J/ApJS/278/16ivo://CDS.VizieR/J/ApJS/278/16doi:10.26093/cds/vizier/bb-8p-gCDSZhang B.Chen B.Yuan H.Chen P.Wang S.Zhang L.Ren YiGuo H.2026-08-03T07:26:24Z2026-03-09T12:38:47ZCDS support team

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

cds-question@unistra.frgalaxiesopen-star-clustersinfrared-photometryvisible-astronomyphotometryThe identification of star clusters holds significant importance in studying galaxy formation and evolution history. However, the task of swiftly and accurately identifying star clusters from vast amounts of photometric images presents an immense challenge. To address these difficulties, we employ deep learning models for image classification to identify young disk star clusters in M31 from the Pan-Andromeda Archaeological Survey (PAndAS) images. For training, validation, and testing, we utilize the Panchromatic Hubble Andromeda Treasury survey catalogs. We evaluate the performance of various deep learning models, using different classification thresholds and limiting magnitudes. Our findings indicate that the ResNet-50 model exhibits the highest overall accuracy. Moreover, using brighter limiting magnitudes and increasing the classification thresholds can effectively enhance the accuracy and precision of cluster identification. Through our experiments, we found that the model achieves optimal performance when the limiting magnitude is set to brighter than 21 mag. Based on this, we constructed a training data set with magnitudes less than 21 mag and trained a second ResNet-50 model. This model achieved a purity of 89.30%, a recall of 73.55%, and an F1 score of 80.66% when the classification threshold was set to 0.669. Applying the second model to all sources in the PAndAS fields within a projected radius of 30 kpc from the center of M31, we identified 2228 new unique star cluster candidates. We conducted visual inspections to validate the results produced by our automated methods, and we ultimately obtained 1057 star cluster candidates, of which 745 are newly identified.2025ApJS..278...16Zhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJS/278/16CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toJ/AJ/137/94 : Star clusters in M31 (Caldwell+, 2009)J/PASP/122/745 : HST WFPC2 star clusters in M31. III. (Hodge+, 2010)J/AJ/141/61 : Star clusters in M31. II. (Caldwell+, 2011)J/ApJ/752/95 : PHAT stellar cluster survey. I. Year 1 (Johnson+, 2012)J/other/RAA/15.1392 : LAMOST globular clusters in M 31 and M 33 (Chen+, 2015)J/ApJ/802/127 : PHAT stellar cluster survey. II. AP catalog (Johnson+, 2015)J/ApJ/868/55 : Structure of M31 halo. II. PAndAS (McConnachie+, 2018)J/A+A/658/A51 : New M31 star cluster candidates (Wang+, 2022)J/ApJ/954/206 : GC search in M31 with Gaia, PS1, LAMOST, PAndAS (Wang+, 2023)http://www.cfht.hawaii.edu/Science/PandAS/ : PandAS data accesshttps://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJS/278/16https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJS/278/16http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJS/278/16https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJS/278/16https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJS/278/16http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJS/278/16GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/ApJS/278/16/table7 (Catalog of the newly identified 1057 star cluster candidates in M31)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/ApJS/278/16/table7?https://vizier.iucaa.in/viz-bin/conesearch/J/ApJS/278/16/table7?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/ApJS/278/16/table7?GETtext/xml+votable180.050000true7.8646958339.539383330.0055555555555555565/655 677 6/2618-2619 2664 2666-2667 2693 2704-2705 2707 2752-27532.4270961532559724e-19 4.74824145408272e-19https://cdsarc.cds.unistra.fr/viz-bin/moc/J/ApJS/278/16?format=asciiOpticalInfrareddefaultJ/ApJS/278/16/table7Catalog of the newly identified 1057 star cluster candidates in M31recnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintSeq[1/1057] Candidate sequential identifiermeta.id;meta.mainintRAJ2000[0] Hour of Right Ascension (J2000)pos.eq.ra;meta.mainDEJ2000[38/43] Degree of Declination (J2000)pos.eq.dec;meta.maingmag[13.5/21] PAndAS CFHT/MegaCam g-band AB magnitudemagphot.mag;em.opt.Bfloate_gmag[0.001/0.03] Uncertainty in gmagmagstat.error;phot.magfloatimag[12.74/35.02] PAndAS CFHT/MegaCam i-band AB magnitudemagphot.mag;em.opt.Ifloate_imag[0.001/9.4] Uncertainty in imagmagstat.error;phot.magfloatPAndAS[207/285] PAndAS field IDmeta.id;obs.fieldintRproj[1/83] Projected distance to center of M31kpcpos.distancefloatConf[0/1] Classification Confidence (highest probability = most likely class; Section 3.1)meta.code.qualfloatScore[3/4] Visual inspection score (1)meta.code.qualintC09Name in Caldwell et al. 2009, J/AJ/137/94meta.id.crosscharRBCName in Galleti et al. 2004, J/A+A/416/917 (2)meta.id.crosscharC11Name in Caldwell et al. 2011, J/AJ/141/61meta.id.crosscharW22? Name in Wang et al. 2022, J/A+A/658/A51meta.id.crossintnullableW23? Name in Wang et al. 2023, J/ApJ/954/206meta.id.crossintnullableH14Name in Huxor et al. 2014MNRAS.442.2165Hmeta.id.crosschar