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Particle identification using boosted decision trees in the semi-digital hadronic calorimeter prototype

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    0539356 - FZÚ 2021 RIV GB eng J - Journal Article
    Boumediene, D. - Pingault, A. - Tytgat, M. - Cvach, Jaroslav - Janata, Milan - Kovalčuk, Michal - Kvasnička, Jiří - Polák, Ivo - Smolík, Jan - Vrba, Václav - Zálešák, Jaroslav - Zuklín, Josef
    Particle identification using boosted decision trees in the semi-digital hadronic calorimeter prototype.
    Journal of Instrumentation. Roč. 15, č. 10 (2020), s. 1-17, č. článku P10009. ISSN 1748-0221. E-ISSN 1748-0221
    R&D Projects: GA MŠk(CZ) LTT17018
    Research Infrastructure: CERN-CZ II - 90104
    Institutional support: RVO:68378271
    Keywords : particle identification * CALICE * performance * GEANT * data analysis method
    Subject RIV: BF - Elementary Particles and High Energy Physics
    OBOR OECD: Particles and field physics
    Impact factor: 1.415, year: 2020
    https://doi.org/10.1088/1748-0221/15/10/P10009

    The CALICE Semi-Digital Hadronic CALorimeter (SDHCAL) prototype using Glass Resistive Plate Chambers as a sensitive medium is the first technological prototype of a family of high-granularity calorimeters developed by the CALICE collaboration to equip the experiments of future leptonic colliders. It was exposed to beams of hadrons, electrons and muons several times in the CERN PS and SPS beamlines between 2012 and 2018. We present here a new method of particle identification within the SDHCAL using the Boosted Decision Trees (BDT) method applied to the data collected in 2015. The performance of the method is tested first with Geant4-based simulated events and then on the data collected by the SDHCAL in the energy range between 10 and 80 GeV with 10 GeV energy steps. The BDT method is then used to reject the electrons and muons that contaminate the SPS hadron beams.
    Permanent Link: http://hdl.handle.net/11104/0317045
     
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