This thesis deals with the practical application of Weak Gravitational Lensing (WGL) as a tool for studying two of the most challenging problems in modern cosmology: the nature of dark energy and tests of Einstein’s General Relativity. To be a useful tool, WGL must be able to put robust constraints on the parameters of interest even in the presence of a strong systematic effect like the Intrinsic Alignment (IA) of galaxies. In chapter 2 we demonstrate how ignoring the effect of IAs will lead to strongly biased measurements of cosmology. We introduce a simple IA model and demonstrate how the bias can be removed, at the cost of weaker constraints, by marginalising over nuisance parameters in the model. We present the first joint constraints on IAs and cosmology from WGL and galaxy position information. The combination returns errorbars of the same order as the naive WGL calculation which ignored IAs. We extend the IA model to treat shear and position correlations in a unified way with > 100 nuisance parameters. We parameterise deviations from GR and show, in chapter 3, how the considerable (~75%) decrease in constraining power caused by IAs can be partially mitigated by the inclusion of position-position and shear-position correlations. In chapter 4 we find these results to extend across a wide range of survey specifications. We find that increased survey area is not always favoured at the expense of source density and that the impact of improved redshift knowledge is not dramatic. In chapters 5-7 we note the potentially very powerful constraints from a joint analysis of WGL and Redshift Space Distortions (RSDs) from a spectroscopic survey. We summarise some important preparatory work for future cosmic shear surveys and advances in shear measurement techniques before concluding and describing some directions for future work.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:565466 |
| Date | January 2011 |
| Creators | Kirk, D. |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/1331890/ |
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