Unsupervised learning architecture for classifying the transient noise of interferometric gravitational-wave detectors

Abstract In the data obtained by laser interferometric gravitational wave detectors, transient noise with non-stationary and non-Gaussian features occurs at a high rate. This often results in problems such as detector instability and the hiding and/or imitation of gravitational-wave signals. This tr...

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Bibliographic Details
Published in:Scientific Reports
Main Authors: Yusuke Sakai, Yousuke Itoh, Piljong Jung, Keiko Kokeyama, Chihiro Kozakai, Katsuko T. Nakahira, Shoichi Oshino, Yutaka Shikano, Hirotaka Takahashi, Takashi Uchiyama, Gen Ueshima, Tatsuki Washimi, Takahiro Yamamoto, Takaaki Yokozawa
Format: Article
Language:English
Published: Nature Portfolio 2022-06-01
Online Access:https://doi.org/10.1038/s41598-022-13329-4

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