View Item 
        •   Utrecht University Student Theses Repository Home
        • UU Theses Repository
        • Theses
        • View Item
        •   Utrecht University Student Theses Repository Home
        • UU Theses Repository
        • Theses
        • View Item
        JavaScript is disabled for your browser. Some features of this site may not work without it.

        Browse

        All of UU Student Theses RepositoryBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

        Photon Conversion Classi?cation by Boosting Decision Trees

        Thumbnail
        View/Open
        Bachelor Thesis Tijmen Schaapherder Final.pdf (2.545Mb)
        Publication date
        2018
        Author
        Schaapherder, T.
        Metadata
        Show full item record
        Summary
        The ALICE detector located at CERN studies subatomic particles produced in heavy-ion collisions. These collisions generate enormous amounts of particles including photons. The data gathered from these collisions is contaminated with background. This research focuses on generating a viable and efficient machine-learning algorithm for selecting photon conversions and discriminating them from background. The method used is that of the boosted decision tree (BDT). A Monte Carlo simulation is used to train and test the BDT and afterwards to test the performance of the BDT. The Monte Carlo simulation consists of data taken from a simulated collision of 40%-60% centrality and a center of mass energy of 2.76$ TeV (Tera electron Volts).
        URI
        https://studenttheses.uu.nl/handle/20.500.12932/37588
        Collections
        • Theses
        Utrecht university logo