Detecting gravitational-wave transients at five sigma: a hierarchical approach

TL;DR

This paper introduces a hierarchical method for detecting long-duration gravitational-wave transients with high significance, effectively balancing detection sensitivity and computational efficiency.

Contribution

It presents a novel hierarchical approach utilizing seedless clustering to identify high-significance gravitational-wave transients efficiently.

Findings

Detects transients with >5σ significance using modest resources

Applies seedless clustering to large datasets effectively

Balances sensitivity and computational cost in gravitational-wave detection

Abstract

As second-generation gravitational-wave detectors prepare to analyze data at unprecedented sensitivity, there is great interest in searches for unmodeled transients, commonly called bursts. Significant effort has yielded a variety of techniques to identify and characterize such transient signals, and many of these methods have been applied to produce astrophysical results using data from first-generation detectors. However, the computational cost of background estimation remains a challenging problem; it is difficult to claim a 5{\sigma} detection with reasonable computational resources without paying for efficiency with reduced sensitivity. We demonstrate a hierarchical approach to gravitational-wave transient detection, focusing on long-lived signals, which can be used to detect transients with significance in excess of 5{\sigma} using modest computational resources. In particular, we show how previously developed seedless clustering techniques can be applied to large datasets to identify high-significance candidates without having to trade sensitivity for speed.