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.
@article{arxiv.1507.00537,
title = {Detecting gravitational-wave transients at five sigma: a hierarchical approach},
author = {Eric Thrane and Michael Coughlin},
journal= {arXiv preprint arXiv:1507.00537},
year = {2015}
}