What can we learn from the abundance and clustering of galaxies?

Models that are able to reproduce the abundance and clustering of galaxies
are based on a statistical match between halos (or subhalos) and galaxies at
a given redshift. The observational data are then used to constrain the mass
relation between halos and galaxies. These models have been widely used to
predict cosmological parameters, star formation rates, merger rates, weak
lensing signal, and to interpret the results of hydrodynamical simulations.
I will first introduce and discuss this approach, pointing out its
advantages and limitations. I will then argue that the evolution of
satellite galaxies is the main unknown in these models, and is probably more
complicated than what is usually assumed. For example, the stellar mass of a
satellite galaxy might depend not only on its host subhalo mass, but also on
the mass of its group, and on the time it first became a satellite. A new
methodology will be presented that is capable of exploring the complex
behavior of satellite galaxies in a relatively simple manner. Using this new
approach we were able to compute the correlation functions for a very large
number of models (~10^7), finding a large range of accepted models, much
larger than previously claimed. The new method is useful for various
clustering studies, including AGNs, HI gas, and high-redshift galaxies.