J/A+A/712/A207ivo://CDS.VizieR/J/A+A/712/A207CDSEuclid Coll.Xu X.Chen R.Li T.Cooray A.R.Schuldt S.,Acevedo Barroso J.A.Stern D.Scott D.Meneghetti M.Despali G.,Chopra J.Cao Y.Cheng M.Buda J.Zhang J.Furumizo J.Valencia R.,Jiang Z.Tortora C.Lines N.E.P.Collett T.E.Fotopoulou S.Galan A.,Manjon-Garcia A.Gavazzi R.Iwamoto L.Kruk S.Millon M.Nugent P.,Saulder C.Sluse D.Wilde J.Walmsley M.Courbin F.Metcalf R.B.,Altieri B.Amara A.Andreon S.Auricchio N.Baccigalupi C.Baldi M.,Balestra A.Bardelli S.Battaglia P.Bender R.Biviano A.Branchini E.,Brescia M.Camera S.Capobianco V.Carbone C.Cardone V.F.,Carretero J.Casas S.Castellano M.Castignani G.Cavuoti S.,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.Dolding C.Dole H.Dubath F.Dupac X.Dusini S.,Escoffier S.Farina M.Farinelli R.Farrens S.Ferriol S.Finelli F.,Fosalba P.Frailis M.Franceschi E.Fumana M.Galeotta S.George K.,Gillard W.Gillis B.Giocoli C.Gomez-Alvarez P.Gracia-Carpio J.,Grazian A.Grupp F.Haugan S.V.H.Holmes W.Hormuth F.Hornstrup A.,Jahnke K.Jhabvala M.Joachimi B.Kermiche S.Kiessling A.Kubik B.,Kuemmel M.Kunz M.Kurki-Suonio H.Le Brun A.M.C.Ligori S.,Lilje P.B.Lindholm V.Lloro I.Mainetti G.Maiorano E.Mansutti O.,Marcin S.Marggraf O.Martinelli M.Martinet N.Marulli F.Massey R.J.,Medinaceli E.Mei S.Melchior M.Merlin E.Meylan G.Mora A.,Moresco M.Moscardini L.Nakajima R.Neissner C.Nichol R.C.,Niemi S.-M.Nightingale J.W.Padilla C.Paltani S.Pasian F.,Pedersen K.Percival W.J.Pettorino V.Polenta G.Poncet M.Popa L.A.,Raison F.Renzi A.Rhodes J.Riccio G.Romelli E.Roncarelli M.,Saglia R.Sakr Z.Sapone D.Schirmer M.Schneider P.Schrabback T.,Secroun A.Seidel G.Sihvola E.Simon P.Sirignano C.Sirri G.,Stanco L.Tallada-Crespi P.Taylor A.N.Tereno I.Tessore N.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.,Burigana C.Cabanac R.Calabrese M.Cappi A.Castro T.,Escartin Vigo J.A.Gabarra L.Hemmati S.Macias-Perez J.Maoli R.,Martin-Fleitas J.Mauri N.Monaco P.Nucita A.A.Pezzotta A.,Poentinen M.Risso I.Scottez V.Sereno M.Tenti M.Tucci M.Viel M.,Wiesmann M.Akrami Y.Andika I.T.Angora G.Anselmi S.Archidiacono M.,Atrio-Barandela F.Bazzanini L.Bergamini P.Bertacca D.Bethermin M.,Beutler F.Blot L.Borgani S.Brown M.L.Bruton S.Calabro A.,Camacho Quevedo B.Caro F.Carvalho C.S.Cogato F.Conseil S.,Cucciati O.Davini S.Desprez G.Diaz-Sanchez A.Di Domizio S.,Diego J.M.Duc P.-A.Duret V.Elkhashab M.Y.Enia A.Fang Y.,Finoguenov A.Franco A.Ganga K.Gasparetto T.Gaztanaga E.,Giacomini F.Gianotti F.Gozaliasl G.Guidi M.Gutierrez C.M.Hall A.,Hernandez-Monteagudo C.Hildebrandt H.Hjorth J.Kajava J.J.E.Kang Y.,Kansal V.Karagiannis D.Kiiveri K.Kim J.Kirkpatrick C.C.Lepori F.,Leroy G.Lesci G.F.Lesgourgues J.Liaudat T.I.Liu S.J.,Magliocchetti M.Magnier E.A.Mannucci F.Martins C.J.A.P.Maurin L.,Miluzio M.Moretti C.Morgante G.Naidoo K.Navarro-Alsina A.,Nesseris S.Paoletti D.Passalacqua F.Paterson K.Patrizii L.,Pisani A.Potter D.Pratt G.W.Quai S.Radovich M.Rojas K.Roster W.,Sacquegna S.Sahlen M.Sanders D.B.Sarpa E.Scarlata C.Schneider A.,Schultheis M.Sciotti D.Sellentin E.Smith L.C.Tanidis K.Tao C.,Tarsitano F.Testera G.Teyssier R.Tosi S.Troja A.Venhola A.,Vergani D.Vernardos G.Verza G.Vinciguerra S.Walton N.A.,Wright A.H.Yeung H.W.2026-08-21T07:27:07Z2026-08-21T08:26:06ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frgravitational-lensingphotometryvisible-astronomyinfrared-astronomyWe present an end-to-end, iterative pipeline for efficient identification of strong galaxy-galaxy lensing systems, applied to the Euclid Q1 imaging data. Starting from VIS catalogues, we reject point sources, apply a magnitude cut (IE<=24) on deflectors, and run a pixel-level artefact/noise filter to build 96x96 pix cutouts; VIS+NISP colour composites are constructed with a VIS-anchored luminance scheme that preserves VIS morphology and NISP colour contrast. A VIS-only seed classifier supplies clear positives and typical impostors, from which we curate a morphology-balanced negative set and augment scarce positives. Among the six compact CNNs studied initially, a modified VGG16 (GlobalAveragePooling + 256/128 dense layers with the last nine layers trainable) performs best; the training set grows from 27 seed lenses (augmented 67x to 1809) plus 2000 negatives to a colour dataset of 30686 images. After three rounds of iterative fine-tuning, human grading of the top 4000 candidates ranked by the final model yields 441 Grade A/B candidate lensing systems, including 311 overlapping with the existing Q1 strong-lens catalogue, and 130 additional A/B candidates (9 As and 121 Bs) not previously reported. Independently, the model recovers 740 out of 905 (81.8%) candidate Q1 lenses within its top 20000 predictions, considering off-centred samples. Candidates span IE~17-24 AB mag (median 21.3 AB mag) and are redder in YE-HE than the parent population, consistent with massive early-type deflectors. Each training iteration required about a week for a small team, and the approach easily scales to future wide-area Euclid releases; future work will calibrate the selection function via lens injection, extend recall through uncertainty-aware active learning, and explore multi-scale or attention-based neural networks with fast post-hoc vetters that incorporate lens models into the classification.2026A&A...712A.207Ehttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/712/A207CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toII/388 : Euclid final merged catalog. Q1 data release (Euclid Coll., 2025)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/712/A207https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/712/A207http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/712/A207https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/712/A207https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/712/A207http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/712/A207GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/A+A/712/A207/tablee1 (Catalog of classified strong gravitational lens candidates identified in Euclid Q1)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/712/A207/tablee1?https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/712/A207/tablee1?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/712/A207/tablee1?GETtext/xml+votable180.050000true63.1323422503246-47.99496285593130.0055555555555555565/2559 2901 2903 4010-4011 8579-8582 8592 8983 8989 6/10229-10231 11601 11603 11609 15354-15355 15357-15359 16035 16038 16056 33979 33982-33983 34025-34028 34030 34310-34311 34313 34315 34332-34334 34337 34340-34342 34352 34372 34376 35927 35929 35931 35953 35955 36104 36106 36128 36130https://cdsarc.cds.unistra.fr/viz-bin/moc/J/A+A/712/A207?format=asciiOpticalInfrareddefaultJ/A+A/712/A207/tablee1Catalog of classified strong gravitational lens candidates identified in Euclid Q1recnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintIndexInternal cutout identifiermeta.idintcutoutNameAlternative identifier composed of the Euclid mosaic tile and cutout identifiermeta.idcharobjNameEuclid object identifierR (EUCLJHHMMSS.ss+DDMMSS.ss)meta.id;meta.maincharRAJ2000Right ascension (J2000)degpos.eq.ra;meta.mainDEJ2000Declination (J2000)degpos.eq.dec;meta.mainVISmagEuclid VIS-band magnitude derived from FLUX_DETECTION_TOTALmagphot.mag;em.optdoubleYmagEuclid Y-band magnitude derived from FLUX_Y_2FWHM_APERmagphot.mag;em.IR.JdoubleHmagEuclid H-band magnitude derived from FLUX_H_2FWHM_APERmagphot.mag;em.IR.HdoubleJmag? Euclid J-band magnitude derived from FLUX_J_2FWHM_APERmagphot.mag;em.IR.JdoublenullableGradeProcessed human-expert classification grademeta.code.classcharNew[Y/N] Indicates whether the lens candidate is newly identified in this work (Y/N)meta.notecharRawScoreRaw score produced by the machine-learning modelmeta.codedoubleNotesReferences and additional remarks (1)meta.notechar