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GstLAL: A software framework for gravitational wave discovery

  • Kipp Cannon
  • , Sarah Caudill
  • , Chiwai Chan
  • , Bryce Cousins
  • , Jolien D.E. Creighton
  • , Becca Ewing
  • , Heather Fong
  • , Patrick Godwin
  • , Chad Hanna
  • , Shaun Hooper
  • , Rachael Huxford
  • , Ryan Magee
  • , Duncan Meacher
  • , Cody Messick
  • , Soichiro Morisaki
  • , Debnandini Mukherjee
  • , Hiroaki Ohta
  • , Alexander Pace
  • , Stephen Privitera
  • , Iris de Ruiter
  • Surabhi Sachdev, Leo Singer, Divya Singh, Ron Tapia, Leo Tsukada, Daichi Tsuna, Takuya Tsutsui, Koh Ueno, Aaron Viets, Leslie Wade, Madeline Wade

Research output: Contribution to journalArticlepeer-review

Abstract

The GstLAL library, derived from Gstreamer and the LIGO Algorithm Library, supports a stream-based approach to gravitational-wave data processing. Although GstLAL was primarily designed to search for gravitational-wave signatures of merging black holes and neutron stars, it has also contributed to other gravitational-wave searches, data calibration, and detector-characterization efforts. GstLAL has played an integral role in all of the LIGO-Virgo collaboration detections, and its low-latency configuration has enabled rapid electromagnetic follow-up for dozens of compact binary candidates.

Original languageEnglish (US)
Article number100680
JournalSoftwareX
Volume14
DOIs
StatePublished - Jun 2021

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications

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