Mitigating the effects of instrumental artifacts on source localizations

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Abstract:: Instrumental artifacts which materialize as glitches in strain data can overlap with gravitational wave detections and significantly impair the accuracy of sky localizations of compact binary coalescence(CBC) signals. We present our Python package, PySLIDE (Python-based Skymap Localization with Inpainted Data Editor), which takes gravitational wave (GW) signals, removes a segment of the data, and corrects for the removal. To make this correction, we employ a method that applies a reweighting formula to the signal-to-noise ratio (SNR) of the signal. From tests on ≈ 500 simulated GW signals, we determined that reweighting the SNR timeseries is able to improve the accuracy over simply removing the bad data. When we repeated this process for raw data with a simulated pitch, the reweighting formula likewise improves upon removing the data alone. In this report, we discuss the method we used to reweight the SNR, features of PySLIDE, and the results of our tests on simulated GW signals.

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LIGO Document T2100202-v1