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 ({\it blip}) in the time domain. We share the trained network through a user-friendly open-source software package called \texttt{gengli} and provide practical examples of its usage.
@article{arxiv.2205.09204,
title = {Simulating Transient Noise Bursts in LIGO with gengli},
author = {Melissa Lopez and Vincent Boudart and Stefano Schmidt and Sarah Caudill},
journal= {arXiv preprint arXiv:2205.09204},
year = {2022}
}