J/ApJS/272/42ivo://CDS.VizieR/J/ApJS/272/42doi:10.26093/cds/vizier.22720042CDSSong J.Fang G.Ba S.Lin Z.Gu Y.Zhou C.Wang T.Hao C.-N.,Liu G.Zhang H.Yao Y.Kong Xu2025-02-13T20:14:05Z2024-11-15T15:49:18ZCDS support team

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

cds-question@unistra.frgalaxiesvisible-astronomyhst-photometryredshiftedgalaxy-classification-systemsMorphological classification conveys abundant information on the formation, evolution, and environment of galaxies. In this work, we refine a two-step galaxy morphological classification framework (USmorph), which employs a combination of unsupervised machine-learning and supervised machine-learning techniques, along with a self-consistent and robust data-preprocessing step. The updated method is applied to galaxies with Imag<25 at 0.2<z<1.2 in the COSMOS field. Based on their Hubble Space Telescope/Advanced Camera for Survey I-band images, we classify them into five distinct morphological types: spherical (SPH, 15200), early-type disk (17369), late-type disk (21143), irregular disk (IRR, 28965), and unclassified (UNC, 17129). In addition, we have conducted both parametric and nonparametric morphological measurements. For galaxies with stellar masses exceeding 10^9^M_{sun}_, a gradual increase in effective radius from SPHs to IRRs is observed, accompanied by a decrease in the Sersic index. Nonparametric morphologies reveal distinct distributions of galaxies across the Gini-M_20_ and C-A parameter spaces for different categories. Moreover, different categories exhibit significant dissimilarity in their G_2_ and {Psi} distributions. We find morphology to be strongly correlated with redshift and stellar mass. The consistency of these classification results with expected correlations among multiple parameters underscores the validity and reliability of our classification method, rendering it a valuable tool for future studies.2024ApJS..272...42Shttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJS/272/42CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toVII/265 : COSMOS Morphological Catalog (V1.1) (Tasca+ 2009)J/ApJS/147/1 : Classification of nearby galaxies (Conselice+, 2003)J/AJ/128/163 : Galaxy morphological classification (Lotz+, 2004)J/A+A/468/937 : NIR AO imaging in COSMOS deep field (Huertas-Company+, 2007)J/AJ/136/773 : Classical bulge & pseudobulge structures (Fisher+, 2008)J/ApJ/690/1236 : COSMOS photometric redshift catalog (Ilbert+, 2009)J/MNRAS/410/166 : Morphological types from Galaxy Zoo 1 (Lintott+, 2011)J/MNRAS/428/1460 : Massive early-type galaxies (Buitrago+, 2013)J/MNRAS/440/843 : SIM2D parameters of SDSS-DR7 galaxies (Omand+, 2014)J/ApJS/224/24 : The COSMOS2015 catalog (Laigle+, 2016)J/A+A/631/A38 : Local galaxies dust properties (Lianou+, 2019)J/A+A/664/A92 : GAMA. MegaMorp/GalfitM profile fits (Haeussler+, 2022)J/ApJS/258/11 : The COSMOS2020 catalog (Weaver+, 2022)J/ApJS/268/34 : Morphology of COSMOS -UltraVISTA -DASH galaxies (Dai+, 2023)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJS/272/42https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJS/272/42http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJS/272/42https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJS/272/42https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJS/272/42http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJS/272/42GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/ApJS/272/42/table2 (Final catalog)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/ApJS/272/42/table2?https://vizier.iucaa.in/viz-bin/conesearch/J/ApJS/272/42/table2?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/ApJS/272/42/table2?GETtext/xml+votable180.050000true150.712491.792110.0055555555555555565/6814 6/27245 27247 273442.3657755224268815e-19 2.565265938961496e-19https://cdsarc.cds.unistra.fr/viz-bin/moc/J/ApJS/272/42?format=asciiOpticaldefaultJ/ApJS/272/42/table2Final catalogFlag2[0/16388] Flag of the nonparametric morphological measurements (0=good measurement)meta.code.errorintClassDerived galaxy morphological type (3)src.classcharrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintSeq[1/99806] Sequential number identifiermeta.id;meta.mainintRAJ2000[149.4/150.8] Right Ascension (J2000) (ALPHAJ2000) (1)degpos.eq.ra;meta.mainindexedDEJ2000[1.6/2.9] Declination (J2000) (DELTA_J2000) (1)degpos.eq.dec;meta.mainindexedImag[17.24/25] HST/ACS F814W (I-band) AB magnitude (ACS_F814W_MAG) (1)magphot.mag;em.opt.Ifloatz[0.2/1.2] Redshift (lp_zBEST) (1)src.redshiftfloatlogMs[6/13.3] Log of stellar mass (lp_mass_best) (1)log(solMass)phys.massfloatReff[0.03/99.2]? Effective radius at I bandkpcphys.size.radiusfloatnullablen[-0/8]? Sersic indexstat.fit.paramfloatnullableFlag1[-1/2] Flag of single Sersic fitting (2=good fitting)meta.code.errorintC[0/5.41] Concentration index, statmorph_csst (2)meta.code;spect.indexfloatA[-4.7/1.13] Asymmetry index, statmorph_csst (2)meta.code;spect.indexfloatS[-3.1/2]? Smoothness index (clumpiness), statmorph_csst (2)src.morph.paramfloatnullableGini[0.07/1]? Gini index, statmorph_csst (2)src.morph.paramfloatnullableM20[-2.8/1]? M20 index, statmorph_csst (2)src.morph.paramfloatnullableM[0/1] Multimode index, statmorph_csst (2)src.morph.paramfloatI[0/1] Intensity index, statmorph_csst (2)src.morph.paramfloatD[0/2.5]? Deviation index, statmorph_csst (2)src.morph.paramfloatnullablePsi[-99/22.7]? Multiplicity, statmorph_csst, Equation 4 (2)src.morph.paramfloatnullableG2[0/2]? Second gradient moment, statmorph_csst, Equation 1; Rosa+ (2018MNRAS.477L.101R) (2)src.morph.paramfloatnullableCOSMOS2020Display data from the "Farmer" COSMOS2020 cat. (Weaver+ 2022, J/ApJS/258/11) within 0.3"meta.ref.urlchar