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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Probing the primordial Universe using the SKA in combination with other cosmological surveys

Matthewson, William January 2019 (has links)
>Magister Scientiae - MSc / Next-generation surveys of the large-scale structure of the Universe will be of great importance in allowing us to extract invaluable information about the nature of the Universe and the physical laws that govern it, at a higher precision than previously possible. In particular, they will allow us to more closely study primordial non-Gaussianity, a feature which leaves an imprint on the power spectrum of galaxies on the ultra-large scales and which acts as a powerful probe of the physics of the early Universe. To investigate the extent to which upcoming surveys will be able to improve our knowledge of primordial non-Gaussianity, we perform a forecast to predict the observational constraints on local-type primordial non-Gaussianity, as well as an extension that includes a scale dependence. We study the constraining power of a multi-tracer approach, where information from different surveys is combined to help suppress cosmic variance and break parameter degeneracies. More specifically, we consider the combination of a 21cm intensity mapping survey with each of two different photometric galaxy surveys, and also examine the effect of including CMB lensing as an additional probe. The forecast constraint from a combination of SKA1, a Euclid-like (LSST-like) survey and a CMB Stage 4 lensing experiment is (fNL) ' 0:9 (1:4) which displays a factor of 2 improvement over the case without CMB lensing, indicating that the surveys considered are indeed complementary. The constraints on the running index of the scale-dependent model are forecast as (nNL) ' 0:12 (0:22) from the same combination of surveys.

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