Taylor, Peter Llewelyn;
(2019)
Cosmological Inference with Cosmic Shear.
Doctoral thesis (Ph.D), UCL (University College London).
Preview |
Text
main.pdf - Accepted Version Download (7MB) | Preview |
Abstract
Over the next decade, data from large Stage IV survey telescopes including Euclid, LSST and WFIRST will provide some of the tightest cosmological constraints. To extract information from these surveys we take advantage of gravitational lensing, an effect predicted by Einstein's general theory of relativity. Gravitational lensing simply refers to the bending of light rays around massive bodies. This causes small changes in the observed ellipticity of galaxies, which is called weak gravitational lensing or | on the largest scales | cosmic shear. By examining these shape distortions over millions, or even billions of galaxies, we can distinguish between alternative cosmological models and measure the fundamental cosmological parameters precisely. While the constraining power of these upcoming data sets will improve by more than an order of magnitude, our statistical methods are not keeping pace. In this thesis I develop three new techniques to take full advantage of next generation surveys. The first of these is a method called k-cut cosmic shear. It allows us to efficiently remove sensitivity to small scales that are too difficult to model accurately due to complicated baryonic physics and nonlinear structure formation. Next I present a method called non-parametric cosmology with cosmic shear. I show how to extract information about the growth of structure and the background expansion of the Universe with no a priori assumption about the underlying cosmological model. This can be used to search for failures of the Lambda-Cold Dark Matter (LCDM) model. Finally I show how to perform inference with full forward models of the cosmic shear data. This approach allows us to seamlessly propagate all astrophysical, theoretical and instrumental systematics into the final parameter constraints, sidestepping complicated issues including the deconvolution of the survey mask and an assumption about the functional form of the likelihood.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Cosmological Inference with Cosmic Shear |
| Event: | UCL |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2019. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Space and Climate Physics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10079030 |
Archive Staff Only
 |
View Item |
