Electron/Pion Identification with ALICE TRD Prototypes using a Neural Network Algorithm
Instrumentation and Detectors
2012-08-27 v1
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.
Cite
@article{arxiv.physics/0506202,
title = {Electron/Pion Identification with ALICE TRD Prototypes using a Neural Network Algorithm},
author = {ALICE TRD Collaboration},
journal= {arXiv preprint arXiv:physics/0506202},
year = {2012}
}
Comments
13 pages, 9 Figures