Analysis of the two degree field galaxy redshift survey
In this Thesis we analyse in detail the Anglo-Australian 2 degree Field Galaxy Redshift Survey (2dFGRS). The goal of this survey is to measure all galaxy redshifts for the 250 000 galaxies brighter than b(_J) = 19.45 spread over ~ 2000 square degrees. At present, the 2dFGRS has obtained redshifts for ~ 190 000 galaxies. It is currently the biggest galaxy redshift survey in existence and represents an order of magnitude increase in size over any previous survey. The study of the large-scale structure of the Universe is undergoing a revolution due to important technological advances in observational astronomy that make surveys like the 2dFGRS possible. This new era in mapping the Universe demands the development of new theoretical analysis tools, both to exploit the large amounts of data, and to take advantage of, for the first time in cosmology, the extraordinary opportunity to push random errors below the level of the systematic errors. By a detailed analysis of the survey construction and observing strategy, we implement a set of maps to estimate, as precisely as possible, the selection function of the 2dFGRS. These maps, which characterize the survey completeness, enable us to estimate accurately fundamental properties of a homogeneous galaxy sample: the galaxy luminosity function and real space galaxy clustering. By combining the 2dFGRS with the near infra-red 2MASS survey, we estimate the K(_s)-band galaxy luminosity function, from which we infer the stellar mass function of galaxies. This yields a total mass fraction in stars between 0.1% and 0.3% of the critical cosmic density. Exploiting the size of the survey, we undertake the first precise measurement of the dependence of galaxy clustering on luminosity and spectral type. Star-forming galaxies as well as more quiescent galaxies show a clear increase in clustering strength with luminosity at a similar rate. This is the first time that we are able to examine in detail the properties of galaxies that drive their spatial distribution.