Skip to content

CPU/GPU agnostic gravitational-wave population inference

License

Notifications You must be signed in to change notification settings

jacobgolomb/gwpopulation

 
 

Repository files navigation


Python package codecov Versions Conda Downloads

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

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


Please cite Talbot et al. (2019) if you use GWPopulation in your research.

@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.

About

CPU/GPU agnostic gravitational-wave population inference

Resources

License

Code of conduct

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 100.0%