Welcome to Galacticus

Galacticus is a semi-analytic model of galaxy formation — a powerful, flexible toolkit for modeling the physics of how galaxies form and evolve. For the science behind it, see the description paper; for everything else, the documentation.

Install: pip install galacticus gets you a ready-to-run model with no compilation — pre-built binaries, datasets, and tools are downloaded automatically for Linux and macOS. See the Quickstart and the pip installation guide.

Have questions? Ask in the discussion forum, or browse the wiki.

Quickstart

Just want to run models? If you don't need to modify the code, the easiest way to get started is to install the pre-built launcher from PyPI — no compiler or manual setup required:

pip install galacticus
galacticus run parameters/quickTest.xml

The first run downloads the right binary, datasets, and tools for your platform (Linux x86-64, macOS Intel, or macOS Apple Silicon) and configures the environment for you. See the pip installation guide. The rest of this section covers building from source, which you need only if you want to modify or extend Galacticus.

This section walks you through building and running a minimal Galacticus model for the first time.

Prerequisites

Before building, make sure you have the following available:

• A modern Fortran compiler (gfortran ≥ 16; earlier versions will not compile Galacticus)
• make
• GSL, zlib, HDF5, FoX, and BLAS libraries (HDF5 and FoX must be built with the same compiler used for Galacticus)
• Python 3 (≥ 3.9; used by the build system for code generation and various supporting scripts)

FFTW3, ANN, and libmatheval are optional (needed only for specialized calculations). For the full, platform-specific prerequisite list and step-by-step instructions, see the Installation guide.

Tip: The easiest way to get a fully configured environment is to use GitHub Codespaces (click the badge above). All dependencies are pre-installed.

Installing Python dependencies

The build system imports modules from python/. Make those modules importable, and install the third-party packages they depend on (numpy, scipy, h5py, lxml, matplotlib, …), with a single editable install from the repo root:

pip install -e .

This is sufficient for building Galacticus and running its supporting scripts. Heavy emulation pipelines have additional dependencies (TensorFlow, lenstronomy, etc.); install those on demand with pip install -e '.[emulation]'. To run the Python test suite, install with pip install -e '.[test]'.

Building Galacticus

From the root of the repository, run:

make -jN Galacticus.exe

Replace N with the number of CPU cores you want to use in parallel (e.g., make -j4 Galacticus.exe to use 4 cores). Using multiple cores significantly speeds up the build. If you are unsure how many cores are available, you can run nproc on Linux to find out.

Running a minimal model

Once the build completes successfully, run the included quick-test parameter file:

./Galacticus.exe parameters/quickTest.xml

This runs a small, pre-configured galaxy formation model designed to complete quickly.

What to expect

A successful run will:

• Exit with code 0 (no error message printed to the terminal).
• Write output to an HDF5 file in the working directory. parameters/quickTest.xml does not set an output filename, so Galacticus uses the default, galacticus.hdf5. Open that file to inspect the results (e.g., with h5ls or any HDF5 viewer).
• Print progress information to standard output during the run. The final line should indicate that the run completed without errors.

The output is written to galacticus.hdf5 in the directory you ran from. To change this, set an outputFileName parameter in the parameter file.

Troubleshooting

For further help, visit the wiki or ask in the discussion forum.

Analyzing Galacticus output

Analysis and visualization of Galacticus outputs - including plotting of on-the-fly analyses, MCMC chain diagnostics, and posterior corner plots - is provided by the Dendros package, available on PyPI:

python3 -m pip install dendros

Publications

The Galacticus Publications repository collects the parameter files and the exact Galacticus commit hash used to run the models in published papers, so that those results are easy to find and reproduce. The commit behind each paper is also tagged in this repository (e.g. publication/arXiv/XXXX.XXXXX), letting you check out the precise version of the code used.

Written a paper that uses Galacticus? We'd welcome your contribution — see the contribution guidelines for how to add it.