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Accurate modeling and mitigation of overlapping signals and glitches in gravitational-wave data

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arxiv 2205.13580 v2 pith:HMHB45WM submitted 2022-05-26 gr-qc astro-ph.IM

classification gr-qcastro-ph.IM
keywords glitchessignalglitchsignalsdetectormodelingwaveformwavelets
verification ladder T0 review T1 audit T2 compute T3 formal
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The increasing sensitivity of gravitational-wave detectors has brought about an increase in the rate of astrophysical signal detections as well as the rate of "glitches"; transient and non-Gaussian detector noise. Temporal overlap of signals and glitches in the detector presents a challenge for inference analyses that typically assume the presence of only Gaussian detector noise. In this study we perform an extensive exploration of the efficacy of a recently proposed method that models the glitch with sine-Gaussian wavelets while simultaneously modeling the signal with compact-binary waveform templates. We explore a wide range of glitch families and signal morphologies and demonstrate that the joint modeling of glitches and signals (with wavelets and templates respectively) can reliably separate the two. We find that the glitches that most affect parameter estimation are also the glitches that are well modeled by such wavelets due to their compact time-frequency signature. As a further test, we investigate the robustness of this analysis against waveform systematics like those arising from the exclusion of higher-order modes and spin-precession effects. Our analysis provides an estimate of the signal parameters; the glitch waveform to be subtracted from the data; and an assessment of whether some detected excess power consists of a glitch, signal, or both. We analyze the low-significance triggers (191225_215715 and 200114_020818) and find that they are both consistent with glitches overlapping high-mass signals.

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Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. When (not) to trust Monte Carlo approximations for hierarchical Bayesian inference

    astro-ph.HE 2025-09 conditional novelty 7.0 of 10

    A unified error statistic E-hat measures information lost to Monte Carlo noise in hierarchical Bayesian inference, with a recommended cutoff of 0.2 bits.

  2. Modeling non-stationary noise: applications in gravitational wave astronomy

    gr-qc 2026-07 conditional novelty 6.0 of 10

    A positive dynamic spectrum S(f,t) generalizes the stationary power spectrum by defining Gramian closed-form noise covariances in Fourier and Wilson-Daubechies wavelet bases for gravitational wave data.

  3. Joint inference for gravitational-wave signal and noise glitch: Method and application

    gr-qc 2026-07 accept novelty 6.0 of 10

    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.

  4. The first decade of gravitational-wave measurements of black hole spins

    gr-qc 2026-06 unverdicted novelty 1.0 of 10

    A review summarizing formation-channel predictions, waveform effects, and population-level constraints on stellar-mass black hole spins from the first decade of gravitational-wave observations.

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