REVIEW 4 cited by
Accurate modeling and mitigation of overlapping signals and glitches in gravitational-wave data
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
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.
Forward citations
Cited by 4 Pith papers
-
When (not) to trust Monte Carlo approximations for hierarchical Bayesian inference
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.
-
Modeling non-stationary noise: applications in gravitational wave astronomy
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.
-
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.
-
The first decade of gravitational-wave measurements of black hole spins
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.
Discussion (0). Continue with ORCID to comment.