Mon. Not. R. Astron. Soc., 376, 1861-1878 (2007/April-3)
Constraints on physical properties of z ∼ 6 galaxies using cosmological hydrodynamic simulations.
FINLATOR K., DAVE R. and OPPENHEIMER B.D.
Abstract (from CDS):
We conduct a detailed comparison of broad-band spectral energy distributions of six z ≳ 5.5 galaxies against galaxies drawn from cosmological hydrodynamic simulations. We employ a new tool called spoc (Simulated photometry-derived observational constraints), which constrains the physical properties of observed galaxies through a Bayesian likelihood comparison with model galaxies. We first show that spoc self-consistently recovers the physical properties of a test sample of high-redshift galaxies drawn from our simulations, although dust extinction can yield systematic uncertainties at the ~50 per cent level. We then use spoc to test whether our simulations can reproduce the observed photometry of six z > 5.5 galaxies drawn from the literature. We compare physical properties derived from simulated star formation histories (SFHs) versus assuming simple models such as constant, exponentially decaying and constantly rising. For five objects, our simulated galaxies match the observations at least as well as simple SFH models, with similar favoured values obtained for the intrinsic physical parameters such as stellar mass and star formation rate, but with substantially smaller uncertainties. Our results are broadly insensitive to simulation choices for galactic outflows and dust reddening. Hence the existence of early galaxies as observed is broadly consistent with current hierarchical structure formation models. However, one of the six objects has photometry that is best fitted by a bursty SFH unlike anything produced in our simulations, driven primarily by a high K-band flux. These findings illustrate how spoc provides a robust tool for optimally utilizing hydrodynamic simulations (or any model that predicts galaxy SFHs) to constrain the physical properties of individual galaxies having only photometric data, as well as identify objects that challenge current models.