Title of article
Applications of neural networks to shower analysis in a highly segmented LAr calorimeter
Author/Authors
Hِppner، نويسنده , , M and Wegener، نويسنده , , D، نويسنده ,
Pages
3
From page
154
To page
156
Abstract
A new method was developed to evaluate the signals of a calorimeter with neural networks. After training with simulated data, energy reconstruction and particle identification is possible. The method was developed for the liquid argon calorimeter of the H1 experiment at DESY in Hamburg, Germany, but it uses quantities which are available at any segmented calorimeter.
Keywords
Calorimeter , Evolutionary algorithms , Energy reconstruction , NEURAL NETWORKS , Particle identification
Journal title
Astroparticle Physics
Record number
2001227
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