CHIMERA

CHIMERA#

CHIMERA is a hierarchical Bayesian pipeline for standard siren cosmology with gravitational wave data alone or in combination with galaxy catalogs.

The latest version delivers 10-1000× speedup through JAX and GPU acceleration, enabling the analysis of thousands of events for next-generation gravitational wave observatories.

GitHub arXiv arXiv Documentation Status License Release

Quick start installation#

The code can be quickly installed from Pypi:

pip install chimera-gw

For more flexibility, clone the source repository into your working folder and install it locally (or append the local folder using sys):

git clone https://github.com/CosmoStatGW/CHIMERA
cd CHIMERA/
pip install -e .

To test the installation, run the following command:

python -c "import CHIMERA; print(CHIMERA.__version__)"

For HPC systems and GPU support, see the dedicated HPC and GPU Installation guide.

Citation#

If you find this code useful in your research, please cite the following papers:

BibTeX from INSPIRE:

@article{Borghi:2023opd,
    author = "Borghi, Nicola and Mancarella, Michele and Moresco, Michele and Tagliazucchi, Matteo and Iacovelli, Francesco and Cimatti, Andrea and Maggiore, Michele",
    title = "{Cosmology and Astrophysics with Standard Sirens and Galaxy Catalogs in View of Future Gravitational Wave Observations}",
    eprint = "2312.05302",
    archivePrefix = "arXiv",
    primaryClass = "astro-ph.CO",
    doi = "10.3847/1538-4357/ad20eb",
    journal = "Astrophys. J.",
    volume = "964",
    number = "2",
    pages = "191",
    year = "2024"
}

@article{Tagliazucchi:2025ofb,
    author = "Tagliazucchi, Matteo and Moresco, Michele and Borghi, Nicola and Fiebig, Manfred",
    title = "{Accelerating the Standard Siren Method: Improved Constraints on Modified Gravitational Wave Propagation with Future Data}",
    eprint = "2504.02034",
    archivePrefix = "arXiv",
    primaryClass = "astro-ph.CO",
    month = "4",
    year = "2025"
}

Contributions#

CHIMERA is actively maintained at the University of Bologna by: Nicola Borghi (nicola.borghi6@unibo.it), Matteo Tagliazucchi (matteo.tagliazucchi2@unibo.it), and Michele Moresco (michele.moresco@unibo.it).

Michele Mancarella, Francesco Iacovelli and Michele Maggiore contributed to the development of the first version of the code.

The development of CHIMERA has also been supported from the work of Master’s thesis students at the University of Bologna (in reverse chronological order):

  • Giulia Cuomo (2025, thesis): incompleteness function and application to GWTC-3 data

  • Manfred Fiebig (2025, thesis): modified GW propagation function and forecasts for LVK-O5

  • Niccolò Passaleva (2024, thesis): mass function models and inference with nested sampling

  • Matteo Schulz (2024, thesis): mass function models and cosmological analysis

Documentation#

User Guide

Python APIs

Contents