Artificial Neural Networks for the shower reconstruction of gamma-showers in the energy range [20-300] GeV

Authors
Dumora, D Maneva, GM Procureur, J Smith, DA Temnikov, PP
Citation
D. Dumora et al., Artificial Neural Networks for the shower reconstruction of gamma-showers in the energy range [20-300] GeV, NUCL PH B-P, 97, 2001, pp. 255-258
Citations number
8
Categorie Soggetti
Physics
Journal title
NUCLEAR PHYSICS B-PROCEEDINGS SUPPLEMENTS
ISSN journal
09205632 → ACNP
Volume
97
Year of publication
2001
Pages
255 - 258
Database
ISI
SICI code
0920-5632(200104)97:<255:ANNFTS>2.0.ZU;2-S
Abstract
A first approach to the shower reconstruction from the amplitudes of the Ce renkov photons is made using Artificial Neural Networks, (ANN). We show tha t ANN method gives good results for the photon-proton discrimination, the p rimary energy determination and encouraging perspectives for the determinat ion of the location of the shower core.