A blind hierarchical coherent search for gravitational-wave signals from coalescing compact binaries in a network of interferometric detectors

TL;DR

This paper introduces a hierarchical, blind, coherent search pipeline for gravitational wave signals from compact binary coalescences across multiple detectors, improving detection performance over traditional coincidence methods.

Contribution

It presents a novel hierarchical pipeline that combines coincidence and coherent analysis without prior source information, enhancing gravitational wave detection accuracy.

Findings

Hierarchical pipeline outperforms coincidence-only methods in Gaussian noise.

Coherent statistics improve signal consistency checks across detectors.

Pipeline is effective without prior sky or event time information.

Abstract

We describe a hierarchical data analysis pipeline for coherently searching for gravitational wave (GW) signals from non-spinning compact binary coalescences (CBCs) in the data of multiple earth-based detectors. It assumes no prior information on the sky position of the source or the time of occurrence of its transient signals and, hence, is termed "blind". The pipeline computes the coherent network search statistic that is optimal in stationary, Gaussian noise, and allows for the computation of a suite of alternative statistics and signal-based discriminators that can improve its performance in real data. Unlike the coincident multi-detector search statistics employed so far, the coherent statistics are different in the sense that they check for the consistency of the signal amplitudes and phases in the different detectors with their different orientations and with the signal arrival times in them. The first stage of the hierarchical pipeline constructs coincidences of triggers from the multiple interferometers, by requiring their proximity in time and component masses. The second stage follows up on these coincident triggers by computing the coherent statistics. The performance of the hierarchical coherent pipeline on Gaussian data is shown to be better than the pipeline with just the first (coincidence) stage.