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Title: Cosmology with future radio surveys
Author: Wolz, L.
ISNI:       0000 0004 8502 0026
Awarding Body: (UCL) University College London
Current Institution: University College London (University of London)
Date of Award: 2014
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The discovery of the accelerated expansion of the Universe more than 20 years ago has started a new era of precision cosmology. The Cosmic expansion history can be determined by distance measurements using standard rulers such as the Baryon Acoustic Oscillations (BAO). Optical surveys have detected the BAO scales at different times and thereby set constraints on many cosmological parameters. In recent years, large-scale structure surveys in radio frequencies have become more important due to novel tools such as interferometric observations which can significantly increase the sensitivity and spatial resolution. In addition, new receiver technology can observe large fields-of-view (FoV) which remarkably enlarge the survey volume. A new survey type called intensity mapping is specifically designed to measure the largest modes in the matter distribution by mapping the neutral hydrogen flux with coarse resolution. These 21cm maps are powerful tools to access cosmological distances in a wide redshift range within short observation times. The drawback is the high foregrounds of the Milky Way which contaminate the measurements significantly. In this thesis, we simulate a future intensity mapping experiment including realistic Galactic foregrounds and instrumental noise. We use a blind search algorithm to remove those foregrounds and present the residual contamination of the maps. The cosmological parameter estimation shows a significant bias, however, the BAO scale recovery is nearly unbiased by the foreground removal. In this way, we present the first realistic end-to-end simulation of demonstrating the BAO recovery in the presence of realistic foregrounds. Furthermore, we employ our removal method on intensity mapping data of the Green Bank telescope and compute the temperature power spectrum of the cleaned maps. We thereby show that this technique may be applied to real data sets and produce measurements  3 which are competitive with existing approaches. In the third study, a new algorithm for radio interferometric image reconstruction is presented. We use a new imaging method called compressive sensing employing the image sparsity. Next-generation of radio interferometers will have considerably wide FoVs which requires considering the third dimension in the imaging algorithms. We develop a fast algorithm to include the wide FoV into existing codes. Furthermore, we show that in the sparse framework, the wide FoV can improve the image fidelity compared to the flat-sky approximation.
Supervisor: Abdalla, F. B. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available