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dc.contributor.authorDhungana, Navaraj-
dc.description.abstractThe Project in Canada to Search for Supersymmetric Objects (PICASSO) searches for cold dark matter through the direct detection of Weakly Interacting Massive Particles (WIMPs) via spin-dependent and spin independent interactions with 19F nuclei. The detection principle is based on the superheated droplet technique; the detectors consist of a gel matrix with millions of liquid droplets of superheated fluorocarbon (C4F10) dispersed in it. In order to reduce the background, it is essential to distinguish the signature of different background particles interacting in the detector. A dedicated setup was developed in order to study the response of the C4F10 droplets in the presence of different backgrounds. The main objectives of this research are to identify the actual size (diameter) of the droplet increases due to phase transition and to check and establish the correlation between the droplet size and the maximum amplitude of the signal. In addition, the alpha-neutron discrimination was studied by observing each event’s image frames and the associated acoustic signal to get the amplitude distribution. The mean ratio of bubble size to droplet size was found to be 5.48, independent of temperature and type of interacting particle. Furthermore, no correlation was found between the droplet size and the maximum amplitude of the signal. As for the discrimination studies, the analysis of the signal events has confirmed that alphas generated outside the active liquid in the gel are much more difficult to discriminate from neutron than when alphas are generated inside the active liquid.en_CA
dc.publisherLaurentian University of Sudburyen_CA
dc.subjectdark matteren_CA
dc.subjectphase transitionen_CA
dc.titleBackground discrimination studies and measurements of droplet and bubble size for the Picasso experiment.en_CA
dc.description.degreeMaster's Thesesen_CA
dc.publisher.grantorLaurentian University of Sudburyen_CA
Appears in Collections:Master's Theses
Physics / Physique - Master's Theses

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