Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.788074
Title: Preparing for Dark Matter : maximising our discrimination power in the event of detection
Author: Cheek, Andrew
ISNI:       0000 0004 7973 1710
Awarding Body: Durham University
Current Institution: Durham University
Date of Award: 2019
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Abstract:
Numerous experimental observations place Dark Matter (DM) as a central character in our cosmological history. Many extensions to the Standard Model of particles physics provide candidates for DM, often predicting interactions additional to gravity. This gives us the opportunity to experimentally probe these extensions and determine the nature of DM. In this thesis, we explore how direct DM detection could be used most effectively to achieve this goal. With this in mind, we have developed a tool for performing multidimensional parameter scans. This tool allows us to evaluate the capabilities of current and future detectors for detecting and understanding DM interactions. We show that by extending the energy region analysed, detection sensitivities and parameter reconstruction can be improved substantially. These insights play an important role in more global analyses, where hints of DM could come from other experiments, but verification depends on direct detection.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.788074  DOI: Not available
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