Simulating transient burst noise with gengli
Publication date
2025-08
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taverne
Abstract
In the field of gravitational-wave (GW) interferometers, the most severe limitation to the detection of transient signals from astrophysical sources comes from transient noise artefacts, known as glitches, that happens at a rate around 1 per minute. Because glitches reduce the amount of scientific data available, there is a need for better modelling and inclusion of glitches in large-scale studies, such as stress testing the search pipelines and increasing the confidence of detection. In this work, we employ a Generative Adversarial Network (GAN) to produce a particular class of glitches (blip) in the time domain. We share the trained network through a user-friendly open-source software package called gengli and provide practical examples of its usage.
Keywords
Generative adversarial networks, gravitational waves, machine learning, synthetic data, Taverne, Astronomy and Astrophysics, Space and Planetary Science
Citation
Lopez, M, Boudart, V, Schmidt, S & Caudill, S 2025, 'Simulating transient burst noise with gengli', Proceedings of the International Astronomical Union, vol. 19, no. S368, pp. 73-79. https://doi.org/10.1017/S1743921323001047