This thesis explores the properties of distant galaxies in the Universe, in particular their redshifts,
morphologies, evolutionary history and star formation processes within them.
The first part is concerned with photometric redshift estimation. I present different photo-z
methods and compare them using a sample of Luminous Red Galaxies (LRGs). Photo-z design
studies are then carried out for the upcoming Dark Energy Survey as well as the planned space-based
Euclid mission. I show the importance of adding near infra-red data to optical data in
obtaining accurate redshift estimates for both these projects and how this may prove crucial for
some of the cosmological analysis intended with them.
In Chapter 5, I present automated morphological classifications for ∼ 1 million objects from
the Sloan Digital Sky Survey and compare them to visual classifications of the same objects obtained
as part of the Galaxy Zoo project. I find that a neural network is able to reproduce the
human classifications to an accuracy of better than 90%.
In Chapter 6 I study the evolution of the luminosity and mass functions of LRGs using spectroscopic
data. I find that these objects are mainly composed of old stars that were formed very
early in the history of the Universe and also that the most massive objects were already well assembled
at redshifts of ∼0.8 in direct contradiction with predictions of most current models of
galaxy formation.
Chapter 7 presents an alternative means of determining the approximate nature of the stellar
initial mass function of extragalactic systems by considering timescales for low-mass star formation
in different environments. I find that a galaxy’s metallicity is a key parameter in determining
the shape of its IMF and make some predictions about trends in molecular emission in different
extragalactic systems with different IMFs
