Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.489729
Title: Three Dimensional Analysis and Track Reconstruction in the DRIFT-II Dark Matter Detector
Author: Muna, Demitri Nadeem
ISNI:       0000 0001 3431 2545
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2008
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Abstract:
The biggest question in astrophysics and cosmology today is identifying the composition of the Universe. Approximately 25% is thought to be comprised of dark matter, particles that lie outside of the standard model of particle physics and have such a low cross section that they have to date evaded detection despite the substantial indirect observational evidence. DRIFT-II is one of about two dozen experiments designed to directly detect dark matter in the laboratory. Dark matter particles, through an elastic nuclear recoil, should create ionisation tracks in the detector. A positive signal would be the identification of a number of dark matter events that have an anisotropic distribution of recoil directions peaked in the direction of solar motion. The work presented here is a detailed analysis of the data from the DRIFT-lIb experiment and includes event discrimination and techniques for two and three dimensional track reconstruction. The expected dark matter event rate given the latest experimental results is calculated for this particular experiment with a result of 8.6 . 10-3 events per kg·day. The lower energy resolution limit of the detector is measured as 1.23 keV for an electron recoil and 3.46 keV for a sulphur nucleus recoil. Simulations of the particle interactions expected in the detector are performed and applied to experimental data. A full analysis of the directional sensitivity of the detector is also presented. Finally, a dark matter exclusion limit is calculated from experimental data to be 6.9 10-2 pb for a WIMP mass of 100 GeV/c2
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.489729  DOI: Not available
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