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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書誌詳細

出版年:	Scientific Reports
主要な著者:	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
フォーマット:	論文
言語:	英語
出版事項:	Nature Portfolio 2022-06-01
オンライン･アクセス:	https://doi.org/10.1038/s41598-022-13329-4