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GR: Fachverband Gravitation und Relativitätstheorie

GR 9: Gravitational Waves

GR 9.1: Talk

Wednesday, March 23, 2022, 16:15–16:35, GR-H2

Machine Learning Gravitational-Wave Search Mock Data Challenge — •Marlin Benedikt Schäfer — Albert-Einstein-Institut, D-30167 Hannover, Germany — Leibniz Universität Hannover, D-30167 Hannover, Germany

Gravitational wave astronomy is a rapidly growing field and the number of detections is rising faster with each observational period. With this come new challenges when extracting the signals from noise. A new approach to handle large quantities of data and possibly search regions of parameter space that are computationally prohibitive to search with state-of-the-art classical algorithms is the utilization of machine learning techniques. This projects aims to clarify the capabilities of current deep learning algorithms and how they compare to traditional methods. The challenge provides mock data of gradually increasing realism to aid the adoption of machine learning based algorithms in detection pipelines and wants to help establishing the wide adoption of astrophysically motivated evaluation metrics.