Method for removing signal contamination during significance estimation of a GstLAL analysis

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.