Impact of noise transients on gravitational-wave burst detection efficiency of the BayesWave pipeline with multidetector networks

Detection confidence of the source-agnostic gravitational-wave burst search pipeline BayesWave is quantified by the log signal-versus-glitch Bayes factor, lnB_S,G. A recent study shows that lnB_S,G increases with the number of detectors. However as the detector network expands, non-Gaussian detector noise transients (glitches) become more frequent. In this talk, we present an empirical study on the impact of false alarms on the overall performance of BayesWave with expanded detector networks; specifically the Hanford-Livingston (HL, two-detector) and Hanford-Livingston-Virgo (HLV, three-detector) networks in the first half of Advanced LIGO and Advanced Virgo's Third Observing Run (O3a). The study consists of two independent analyses using two different sets of simulated injections, both of which show comparable performances with the HL and HLV networks. Consistent results from both analyses confirms that the overall burst-detection performance of BayesWave does not improve with larger detected networks, because the increased false alarm probability offsets the advantage of higher lnB_S,G.