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In this paper we investigate the impact of transient noise artifacts, or glitches, on gravitational- wave inference from ground-based interferometer data, and test how modeling and subtracting these glitches affects the inferred parameters. Due to their time-frequency morphology, broadband glitches cause moderate to significant biasing of posterior distributions away from true values. In contrast, narrowband glitches induce negligible biasing effects, due to distinct signal and glitch morphologies. We inject simulated binary black hole signals into data containing three occurring glitch types from past LIGO-Virgo observing runs, and reconstruct both signal and glitch waveforms using BayesWave, a wavelet-based Bayesian analysis. We apply the standard LIGO-Virgo-KAGRA deglitching pro- cedure to the detector data, which consists of subtracting from calibrated LIGO data the glitch waveform estimated by the joint BayesWave inference. We produce posterior distributions on the parameters of the injected signal before and after subtracting the glitch, and we show that removing the transient noise effectively mitigates bias from broadband glitches. This study provides a baseline validation of existing techniques, while demonstrating waveform reconstruction improvements to the Bayesian algorithm for robust astrophysical characterization in glitch-prone detector data. 

Abstract Since the initial discovery of gravitational waves in 2015, significant developments have been made towards waveform interpretation and estimation of compact binary source parameters. We present herein an implementation of the generalized precession parameter ⟨ χ p ⟩ [Gerosa et al 2021], which averages over all angular variations on the precession timescale, within the RIFT parameter estimation framework. Relative to the precession parameter χ p , which characterizes the single largest dynamical spin in a binary, ⟨ χ p ⟩ has a unique domain 1 < ⟨ χ p ⟩ < 2, which is exclusive to binaries with two precessing spins. After reviewing the physical differences between these two parameters, we describe how ⟨ χ p ⟩ was implemented in RIFT and apply it to all 36 events from the second half of the Advanced LIGO and Advanced Virgo third observing run (O3b). In O3b, ten events show significant amounts of precession ⟨ χ p ⟩ > 0.5. Of particular interest is GW191109_010717; we show it has a ∼ 28 % probability that the originating system necessarily contains two misaligned spins.