Astronomy and Astrophysics – Astrophysics – Cosmology and Extragalactic Astrophysics
Scientific paper
2010-05-21
Astronomy and Astrophysics
Astrophysics
Cosmology and Extragalactic Astrophysics
25 pages, 14 figures, accepted to MNRAS
Scientific paper
Cosmological hydrodynamic simulations robustly predict that high-redshift galaxy star formation histories (SFHs) are smoothly-rising and vary with mass only by a scale factor. We use our latest simulations to test whether this scenario can account for recent observations at z>=6 from WFC3/IR, NICMOS, and IRAC. Our simulations broadly reproduce the observed ultraviolet (UV) luminosity functions and stellar mass densities and their evolution at z=6-8, all of which are nontrivial tests of the mean SFH. In agreement with observations, simulated galaxies possess blue UV continua owing to young ages (50-150 Myr), low metallicities (0.1-0.5 Zsun), and low dust columns (E(B-V) <= 0.05). Observations imply a near-unity slope in the stellar mass--star formation rate relation at all z=6-8, confirming the prediction that SFH shapes are invariant. Current surveys detect the majority of galaxies with stellar masses exceeding 10^9 Msun and few galaxies less massive than 10^{8.5} Msun, implying that they probe no more than the brightest 30% of the complete star formation and stellar mass densities at z>=6. Finally, we demonstrate that there is no conflict between smoothly-rising SFHs and recent clustering observations. This is because momentum-driven outflows suppress star formation in low-mass halos, leading to overall occupancies of 0.2-0.4 even though the star formation duty cycle is one. This leads to many interesting predictions at z>=4, among them that (1) optically-selected and UV-selected samples largely overlap; (2) few galaxies exhibit significantly suppressed specific star formation rates; and (3) occupancy is constant or increasing with decreasing luminosity. These predictions are in tentative agreement with current observations, but further analysis of existing and upcoming data sets is required in order to test them more thoroughly. (abridged)
Dav'e Romeel
Finlator Kristian
Oppenheimer Benjamin Darwin
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