Information-theoretic approach to the gravitational-waveburst detection problem

International audienceThe observational era of gravitational-wave astronomy began in the fall of 2015 with the detection ofGW150914. One potential type of detectable gravitational wave is short-duration gravitational-wave bursts,whose waveforms can be difficult to predict. We present the framework for a detection algorithm for suchburst events—oLIB—that can be used in low latency to identify gravitational-wave transients. Thisalgorithm consists of (1) an excess-power event generator based on the Q transform—Omicron—,(2) coincidence of these events across a detector network, and (3) an analysis of the coincident events usinga Markov chain Monte Carlo Bayesian evidence calculator—LALInferenceBurst. These steps compressthe full data streams into a set of Bayes factors for each event. Through this process, we use elements frominformation theory to minimize the amount of information regarding the signal-versus-noise hypothesisthat is lost. We optimally extract this information using a likelihood-ratio test to estimate a detectionsignificance for each event. Using representative archival LIGO data across different burst waveformmorphologies, we show that the algorithm can detect gravitational-wave burst events of astrophysicalstrength in realistic instrumental noise. We also demonstrate that the combination of Bayes factors bymeans of a likelihood-ratio test can improve the detection efficiency of a gravitational-wave burst search.Finally, we show that oLIB’s performance is robust against the choice of gravitational-wave populationsused to model the likelihood-ratio test likelihoods