Improved ranking statistics of the GstLAL inspiral search for compact binary coalescences

TL;DR

This paper introduces new features for the GstLAL inspiral search pipeline, significantly enhancing its sensitivity to gravitational waves from compact binary coalescences for upcoming observing runs.

Contribution

The paper presents novel ranking statistic features, including contamination removal and model upgrades, tailored for the expanded detector network and improved sensitivities.

Findings

Sensitivity improved by 15-20% with new features

Enhanced detection capabilities for upcoming observing runs

Integration of KAGRA detector into the pipeline

Abstract

Starting from May 2023, the LIGO Scientific, Virgo and KAGRA Collaboration is planning to conduct the fourth observing run with improved detector sensitivities and an expanded detector network including KAGRA. Accordingly, it is vital to optimize the detection algorithm of low-latency search pipelines, increasing their sensitivities to gravitational waves from compact binary coalescences. In this work, we discuss several new features developed for ranking statistics of GstLAL-based inspiral pipeline, which mainly consist of: the signal contamination removal, the bank-$\xi^2$ incorporation, the upgraded $\rho-\xi^2$ signal model and the integration of KAGRA. An injection study demonstrates that these new features improve the pipeline's sensitivity by approximately 15% to 20%, paving the way to further multi-messenger observations during the upcoming observing run.