A geometric algorithm for efficient coincident detection of gravitational waves

TL;DR

This paper introduces a geometric algorithm that improves the detection of gravitational waves by optimally combining data from multiple detectors, reducing false alarms and increasing detection efficiency.

Contribution

The paper presents a novel geometric algorithm that uses covariance-based ellipsoidal regions for coincident detection, outperforming traditional uncorrelated window methods.

Findings

Reduces background rate significantly

Increases detection efficiency at fixed false alarm rate

Utilizes covariance information for optimal coincidence detection

Abstract

Data from a network of gravitational wave detectors can be analyzed in coincidence to increase detection confidence and reduce non-stationarity of the background. We propose and explore a geometric algorithm to combine the data from a network of detectors. The algorithm makes optimal use of the variances and covariances that exist amongst the different parameters of a signal in a coincident detection of events. The new algorithm essentially associates with each trigger ellipsoidal regions in parameter space defined by the covariance matrix. Triggers from different detectors are deemed to be in coincidence if their ellipsoids have a non-zero overlap. Compared to an algorithm that uses uncorrelated windows separately for each of the signal parameters, the new algorithm greatly reduces the background rate thereby increasing detection efficiency at a given false alarm rate.