Leveraging cross-detector parameter consistency measures to enhance sensitivities of gravitational wave searches
Sayantan Ghosh, Leigh Smith, Jiyoon Sun, Archana Pai, Ik Siong Heng, V. Gayathri
公開日: 2025/4/1
Abstract
All-sky searches for generic short-duration astrophysical GW transients are often challenging because of noise transients. Developing novel signal-noise discriminators is crucial for GW transient searches with LIGO Scientific, Virgo, and KAGRA (LVK) detectors. In this work, we adapt a recently developed Jensen Shannon divergence (JSD)-based measure, which assesses the cross-detector parameter consistency to distinguish between weakly modeled or unmodelled astrophysical GW signals and loud noise triggers. We first extend a 2-detector JSD-based measure, developed in an earlier work, to a 3-detector network. We leverage this to modify the test statistic of the existing Coherent Waveburst (cWB)-Gaussian Mixture Modelling (GMM) algorithm for short-duration transients towards improving the search sensitivity to ad-hoc waveforms like Sine-Gaussians, Gaussian Pulses, and White Noise Bursts. We find that with the new method, which we term cWB-GMM-JSD, the sensitivity to the ad-hoc waveforms, given by $h_{\mathrm{rss50}}$, improves by $\sim 10-20 \%$ at an IFAR of 10 years for the 2-detector network consisting of LHO and LLO detectors, and by $\sim 5-10 \%$ at the same IFAR for the 3-detector network consisting of LHO, LLO and Virgo detectors. Finally, we apply the modified statistic in the revised data analysis pipeline on the publicly available data from the third observing run (O3) of the LIGO and Virgo detectors. Although we do not find any new event in the O3 data, we see a notable rise in the statistical significance of most of the known GW events, which further testifies to the enhancement in sensitivities.