大型強子對撞機(LHC)計劃升級爲高亮度大型強子對撞機(HL-LHC),熱量計將須承受原計劃十倍的亮度。 新的端蓋熱量計 HGCAL 由前方的電磁熱量計 ECAL(CE-E)及後方的 HCAL(CE-H)組成。 2018年,在歐洲核子研究組織(CERN)中 SPS 的 H2 beam line 舉行了該熱量計原型的測試。 爲了提高辨識粒子的表現,我們希望區分電子及主要在ECAL中而非HCAL產生射叢的介子,TMVA 提供了自動且易於使用的方法發揮HGCAL精細的射叢閥發展資訊來辨認粒子。 在本論文中我們執行了詳細的以GEANT4組件產生的模擬來訓練的TMVA分析,來展現 HGCAL 分別由 20 到 300 十億電子伏特能量的電磁射叢之能力。 我們用2018年測試的資料驗證其性能,以將此程序應用於在緊湊緲子線圈的普遍粒子辨識。
The Large Hadron Collider (LHC) is expected to go into the High luminosity-L- HC operational phase, in which the calorimeter would have to cope with a ten-fold lu- minosity increase with respect to the original design. The new end-cap calorimeter High-Granularity Calorimeter (HGCAL) will cons-ist of a silicon-based ECAL (CE-E) at the front and a HCAL(CE-H) at the back. In 2- 018, a prototype of such a detector was tested in the CERN H2 beam line at SPS. To improve the particle identification performance, we want to separate electrons from pions that mostly shower inside the ECal instead of the HCal. The TMVA packa-ge provides an automatic and easy-to-use solution for exploiting the detailed HGCAL shower shape development information for particle-id. In this thesis we perform a detailed MVA analysis training simulations generated by the Geant4 package, to show the capability of HGCAL to separate EM showers of different energies ranging from 20 to 300 GeV. We validate this performance with dat- a for the 2018 test beam with the goal to apply this procedure for general parti-cle-id at CMS.