Biases and Uncertainties in Constraining the Stellar Populations of Lyman Break Galaxies

Details Biases and Uncertainties in Constraining the Stellar Populations of Lyman Break Galaxies Biases and Uncertainties in Constraining the Stellar Populations of Lyman Break Galaxies

Dec 2007

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007aas...211.5212l&link_type=abstract

American Astronomical Society, AAS Meeting #211, #52.12; Bulletin of the American Astronomical Society, Vol. 39, p.821

Physics

Scientific paper

We investigate the statistical biases in constraining the stellar population parameters of high redshift Lyman break galaxies (LBGs), that arise from the simplifying assumptions often used in fitting their spectral energy distributions (SEDs).
By combining LCDM hierarchical structure formation theory, semi-analytic treatments of baryonic physics (including gas cooling, star formation, supernova feedback, dust extinction, and galaxy merging), and stellar population synthesis models, we construct model galaxy catalogs from which we select LBGs at redshifts near z 3.3, 4.0, and 5.0.
The broad-band photometric SEDs of these model LBGs are then analysed by fitting galaxy template SEDs derived from stellar population synthesis models with smoothly declining star formation rates.
Then we compare the statistical properties of LBGs’ stellar populations -- such as stellar mass, star formation rate (SFR), and stellar population age -- from the semi-analytic model parameters, and from the best-fit stellar population synthesis model galaxy templates.
We find some trends in these statistical distributions: First, when redshift is known in advance, the parameters of the best fit SED models reproduce well the input statistical distribution of galaxies' stellar masses with small underestimation as a whole, but with substantial scatters.
Second, there are systematic biases in statistical distributions of best-fit SFRs and mean ages, in a sense that SED-fitting methods underestimate SFRs and overestimate stellar population mean ages.
We attribute these trends to the differences in assumed star formation histories in semi-analytic models of galaxy formation and in simple stellar population synthesis models, and to the fact that broadband photometry is more sensitive to lights from current generation of star formation hiding stellar populations of previous generation of star formation.
When we assume redshifts are not known, and vary them as an additional free parameter, stellar masses are more underestimated, and the distributions of SFRs and mean ages become bimodal.

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