A comparison of multivariate data analysis techniques as applied to the identification of electrons and tau leptons

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dc.contributor.advisorPadley, B. Paul
dc.creatorAskew, Andrew Warren
dc.date.accessioned2009-06-04T08:13:22Z
dc.date.available2009-06-04T08:13:22Z
dc.date.issued2001
dc.description.abstractThis thesis compares the performance of Probability Density Estimation and Neural Networks as applied to the identification of tau leptons and electrons at the DO detector for Run II. The theory behind each method of multivariate analysis is briefly described. The efficiencies of each of the methods are compared from analysis of Monte Carlo data samples, and optimal choices for the discrimination between signal and background are made.
dc.format.extent99 p.en_US
dc.format.mimetypeapplication/pdf
dc.identifier.callnoTHESIS PHYS. 2001 ASKEW
dc.identifier.citationAskew, Andrew Warren. "A comparison of multivariate data analysis techniques as applied to the identification of electrons and tau leptons." (2001) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/17401">https://hdl.handle.net/1911/17401</a>.
dc.identifier.urihttps://hdl.handle.net/1911/17401
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectParticle physics
dc.subjectElementary particles
dc.subjectHigh energy physics
dc.titleA comparison of multivariate data analysis techniques as applied to the identification of electrons and tau leptons
dc.typeThesis
dc.type.materialText
thesis.degree.departmentPhysics
thesis.degree.disciplineNatural Sciences
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
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