Complete Parameter Inference for Binary Black Hole Coalescences using Deep Learning

Stephen Green Albert Einstein Institute Potsdam Postdoctoral Researcher Abstract: The LIGO and Virgo gravitational-wave observatories have detected many exciting events over the past five years. As the rate of detections grows with detector sensitivity, this poses a growing computational challenge for data analysis. With this in mind, in this work we apply deep learning techniques to perform fast likelihood-free Bayesian inference for gravitational waves. We train a neural-network conditional density estim