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Transient signals arising from instrumental or environmental factors, commonly referred to as glitches, constitute the predominant background of false alarms in the detection of gravitational waves in data collected from ground-based detectors. Therefore, effective data analysis methods for vetoing glitch-induced false alarms are crucial to enhancing the sensitivity of a search for gravitational waves. We present a veto method for glitches that impact matched filtering-based searches for binary inspiral signals. The veto uses unphysical sectors in the space of chirp time parameters as well as an unphysical extension including negative chirp times to efficiently segregate glitches from gravitational wave signals in data from a single detector. Inhabited predominantly by glitches but nearly depopulated of genuine gravitational wave signals, these unphysical sectors can be efficiently explored using Particle Swarm Optimization. In a test carried out on data taken from both LIGO detectors spanning multiple observation runs, the veto was able to reject 99.9% of glitches with no loss of injected signals detected with a signal-to-noise ratio ≥9.0. Our results show that extending a matched filter search to unphysical parts of a signal parameter space promises to be an effective strategy for mitigating glitches.



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