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Extracting physical parameters from galaxies with machine learning","","Euclid preparation LXVIII presents a study on deriving physical parameters of galaxies using machine learning, supported by the Euclid Collaboration. The work is published in Astronomy & Astrophysics (A&A) with bibliographic details for volume and article number, and it lists the collaboration’s participating authors and affiliations. 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Extracting physical parameters from galaxies with machine learning  \nEuclid Collaboration: I. Kovai1; ?, M. Baes 1, A. Nersesian2 , 1, N. Andreadis 1, L. Nemani3 , Abdurro'uf4, L. Bisigello5 ,6, M. Bolzonella7, C. Tortora8, A. van der Wel 1, S. Cavuoti8 ,9, C. J. Conselice 10 , A. Enia 11 ,7, L. K. Hunt 12, P. Iglesias-Navarro 13 , 14, E. Iodice8, J. H. Knapen 13 , 14, F. R. Marleau 15 , O. Müller 16, R. F. Peletier 17, J. Román 14 , 13, R. Ragusa8 , P. Salucci 18 , 19, T. Saifollahi20, M. Scodeggio21, M. Siudek22 ,23 , T. De Waele 1, A. Amara24 , S. Andreon25 , N. Auricchio7 , C. Baccigalupi26 ,27 , 19 , 18 , M. Baldi 11 ,7 ,28 , S. Bardelli7 , P. Battaglia7 , R. Bender29 ,30 , C. Bodendorf29 , D. Bonino31 , W. Bon32 , E. Branchini33 ,34 ,25 , M. Brescia35 ,8 ,9 , J. Brinchmann36 ,37 , S. Camera38 ,39 ,31 , V. Capobianco31 , C. Carbone21 , J. Carretero40 ,41 , S. Casas42 ,  \nF. J. Castander23 ,43 , M. Castellano3 , G. Castignani7 , A. Cimatti44 , C. Colodro-Conde 13 , G. Congedo45 ,  \nL. Conversi46 ,47 , Y. Copin48 , F. Courbin 16 ,49 ,50 , H. M. Courtois51 , A. Da Silva52 ,53 , H. Degaudenzi54 , G. De Lucia27 , A. M. Di Giorgio55 , J. Dinis52 ,53 , M. Douspis56 , F. Dubath54 , X. Dupac47 , S. Dusini57 , A. Ealet48 , M. Farina55 , S. Farrens58 , F. Faustini59 ,3 , S. Ferriol48 , P. Fosalba43 ,23 , M. Frailis27 , E. Franceschi7 , S. Galeotta27 , B. Gillis45 , C. Giocoli7 ,60 , A. Grazian61 , F. Grupp29 ,30 , L. Guzzo62 ,25 , S. V. H. Haugan63 , W. Holmes64 , I. Hook65 , F. Hormuth66 , A. Hornstrup67 ,68 , K. Jahnke69 , M. Jhabvala70 , B. Joachimi71 , E. Keihänen72 , S. Kermiche73 , A. Kiessling64 , M. Kilbinger58 , B. Kubik48 , K. Kuijken74 , M. Kümmel30 , M. Kunz75 , H. Kurki-Suonio76 ,77 , S. Ligori31 , P. B. Lilje63 , V. Lindholm76 ,77 , I. Lloro78 , D. Maino62 ,21 ,79 , E. Maiorano7 , O. Mansutti27 , S. Marcin80 , O. Marggraf81 , K. Markovic64 , M. Martinelli3 ,82 , N. Martinet32 , F. Marulli83 ,7 ,28 , R. Massey84 , E. Medinaceli7 , S. Mei85 , M. Melchior80 , Y. Mellier86 ,87 , M. Meneghetti7 ,28 , E. Merlin3 , G. Meylan 16 , M. Moresco83 ,7 , L. Moscardini83 ,7 ,28 ,  \nS.-M. Niemi88 , J. W. Nightingale89 , C. Padilla90 , S. Paltani54 , F. Pasian27 , K. Pedersen91 , V. Pettorino88 , S. Pires58 , G. Polenta59 , M. Poncet92 , L. A. Popa93 , L. Pozzetti7 , F. Raison29 , R. Rebolo 13 , 14 ,94 , A. Renzi6 ,57 , J. Rhodes64 , G. Riccio8 , E. Romelli27 , M. Roncarelli7 , E. Rossetti 11 , R. Saglia30 ,29 , Z. Sakr95 ,96 ,97 , A. G. Sánchez29 , D. Sapone98 , B. Sartoris30 ,27 , M. Schirmer69 , P. Schneider81 , T. Schrabback 15 , A. Secroun73 , G. Seidel69 , S. Serrano43 ,99 ,23 , C. Sirignano6 ,57 , G. Sirri28 , L. Stanco57 , J. Steinwagner29 , P. Tallada-Crespí40 ,41 , D. Tavagnacco27 , A. N. Taylor45 , H. I. Teplitz 100 , I. Tereno52 , 101 , R. Toledo-Moreo 102 , F. Torradeflot41 ,40 , I. Tutusaus96 , L. Valenziano7 , 103 , T. Vassallo30 ,27 , G. Verdoes Kleijn 17 , A. Veropalumbo25 ,34 , 104 , Y. Wang 100 , J. Weller30 ,29 , A. Zacchei27 ,26 , G. Zamorani7 , E. Zucca7 , A. Biviano27 ,26 , E. Bozzo54 , C. Burigana5 , 103 , M. Calabrese 105 ,21 , D. Di Ferdinando28 , J. A. Escartin Vigo29 , F. Finelli7 , 103 , J. Gracia-Carpio29 , S. Matthew45 , N. Mauri44 ,28 , M. Pöntinen76 , V. Scottez86 , 106 ,  \nM. Tenti28 , M. Viel26 ,27 , 18 , 19 , 107 , M. Wiesmann63 , Y. Akrami 108 , 109 , V. Allevato8 , S. Alvi 110 , S. Anselmi57 ,6 , 111 , M. Archidiacono62 ,79 , F. At","cbCaii2wQe4pNkcd","https://ap.wps.com/l/cbCaii2wQe4pNkcd","pdf",7827726,26,"English","# Euclid preparation\n## LXVIII. Extracting physical parameters from galaxies with machine learning\n## Publication and authorship details","[{\"question\":\"What is the main topic of Euclid preparation LXVIII?\",\"answer\":\"Extracting physical parameters from galaxies using machine learning.\"},{\"question\":\"Which collaboration is associated with the work?\",\"answer\":\"The Euclid Collaboration is listed as the author group.\"},{\"question\":\"Where and when was the paper received and accepted?\",\"answer\":\"The document states it was received on 21 November 2024 and accepted on 23 January 2025.\"}]","Euclid preparation - LXVIII. Extracting physical parameters from galaxies with machine learning | PDF",66]