Simulating Deep Hubble Images With Semi-empirical Models of Galaxy
  Formation
  We simulate deep images from the Hubble Space Telescope (HST) using
semi-empirical models of galaxy formation with only a few basic assumptions and
parameters. We project our simulations all the way to the observational domain,
adding cosmological and instrumental effects to the images, and analyze them in
the same way as real HST images ("forward modeling"). This is a powerful tool
for testing and comparing galaxy evolution models, since it allows us to make
unbiased comparisons between the predicted and observed distributions of galaxy
properties, while automatically taking into account all relevant selection
effects.
  Our semi-empirical models populate each dark matter halo with a galaxy of
determined stellar mass and scale radius. We compute the luminosity and
spectrum of each simulated galaxy from its evolving stellar mass using stellar
population synthesis models. We calculate the intrinsic scatter in the stellar
mass-halo mass relation that naturally results from enforcing a monotonically
increasing stellar mass along the merger history of each halo. The simulated
galaxy images are drawn from cutouts of real galaxies from the Sloan Digital
Sky Survey, with sizes and fluxes rescaled to match those of the model
galaxies.
  The distributions of galaxy luminosities, sizes, and surface brightnesses
depend on the adjustable parameters in the models, and they agree well with
observations for reasonable values of those parameters. Measured galaxy
magnitudes and sizes have significant magnitude-dependent biases, with both
being underestimated near the magnitude detection limit. The fraction of
galaxies detected and fraction of light detected also depend sensitively on the
details of the model.
