J/A+A/699/A350ivo://CDS.VizieR/J/A+A/699/A350doi:10.26093/cds/vizier.36990350CDSSchuldt S.Canameras R.Shu Y.Andika I.T.Bag S.Grillo C.Melo A.,Suyu S.H.Taubenberger S.2025-08-01T20:03:27Z2025-07-22T10:01:22ZCDS support team

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

cds-question@unistra.frgravitational-lensinggalaxy-classification-systemsastronomical-modelsWe have carried out a systematic search for galaxy-scale lenses exploiting multi-band imaging data from the third public data release of the Hyper Suprime-Cam (HSC) survey with the focus on false-positive removal, after applying deep learning classifiers to all ~110 million sources with i-Kron radius above 0.8". To improve the performance, we tested the combination of multiple networks from our previous lens search projects and found the best performance by averaging the scores from five of our networks. Although this ensemble network leads already to a false-positive rate (FPR) of ~0.01% at a true-positive rate (TPR) of 75% on known real lenses, we have elaborated techniques to further clean the network candidate list before visual inspection. In detail, we tested the rejection using SExtractor and the modeling network from HOLISMOKES IX, which resulted together in a candidate rejection of 29% without lowering the TPR. After the initial visual inspection stage to remove obvious non-lenses, 3408 lens candidates of the ~110 million parent sample remained. We carried out a comprehensive multi-stage visual inspection involving eight individuals and identified finally 95 grade A (average grade G>=2.5) and 503 grade B (2.5>G>=1.5) lens candidates, including 92 discoveries showing clear lensing features that are reported for the first time. This inspection also incorporated a novel environmental characterization using histograms of photometric redshifts. We publicly release the average grades, mass model predictions, and environment characterization of all visually inspected candidates, while including references for previously discovered systems, which makes this catalog one of the largest compilation of known lenses. The results demonstrate that (1) the combination of multiple networks enhances the selection performance and (2) both automated masking tools as well as modeling networks, which can be easily applied to hundreds of thousands of network candidates expected in the near future of wide-field imaging surveys, help reduce the number of false positives that is the main limitation in lens search to date.2025A&A...699A.350Shttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/699/A350CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toJ/A+A/644/A163 : Pan-STARRS lens candidates from neural networksJ/A+A/653/L6 : HSC-SSP lens candidates from neural networksJ/A+A/662/A4 : Strong-lens candidates from HSC-SSP PDR2 (Shu+, 2022)J/A+A/693/A291 : Characteristics of 162 strong lenses (Schuldt+, 2025)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/699/A350https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/699/A350http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/699/A350https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/699/A350https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/699/A350http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/699/A350GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/A+A/699/A350/table2 (Characteristics of strong lens candidates)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/699/A350/table2?https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/699/A350/table2?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/699/A350/table2?GETtext/xml+votable180.050000true337.16841173397960.37009897532840.0055555555555555564/256 1105-1107 1110 1113 1125 1130 1173-1174 1200-1202 1365 1367 1621-1623 1625-1626 1637-1638 1641-1644 1685-1687 1689 1691-1692 1701-1703 1705-1708 1712 1728 5/1028-1030 1032-1034 2048 2050-2051 2056 2455 2459-2460 2470-2471 2475-2476 2480 2496 2647 2651-2652 2672 2816 2856 4351 4419 4432 4434-4435 4444 4446 4449 4457-4461 4464-4466 4499 4508-4509 4518-4519 4524-4526 4544 4546 4671 4687 4691 4700-4702 4707 4709-4711 4713-4716 4718-4722 4757-4759 4761 4764-4765 4767 4789 4812 4832-4833 4864-4866 5459 6399 6463 6479 6483 6499 6508 6510 6512 6543 6547 6556 6563 6584 6592 6719 6735 6738-6739 6755 6760-6761 6763 6772 6776 6798-6799 6803 6819 6836-6838 6840-6842 6852-6854 6856-6858 6916 6920-6922 9199 10239 11263 6/4124 4140 4144 4160 4162 4224 8196 8198 8228-8230 8232-8233 9641-9644 9646 9813-9815 9817-9819 9829-9831 9833-9835 9844-9846 9848-9850 9877-9879 9893-9895 9897-9899 9908-9910 9912-9914 9924-9926 9928-9930 9988 9990 9992-9994 10581-10583 10585-10587 10597-10599 10601-10603 10612-10614 10616 10618 10645 10692-10694 10696-10697 11268-11270 11272 11274 17399 17403 17525 17527 17533 17535 17659 17661-17663 17669-17671 17673-17675 17734 17788 17792-17793 17795 17804-17805 17807 17826-17827 17848-17850 17852 17868 17872 17888-17890 18020-18021 18023 18040-18041 18043-18045 18061-18063 18065-18068 18070-18071 18114 18120 18122 18144 18180-18182 18188 18208-18209 18683 18759 18763 18812 18833-18835 18849-18851 18868-18870 18892 18912 18922 19015 19021-19023 19025-19027 19041 19053 19064-19065 19067 19153 19252 19256-19258 19264-19266 19272 19336-19337 19339 19344 19468 19472 19474 19488 21829-21831 21833 21835 21857 21860-21861 21863 21969 21972-21973 25589-25591 25593-25595 25823 25845-25847 25849-25851 25909-25911 25913-25915 25925-25927 25929-25931 25989-25991 25993-25995 26036 26038 26052-26054 26056-26058 26165-26167 26169-26171 26181-26183 26185-26187 26228-26229 26232 26245-26247 26249-26251 26320 26322 26328 26340 26344 26346 26372 26374 26376-26378 26384 26869-26871 26873-26875 26911 26933-26935 26937-26939 26949-26951 27013-27015 27017-27019 27048-27049 27051 27092-27093 27096-27098 27108 27110 27112-27114 27189-27191 27205-27207 27209-27211 27269-27271 27273 27275 27356 27372 27376-27377 27420 27436 27438 27440 27456 27520 27668-27670 27672 27674 27692 27694 27696 27776 31400 31402-31403 36793-36795 36842-36843 40950-40951 40953-40955 45046 45049 45051https://cdsarc.cds.unistra.fr/viz-bin/moc/J/A+A/699/A350?format=asciiOpticaldefaultJ/A+A/699/A350/table2Characteristics of strong lens candidatesrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintRAJ2000Right Ascension of the inspected candidate (J2000)degpos.eq.ra;meta.mainindexedDEJ2000Declination of the inspected candidate (J2000)degpos.eq.dec;meta.mainindexediradKron radius in the i band provided by HSC used for source selection (see Sect. 2)arcsecphys.angSizedoublepAverage score predicted by the network committeestat.fit.goodnessdoublee_gam2med? 1 {sigma} value of the {gamma}2-component predicted by the modeling network (2)stat.errordoublenullableFlagFlag if the model predict is reliable, only for systems inspected in the second roundmeta.codecharODvisFlag if the system falls into a significant overdense regionmeta.codecharODzFlag if the system is in a significant overdense environment according to the criteria defined by Schuldt et al. (2025A&A...693A.291S, Cat. J/A+A/693/A291)meta.codecharz? Photometric redshift value (3)src.redshift.photdoublenullableNmax? Peak of the photo-z histogram following the procedure of Schuldt et al. (2025A&A...693A.291S, Cat. J/A+A/693/A291)meta.noteintnullablezlow? Lower bound of Nmax in the photo-z histogram indicating the redshift of the overdensitysrc.redshift.photfloatnullableNtot? Sum of objects with photo-z within a box of 200" on a sidemeta.numberfloatnullableRefReferences (4)meta.refcharNameName for grade A and B lens candidates, HSCJHHMM+DDMMmeta.id;meta.maincharC21Flag to indicate systems discovered by this network committee but not re-inspected. Instead, we report the visual inspection grade from our earlier work Canameras et al. (2021A&A...653L...6C, Cat. J/A+A/653/L6)meta.codecharG[0/3] Average grade between 0 and 3 obtained through visual inspection (see Sect. 4) (1)meta.code.qualfloats_GStandard deviation of obtained visual inspection gradesstat.stdev;pos.cartesian.ydoubleNgradersNumber of visual inspectors (see Sect. 4)meta.numberintBinaryFlag to indicate sources inspected only in the binary stage (two different graders)meta.codecharRound1Flag to indicate systems inspected also in the first round (four different graders)meta.codecharRound2Flag to indicate systems inspected also in the second round (eight different graders)meta.codecharA24Flag to indicate if system jointly inspected with candidates discovered by Andika et al. (2024, arXiv:2412.12709)meta.codecharS22Flag to indicate systems discovered by this network committee but not re-inspected. Instead, we report the visual inspection grade from our earlier work Shu et al. (2022A&A...662A...4S, Cat. J/A+A/662/A4)meta.codecharS25Flag to indicate systems discovered by this network committee but not re-inspected. Instead, we report the visual inspection grade from our earlier work S25meta.codecharxmed? x center coordinate predicted by the modeling network (2)arcsecpos.cartesian.x;instr.detdoublenullablee_xmed? 1 {sigma} value for the x center coordinate predicted by the modeling network (2)arcsecstat.errordoublenullableymed? y center coordinate predicted by the modeling network (2)arcsecpos.cartesian.y;instr.detdoublenullablee_ymed? 1 {sigma} value for the y center coordinate predicted by the modeling network (2)arcsecstat.errordoublenullableexmed? x component of the complex ellipticity predicted by the modeling network (2)stat.fit.paramdoublenullablee_exmed? 1 {sigma} value for the x component of the complex ellipticity predicted by the modeling network (2)stat.errordoublenullableeymed? y component of the complex ellipticity predicted by the modeling network (2)stat.fit.paramdoublenullablee_eymed? 1 {sigma} value for the y component of the complex ellipticity predicted by the modeling network (2)stat.errordoublenullablerEmed? Einstein radius value of the given candidate predicted by the modeling network (2)arcsecphys.angSize;srcdoublenullablee_rEmed? 1 {sigma} value of the Einstein radius predicted by the modeling network (2)arcsecstat.errordoublenullablegam1med? {gamma}1 component of the external shear predicted by the modeling network (2)stat.fit.paramdoublenullablee_gam1med? 1 {sigma} value of the {gamma}1-component predicted by the modeling network (2)stat.errordoublenullablegam2med? {gamma}2 component of the external shear predicted by the modeling network (2)stat.fit.paramdoublenullable