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

Abstract

Non-Gaussian noise transients ("glitches") in gravitational-wave observatories degrade our ability to accurately perform astrophysical inference. We present the analysis pipeline bilby_glitch, which allows for simultaneous Bayesian inference of gravitational-wave signals and glitches. Our framework is modular and built on top of the popular bilby framework, facilitating future extensions with additional glitch and signal models. We integrate transdimensional bilby into our framework and discuss three glitch models: a physically-motivated slow scattering model, and flexible sine-Gaussian and chirplet models. Using a combination of simulated and real data, we demonstrate that bilby_glitch produces reliable results. We then reanalyse two gravitational-wave events - GW191109 and GW200129 - which show signs of interesting black-hole spins, but which may also be affected by data-quality issues. Our results for GW191109 are consistent with previous analysis. For GW200129, we recover results consistent with Payne et al., where the evidence of spin-precession is much weaker when using the waveform approximant NRSur7dq4 in combination with wavelet-based glitch modeling. Furthermore, we show the astrophysical conclusion of this event is dependent on the interplay between the waveform approximant and glitch model, since in contrast to NRSur7dq4 we find that inference with the waveform approximant IMRPhenomXPHM shows strong evidence of spin-precession when used in combination with wavelet-based glitch modeling.