J/ApJ/812/147ivo://CDS.VizieR/J/ApJ/812/147doi:10.26093/cds/vizier.18120147CDSKrumholz M.R.Adamo A.Fumagalli M.Wofford A.Calzetti D.Lee J.C.,Whitmore B.C.Bright S.N.Grasha K.Gouliermis D.A.Kim H.Nair P.,Ryon J.E.Smith L.J.Thilker D.Ubeda L.Zackrisson E.2017-01-23T22:00:00Z2016-03-11T15:10:37ZCDS support team

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

cds-question@unistra.fropen-star-clustersgalaxiesextinctionastronomical-modelsWe investigate a novel Bayesian analysis method, based on the Stochastically Lighting Up Galaxies (slug) code, to derive the masses, ages, and extinctions of star clusters from integrated light photometry. Unlike many analysis methods, slug correctly accounts for incomplete initial mass function (IMF) sampling, and returns full posterior probability distributions rather than simply probability maxima. We apply our technique to 621 visually confirmed clusters in two nearby galaxies, NGC 628 and NGC 7793, that are part of the Legacy Extragalactic UV Survey (LEGUS). LEGUS provides Hubble Space Telescope photometry in the NUV, U, B, V, and I bands. We analyze the sensitivity of the derived cluster properties to choices of prior probability distribution, evolutionary tracks, IMF, metallicity, treatment of nebular emission, and extinction curve. We find that slug's results for individual clusters are insensitive to most of these choices, but that the posterior probability distributions we derive are often quite broad, and sometimes multi-peaked and quite sensitive to the choice of priors. In contrast, the properties of the cluster population as a whole are relatively robust against all of these choices. We also compare our results from slug to those derived with a conventional non-stochastic fitting code, Yggdrasil. We show that slug's stochastic models are generally a better fit to the observations than the deterministic ones used by Yggdrasil. However, the overall properties of the cluster populations recovered by both codes are qualitatively similar.2015ApJ...812..147Khttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/812/147CatalogResearchIsServedByTAP VizieR generic servicerelated-toB/hst : HST Archived Exposures Catalog (STScI, 2007)J/MNRAS/445/899 : LVL SEDs and physical properties (Cook+, 2014)J/ApJ/752/95 : PHAT stellar cluster survey. I. Year 1 (Johnson+, 2012)J/ApJ/751/122 : Ages and masses for 920 LMC clusters (Popescu+, 2012)J/A+A/537/A146 : Stellar models with rotation Z=0.014 (Ekstrom+, 2012)J/MNRAS/417/L6 : Catalog of stellar cluster properties in M83 (Bastian+, 2011)J/A+A/532/A131 : New Galactic star clusters in VVV survey (Borissova+, 2011)J/MNRAS/405/857 : Star clusters in NGC 3256 (Goddard+, 2010)J/ApJ/706/599 : H{alpha} and UV SFR in the local volume (Lee+, 2009)J/A+A/443/41 : NGC 4038/4039 broad & narrow band photometry (Mengel+, 2005)J/AJ/129/2701 : UBVRI photometry of SMC star clusters (Rafelski+, 2005)J/A+A/397/473 : HST photometry of M51 cluster (Bik+, 2003)J/AJ/124/1418 : Radio-opt. identification of star clusters (Whitmore+, 2002)J/A+AS/141/371 : Low-mass stars evolutionary tracks+isochrones (Girardi+, 2000)http://legus.stsci.edu/ : LEGUS (HST Legacy Extragalactic UV Survey) home pagehttp://www.slugsps.com/ : SLUG home pagehttps://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJ/812/147https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJ/812/147http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJ/812/147https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJ/812/147https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJ/812/147http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJ/812/147GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapdefaultJ/ApJ/812/147/table3*Summary marginal posterior probability distribution functions (PDFs)FieldField identifier (1)meta.id;obs.fieldcharrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintID[1/1753] ID in the LEGUS photometric catalogmeta.id;meta.mainintModeVisual classification, mode of classifiers (2)meta.code.classfloatMeanVisual classification, mean of classifiers (2)meta.code.classfloatLibName of the cluster_slug library (3)meta.id;meta.datasetcharbeta[-2/-2] Slope of the mass prior, dN/dM~M^beta^stat.fit.paramfloatgamma[-1/-0] Slope of the age prior, dN/dT~T^gamma^stat.fit.paramfloatlogM-14[1.9/6.8] The 14th percentile of log masslog(solMass)phys.massfloatlogM-25The 25th percentile of log masslog(solMass)phys.massfloatlogM-50The 50th percentile of log masslog(solMass)phys.massfloatlogM-75The 75th percentile of log masslog(solMass)phys.massfloatlogM-84[2.3/7.1] The 84th percentile of log masslog(solMass)phys.massfloatlogT-14[5.2/9.7] The 14th percentile of log agelog(yr)time.agefloatlogT-25The 25th percentile of log agelog(yr)time.agefloatlogT-50The 50th percentile of log agelog(yr)time.agefloatlogT-75The 75th percentile of log agelog(yr)time.agefloatlogT-84[5.8/10.2] The 84th percentile of log agelog(yr)time.agefloatAV-14[0.02/2.8] The 14th percentile of V band extinctionmagphys.absorptionfloatAV-25The 25th percentile of V band extinctionmagphys.absorptionfloatAV-50The 50th percentile of V band extinctionmagphys.absorptionfloatAV-75The 75th percentile of V band extinctionmagphys.absorptionfloatAV-84[0.1/3] The 84th percentile of V band extinctionmagphys.absorptionfloatD5[0/76] The 5th nearest neighbor distance in librarymagstat.paramfloatDnorm5[0.003/73] The 5th nearest neighbor distance in library normalized to photometric errorsstat.paramfloat