J/ApJ/864/71ivo://CDS.VizieR/J/ApJ/864/71doi:10.26093/cds/vizier.18640071CDSMartinez-Galarza J.R.Protopapas P.Smith H.A.Morales E.F.E.2019-09-24T11:31:30Z2019-09-23T08:59:12ZCDS support team

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

cds-question@unistra.fryoung-stellar-objectsinfrared-photometrystellar-agesstellar-massesstellar-distanceextinctiongalaxy-planesmilky-way-galaxyDespite significant evidence suggesting that intermediate- and high-mass stars form in clustered environments, how stars form when the available resources are shared is still not well understood. A related question is whether the initial mass function (IMF) is in fact universal across galactic environments, or whether it is an average of IMFs that differ, for example, in massive versus low-mass molecular clouds. One of the long-standing problems in resolving these questions and in the study of young clusters is observational: how to accurately combine multiwavelength data sets obtained using telescopes with different spatial resolutions. The resulting confusion hinders our ability to fully characterize clustered star formation. Here we present a new method that uses Bayesian inference to fit the blended spectral energy distributions and images of individual young stellar objects (YSOs) in confused clusters. We apply this method to the infrared photometry of a sample comprising 70 Spitzer-selected, low-mass (M_cl_<100M_{sun}_) young clusters in the galactic plane, and we use the derived physical parameters to investigate how the distribution of YSO masses within each cluster relates to the total mass of the cluster. We find that for low-mass clusters this distribution is indistinguishable from a randomly sampled Kroupa IMF for this range of cluster masses. Therefore, any effects of self-regulated star formation that affect the IMF sampling are likely to play a role only at larger cluster masses. Our results are also compatible with smoothed particle hydrodynamics models that predict a dynamical termination of the accretion in protostars, with massive stars undergoing this stopping at later times in their evolution.2018ApJ...864...71Mhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/864/71CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toII/293 : GLIMPSE Source Catalog (I + II + 3D) (IPAC 2008)VIII/96 : 6-GHz methanol multibeam maser catalogue (Caswell+, 2010-12)J/A+A/434/613 : Water maser survey of methanol masers (Szymczak+, 2005)J/ApJ/669/327 : S3MC: YSOs in N66, in SMC (Simon+, 2007)J/AJ/136/2413 : Galactic midplane Spitzer red sources (Robitaille+, 2008)J/A+A/525/A149 : Red MSX Survey (RMS): bol. fluxes of YSOs (Mottram+, 2011)J/A+A/542/A66 : YSOs in 9 LMC star forming regions (Carlson+, 2012)J/A+A/560/A76 : Stellar clusters in the inner Galaxy (Morales+, 2013)J/MNRAS/431/1752 : ATLASGAL 6.7GHz methanol masers (Urquhart+, 2013)J/ApJ/778/96 : Spitzer and NEWFIRM observations of NGC 6334 (Willis+, 2013)J/AJ/149/64 : MIPSGAL 24{mu}m point source catalog (Gutermuth+, 2015)J/AJ/150/95 : Masses and ages of YSOs in Per OB2 (Azimlu+, 2015)J/ApJ/815/130 : High-mass molecular clumps from MALT90 (Guzman+, 2015)J/A+A/579/A91 : ATLASGAL inner Gal. massive cold dust clumps (Wienen+, 2015)J/ApJ/818/73 : Protostars in Perseus molecular cloud (Tobin+, 2016)J/A+A/599/A14 : Taurus ultra-wide pairs (Joncour+, 2017)J/ApJ/839/113 : Mol. clouds with GLIMPSE/MIPSGAL data (Retes-Romero+, 2017)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJ/864/71https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJ/864/71http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJ/864/71https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJ/864/71https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJ/864/71http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJ/864/71GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/ApJ/864/71/table2 (GLIMPSE sources, derived fluxes and physical parameters)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/ApJ/864/71/table2?https://vizier.iucaa.in/viz-bin/conesearch/J/ApJ/864/71/table2?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/ApJ/864/71/table2?GETtext/xml+votable180.050000true267.2023-28.01990.0055555555555555566/14355 14359 28824 28827 28831 28890 28900 28901 28912 28913 28918 29090 29094 29100 29103 29113 29114 29115 29119 29461 29504 29505 29506 29508 29533 29535 30218 30219 30245 30256 30258 30262 30268 30269 30312 30314 30317 30318 30319 30330 30423 30594 30605 30616 30618 30619 30716 307192.0616683193919197e-20 6.185923063528282e-20https://cdsarc.cds.unistra.fr/viz-bin/moc/J/ApJ/864/71?format=asciiInfrareddefaultJ/ApJ/864/71/table2GLIMPSE sources, derived fluxes and physical parametersrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintID[360/18738] Source identifiermeta.id;meta.mainintRAJ2000[265.7/297] Right ascension (J2000)degpos.eq.ra;meta.mainDEJ2000[-30.6/25.3] Declination (J2000)degpos.eq.dec;meta.mainl_DistLimit flag on Distmeta.code.errorcharDist[0.5/14] Distancekpcpos.distancefloate_Dist[0.09/2.1] Distance uncertainty {delta}dkpcstat.errorfloatF3.6[0.01/117]? Spitzer/IRAC 3.6um fluxmJyphot.mag;em.IR.3-4umfloatnullablee_F3.6[0.01/9]? F3.6 uncertaintymJystat.errorfloatnullableF4.5[0.01/333]? Spitzer/IRAC 4.5um fluxmJyphot.mag;em.IR.4-8umfloatnullablee_F4.5[0.01/26]? F4.5 uncertaintymJystat.errorfloatnullableF5.8[0.01/583]? Spitzer/IRAC 5.8um fluxmJyphot.flux.density;em.IR.4-8umfloatnullablee_F5.8[0.01/37]? F5.8 uncertaintymJystat.errorfloatnullableF8.0[0.01/583]? Spitzer/IRAC 8.0um fluxmJyphot.flux.density;em.IR.8-15umfloatnullablee_F8.0[0.01/37]? F8.0 uncertaintymJystat.errorfloatnullablelogt*[0.06/7] Agelog(yr)time.agefloate_logt*[0/2]? Negative uncertainty on logt*log(yr)stat.errorfloatnullableE_logt*[0/1.7]? Positive uncertainty on logt*log(yr)stat.error;stat.maxfloatnullablelogM*[-1/1.4]? Stellar masslog(solMass)phys.massfloatnullablee_logM*[0/0.7]? Negative uncertainty on logM*log(solMass)stat.errorfloatnullableE_logM*[0/1.4]? Positive uncertainty on logM*log(solMass)stat.error;stat.maxfloatnullablelogAv[-1.4/1.9]? Visual extinctionmagphys.absorptionfloatnullablee_logAv[0/0.8]? Negative uncertainty on logAvmagstat.errorfloatnullableE_logAv[0/0.8]? Positive uncertainty on logAvmagstat.error;stat.maxfloatnullableGLIMPSEDisplay the data from GLIMPSE (II/293) within 1"meta.ref.urlchar