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arXiv · 2305.18233

Background Filter: A method for removing signal contamination during significance estimation of a GstLAL anaysis

Prathamesh Joshi·Leo Tsukada·Chad Hanna
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Abstract

To evaluate the probability of a gravitational-wave candidate originating from noise, GstLAL collects noise statistics from the data it analyzes. Gravitational-wave signals of astrophysical origin get added to the noise statistics, harming the sensitivity of the search. We present the Background Filter, a novel tool to prevent this by removing noise statistics that were collected from gravitational-wave candidates. To demonstrate its efficacy, we analyze one week of LIGO and Virgo O3 data, and show that it improves the sensitivity of the analysis by 20-40% in the high mass region, in the presence of 868 simulated gravitational-wave signals. With the upcoming fourth observing run of LIGO, Virgo, and KAGRA expected to yield a high rate of gravitational-wave detections, we expect the Background Filter to be an important tool for increasing the sensitivity of a GstLAL analysis.

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Prathamesh Joshi, Leo Tsukada, Chad Hanna. 2023-05-29. Background Filter: A method for removing signal contamination during significance estimation of a GstLAL anaysis. https://arxiv.org/abs/2305.18233

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