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Particle identification using Boosted Decision Trees in the Semi-Digital Hadronic Calorimeter prototype
Journal of Instrumentation ( IF 1.3 ) Pub Date : 2020-10-13 , DOI: 10.1088/1748-0221/15/10/p10009
D. Boumediene 1 , A. Pingault 2 , M. Tytgat 2 , B. Bilki 3 , D. Northacker 3 , Y. Onel 3 , G. Cho 4 , D.-W. Kim 4 , S.C. Lee 4 , W. Park 4 , S. Vallecorsa 4 , Y. Deguchi 5 , K. Kawagoe 5 , Y. Miura 5 , R. Mori 5 , I. Sekiya 5 , T. Suehara 5 , T. Yoshioka 5 , L. Caponetto 6 , C. Combaret 6 , R. Ete 6 , G. Garillot 6 , G. Grenier 6 , J.-C. Ianigro 6 , T. Kurca 6 , I. Laktineh 6 , B. Liu 6, 7 , B. Li 6 , N. Lumb 6 , H. Mathez 6 , L. Mirabito 6 , A. Steen 6 , E. Calvo Alamillo 8 , M.C. Fouz 8 , J. Marin 8 , J. Navarrete 8 , J. Puerta Pelayo 8 , A. Verdugo 8 , F. Corriveau 9 , M. Chadeeva 10 , M. Danilov 10 , L. Emberger 11 , C. Graf 11 , L.M.S. de Silva 11 , F. Simon 11 , C. Winter 11 , J. Bonis 12 , D. Breton 12 , P. Cornebise 12 , A. Gallas 12 , J. Jeglot 12 , A. Irles 12 , J. Maalmi 12 , R. Pöschl 12 , A. Thiebault 12 , F. Richard 12 , D. Zerwas 12 , M. Anduze 13 , V. Balagura 13 , V. Boudry 13 , J.-C. Brient 13 , E. Edy 13 , F. Gastaldi 13 , R. Guillaumat 13 , F. Magniette 13 , J. Nanni 13 , H. Videau 13 , S. Callier 14 , F. Dulucq 14 , Ch. de la Taille 14 , G. Martin-Chassard 14 , L. Raux 14 , N. Seguin-Moreau 14 , J. Cvach 15 , M. Janata 15 , M. Kovalcuk 15 , J. Kvasnicka 15 , I. Polak 15 , J. Smolik 15 , V. Vrba 15 , J. Zalesak 15 , J. Zuklin 15 , Y.Y. Duan 7 , S. Li 7 , J. Guo 7 , J.F. Hu 7 , F. Lagarde 7 , Q.P. Shen 7 , X. Wang 7 , W.H. Wu 7 , H.J. Yang 7 , Y.F. Zhu 7 , L. Emberger 11 , C. Graf 11 , F. Simon 11 , C. Winter 11
Affiliation  

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.

中文翻译:

在半数字强子量热仪原型中使用增强决策树进行粒子识别

CALICE 半数字强子热量计 (SDHCAL) 原型使用​​玻璃电阻板室作为敏感介质,是 CALICE 合作开发的高粒度热量计系列的第一个技术原型,用于装备未来轻子对撞机的实验。在 2012 年至 2018 年期间,它在 CERN PS 和 SPS 光束线中多次暴露于强子、电子和 μ 子束。我们在此介绍了一种使用应用于数据的增强决策树 (BDT) 方法在 SDHCAL 中进行粒子识别的新方法2015 年收集。首先使用基于 Geant4 的模拟事件测试该方法的性能,然后使用 SDHCAL 在 10 到 80~GeV 能量范围内以 10~GeV 能量步长收集的数据进行测试。
更新日期:2020-10-13
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