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The first observing run of Advanced LIGO spanned 4 months, from September 12,2015 to January 19, 2016, during which gravitational waves were directlydetected from two binary black hole systems, namely GW150914 and GW151226.Confident detection of gravitational waves requires an understanding ofinstrumental transients and artifacts that can reduce the sensitivity of asearch. Studies of the quality of the detector data yield insights into thecause of instrumental artifacts and data quality vetoes specific to a searchare produced to mitigate the effects of problematic data. In this paper, thesystematic removal of noisy data from analysis time is shown to improve thesensitivity of searches for compact binary coalescences. The output of thePyCBC pipeline, which is a python-based code package used to search forgravitational wave signals from compact binary coalescences, is used as ametric for improvement. GW150914 was a loud enough signal that removing noisydata did not improve its significance. However, the removal of data with excessnoise decreased the false alarm rate of GW151226 by more than two orders ofmagnitude, from 1 in 770 years to less than 1 in 186000 years.

Effects of Data Quality Vetoes on a Search for Compact Binary Coalescences in Advanced LIGO's First Observing Run