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Title: The XMM Cluster Survey : a new cluster catalogue and applications
Author: Rooney, Philip
ISNI:       0000 0004 5923 6990
Awarding Body: University of Sussex
Current Institution: University of Sussex
Date of Award: 2016
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In this thesis, we present the XMM Cluster Survey Second Data Release (XCS-DR2) and use it to test possible spectroscopic biases, fit scaling relations, and find massive, relaxed galaxy clusters. XCS finds clusters in the XMM public archive. The new cluster candidate list includes 15,642 objects found in the 688 square degrees of sky suitable for cluster detection. XCS-DR2 is the largest X-ray selected cluster catalogue to date. It contains 7,129 unique preliminary cluster identifications and 1,177 unique firm cluster identifications. Where redshifts were available, a spectral fitting was made leading to 4,987 unique cluster temperature and luminosity measurements. XCS-DR2 is more than an order of magnitude larger than XCS-DR1. As XCS-DR2 is a catalogue of homogeneously processed galaxy clusters, it is an ideal dataset to test possible spectroscopic biases during X-ray spectral fitting. This thesis answers seven questions related to the combining and fitting of multi-observational data and the instrumental calibration of XMM. Notably we present strong evidence that spectral selection must take place before any final X-ray spectral fitting takes place. XCS-DR1 clusters have been used to fit a luminosity temperature scaling relation. This thesis presents new spectral fitting pipelines, so the previous scaling relations work was revisited to ascertain how the results have changed. Additionally, by using the latest SPT cluster catalogue, a scaling relation was fit between the X-ray and the SunyaevZel'dovich effect properties of XCS-DR2 clusters. Massive, relaxed galaxy clusters have been used to fit cosmological parameters through measurements of their baryon fractions. XCS-DR2 contains 342 clusters observed on-axis with temperature, TX ≥ 4:5 keV. A morphological analysis of these clusters shows that 20 of them appear to be relaxed. When added to the latest analysis, a subsample of six relaxed clusters, can improve ΩM and w estimates by 18% and 12% respectively.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QB0460 Astrophysics