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We simulate deep images from the Hubble Space Telescope (HST) usingsemi-empirical models of galaxy formation with only a few basic assumptions andparameters. We project our simulations all the way to the observational domain,adding cosmological and instrumental effects to the images, and analyze them inthe same way as real HST images ("forward modeling"). This is a powerful toolfor testing and comparing galaxy evolution models, since it allows us to makeunbiased comparisons between the predicted and observed distributions of galaxyproperties, while automatically taking into account all relevant selectioneffects.  Our semi-empirical models populate each dark matter halo with a galaxy ofdetermined stellar mass and scale radius. We compute the luminosity andspectrum of each simulated galaxy from its evolving stellar mass using stellarpopulation synthesis models. We calculate the intrinsic scatter in the stellarmass-halo mass relation that naturally results from enforcing a monotonicallyincreasing stellar mass along the merger history of each halo. The simulatedgalaxy images are drawn from cutouts of real galaxies from the Sloan DigitalSky Survey, with sizes and fluxes rescaled to match those of the modelgalaxies.  The distributions of galaxy luminosities, sizes, and surface brightnessesdepend on the adjustable parameters in the models, and they agree well withobservations for reasonable values of those parameters. Measured galaxymagnitudes and sizes have significant magnitude-dependent biases, with bothbeing underestimated near the magnitude detection limit. The fraction ofgalaxies detected and fraction of light detected also depend sensitively on thedetails of the model.

Simulating Deep Hubble Images With Semi-empirical Models of Galaxy Formation