Particle identification using Boosted Decision Trees in the Semi-Digital Hadronic Calorimeter prototype

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Published 13 October 2020 © 2020 IOP Publishing Ltd and Sissa Medialab
, , Citation D. Boumediene et al 2020 JINST 15 P10009 DOI 10.1088/1748-0221/15/10/P10009

1748-0221/15/10/P10009

Abstract

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. The rejection power of the new method is estimated to be as high as 99.0% for the muons and 99.4% for the electrons associated to a pion selection efficiency of about 95.0%.

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