Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.817547
Title: Using clusters of galaxies as novel and standard probes of dark matter
Author: Bhargava, Sunayana
ISNI:       0000 0004 9357 5013
Awarding Body: University of Sussex
Current Institution: University of Sussex
Date of Award: 2020
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Abstract:
In this thesis, we apply samples of red-sequence selected galaxy clusters with archival Xray observations as novel and standard probes of dark matter. We detail the construction of samples consisting of clusters in the Sloan Digital Sky Survey and Dark Energy Survey areas selected using the redMaPPer cluster finder, with X-ray confirmation provided by the XMM Cluster Survey (XCS). We apply one of these samples to the investigation of an unmodelled X-ray line at ≃3.5 keV in the spectra of clusters of galaxies. Using the largest cluster sample to date for such a study, we analyse the spectra of 118 galaxy clusters to search for evidence of a flux excess at ≃3.5 keV, which has a suggested origin in the decay of resonantly produced sterile neutrino dark matter with mass ms ≃7 keV. Our results find evidence against a dark matter interpretation of the 3.5 keV feature. We then apply all three samples to calibrating the centering performance of redMaPPer. Central galaxies selected by redMaPPer do not always robustly trace the centre of the cluster's underlying dark matter distribution, while X-ray emission is seen to be a more reliable tracer of the cluster potential. We therefore model the o↵set between optical and X-ray determinations of the cluster centre using the redMaPPer catalogues and public data from XMM-Newton. The centering performance of the cluster finder is a key component in the accurate measurement of cluster masses and derived estimates of cosmological parameters. Although we find cluster miscentering to be a subdominant source of systematic error in optical datasets (∼2%), it is likely to constitute a more significant contribution to cluster cosmology in future, larger datasets such as LSST.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.817547  DOI: Not available
Keywords: QB0791.3 Dark matter ; QB0856 Galaxies
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