Bayesian Inference Analysis of Unmodelled Gravitational-Wave Transients

Understand

We report the results of an in-depth analysis of the parameter estimation capabilities of BayesWave, an algorithm for the reconstruction of gravitational-wave signals without reference to a specific signal model.

• Using binary black hole signals, we compare BayesWave's performance to the theoretical best achievable performance in three key areas: sky localisation accuracy, signal/noise discrimination, and waveform reconstruction accuracy.
• BayesWave is most effective for signals that have very compact time-frequency representations.
• For binaries, where the signal time-frequency volume decreases with mass, we find that BayesWave's performance reaches or approaches theoretical optimal limits for system masses above approximately 50 M_sun.