Improvement in the 3D shower shapes description in the Monte Carlo simulation for a lead-scintillating fiber electromagnetic calorimeter
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Abstract
BackgroundThe lead-scintillating fiber electromagnetic calorimeter (ECAL) of the Alpha Magnetic Spectrometer measures the energy of positrons/electrons and separates them from hadrons. The electromagnetic shower shapes from Monte Carlo (MC) simulation and data show disagreement.
PurposeTuning the MC to make the shower shapes from MC and data agree with each other.
MethodsThe tuning is based on a 3D electromagnetic shower model.
ResultsAfter tuning, the electromagnetic shower shapes are well described by MC up to TeV. As a result, the output of ECAL electron/proton separation estimator, ECAL BDT, shows that MC and data are in good agreement. The proton rejection power of the ECAL BDT trained with MC electron samples is improved by a factor of 5 at \sim \,800\,\hbox GeV compared to the one trained with data.
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Xue-Qiang Wang, Zu-Hao Li, Zhi-Cheng Tang, et al. Improvement in the 3D shower shapes description in the Monte Carlo simulation for a lead-scintillating fiber electromagnetic calorimeter[J]. Radiation Detection Technology and Methods, 2019, 3(3): 34-34. DOI: 10.1007/s41605-019-0113-3
Citation:
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Xue-Qiang Wang, Zu-Hao Li, Zhi-Cheng Tang, et al. Improvement in the 3D shower shapes description in the Monte Carlo simulation for a lead-scintillating fiber electromagnetic calorimeter[J]. Radiation Detection Technology and Methods, 2019, 3(3): 34-34. DOI: 10.1007/s41605-019-0113-3
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Xue-Qiang Wang, Zu-Hao Li, Zhi-Cheng Tang, et al. Improvement in the 3D shower shapes description in the Monte Carlo simulation for a lead-scintillating fiber electromagnetic calorimeter[J]. Radiation Detection Technology and Methods, 2019, 3(3): 34-34. DOI: 10.1007/s41605-019-0113-3
Citation:
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Xue-Qiang Wang, Zu-Hao Li, Zhi-Cheng Tang, et al. Improvement in the 3D shower shapes description in the Monte Carlo simulation for a lead-scintillating fiber electromagnetic calorimeter[J]. Radiation Detection Technology and Methods, 2019, 3(3): 34-34. DOI: 10.1007/s41605-019-0113-3
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