Includes an introduction to AsterX and hands-on sessions. -
AsterX: A New Open-Source GPU-Accelerated GRMHD Code for Dynamical Spacetimes
Slides from a talk by Jay Kalinani at the APS April Meeting 2023.