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Title: Capturing the cosmic web for cosmology
Author: Naidoo, Krishna
ISNI:       0000 0004 9353 4297
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2020
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In this thesis the minimum spanning tree (MST) is developed to infer cosmological parameters from future galaxy redshift surveys. Studies of the distribution of galaxies typically determine constraints on cosmological models by measuring how galaxies are clustered using two-point statistics. However, these technique do not extract all the information present, especially from the non-linear cosmic web. To incorporate this information the MST is used and is shown to improve constraints on the sum of neutrino masses and parameters from the standard model of cosmology (ΛCDM). In Chapter 2 the MST is introduced and developed in a cosmological context. The MST is shown to be sensitive to information additional to that provided by the power spectrum or the bispectrum. In Chapter 3 the Quijote simulations are used to derive Fisher matrix constraints on the MST and power spectrum. The MST is shown to be much more sensitive to the sum of neutrino masses and when combined with the power spectrum the constraints on ΛCDM parameters improve by a factor ~2. In Chapter 4 the MST is constructed on BOSS galaxies and shown to be consistent with ΛCDM mocks. In the latter Chapters, the effect of large scale structure evolution on light from the cosmic microwave background, known as the integrated Sachs-Wolfe (ISW), are considered. In Chapter 5 voids in ΛCDM are shown to be correlated with the Cold Spot on the CMB. Therefore the discovery of such voids is not evidence of new physics. In Chapter 6, ISW maps for the MICE and Flagship simulations are constructed. These maps will enable studies of the ISW from a larger parameter space. In Chapter 7 the work presented in this thesis is summarised and future work is discussed.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available