Electron/Pion Identification with ALICE TRD Prototypes using a Neural Network Algorithm

2005/06/28 by ALICE TRD Collaboration
Physics and Astronomy · #FOS: Physical sciences #High-Energy Particle Collisions Research #Instrumentation and Detectors (physics.ins-det) #Particle Detector Development and Performance #Particle physics theoretical and experimental studies #physics.ins-det

paper · pdf · doi:10.48550/arxiv.physics/0506202

13 pages, 9 Figures

arxiv created 2005/06/28 · openalex publication_date 2005/06/28 · arxiv updated 2012/08/27 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28

Abstract

We study the electron/pion identification performance of the ALICE Transition Radiation Detector (TRD) prototypes using a neural network (NN) algorithm. Measurements were carried out for particle momenta from 2 to 6 GeV/c. An improvement in pion rejection by about a factor of 3 is obtained with NN compared to standard likelihood methods.

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