paper

Neural Network based Electron Identification in the ZEUS Calorimeter

arXiv:hep-ex/9505004 · doi:10.1016/0168-9002(95)00612-5

Abstract

We present an electron identification algorithm based on a neural network approach applied to the ZEUS uranium calorimeter. The study is motivated by the need to select deep inelastic, neutral current, electron proton interactions characterized by the presence of a scattered electron in the final state. The performance of the algorithm is compared to an electron identification method based on a classical probabilistic approach. By means of a principle component analysis the improvement in the performance is traced back to the number of variables used in the neural network approach.

20 pages, latex, 16 figures appended as uuencoded file

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