chimera-gw 1.0.2

Combined Hierarchical Inference Model for Electromagnetic and gRavitational-wave Analysis

CHIMERA

CHIMERA (Combined Hierarchical Inference Model for Electromagnetic and gRavitational-wave Analysis) is a flexible Python code to analyze standard sirens with galaxy catalogs, allowing for a joint fitting of the cosmological and astrophysical population parameters within a Hierarchical Bayesian Inference framework.

The code is designed to be accurate for different scenarios, encompassing bright, dark, and spectral sirens methods, and computationally efficient in view of next-generation GW observatories and galaxy surveys. It uses the LAX-backend implementation and Just In Time (JIT) computation capabilities of JAX.

Installation

The code can be quikly installed from PyPI:

pip install chimera-gw

For greater flexibility, clone the source repository into your working folder and install it locally:

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

Documentation

The full documentation is provided at chimera-gw.readthedocs.io

Citation

If you find this code useful in your research, please cite the following paper (ADS, arXiv, INSPIRE):

@ARTICLE{2023arXiv231205302B,
    author = {{Borghi}, Nicola and {Mancarella}, Michele and {Moresco}, Michele and et al.},
        title = "{Cosmology and Astrophysics with Standard Sirens and Galaxy Catalogs in View of Future Gravitational Wave Observations}",
    journal = {arXiv e-prints},
    keywords = {Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, General Relativity and Quantum Cosmology},
        year = 2023,
        month = dec,
        eid = {arXiv:2312.05302},
        pages = {arXiv:2312.05302},
        doi = {10.48550/arXiv.2312.05302},
archivePrefix = {arXiv},
    eprint = {2312.05302},
primaryClass = {astro-ph.CO},
    adsurl = {https://ui.adsabs.harvard.edu/abs/2023arXiv231205302B},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}