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arxiv: 2503.15312 · v1 · pith:PN2LYZHUnew · submitted 2025-03-19 · 🌌 astro-ph.GA

Euclid Quick Data Release (Q1) Exploring galaxy properties with a multi-modal foundation model

Euclid Collaboration: M. Siudek , M. Huertas-Company , M. Smith , G. Martinez-Solaeche , F. Lanusse , S. Ho , E. Angeloudi , P. A. C. Cunha
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H. Dom\'inguez S\'anchez M. Dunn Y. Fu P. Iglesias-Navarro J. Junais J. H. Knapen B. Laloux M. Mezcua W. Roster G. Stevens J. Vega-Ferrero N. Aghanim B. Altieri A. Amara S. Andreon N. Auricchio H. Aussel C. Baccigalupi M. Baldi S. Bardelli P. Battaglia A. Biviano A. Bonchi E. Branchini M. Brescia J. Brinchmann S. Camera G. Ca\~nas-Herrera V. Capobianco C. Carbone J. Carretero S. Casas F. J. Castander M. Castellano G. Castignani S. Cavuoti K. C. Chambers A. Cimatti C. Colodro-Conde G. Congedo C. J. Conselice L. Conversi Y. Copin F. Courbin H. M. Courtois M. Cropper A. Da Silva H. Degaudenzi G. De Lucia A. M. Di Giorgio J. Dinis C. Dolding H. Dole F. Dubath C. A. J. Duncan X. Dupac S. Dusini S. Escoffier M. Farina R. Farinelli F. Faustini S. Ferriol F. Finelli S. Fotopoulou M. Frailis E. Franceschi S. Galeotta K. George B. Gillis C. Giocoli J. Gracia-Carpio B. R. Granett A. Grazian F. Grupp S. Gwyn S. V. H. Haugan W. Holmes I. M. Hook F. Hormuth A. Hornstrup K. Jahnke M. Jhabvala E. Keih\"anen S. Kermiche A. Kiessling B. Kubik M. K\"ummel M. Kunz H. Kurki-Suonio Q. Le Boulc'h A. M. C. Le Brun D. Le Mignant S. Ligori P. B. Lilje V. Lindholm I. Lloro G. Mainetti D. Maino E. Maiorano O. Mansutti S. Marcin O. Marggraf M. Martinelli N. Martinet F. Marulli R. Massey S. Maurogordato H. J. McCracken E. Medinaceli S. Mei M. Melchior Y. Mellier M. Meneghetti E. Merlin G. Meylan A. Mora M. Moresco L. Moscardini R. Nakajima C. Neissner S.-M. Niemi J. W. Nightingale C. Padilla S. Paltani F. Pasian K. Pedersen W. J. Percival V. Pettorino S. Pires G. Polenta M. Poncet L. A. Popa L. Pozzetti F. Raison A. Renzi J. Rhodes G. Riccio E. Romelli M. Roncarelli R. Saglia Z. Sakr A. G. S\'anchez D. Sapone B. Sartoris J. A. Schewtschenko P. Schneider T. Schrabback M. Scodeggio A. Secroun G. Seidel M. Seiffert S. Serrano P. Simon C. Sirignano G. Sirri L. Stanco J. Steinwagner P. Tallada-Cresp\'i A. N. Taylor I. Tereno S. Toft R. Toledo-Moreo F. Torradeflot I. Tutusaus L. Valenziano J. Valiviita T. Vassallo G. Verdoes Kleijn A. Veropalumbo Y. Wang J. Weller A. Zacchei G. Zamorani F. M. Zerbi I. A. Zinchenko E. Zucca V. Allevato M. Ballardini M. Bolzonella E. Bozzo C. Burigana R. Cabanac A. Cappi D. Di Ferdinando J. A. Escartin Vigo L. Gabarra J. Mart\'in-Fleitas S. Matthew N. Mauri R. B. Metcalf A. Pezzotta M. P\"ontinen C. Porciani I. Risso V. Scottez M. Sereno M. Tenti M. Viel M. Wiesmann Y. Akrami I. T. Andika S. Anselmi M. Archidiacono F. Atrio-Barandela C. Benoist K. Benson D. Bertacca M. Bethermin L. Bisigello A. Blanchard L. Blot M. L. Brown S. Bruton A. Calabro B. Camacho Quevedo F. Caro C. S. Carvalho T. Castro Y. Charles F. Cogato A. R. Cooray O. Cucciati S. Davini F. De Paolis G. Desprez A. D\'iaz-S\'anchez J. J. Diaz S. Di Domizio J. M. Diego P.-A. Duc A. Enia Y. Fang A. G. Ferrari P. G. Ferreira A. Finoguenov A. Fontana A. Franco K. Ganga J. Garc\'ia-Bellido T. Gasparetto V. Gautard E. Gaztanaga F. Giacomini F. Gianotti G. Gozaliasl M. Guidi C. M. Gutierrez A. Hall W. G. Hartley S. Hemmati C. Hern\'andez-Monteagudo H. Hildebrandt J. Hjorth J. J. E. Kajava Y. Kang V. Kansal D. Karagiannis K. Kiiveri C. C. Kirkpatrick S. Kruk J. Le Graet L. Legrand M. Lembo F. Lepori G. Leroy G. F. Lesci J. Lesgourgues L. Leuzzi T. I. Liaudat A. Loureiro J. Macias-Perez G. Maggio M. Magliocchetti E. A. Magnier F. Mannucci R. Maoli C. J. A. P. Martins L. Maurin M. Miluzio P. Monaco C. Moretti G. Morgante C. Murray K. Naidoo A. Navarro-Alsina S. Nesseris F. Passalacqua K. Paterson L. Patrizii A. Pisani D. Potter S. Quai M. Radovich S. Sacquegna M. Sahl\'en D. B. Sanders E. Sarpa A. Schneider D. Sciotti D. Scognamiglio E. Sellentin L. C. Smith K. Tanidis G. Testera R. Teyssier S. Tosi A. Troja M. Tucci C. Valieri A. Venhola D. Vergani G. Verza P. Vielzeuf N. A. Walton J. G. Sorce
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classification 🌌 astro-ph.GA
keywords dataeuclidmulti-modalastroptgalaxiesmodelembeddingsestimation
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Modern astronomical surveys, such as the Euclid mission, produce high-dimensional, multi-modal data sets that include imaging and spectroscopic information for millions of galaxies. These data serve as an ideal benchmark for large, pre-trained multi-modal models, which can leverage vast amounts of unlabelled data. In this work, we present the first exploration of Euclid data with AstroPT, an autoregressive multi-modal foundation model trained on approximately 300 000 optical and infrared Euclid images and spectral energy distributions (SEDs) from the first Euclid Quick Data Release. We compare self-supervised pre-training with baseline fully supervised training across several tasks: galaxy morphology classification; redshift estimation; similarity searches; and outlier detection. Our results show that: (a) AstroPT embeddings are highly informative, correlating with morphology and effectively isolating outliers; (b) including infrared data helps to isolate stars, but degrades the identification of edge-on galaxies, which are better captured by optical images; (c) simple fine-tuning of these embeddings for photometric redshift and stellar mass estimation outperforms a fully supervised approach, even when using only 1% of the training labels; and (d) incorporating SED data into AstroPT via a straightforward multi-modal token-chaining method improves photo-z predictions, and allow us to identify potentially more interesting anomalies (such as ringed or interacting galaxies) compared to a model pre-trained solely on imaging data.

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