Speaker
Ondřej Zelenka
(Czech Academy of Sciences)
Description
Conventional searches for gravitational wave signals in detector data are computationally demanding and struggle when certain transient noise sources are present. Recently, machine-learning algorithms have been proposed to address current and future challenges. We present a neural-network based algorithm to search for binary black hole waveforms. We also apply our algorithm to real O3b data and recover the relevant events of the GWTC-3 catalog.
