Skip to main content

Continuous-wave search sensitivity simulator

Project description

Continuous-wave search sensitivity simulator (COWS3)

A Python package to estimate the sensitivity of general continuous gravitational-wave searches.

The method should be equivalent to the semi-analytical approach derived in Dreissigacker, Prix, Wette (2018) and implemented in Octapps, but here we implement it in Python to make it more convenient to use.

Citing this work

If COWS3 was useful to your research, we would appreciate if you cited Mirasola & Tenorio (2024) where this implementation was first presented:

@article{Mirasola:2024lcq,
    author = "Mirasola, Lorenzo and Tenorio, Rodrigo",
    title = "{Towards a computationally-efficient follow-up pipeline for blind continuous gravitational-wave searches}",
    eprint = "2405.18934",
    archivePrefix = "arXiv",
    primaryClass = "gr-qc",
    reportNumber = "LIGO-P2400221",
    month = "5",
    year = "2024",
    journal = "arXiv e-prints"
}

as well as a Zenodo release of this software.

For the semi-analytical sensitivity estimation method you should also cite Wette (2012) and Dreissigacker, Prix, Wette (2018). Also, this package makes extensive use of SWIG bindings, so please cite Wette (2021) as well.

Authors

  • Rodrigo Tenorio
  • Lorenzo Mirasola

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cows3-0.0.1.tar.gz (11.2 kB view details)

Uploaded Source

Built Distribution

cows3-0.0.1-py3-none-any.whl (8.7 kB view details)

Uploaded Python 3

File details

Details for the file cows3-0.0.1.tar.gz.

File metadata

  • Download URL: cows3-0.0.1.tar.gz
  • Upload date:
  • Size: 11.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for cows3-0.0.1.tar.gz
Algorithm Hash digest
SHA256 ba273d298f9c065d3451d938f6aa1530ce2cf2ae33d241a3f34c2c66153c4e75
MD5 f456d2613568c79588ef927dfcc40a77
BLAKE2b-256 70e89267a0dc1f71af67abf89a8aae41171d614aec773946e9f0783f89a61c8a

See more details on using hashes here.

File details

Details for the file cows3-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: cows3-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 8.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for cows3-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 b9ba40e3efadbae539461b05e63357b6d0c2b0355871e666ccaaba7785251eac
MD5 2fe05e8ee733ebe0fe70523e3e382b62
BLAKE2b-256 17366e7b9261a66080f4e5a21cef820e38b1be083a2c088ec04c9e6997ab80b3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page