Home

Welcome to the GRANITE Wiki

GRANITE (General‑Relativistic Adaptive N‑body Integrated Tool for Extreme Astrophysics) is a high‑performance, open‑source numerical relativity engine designed to simulate the most violent events in the universe: the simultaneous inspiral, tidal disruption, and merger of multiple supermassive black holes in the presence of massive stars, magnetic fields, radiation, and neutrino microphysics.

What makes GRANITE different?

Unlike traditional numerical relativity codes that focus on binary black hole or binary neutron star mergers, GRANITE is built from the ground up for N‑body supermassive black hole coalescence (N ≥ 3) with full physics:

• CCZ4 spacetime evolution – 22 evolved variables, 4th‑order finite differences, moving‑puncture gauge, Kreiss–Oliger dissipation.
• GRMHD with advanced Riemann solvers – HLLE and HLLD (Miyoshi & Kusano 2005), MP5/PPM/PLM reconstruction, constrained transport (∇·B = 0).
• Multi‑physics matter – tabulated nuclear EOS, M1 grey radiation transport, hybrid neutrino leakage + moments.
• Block‑structured AMR – Berger–Oliger subcycling, gradient‑based tagging, tracking spheres for moving horizons (full multi‑level AMR is under active development).
• Post‑processing suite – Ψ₄ gravitational‑wave extraction, spin‑weighted spherical harmonics, recoil velocity, Blandford–Znajek jet power, and EM light curves.
• HPC ready – MPI + OpenMP + HDF5 parallel I/O. GPU backends (CUDA/HIP) are on the roadmap.

Current status

• Latest stable release: v0.6.5 (“The Stability Update”)
• Test suite: 92 unit tests, 100% pass rate (GoogleTest)
• Validated benchmarks: single_puncture (Schwarzschild stability), B2_eq (equal‑mass binary black hole merger), gauge_wave (CCZ4 code validation)
• Production‑grade components: CCZ4 core, GRMHD Valencia formulation, HLLD+CT, tabulated EOS, horizon finder, Python analysis tools.

Quick links

• User Guide – installation, parameter files, running simulations
• Developer Documentation – code architecture, module interfaces, contributing
• Benchmark Library – YAML parameter files for standard scenarios
• Validation & Test Catalog – convergence tests, SXS comparisons
• Troubleshooting & FAQ – known issues, NaN forensics, performance tuning

Getting started

1. Follow the Installation Guide (Linux / WSL2 only).
2. Run the health check: python3 scripts/health_check.py
3. Launch the single‑puncture benchmark: python3 scripts/run_granite.py run --benchmark single_puncture
4. Explore the dev_benchmark\sim_tracker.py live dashboard for constraint monitoring, NaN forensics, and phase classification.

Contributing

GRANITE is a community‑oriented project. We welcome code contributions, physics validation, bug reports, and documentation improvements.
Please read our Contributing Guidelines and Code of Conduct before submitting pull requests.

For academic collaborations, supercomputer deployments, or joint publications, open an issue with the [partnership] tag or contact the maintainers directly.

---

“Simulate the unimaginable.”