In this thesis, we present three projects that describe the use of the XMM-Newton Cluster Survey (XCS) to investigate exotic astrophysical phenomena. Each project widens the scope of XCS beyond the study of cluster cosmology. In the first project, we derive correlations between X-ray properties of Active Galactic Nuclei (AGN) and mass of its Super Massive Black Hole (SMBH). These properties are the X-ray luminosity (LX) and a measure of the variability of the AGN - the normalised excess variance (σ2NXS). We confirm previous results indicating an anti-correlation between black hole mass (MBH) and σ2NXS, as well as anti-correlation between LX and σ2NXS, and a positive correlation between LX and MBH. We investigate whether there is a redshift evolution in these relations. We then develop methods to estimate MBH from short exposure X-ray observations specific to the eROSITA observatory, to allow us to measure LX of millions of AGN. The second project describes a new method to detect the rarest of X-ray transient sources, X-ray ashes (XRFs), through a serendipitous search of the XCS catalogue. We categorize the detected XRF candidates and look in more detail at one that is most likely to be an XRF. Based on its properties, we estimate an upper limit to their occurrence. A third project describes our method to search for an unknown emission line in the stacked spectra of galaxy clusters from the XCS extended source catalogue. This line, if found, may be evidence of a hypothetical particle - the sterile neutrino - which has been postulated as a candidate for dark matter. We review other research that has led to published work, as well as laying the foundation for future collaborations. This includes work on improving the XCS temperature pipeline in order to estimate the temperatures of galaxy clusters.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:742164 |
| Date | January 2018 |
| Creators | Mayers, Julian |
| Publisher | University of Sussex |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://sro.sussex.ac.uk/id/eprint/76076/ |
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