gwpopulation 1.3.1

Unified population inference

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Flexible, extensible, hardware-agnostic gravitational-wave population inference.

• Documentation
• Source Repository
• Issues
• Contributing

It provides:

• Simple use of GPU-acceleration via JAX and cupy.
• Implementations of widely used likelihood compatible with Bilby.
• A standard format for defining new population models.
• A collection of standard population models.

If you're using this on high-performance computing clusters, you may be interested in the associated pipeline code gwpopulation_pipe.

Attribution

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Please cite Talbot et al. (2025) if you use GWPopulation in your research.

@article{Talbot2025,
  author = {Colm Talbot and Amanda Farah and Shanika Galaudage and Jacob Golomb and Hui Tong},
  title = {GWPopulation: Hardware agnostic population inference for compact binaries and beyond},
  journal = {Journal of Open Source Software},
  doi = {10.21105/joss.07753},
  url = {https://doi.org/10.21105/joss.07753},
  year = {2025},
  publisher = {The Open Journal},
  volume = {10},
  number = {109},
  pages = {7753},
  archivePrefix = {arXiv},
  eprint = {2409.14143},
  primaryClass = {astro-ph.IM},
}

The older citation can also be included for the initial proof-of-principle for the application of hardware acceleration Talbot et al. (2019).

@ARTICLE{2019PhRvD.100d3030T,
  author = {{Talbot}, Colm and {Smith}, Rory and {Thrane}, Eric and {Poole}, Gregory B.},
  title = "{Parallelized inference for gravitational-wave astronomy}",
  journal = {\prd},
  year = 2019,
  month = aug,
  volume = {100},
  number = {4},
  eid = {043030},
  pages = {043030},
  doi = {10.1103/PhysRevD.100.043030},
  archivePrefix = {arXiv},
  eprint = {1904.02863},
  primaryClass = {astro-ph.IM},
}

Additionally, please consider citing the original references for the implemented models which should be include in docstrings.