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

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arxiv 2305.18233 v1 pith:SF4WMZCM submitted 2023-05-29 gr-qc

Prathamesh Joshi , Leo Tsukada , Chad Hanna This is my paper · ORCID
classification gr-qc
keywords gravitational-wavenoisebackgroundfiltergstlalsensitivitystatisticsanalysis
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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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Cited by 1 Pith paper

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  1. PINCH: Pipeline-Informed Noise Characterization in LIGO's Third Observing Run

    gr-qc 2025-05 conditional novelty 6.0 of 10

    PINCH uses support vector machines trained on clean GstLAL triggers to identify glitch-induced triggers, revealing class-specific patterns in how transient noise contaminates LIGO's third observing run.

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