Mathematics – Logic
Scientific paper
Dec 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010phdt.......173a&link_type=abstract
ProQuest Dissertations And Theses; Thesis (Ph.D.)--University of California, Davis, 2010.; Publication Number: AAT 3443994; ISBN
Mathematics
Logic
Scientific paper
Future advances in cosmology will depend on the next generation of cosmological observations and how they shape our theoretical understanding of the universe. Current theoretical ideas, however, have an important role to play in guiding the design of such observational programs. The work presented in this thesis concerns the intersection of observation and theory, particularly as it relates to advancing our understanding of the accelerated expansion of the universe (or the dark energy). Chapters 2 - 4 make use of the simulated data sets developed by the Dark Energy Task Force (DETF) for a number of cosmological observations currently in the experimental pipeline. We use these forecast data in the analysis of four quintessence models of dark energy: the PNGB, Exponential, Albrecht-Skordis and Inverse Power Law (IPL) models. Using Markov Chain Monte Carlo sampling techniques we examine the ability of each simulated data set to constrain the parameter space of these models. We examine the potential of the data for differentiating time-varying models from a pure cosmological constant. Additionally, we introduce an abstract parameter space to facilitate comparison between models and investigate the ability of future data to distinguish between these quintessence models. In Chapter 5 we present work towards understanding the effects of systematic errors associated with photometric redshift estimates. Due to the need to sample a vast number of deep and faint galaxies, photometric redshifts will be used in a wide range of future cosmological observations including gravitational weak lensing, baryon accoustic oscillations and type 1A supernovae observations. The uncertainty in the redshift distributions of galaxies has a significant potential impact on the cosmological parameter values inferred from such observations. We introduce a method for parameterizing uncertainties in modeling assumptions affecting photometric redshift calculations and for propagating these uncertainties through to uncertainties in the cosmological parameters.
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