This thesis describes the use of the rarest high-mass and high-redshift galaxy clusters to constrain cosmology, with a particular focus on the methodology of Extreme Value Statistics (EVS). Motivated by the prospect that even a single sufficiently high mass and high redshift cluster can provide strong evidence against a given cosmology, we first use exact EVS to construct the probability density function (PDF) for the mass of the most-massive cold dark matter (CDM) halo within a fixed redshift volume. We find that the approximation of uncorrelated haloes is valid for high mass haloes 10¹⁵ and large volumes 100⁻¹Mpc, which are also required before the shape of the PDF converges to an asymptotic Generalised Extreme Value (GEV) form. Furthermore, we show the GEV shape parameter γ to be a weak discriminant of primordial non-Gaussianity on galaxy cluster scales. We then extend this analysis to real observations, predicting the PDF for the most-massive galaxy cluster within an observational survey, showing no cluster so far observed is significantly larger than the most-massive expected at its redshift in a concordance cosmology. We also show how the predictions for most-massive cluster with redshift are changed in cosmologies with primordial non-Gaussianity or coupled scalar field dark energy. Finally, we consider why this result appears at odds with some previous analyses, reaffirming that they make use of a biased statistic and showing how an equivalent unbiased one may be constructed. This is then used to rank a comprehensive sample of galaxy clusters according to their rareness, with the cluster ACT-CLJ0102-4915 found to be the most extreme object so far observed. However, the observation of this (and all other clusters so far seen) is shown to be a not unusual event in a concordance universe.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:590333 |
| Date | January 2013 |
| Creators | Harrison, Ian |
| Publisher | Cardiff University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://orca.cf.ac.uk/56777/ |
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