Identifying glitches near gravitational-wave signals from compact binary coalescences using the Q-transform

Abstract

We present a computational method to identify glitches in gravitational-wave data that occur nearby gravitational-wave signals from compact binary coalescences. The Q-transform, an established tool in LIGO-Virgo-KAGRA data analysis, computes the probability of any excess in the data surrounding a signal against the assumption of a Gaussian noise background, flagging any significant glitches. Subsequently, we perform validation tests on this computational method to ensure self-consistency in colored Gaussian noise, as well as data that contains a gravitational-wave event after subtracting the signal using the best-fit template. Finally, a comparison of our glitch identification results from real events in LIGO-Virgo's third observing run against the list of events which required glitch mitigation shows that this tool will be useful in providing precise information about data quality to improve astrophysical analyses of these events.

24 pages, 6 figures. CGQ accepted

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Cited by in corpus (7)

• GW231123: a Binary Black Hole Merger with Total Mass 190-265 $M_{\odot }$
• GWTC-4.0: Updating the Gravitational-Wave Transient Catalog with Observations from the First Part of the Fourth LIGO-Virgo-KAGRA Observing Run
• LIGO Detector Characterization in the first half of the fourth Observing run
• Bayesian modelling of scattered light in the LIGO interferometers
• A Sensitive Test of Non-Gaussianity in Gravitational-wave Detector Data
• Assessing the similarity of continuous gravitational-wave signals to narrow instrumental artifacts
• Glitches far from transient gravitational-wave events do not bias inference