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Bogolyubsky, M.Yu.; Kharlov, Yu.V.; Sadovsky, S.A., E-mail: bogolyubsky@mx.ihep.su2003
AbstractAbstract
[en] A neural network method is developed to separate direct photons from neutral pions in the PHOS spectrometer of the ALICE experiment at the LHC collider. The neural net has been taught to distinguish different classes of events by analyzing the energy profile tensor of a cluster in its eigenvector coordinate system. The Monte-Carlo simulation shows that this method diminishes the probability of π0-meson misidentification as a photon by an order compared with the direct photon detection efficiency in the energy range up to 120 GeV
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8. international workshop on advanced computing and analysis techniques in physics research; Moscow (Russian Federation); 24-28 Jun 2002; S0168900203005552; Copyright (c) 2003 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: India
Record Type
Journal Article
Literature Type
Conference
Journal
Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment; ISSN 0168-9002;
; CODEN NIMAER; v. 502(2-3); p. 719-722

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