Nuclear and High Energy Physics; astro-ph.IM; glitches; gravitational waves; generative adversarial network; GAN; deep learning; LIGO; noise transients
Abstract :
[en] The noise of gravitational-wave (GW) interferometers limits their sensitivity and impacts the data quality, hindering the detection of GW signals from astrophysical sources. For transient searches, the most problematic are transient noise artifacts, known as glitches, that happen at a rate around 1 min-1, and can mimic GW signals. Because of this, there is a need for better modeling and inclusion of glitches in large-scale studies, such as stress testing the pipelines. In this proof-of concept work we employ generative adversarial networks (GAN), a state-of-the-art deep learning algorithm inspired by game theory, to learn the underlying distribution of blip glitches and to generate artificial populations. We reconstruct the glitch in the time domain, providing a smooth input that the GAN can learn. With this methodology, we can create distributions of ∼103 glitches from Hanford and Livingston detectors in less than 1 sec. Furthermore, we employ several metrics to measure the performance of our methodology and the quality of its generations. This investigation will be extended in the future to different glitch classes with the final goal of creating an open-source interface for mock data generation.
Disciplines :
Space science, astronomy & astrophysics
Author, co-author :
Lopez, Melissa ; Institute for Gravitational and Subatomic Physics (GRASP), Department of Physics, Utrecht University, Utrecht, Netherlands ; Nikhef, Amsterdam, Netherlands
Boudart, Vincent ; Université de Liège - ULiège > Unités de recherche interfacultaires > Space sciences, Technologies and Astrophysics Research (STAR)
Buijsman, Kerwin ; Randstad, Diemen, Netherlands ; Gravitation and Astroparticle Physics Amsterdam (GRAPPA), Institute for Theoretical Physics Amsterdam, University of Amsterdam, Amsterdam, Netherlands
Reza, Amit; Institute for Gravitational and Subatomic Physics (GRASP), Department of Physics, Utrecht University, Utrecht, Netherlands ; Nikhef, Amsterdam, Netherlands
Caudill, Sarah; Institute for Gravitational and Subatomic Physics (GRASP), Department of Physics, Utrecht University, Utrecht, Netherlands ; Nikhef, Amsterdam, Netherlands
Language :
English
Title :
Simulating transient noise bursts in LIGO with generative adversarial networks
FWB - Fédération Wallonie-Bruxelles [BE] NWO - Nederlandse Organisatie voor Wetenschappelijk Onderzoek [NL] NSF - National Science Foundation [US-VA] [US-VA]
Funding text :
The authors thank Chris Messenger, Siddharth Soni, Jess McIver, Marco Cavaglia, Alejandro Torres-Forné, and Harsh Narola for their useful comments. V. B. is supported by the Gravitational Wave Science (GWAS) Grant funded by the French Community of Belgium, and M. L., S. C., and A. R are supported by the research program of the Netherlands Organisation for Scientific Research (NWO). The authors are grateful for computational resources provided by the LIGO Laboratory and supported by the National Science Foundation Grants No. PHY-0757058 and No. PHY-0823459. This material is based upon work supported by NSF’s LIGO Laboratory which is a major facility fully funded by the National Science Foundation.
Commentary :
17 pages, 21 figures to be published in Physical Review D
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