Karlsruhe 2024 – scientific programme

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T: Fachverband Teilchenphysik

T 67: Data, AI, Computing 5 (normalising flows)

T 67.2: Talk

Wednesday, March 6, 2024, 16:15–16:30, Geb. 30.33: MTI

Parameter reconstruction for gravitational wave signals at the Einstein Telescope using conditional normalizing flows — Johannes Erdmann and •Tobias Reike — III. Physikalisches Institut A, RWTH Aachen University

The proposed Einstein Telescope will be a gravitational wave detector of the third generation. It will improve the sensitivity compared to the current interferometers LIGO and VIRGO by an order of magnitude, resulting in a substantial additional volume for observation. The sensitive frequency range of the Einstein Telescope will also be much larger, allowing it to observe signals earlier and for longer durations. These improvements will significantly increase the amount of incoming data compared to current experiments, so that more efficient ways of processing data are needed.

Deep learning presents a promising option for fast analysis of incoming data, handling event detection as well as reconstruction. This talk will focus on simultaneous detection and parameter estimation of gravitational wave signals from Binary Black Hole Mergers using conditional normalizing flows.

Keywords: Einstein Telescope; gravitational waves; deep learning; normalizing flows