Euclid Quick Data Release (Q1): XXVII. The Strong Lensing Discovery Engine B – Early strong lens candidates from visual inspection of high-velocity dispersion galaxies

Rojas, K.; Collett, T.E.; Acevedo Barroso, J.A.; Nightingale, J.W.; Stern, D.; Moustakas, L.A.; Schuldt, S.; Despali, G.; Melo, A.; Walmsley, M.; Ballard, D.J.; Enzi, W.J.R.; Li, T.; Sainz de Murieta, A.; Andika, I.T.; Clément, B.; Courbin, F.; Ecker, L.R.; Gavazzi, R.; Jackson, N.; Kovács, A.; Matavulj, P.; Meneghetti, M.; Serjeant, S.; Sluse, Dominique; Tortora, C.; Verma, A.; Marchetti, L.; O’Riordan, C.M.; McCarthy, K.; Suyu, S.H.; Metcalf, R.B.; Diego, J.M.; Lines, N.E.P.; Aghanim, N.; Altieri, B.; Amara, A.; Andreon, S.; Auricchio, N.; Aussel, H.; Baccigalupi, C.; Baldi, M.; Balestra, A.; Bardelli, S.; Battaglia, P.; Bender, R.; Biviano, A.; Bonchi, A.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Cañas-Herrera, G.; Capobianco, V.; Carbone, C.; Cardone, V.F.; Carretero, J.; Casas, S.; Castellano, M.; Castignani, G.; Cavuoti, S.; Chambers, K.C.; Cimatti, A.; Colodro-Conde, C.; Congedo, G.; Conselice, C.J.; Conversi, L.; Copin, Y.; Courtois, H.M.; Cropper, M.; Da Silva, A.; Degaudenzi, H.; De Lucia, G.; Di Giorgio, A.M.; Dolding, C.; Dole, H.; Dubath, F.; Dupac, X.; Escoffier, S.; Fabricius, M.; Farina, M.; Farinelli, R.; Faustini, F.; Ferriol, S.; Finelli, F.; Fotopoulou, S.; Frailis, M.; Franceschi, E.; Galeotta, S.; George, K.; Gillard, W.; Gillis, B.; Giocoli, C.; Gómez-Alvarez, P.; Gracia-Carpio, J.; Granett, B.R.; Grazian, A.; Grupp, F.; Guzzo, L.; Gwyn, S.; Haugan, S.V.H.; Holmes, W.; Hook, I.M.; Hormuth, F.; Hornstrup, A.; Hudelot, P.; Jahnke, K.; Jhabvala, M.; Keihänen, E.; Kermiche, S.; Kiessling, A.; Kubik, B.; Kuijken, K.; Kümmel, M.; Kunz, M.; Kurki-Suonio, H.; Le Boulc’h, Q.; Le Brun, A.M.C.; Le Mignant, D.; Liebing, P.; Ligori, S.; Lilje, P.B.; Lindholm, V.; Lloro, I.; Mainetti, G.; Maino, D.; Maiorano, E.; Mansutti, O.; Marcin, S.; Marggraf, O.; Martinelli, M.; Martinet, N.; Marulli, F.; Massey, R.; Maurogordato, S.; McCracken, H.J.; Medinaceli, E.; Mei, S.; Melchior, M.; Mellier, Y.; Merlin, E.; Meylan, G.; Mora, A.; Moresco, M.; Moscardini, L.; Nakajima, R.; Neissner, C.; Nichol, R.C.; Niemi, S.-M.; Padilla, C.; Paltani, S.; Pasian, F.; Pedersen, K.; Percival, W.J.; Pettorino, V.; Pires, S.; Polenta, G.; Poncet, M.; Popa, L.A.; Pozzetti, L.; Raison, F.; Rebolo, R.; Renzi, A.; Rhodes, J.; Riccio, G.; Romelli, E.; Roncarelli, M.; Saglia, R.; Sakr, Z.; Sánchez, A.G.; Sapone, D.; Sartoris, B.; Schewtschenko, J.A.; Schirmer, M.; Schneider, P.; Schrabback, T.; Secroun, A.; Seidel, G.; Seiffert, M.; Serrano, S.; Simon, P.; Sirignano, C.; Sirri, G.; Stanco, L.; Steinwagner, J.; Tallada-Crespí, P.; Taylor, A.N.; Tereno, I.; Toft, S.; Toledo-Moreo, R.; Torradeflot, F.; Tutusaus, I.; Valenziano, L.; Valiviita, J.; Vassallo, T.; Verdoes Kleijn, G.; Veropalumbo, A.; Wang, Y.; Weller, J.; Zacchei, A.; Zamorani, G.; Zerbi, F.M.; Zucca, E.; Ballardini, M.; Bolzonella, M.; Bozzo, E.; Burigana, C.; Cabanac, R.; Cappi, A.; Di Ferdinando, D.; Escartin Vigo, J.A.; Gabarra, L.; Martín-Fleitas, J.; Matthew, S.; Mauri, N.; Pezzotta, A.; Pöntinen, M.; Porciani, C.; Risso, I.; Scottez, V.; Sereno, M.; Tenti, M.; Viel, M.; Wiesmann, M.; Akrami, Y.; Alvi, S.; Anselmi, S.; Archidiacono, M.; Atrio-Barandela, F.; Benoist, C.; Benson, K.; Bergamini, P.; Bertacca, D.; Bethermin, M.; Blanchard, A.; Blot, L.; Brown, M.L.; Bruton, S.; Calabro, A.; Camacho Quevedo, B.; Caro, F.; Carvalho, C.S.; Castro, T.; Cogato, F.; Cooray, A.R.; Cucciati, O.; Davini, S.; De Paolis, F.; Desprez, G.; Díaz-Sánchez, A.; Diaz, J.J.; Di Domizio, S.; Duc, P.-A.; Enia, A.; Fang, Y.; Ferrari, A.G.; Ferreira, P.G.; Finoguenov, A.; Fontana, A.; Franco, A.; Ganga, K.; García-Bellido, J.; Gasparetto, T.; Gautard, V.; Gaztanaga, E.; Giacomini, F.; Gianotti, F.; Gozaliasl, G.; Guidi, M.; Gutierrez, C.M.; Hall, A.; Hartley, W.G.; Hernández-Monteagudo, C.; Hildebrandt, H.; Hjorth, J.; Kajava, J.J.E.; Kang, Y.; Kansal, V.; Karagiannis, D.; Kiiveri, K.; Kirkpatrick, C.C.; Kruk, S.; Le Graet, J.; Legrand, L.; Lembo, M.; Lepori, F.; Leroy, G.; Lesci, G.F.; Lesgourgues, J.; Leuzzi, L.; Liaudat, T.I.; Loureiro, A.; Macias-Perez, J.; Maggio, G.; Magliocchetti, M.; Magnier, E.A.; Mannucci, F.; Maoli, R.; Martins, C.J.A.P.; Maurin, L.; Miluzio, M.; Monaco, P.; Moretti, C.; Morgante, G.; Nadathur, S.; Naidoo, K.; Navarro-Alsina, A.; Nesseris, S.; Passalacqua, F.; Paterson, K.; Patrizii, L.; Pisani, A.; Potter, D.; Quai, S.; Radovich, M.; Rocci, P.-F.; Sacquegna, S.; Sahlén, M.; Sanders, D.B.; Sarpa, E.; Scarlata, C.; Schneider, A.; Sciotti, D.; Sellentin, E.; Smith, L.C.; Tanidis, K.; Testera, G.; Teyssier, R.; Troja, A.; Tucci, M.; Valieri, C.; Venhola, A.; Vergani, D.; Vernardos, G.; Verza, G.; Vielzeuf, P.; Walton, N.A.; Wilde, J.; Scott, D.; Euclid Collaboration

doi:10.1051/0004-6361/202554605

Article (Scientific journals)

Euclid Quick Data Release (Q1): XXVII. The Strong Lensing Discovery Engine B – Early strong lens candidates from visual inspection of high-velocity dispersion galaxies

Rojas, K.; Collett, T.E.; Acevedo Barroso, J.A. et al.

2026 • In Astronomy and Astrophysics, 711, p. 27

Peer Reviewed verified by ORBi

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https://hdl.handle.net/2268/347744

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10.1051/0004-6361/202554605

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Keywords :

catalogs; gravitational lensing: strong; methods: statistical; Catalog; Data release; Grade B; Gravitational lens; Gravitational lensing: strong; High velocity; Methods:statistical; Training sets; Velocity dispersion; Visual inspection; Astronomy and Astrophysics; Space and Planetary Science

Abstract :

We present a search for strong gravitational lenses in Euclid imaging with a high stellar velocity dispersion (σv > 180 km s−1) reported by SDSS and DESI. We performed expert visual inspection and classification of 11 660 Euclid images. We discovered 38 grade A and 40 grade B candidate lenses, which is consistent with an expected sample of ∼32. Palomar spectroscopy confirmed 5 lens systems, while DESI spectra confirmed one system, provided ambiguous results for another, and helped to discard a third system. The Euclid automated lens modeler modelled 53 candidates, confirmed 38 as lenses, failed to model 9, and ruled out 6 grade B candidates. For the remaining 25 candidates, we were unable to gather additional information. More importantly, our classified non-lenses provide an excellent training set for machine-learning lens classifiers. We created high-fidelity simulations of Euclid lenses by painting realistic lensed sources behind the tagged (non-lens) luminous red galaxies. This training set is the foundation stone for the Euclid galaxy-galaxy strong-lensing discovery engine.

Research Center/Unit :

STAR - Space sciences, Technologies and Astrophysics Research - ULiège

Disciplines :

Space science, astronomy & astrophysics

Author, co-author :

Rojas, K.; School of Engineering, University of Applied Sciences and Arts of Northwestern Switzerland, Windisch, Switzerland ; Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth, United Kingdom

Collett, T.E.; Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth, United Kingdom

Acevedo Barroso, J.A.; Laboratory of Astrophysics, Institute of Physics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Observatoire de Sauverny, Versoix, Switzerland

Nightingale, J.W.; School of Mathematics, Statistics and Physics, Newcastle University, Newcastle-upon-Tyne, United Kingdom

Stern, D.; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States

Moustakas, L.A.; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States

Schuldt, S.; Dipartimento di Fisica “Aldo Pontremoli”, Università degli Studi di Milano, Milano, Italy ; INAF-IASF Milano, Milano, Italy

Despali, G.; Dipartimento di Fisica e Astronomia “Augusto Righi”, Alma Mater Studiorum Università di Bologna, Bologna, Italy ; INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, Bologna, Italy ; INFN-Sezione di Bologna, Bologna, Italy

Melo, A.; Max-Planck-Institut für Astrophysik, Garching, Germany ; Physics Department, Technical University of Munich, TUM School of Natural Sciences, Germany

Walmsley, M.; David A. Dunlap Department of Astronomy & Astrophysics, University of Toronto, Toronto, Canada ; Jodrell Bank Centre for Astrophysics, Department of Physics and Astronomy, University of Manchester, Manchester, United Kingdom

More authors (330 more)

Language :

English

Title :

Euclid Quick Data Release (Q1): XXVII. The Strong Lensing Discovery Engine B – Early strong lens candidates from visual inspection of high-velocity dispersion galaxies

Publication date :

July 2026

Journal title :

Astronomy and Astrophysics

ISSN :

0004-6361

eISSN :

1432-0746

Publisher :

EDP Sciences

Volume :

711

Pages :

A27

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://www.aanda.org/10.1051/0004-6361/202554605/pdf

Funders :

BELSPO - Belgian Federal Science Policy Office

Funding number :

4000143347

Funding text :

The Euclid Consortium acknowledges the European Space Agency and a number of agencies and institutes that have supported the development ofEuclid, in particular the Agenzia Spaziale Italiana, the Austrian Forschungsf\u00F6rderungsgesellschaft funded through BMK, the Belgian Science Policy, the Canadian Euclid Consortium, the Deutsches Zentrum f\u00FCr Luft- und Raumfahrt, the DTU Space and the Niels Bohr Institute in Denmark, the French Centre National d\u2019Etudes Spatiales, the Funda\u00E7\u00E3o para a Ci\u00EAncia e a Tecnologia, the Hungarian Academy of Sciences, the Ministerio de Ciencia, Innovaci\u00F3n y Universidades, the National Aeronautics and Space Administration, the National Astronomical Observatory of Japan, the Netherlandse Onderzoekschool Voor Astronomie, the Norwegian Space Agency, the Research Council of Finland, the Romanian Space Agency, the State Secretariat for Education, Research, and Innovation (SERI) at the Swiss Space Office (SSO), and the United Kingdom Space Agency. A complete and detailed list is available on theEuclidweb site (https://www.euclid-ec.org). K.R. acknowledge support from the Swiss National Science Foundation (SNSF) Grant Nr CRSII5 198674. This work has received funding from the European Research Council (ERC) under the European Union\u2019s Horizon 2020 research and innovation programme (LensEra: grant agreement No 945536). TEC is funded by the Royal Society through a University Research Fellowship. C.T. acknowledges the INAF grant 2022 LEMON. Based on observations obtained at the Hale Telescope, Palomar Observatory, as part of a collaborative agreement between the Caltech Optical Observatories and the Jet Propulsion Laboratory. We thank the following people who participated in the Palomar observing: Connor Auge, Indie Desiderio-Sloane, Jarred Gillette, Ollie Jackson, Grace Kallman, Michael Koss, Ai-Den Le, Alessandro Peca, Krysten Roldan, and Paul Shen. This work used IRIS computing resources funded by the Science and Technology Facilities Council. DESI construction and operations is managed by the Lawrence Berkeley National Laboratory. This research is supported by the U.S. Department of Energy, Office of Science, Office of High-Energy Physics, under Contract No. DE\u2013AC02\u201305CH11231, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract. Additional support for DESI is provided by the U.S. National Science Foundation, Division of Astronomical Sciences under Contract No. AST-0950945 to the NSF\u2019s National Optical-Infrared Astronomy Research Laboratory; the Science and Technology Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology of Mexico (CONACYT); the Ministry of Science and Innovation of Spain, and by the DESI Member Institutions. The DESI collaboration is honored to be permitted to conduct astronomical research on Iolkam Du\u2019ag (Kitt Peak), a mountain with particular significance to the Tohono O\u2019odham Nation.

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