A Deep learning method for event recognition in CALET data

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dc.contributor.authorCALET Collaboration
dc.contributor.authorPicquenot, Adrien
dc.contributor.authorNegro, Michela
dc.contributor.authorCannady, Nicholas
dc.contributor.authorHams, Thomas
dc.contributor.authorAdriani, O.
dc.contributor.authorAkaike, Y.
dc.contributor.authorAsano, K.
dc.contributor.authoret al.
dc.date.accessioned2025-08-13T20:14:41Z
dc.date.issued2025-07-22
dc.descriptionICRC 2025 The Astroparticle Physics Conference. Geneva, Switzerland, 14-24, July 2024. Authors - CALET Collaboration: O. Adriani,1,2 Y. Akaike,3,4 K. Asano,5 Y. Asaoka,5 E. Berti,2,6 P. Betti, 2,6 G. Bigongiari,7,8 W.R. Binns,9 M. Bongi,1,2 P. Brogi,7,8 A. Bruno,10 N. Cannady,11 G. Castellini,6 C. Checchia,7,8 M.L. Cherry,12 G.Collazuol,13,14 G.A. de Nolfo,10 K. Ebisawa,15 A. W. Ficklin,12 H. Fuke,15 S. Gonzi,1,2,6 T.G. Guzik,12 T. Hams,16 K.Hibino,17 M. Ichimura,18 M.H.Israel,9 K. Kasahara,19 J. Kataoka,20 R. Kataoka,21 Y. Katayose,22 C. Kato,23 N. Kawanaka,24,25 Y. Kawakubo,26 K. Kobayashi,3,4 K. Kohri,25,27 H.S. Krawczynski, 9 J.F. Krizmanic,11 P. Maestro,7,8 P.S. Marrocchesi,7,8 M. Mattiazzi,13,14 A.M.Messineo,8,28 J.W. Mitchell,11 S. Miyake,29 A.A. Moiseev, 11,30,31 M. Mori,32 N. Mori,2 H.M. Motz,33 K. Munakata,23 S. Nakahira,15 J.Nishimura,15 M.Negro,12 S. Okuno,17 J.F. Ormes,34 S. Ozawa,35 L. Pacini,2,6 P. Papini,2 B.F. Rauch,9 S.B. Ricciarini,2,6 K. Sakai,36 T. Sakamoto,26 M. Sasaki, 11,30,31 Y. Shimizu,17 A. Shiomi,37 P. Spillantini,1 F. Stolzi,7,8 S. Sugita,26 A. Sulaj, 7,8 M.Takita,5 T.Tamura,17 T.Terasawa,5 S.Torii,3 Y.Tsunesada,38,39 Y.Uchihori,40 E. Vannuccini,2 J.P.Wefel,12 K.Yamaoka,41 S.Yanagita,42 A.Yoshida,26 K.Yoshida,19 and W. V. Zober 9
dc.description.abstractIn this study we:- Apply unsupervised machine learning methods to classify CREs from CALET data. the goal is to minimize dependence on MC simulations and pursue a data-driven classification.- We evaluate algorithm performance using simulations, then apply the optimized models directly to real data.
dc.description.urihttps://indico.cern.ch/event/1258933/contributions/6486501/
dc.format.extent32 pages
dc.genreconference papers and proceedings
dc.genrepresentations (communicative events)
dc.identifierdoi:10.13016/m2xz5u-egwa
dc.identifier.urihttp://hdl.handle.net/11603/39806
dc.language.isoen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Center for Space Sciences and Technology (CSST) / Center for Research and Exploration in Space Sciences & Technology II (CRSST II)
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
dc.rightsPublic Domain
dc.rights.urihttps://creativecommons.org/publicdomain/mark/1.0/
dc.titleA Deep learning method for event recognition in CALET data
dc.typeText

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