Probing the Early Universe and Dark Energy with Multi-epoch Cosmological Data

Probing the Early Universe and Dark Energy with Multi-epoch Cosmological Data
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Book Synopsis Probing the Early Universe and Dark Energy with Multi-epoch Cosmological Data by : Renee Hlozek

Download or read book Probing the Early Universe and Dark Energy with Multi-epoch Cosmological Data written by Renee Hlozek and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Contemporary cosmology is a vibrant field, with data and observations increasing rapidly. This allows for accurate estimation of the parameters describing our cosmolo- gical model. In this thesis we present new research based on two different types of cosmological observations, which probe the universe at multiple epochs. We begin by reviewing the current concordance cosmological paradigm, and the statistical tools used to perform parameter estimation from cosmological data. We highlight the initial conditions in the universe and how they are detectable using the Cosmic Microwave Background radiation. We present the angular power spectrum data from temperature observations made with the Atacama Cosmology Telescope (ACT) and the methods used to estimate the power spectrum from temperature maps of the sky. We then present a cosmological analysis using the ACT data in combination with observations from the Wilkinson Microwave Anisotropy Probe to constrain parameters such as the effective number of relativistic species and the spectral index of the primordial power spectrum, which we constrain to deviate from scale invariance at the 99% confidence limit. We then use this combined dataset to constrain the primordial power spec- trum in a minimally parametric framework, finding no evidence for deviation from a power-law spectrum. Finally we present Bayesian Estimation Applied to Multiple Species, a parameter estimation technique using photometric Type la Supernova data to estimate cosmological parameters in the presence of contaminated data. We apply this algorithm to the full season of the Sloan Digital Sky Survey IT Supernova Search, and find that the constraints are improved by a factor of three relative to the case where one uses a smaller, spectroscopically confirmed subset of supernovae. A thesis submitted in candidature for the degree of Doctor of Philosophy University of Oxford Trinity Term 2011.


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