Training Process of Unsupervised Learning Architecture for Gravity Spy Dataset
Training Process of Unsupervised Learning Architecture for Gravity Spy Dataset
复制标题
重力间谍数据集无监督学习架构的训练过程
DOI：
10.1002/andp.202200140
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发表时间：
2022
影响因子：
2.4
通讯作者：
and Takaaki Yokozawa
中科院分区：
文献类型：
--
作者：
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;and Takaaki Yokozawa
来自引力波探测器的数据中出现的瞬态噪声经常会导致问题，例如探测器的不稳定性以及重叠或模仿引力波信号。由于瞬态噪声被认为与环境和仪器有关，因此对其进行分类将有助于了解其来源并提高探测器的性能。在以前的研究中，提出了一种使用时频2D图像（频谱图）对瞬态噪声进行分类的架构，该架构使用无监督深度学习结合变分自动编码器和不变信息聚类。将所提出的无监督学习架构应用于Gravity Spy数据集，该数据集由高级激光干涉仪引力波天文台（Advanced LIGO）瞬态噪声及其相关元数据组成，以讨论在线或离线数据分析的潜力。在这项研究中，重点关注Gravity Spy数据集，检查并报告了先前研究的无监督学习架构的训练过程。
Transient noise appearing in the data from gravitational‐wave detectors frequently causes problems, such as instability of the detectors and overlapping or mimicking gravitational‐wave signals. Because transient noise is considered to be associated with the environment and instrument, its classification would help to understand its origin and improve the detector's performance. In a previous study, an architecture for classifying transient noise using a time–frequency 2D image (spectrogram) is proposed, which uses unsupervised deep learning combined with variational autoencoder and invariant information clustering. The proposed unsupervised‐learning architecture is applied to the Gravity Spy dataset, which consists of Advanced Laser Interferometer Gravitational‐Wave Observatory (Advanced LIGO) transient noises with their associated metadata to discuss the potential for online or offline data analysis. In this study, focused on the Gravity Spy dataset, the training process of unsupervised‐learning architecture of the previous study is examined and reported.
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影响因子：
3.5
作者：
S. Soni;C. Austin;A. Effler;R. Schofield;G. González;V. Frolov;J. Driggers;A. Pele;A. Urban;G. Valdes;R. Abbott;C. Adams;R. Adhikari;A. Ananyeva;S. Appert;K. Arai;J. Areeda;Y. Asali;S. Aston;A. Baer;M. Ball;S. Ballmer;S. Banagiri;D. Barker;L. Barsotti;J. Bartlett;B. Berger;J. Betzwieser;D. Bhattacharjee;G. Billingsley;S. Biscans;C. Blair;R. Blair;N. Bode;P. Booker;R. Bork;A. Bramley;A. Brooks;D. Brown;A. Buikema;C. Cahillane;K. Cannon;X. Chen;A. Ciobanu;F. Clara;S. Cooper;K. Corley;S. Countryman;P. Covas;D. Coyne;L. Datrier;D. Davis;C. D. Fronzo;K. Dooley;P. Dupej;S. Dwyer;T. Etzel;M. Evans;T. Evans;J. Feicht;Á. Fernández-Galiana;P. Fritschel;P. Fulda;M. Fyffe;J. Giaime;K. Giardina;P. Godwin;E. Goetz;S. Gras;C. Gray;R. Gray;A. Green;E. Gustafson;R. Gustafson;J. Hanks;J. Hanson;T. Hardwick;R. Hasskew;M. Heintze;A. Helmling-Cornell;N. Holland;J. Jones;S. Kandhasamy;S. Karki;M. Kasprzack;K. Kawabe;N. Kijbunchoo;P. King;J. Kissel;Rahul Kumar;M. Landry;B. Lane;B. Lantz;M. Laxen;Y. Lecoeuche;J. Leviton;J. Liu;M. Lormand;A. Lundgren;R. Macas;M. Macinnis;D. Macleod;G. Mansell;S. M'arka;Z. M'arka;D. Martynov;K. Mason;T. Massinger;F. Matichard;N. Mavalvala;R. McCarthy;D. McClelland;S. Mccormick;L. McCuller;J. McIver;T. McRae;G. Mendell;K. Merfeld;E. Merilh;F. Meylahn;T. Mistry;R. Mittleman;G. Moreno;C. Mow-Lowry;S. Mozzon;A. Mullavey;T. Nelson;P. Nguyen;L. Nuttall;J. Oberling;R. Oram;C. Osthelder;D. Ottaway;H. Overmier;J. R. Palamos;W. Parker;E. Payne;R. Penhorwood;C. Perez;M. Pirello;H. Radkins;K. Ramirez;J. Richardson;K. Riles;N. Robertson;J. Rollins;C. Romel;J. Romie;M. Ross;K. Ryan;T. Sadecki;E. Sanchez;L. Sanchez;T. R. Saravanan;R. Savage;D. Schaetzl;R. Schnabel;E. Schwartz;D. Sellers;T. Shaffer;D. Sigg;B. Slagmolen;J. R. Smith;B. Sorazu;A. Spencer;K. Strain;L. Sun;M. J. Szczepa'nczyk;M. Thomas;P. Thomas;K. Thorne;K. Toland;C. Torrie;G. Traylor;M. Tse;G. Vajente;D. Vander-Hyde;P. Veitch;K. Venkateswara;Gautam Venugopalan;A. Viets;T. Vo;C. Vorvick;M. Wade;R. Ward;J. Warner;B. Weaver;R. Weiss;C. Whittle;B. Willke;C. Wipf;L. Xiao;H. Yamamoto;Hang Yu;Haocun Yu;L. Zhang;M. Zucker;J. Zweizig
通讯作者：
S. Soni;C. Austin;A. Effler;R. Schofield;G. González;V. Frolov;J. Driggers;A. Pele;A. Urban;G. Valdes;R. Abbott;C. Adams;R. Adhikari;A. Ananyeva;S. Appert;K. Arai;J. Areeda;Y. Asali;S. Aston;A. Baer;M. Ball;S. Ballmer;S. Banagiri;D. Barker;L. Barsotti;J. Bartlett;B. Berger;J. Betzwieser;D. Bhattacharjee;G. Billingsley;S. Biscans;C. Blair;R. Blair;N. Bode;P. Booker;R. Bork;A. Bramley;A. Brooks;D. Brown;A. Buikema;C. Cahillane;K. Cannon;X. Chen;A. Ciobanu;F. Clara;S. Cooper;K. Corley;S. Countryman;P. Covas;D. Coyne;L. Datrier;D. Davis;C. D. Fronzo;K. Dooley;P. Dupej;S. Dwyer;T. Etzel;M. Evans;T. Evans;J. Feicht;Á. Fernández-Galiana;P. Fritschel;P. Fulda;M. Fyffe;J. Giaime;K. Giardina;P. Godwin;E. Goetz;S. Gras;C. Gray;R. Gray;A. Green;E. Gustafson;R. Gustafson;J. Hanks;J. Hanson;T. Hardwick;R. Hasskew;M. Heintze;A. Helmling-Cornell;N. Holland;J. Jones;S. Kandhasamy;S. Karki;M. Kasprzack;K. Kawabe;N. Kijbunchoo;P. King;J. Kissel;Rahul Kumar;M. Landry;B. Lane;B. Lantz;M. Laxen;Y. Lecoeuche;J. Leviton;J. Liu;M. Lormand;A. Lundgren;R. Macas;M. Macinnis;D. Macleod;G. Mansell;S. M'arka;Z. M'arka;D. Martynov;K. Mason;T. Massinger;F. Matichard;N. Mavalvala;R. McCarthy;D. McClelland;S. Mccormick;L. McCuller;J. McIver;T. McRae;G. Mendell;K. Merfeld;E. Merilh;F. Meylahn;T. Mistry;R. Mittleman;G. Moreno;C. Mow-Lowry;S. Mozzon;A. Mullavey;T. Nelson;P. Nguyen;L. Nuttall;J. Oberling;R. Oram;C. Osthelder;D. Ottaway;H. Overmier;J. R. Palamos;W. Parker;E. Payne;R. Penhorwood;C. Perez;M. Pirello;H. Radkins;K. Ramirez;J. Richardson;K. Riles;N. Robertson;J. Rollins;C. Romel;J. Romie;M. Ross;K. Ryan;T. Sadecki;E. Sanchez;L. Sanchez;T. R. Saravanan;R. Savage;D. Schaetzl;R. Schnabel;E. Schwartz;D. Sellers;T. Shaffer;D. Sigg;B. Slagmolen;J. R. Smith;B. Sorazu;A. Spencer;K. Strain;L. Sun;M. J. Szczepa'nczyk;M. Thomas;P. Thomas;K. Thorne;K. Toland;C. Torrie;G. Traylor;M. Tse;G. Vajente;D. Vander-Hyde;P. Veitch;K. Venkateswara;Gautam Venugopalan;A. Viets;T. Vo;C. Vorvick;M. Wade;R. Ward;J. Warner;B. Weaver;R. Weiss;C. Whittle;B. Willke;C. Wipf;L. Xiao;H. Yamamoto;Hang Yu;Haocun Yu;L. Zhang;M. Zucker;J. Zweizig
影响因子：
3.5
作者：
S. Soni;C. Berry;S. Coughlin;M. Harandi;C. Jackson;Kevin Crowston;C. Osterlund;O. Patane;A. Katsaggelos;L. Trouille;V-G Baranowski;W. Domainko;K. Kamiński;M. A. L. Rodriguez;U. Marciniak;P. Nauta;G. Niklasch;R. Rote;B. T'egl'as;C. Unsworth;C. Zhang
通讯作者：
S. Soni;C. Berry;S. Coughlin;M. Harandi;C. Jackson;Kevin Crowston;C. Osterlund;O. Patane;A. Katsaggelos;L. Trouille;V-G Baranowski;W. Domainko;K. Kamiński;M. A. L. Rodriguez;U. Marciniak;P. Nauta;G. Niklasch;R. Rote;B. T'egl'as;C. Unsworth;C. Zhang
高级 LIGO
影响因子：
3.5
作者：
Aasi, J.;Abbott, B. P.;Zweizig, J.
通讯作者：
Zweizig, J.
KAGRA中的干涉仪校准方法
DOI：
--
发表时间：
2018
期刊：
影响因子：
--
作者：
小坂井 千紘;KAGRA collaboration;Chihiro Kozakai on behalf of the KAGRA collaboration;小坂井 千紘;小坂井千紘;小坂井千紘
通讯作者：
小坂井千紘
影响因子：
3.5
作者：
Nguyen, P.;Schofield, R. M. S.;Zweizig, J.
通讯作者：
Zweizig, J.