<p>In this dissertation, we describe observational and theoretical work related to the large-scale clustering of matter in the universe. Such work is crucial in constraining models of the Universe in future surveys and is one of the most powerful probes of the nature of dark energy. In Chapter \ref{magnification}, we present work performed using the Deep Lens Survey (DLS) to measure the growth of structure over cosmic time using weak lensing magnification. This is the first time such a measurement has been performed and represents a significant step forward for this relatively new probe of large-scale structure (LSS) which is known to be complementary to other weak lensing measurements. Later in Chapter \ref{conclusions}, we discuss steps needed for magnification become a competitive, precision probe of cosmology. Chapter \ref{covariance} presents a model for the emulation cosmology dependent error covariances in LSS probes. Estimating these covariances are necessary in order to compare models to the data and require a large amount of computational time to create the simulations required. Tools to reduce the number of simulations required and model the cosmology dependence are needed. We utilize a novel decomposition of LSS error covariances that allows for construction of a emulator that fulfills both of these criteria. In order for future surveys to reach their goals, methods to model measurement error and new probes of LSS complementary to those planned are required.
The conclusions of this dissertation in Chapter \ref{conclusions} address the future outlook for this work and research that must be done between now and when the next set of survey data is available. Many systematic errors need to be addressed in magnification before it can be considered a precision cosmology tool. For the error covariances, additional methods to reduce the required number of simulations to estimate the matrices are required. In the Appendix, we present a high level description of an open sourced software package that we developed and implemented over the course of these two projects.
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:3602168 |
| Date | 04 January 2014 |
| Creators | Morrison, Christopher Brian |
| Publisher | University of California, Davis |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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