论文标题
使用Gengli模拟Ligo中的瞬态噪声爆发
Simulating Transient Noise Bursts in LIGO with gengli
论文作者
论文摘要
在重力波（GW）干涉仪的领域中，从天体物理源检测到瞬态信号的最严重局限性来自瞬态噪声伪影，称为故障，以每分钟$ 1 $ $ 1美元的速度发生。由于故障减少了可用的科学数据的量，因此需要在大规模研究中更好地建模和包含小故障，例如对搜索管道进行压力测试并提高检测的信心。在这项工作中，我们采用生成对抗网络（GAN）在时域中产生特定的故障（{\ it blip}）。我们通过用户友好的开源软件包共享训练有素的网络，称为\ texttt {gengli}，并提供了其使用情况的实际示例。
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.
