ArchEnemy: Removing scattered-light glitches from gravitational wave data

Abstract

Data recorded by gravitational wave detectors includes many non-astrophysical transient noise bursts, the most common of which is caused by scattered-light within the detectors. These so-called ``glitches'' in the data impact the ability to both observe and characterize incoming gravitational wave signals. In this work we use a scattered-light glitch waveform model to identify and characterize scattered-light glitches in a representative stretch of gravitational wave data. We identify $2749$ scattered-light glitches in $5.96$ days of LIGO-Hanford data and $1306$ glitches in $5.93$ days of LIGO-Livingston data taken from the third LIGO-Virgo observing run. By subtracting identified scattered-light glitches we demonstrate an increase in the sensitive volume of the gravitational wave search for binary black hole signals by $\sim 1\%$.

31 pages + acknowledgements, references and appendices, 13 figures

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Cited by in corpus (7)

• Gravity Spy: Lessons Learned and a Path Forward
• The anti-aligned spin of GW191109: glitch mitigation and its implications
• A Sensitive Test of Non-Gaussianity in Gravitational-wave Detector Data
• DeepExtractor: Time-domain reconstruction of signals and glitches in gravitational wave data with deep learning
• Inferring the spins of merging black holes in the presence of data-quality issues
• A Gaussian process framework for testing general relativity with gravitational waves
• Dark Matter Clumps as Sources of Gravitational-Wave Glitches in LIGO/Virgo/KAGRA data