Astronomy and Astrophysics – Astrophysics – Cosmology and Extragalactic Astrophysics
Scientific paper
2009-06-10
Astrophys.J.701:1839-1864,2009
Astronomy and Astrophysics
Astrophysics
Cosmology and Extragalactic Astrophysics
28 Pages, 13 Figures, 6 Tables. Submitted to ApJ, returned after minimal referee comments. Figures 1 & 2 compressed. Version w
Scientific paper
10.1088/0004-637X/701/2/1839
We present SED modeling of a sample of 34 K-selected galaxies at z ~ 2.3. These galaxies have NIR spectroscopy that samples the rest-frame Balmer/4000A break as well as deep photometry in thirteen broadband filters. New to our analysis is IRAC data that extend the SEDs into the rest-frame NIR. Comparing parameters determined from SED fits with and without the IRAC data we find that the IRAC photometry significantly improves the confidence intervals of Tau, A_v, stellar mass, and SFR for individual galaxies, but does not systematically alter the mean parameters of the sample. We use the IRAC data to assess how well current stellar population synthesis codes describe the rest-frame NIR SEDs of young galaxies where discrepancies between treatments of the TP-AGB phase of stellar evolution are most pronounced. The models of Bruzual & Charlot (2003), Maraston (2005), and Charlot & Bruzual (2008) all successfully reproduce the SEDs of our galaxies with < 5% differences in the quality of fit; however, the best-fit masses from each code differ systematically by as much as a factor of 1.5, and other parameters vary more, up to factors of 2-3. A comparison of best-fit stellar population parameters from different SPS codes, dust laws, and metallicities shows that the choice of SPS code is the largest systematic uncertainty in most parameters, and that systematic uncertainties are typically larger than the formal random uncertainties. The SED fitting confirms our previous result that galaxies with strongly suppressed star formation account for ~ 50% of the K-bright population at z ~ 2.3; however, the uncertainty in this fraction is large due to systematic differences in the SSFRs derived from the three SPS models.
Franx Marijn
Kriek Mariska
Labb'e Ivo
Marchesini Danilo
Muzzin Adam
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