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A neural network for electromagnetic shower energy measurement
Y. Caffari1
OPERA Collaboration(s)
(2006)

This note describes a new method based on a neural network to measure the energy of electromagnetic cascades. After applying a specific algorithm of reconstruction [1], we extract informations from the longitunal and transversal profiles to evaluate the energy of the primary electron. This neural network is tested on Monte Carlo simulations and experimental data (6 GeV, dry scan). Preliminary results are also presented.
1 :  IPNL - Institut de Physique Nucléaire de Lyon
Physique/Physique des Hautes Energies - Expérience
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