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Antiglitch: a Quasi-physical Model for Removing Short Glitches from LIGO and Virgo Data
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Gravitational-wave observatories become more sensitive with each observing run, increasing the number of detected gravitational-wave signals. A limiting factor in identifying these signals is the presence of transient non-Gaussian noise, which generates glitches that can mimic gravitational wave signals. Our work provides a quasi-physical model waveform for the four most common types of short transient glitches, which are particularly problematic in the search for high-mass black hole binaries. Our model has only a few, physically interpretable parameters: central frequency, bandwidth, phase, amplitude and time. We demonstrate the accuracy of this model by fitting and removing a large sample of glitches from a month of LIGO and Virgo data from the O3 observing run. We can effectively remove three of the four types of short transients. We finally map the ability of these glitches to mimic binary black hole signals.
Forward citations
Cited by 2 Pith papers
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Joint inference for gravitational-wave signal and noise glitch: Method and application
A bilby-based joint signal-glitch inference pipeline recovers unbiased parameters in simulations and shows GW200129 spin-precession evidence is sensitive to the waveform-plus-glitch-model combination.
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PINCH: Pipeline-Informed Noise Characterization in LIGO's Third Observing Run
PINCH uses support vector machines trained on clean GstLAL triggers to identify glitch-induced triggers, revealing class-specific patterns in how transient noise contaminates LIGO's third observing run.
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