Combined Hierarchical Inference Model for Electromagnetic and gRavitational-wave Analysis
Project description
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}
}
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