The Properties of Sub-mm Galaxies in Hierarchical Models

Swinbank, Mark, Lacey, Cedric, Smail, Ian, Baugh, Carlton, Frenk, Carlos, Blain, Andrew, Chapman, Scott, Coppin, Kristen, Ivison, Rob, Gonzalez, Juan and Hainline, Laura (2008) The Properties of Sub-mm Galaxies in Hierarchical Models. Monthly Notices of the Royal Astronomical Society (MNRAS), 391 (1). pp. 420-434. ISSN 0035-8711
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We use the combined GALFORM semi-analytical model of galaxy formation and GRASIL spectrophotometric code to investigate the properties of galaxies selected via their sub-mm emission. Our fiducial model has previously been shown to fit the properties of local ULIRGs, as well as the number counts of faint sub-mm galaxies. Here, we test the model in detail by comparing the SEDs and stellar, dynamical, gas and halo masses of sub-mm galaxies against observational data. We precisely mimic the sub-mm and radio selection function of the observations and show that the predicted far-infrared properties of model galaxies with S_850>5mJy and S_1.4>30uJy are in good agreement with observations. Although the dust emission model does not assume a single dust temperature, the far-infrared SEDs are well described by single component modified black-body spectrum with characteristic temperature 32+/-5K. We also find evidence that the observations may have uncovered evolution in the far-infrared--radio relation in ULIRGs out to z~2. We show that the predicted redshift distribution of sub-mm galaxies provides a reasonable fit to the observational data with a median redshift z=2.0, with the radio-selected subset predicted to make up approximately 75% of the population. However, the predicted K-band and mid-infrared (3--8um) flux densities of the sub-mm galaxies (and LBGs) are up to a factor 10x fainter than observed. This discrepancy may indicate that the stellar masses of the sub-mm galaxies in the model are too low: M~10^10Mo, while observations suggest more massive systems, M~10^11Mo. Finally, we discuss the potential modifications to the models which may improve the fit to the observational data. [Abridged]


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