J/ApJ/864/71 Fluxes & physical param. of blended YSOs (Martinez-Galarza+, 2018)

Unraveling the spectral energy distributions of clustered YSOs. Martinez-Galarza J.R., Protopapas P., Smith H.A., Morales E.F.E. <Astrophys. J., 864, 71 (2018)> =2018ApJ...864...71M 2018ApJ...864...71M
ADC_Keywords: YSOs; Photometry, infrared; Stars, ages; Stars, masses; Stars, distances; Extinction; Galactic plane Keywords: methods: statistical ; open clusters and associations: general ; stars: formation ; stars: protostars ; stars: statistics Abstract: Despite 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 (Mcl<100M) 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. Description: We use observations from the GLIMPSE (Benjamin+ 2003PASP..115..953B 2003PASP..115..953B & Churchwell+ 2009PASP..121..213C 2009PASP..121..213C) and MIPS Inner Galactic Plane Survey (MIPSGAL; Carey+ 2005AAS...207.6333C 2005AAS...207.6333C) surveys, carried out with the Spitzer Space Telescope's InfraRed Array Camera (IRAC) using bands IRAC 1 (3.6um), IRAC 2 (4.5um), IRAC 3 (5.6um), and IRAC 4 (8.0um). The data set of observations studied here covers the inner Galactic plane (|l|<65°). File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file table2.dat 133 218 GLIMPSE sources, derived fluxes and physical parameters -------------------------------------------------------------------------------- See also: II/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 24µm 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) Byte-by-byte Description of file: table2.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 5 I5 --- ID [360/18738] Source identifier 7- 14 F8.4 deg RAdeg [265.7/297] Right ascension (J2000) 16- 23 F8.4 deg DEdeg [-30.6/25.3] Declination (J2000) 25 A1 --- l_Dist Limit flag on Dist 26- 30 F5.2 kpc Dist [0.5/14] Distance 32- 35 F4.2 kpc e_Dist [0.09/2.1] Distance uncertainty δd 37- 42 F6.2 mJy F3.6 [0.01/117]?=0 Spitzer/IRAC 3.6um flux 44- 47 F4.2 mJy e_F3.6 [0.01/9]?=0 F3.6 uncertainty 49- 54 F6.2 mJy F4.5 [0.01/333]?=0 Spitzer/IRAC 4.5um flux 56- 60 F5.2 mJy e_F4.5 [0.01/26]?=0 F4.5 uncertainty 62- 67 F6.2 mJy F5.8 [0.01/583]?=0 Spitzer/IRAC 5.8um flux 69- 73 F5.2 mJy e_F5.8 [0.01/37]?=0 F5.8 uncertainty 75- 80 F6.2 mJy F8.0 [0.01/583]?=0 Spitzer/IRAC 8.0um flux 82- 86 F5.2 mJy e_F8.0 [0.01/37]?=0 F8.0 uncertainty 88- 91 F4.2 [yr] logt* [0.06/7] Age 93- 96 F4.2 [yr] e_logt* [0/2]? Negative uncertainty on logt* 98-101 F4.2 [yr] E_logt* [0/1.7]? Positive uncertainty on logt* 103-107 F5.2 [Msun] logM* [-1/1.4]? Stellar mass 109-112 F4.2 [Msun] e_logM* [0/0.7]? Negative uncertainty on logM* 114-117 F4.2 [Msun] E_logM* [0/1.4]? Positive uncertainty on logM* 119-123 F5.2 mag logAv [-1.4/1.9]? Visual extinction 125-128 F4.2 mag e_logAv [0/0.8]? Negative uncertainty on logAv 130-133 F4.2 mag E_logAv [0/0.8]? Positive uncertainty on logAv -------------------------------------------------------------------------------- History: From electronic version of the journal
(End) Emmanuelle Perret [CDS] 16-Aug-2019
The document above follows the rules of the Standard Description for Astronomical Catalogues; from this documentation it is possible to generate f77 program to load files into arrays or line by line