Most of the universe is made up of dark energy, but we are unsure of its fundamental nature. Large, wide-field optical galaxy surveys such as the Dark Energy Survey (DES) seek to measure any time variation in dark energy through its impact on the growth of large scale structure. Among the many features that must be controlled in order to achieve this measurement are the point spread function (PSF) and redshift distribution. In the first half of my thesis I will present a physically motivated model for the optical and atmospheric portions of the PSF and apply them to DES data. In the second half of my thesis I will turn to the measurement and calibration of redshift distributions. First, I present `clustering redshifts, ' a novel method of calibrating the redshift distributions of an ensemble of galaxies using their correlations with quasi-spectroscopic tracers of large scale structure, such as galaxy clusters. Then, I present a calibration of the DES Year 1 source redshift distributions using these clustering redshifts. Finally, I present a scheme for calibrating redshift distributions using self-organizing maps and overlapping infrared data. Both threads of this thesis will be useful for future cosmological galaxy surveys like the Large Synoptic Survey Telescope, Euclid, and the Wide Field Infrared Survey Telescope.