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

TL;DR

This paper introduces a computational method using the Q-transform to identify glitches near gravitational-wave signals, enhancing data quality assessment for better astrophysical analysis in gravitational-wave astronomy.

Contribution

The paper presents a novel application of the Q-transform for glitch identification near signals from compact binary coalescences, validated on real and simulated data.

Findings

Effective glitch detection in gravitational-wave data

Improved data quality assessment for gravitational-wave signals

Potential to enhance astrophysical parameter estimation

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.