Increasing GstLAL search sensitivity through iDQ binning scheme
ORAL
Abstract
iDQ is a data quality pipeline that can detect transient noise in gravitational wave data by using each interferometer's auxiliary data. During the LVK's third observational run the GstLAL pipeline used iDQ to downrank single detector candidates when noise was non-Gaussian, therefore improving single detector sensitivity. We propose to incorporate iDQ information at the background collection stage. This will be helpful in mitigating GstLAL's unnecessary penalization of stretches of data that happen to be coincident with a less noisy background. I will be discussing our methods and improvements to GstLAL's sensitivity.
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Presenters
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Richard George
University of Texas at Austin
Authors
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Richard George
University of Texas at Austin
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RYAN MAGEE
LIGO Laboratory, Caltech
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Alvin Ka Yue Li
LIGO Laboratory, Caltech
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Rachael Huxford
Pennsylvania State University