Application of the independent component analysis to the iKAGRA data

KAGRA Collaboration,Akutsu T.,Ando M.,Arai K.,Arai Y.,Araki S.,Araya A.,Aritomi N.,Asada H.,Aso Y.,Atsuta S.,Awai K.,Bae S.,Bae Y.,Baiotti L.,Bajpai R.,Barton M. A.,Cannon K., Capocasa E.,Chan M.,Chen C.,Chen K.,Chen Y.,Chu H.,Chu Y-K.,Craig K.,Creus W.,Doi K.,Eda K.,Eguchi S.,Enomoto Y.,Flaminio R.,Fujii Y.,Fujimoto M. -K.,Fukunaga M.,Fukushima M.,Furuhata T.,Ge G.,Hagiwara A.,Haino S.,Hasegawa K.,Hashino K.,Hayakawa H.,Hayama K.,Himemoto Y.,Hiranuma Y.,Hirata N.,Hirobayashi S.,Hirose E.,Hong Z.,Hsieh B. H.,Huang G-Z.,Huang P.,Huang Y.,Ikenoue B.,Imam S.,Inayoshi K.,Inoue Y.,Ioka K.,Itoh Y.,Izumi K.,Jung K.,Jung P.,Kaji T.,Kajita T.,Kakizaki M.,Kamiizumi M.,Kanbara S.,Kanda N.,Kanemura S.,Kaneyama M.,Kang G.,Kasuya J.,Kataoka Y.,Kawaguchi K.,Kawai N.,Kawamura S.,Kawasaki T.,Kim C.,Kim J. C.,Kim W. S.,Kim Y. -M.,Kimura N.,Kinugawa T.,Kirii S.,Kita N.,Kitaoka Y.,Kitazawa H.,Kojima Y.,Kokeyama K.,Komori K.,Kong A. K. H.,Kotake K.,Kozakai C.,Kozu R.,Kumar R.,Kume J.,Kuo C.,Kuo H-S.,Kuroyanagi S.,Kusayanagi K.,Kwak K.,Lee H. K.,Lee H. M.,Lee H. W.,Lee R.,Leonardi M.,Lin C.,Lin C-Y.,Lin F-L.,Liu G. C.,Liu Y.,Luo L.,Majorana E.,Mano S.,Marchio M.,Matsui T.,Matsushima F.,Michimura Y.,Mio N.,Miyakawa O.,Miyamoto A.,Miyamoto T.,Miyazaki Y.,Miyo K.,Miyoki S.,Morii W.,Morisaki S.,Moriwaki Y.,Morozumi T.,Musha M.,Nagano K.,Nagano S.,Nakamura K.,Nakamura T.,Nakano H.,Nakano M.,Nakao K.,Nakashima R.,Narikawa T.,Naticchioni L.,Negishi R.,Quynh L. Nguyen,Ni W. -T.,Nishizawa A.,Obuchi Y.,Ochi T.,Ogaki W.,Oh J. J.,Oh S. H.,Ohashi M.,Ohishi N.,Ohkawa M.,Okutomi K.,Oohara K.,Ooi C. P.,Oshino S.,Pan K.,Pang H.,Park J.,Arellano F. E. Pena,Pinto I.,Sago N.,Saijo M.,Saito S.,Saito Y.,Sakai K.,Sakai Y.,Sakuno Y.,Sasaki M.,Sasaki Y.,Sato S.,Sato T.,Sawada T.,Sekiguchi T.,Sekiguchi Y.,Seto N.,Shibagaki S.,Shibata M.,Shimizu R.,Shimoda T.,Shimode K.,Shinkai H.,Shishido T.,Shoda A., Somiya K.,Son E. J.,Sotani H.,Suemasa A.,Sugimoto R.,Suzuki T.,Tagoshi H.,Takahashi H.,Takahashi R.,Takamori A.,Takano S.,Takeda H.,Takeda M.,Tanaka H.,Tanaka K.,Tanaka T.,Tanioka S.,Martin E. N. Tapia San,Tatsumi D.,Telada S.,Tomaru T.,Tomigami Y.,Tomura T.,Travasso F.,Trozzo L.,Tsang T.,Tsubono K.,Tsuchida S.,Tsuzuki T.,Tuyenbayev D.,Uchikata N.,Uchiyama T.,Ueda A.,Uehara T.,Ueki S.,Ueno K.,Ueshima G.,Uraguchi F.,Ushiba T.,van Putten M. H. P. M.,Vocca H.,Wada S.,Wakamatsu T.,Wang J.,Wu C.,Wu H.,Wu S.,Xu W-R.,Yamada T.,Yamamoto A.,Yamamoto K.,Yamamoto S.,Yamamoto T.,Yokogawa K.,Yokoyama J.,Yokozawa T.,Yoon T. H.,Yoshioka T.,Yuzurihara H.,Zeidler S.,Zhao Y.,Zhu Z. -H.

PROGRESS OF THEORETICAL AND EXPERIMENTAL PHYSICS（2020）

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摘要

We apply independent component analysis (ICA) to real data from a gravitational wave detector for the first time. Specifically, we use the iKAGRA data taken in April 2016, and calculate the correlations between the gravitational wave strain channel and 35 physical environmental channels. Using a couple of seismic channels which are found to be strongly correlated with the strain, we perform ICA. Injecting a sinusoidal continuous signal in the strain channel, we find that ICA recovers correct parameters with enhanced signal-to-noise ratio, which demonstrates the usefulness of this method. Among the two implementations of ICA used here, we find the correlation method yields the optimal results for the case of environmental noise acting on the strain channel linearly.

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independent component analysis,data

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