How well can we really estimate the stellar masses of galaxies from
  broadband photometry?
  The estimated stellar masses of galaxies are widely used to characterize how
the galaxy population evolves over cosmic time. If stellar masses can be
estimated in a robust manner, free from any bias, global diagnostics such as
the stellar mass function can be used to constrain the physics of galaxy
formation. We explore how galaxy stellar masses, estimated by fitting
broad-band spectral energy distributions (SEDs) with stellar population models,
can be biased as a result of commonly adopted assumptions for the
star-formation and chemical enrichment histories, recycled fractions and dust
attenuation curves of galaxies. We apply the observational technique of
broad-band SED fitting to model galaxy SEDs calculated by the theoretical
galaxy formation model GALFORM, isolating the effect of each of these
assumptions. We find that, averaged over the entire galaxy population, the
common assumption of exponentially declining star-formation histories does not
adversely affect stellar mass estimation. We show that fixing the metallicity
in SED fitting or using sparsely sampled metallicity grids can introduce mass
dependent systematics into stellar mass estimates. We find that the common
assumption of a star-dust geometry corresponding to a uniform foreground dust
screen can cause the stellar masses of dusty model galaxies to be significantly
underestimated. Finally, we show that stellar mass functions recovered by
applying SED fitting to model galaxies at high redshift can differ
significantly in both shape and normalization from the intrinsic mass functions
predicted by a given model. Given these differences, our methodology of using
stellar masses estimated from model galaxy SEDs offers a new, self-consistent
way to compare model predictions with observations.
