Neural network based electron identification in the ZEUS calorimeter
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 ponciple component analysis the improvement in the performance is traced back to the number of variables used in the neural network approach.
- Publication:
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Nuclear Instruments and Methods in Physics Research A
- Pub Date:
- February 1995
- DOI:
- 10.1016/0168-9002(95)00612-5
- arXiv:
- arXiv:hep-ex/9505004
- Bibcode:
- 1995NIMPA.365..508A
- Keywords:
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- High Energy Physics - Experiment
- E-Print:
- 20 pages, latex, 16 figures appended as uuencoded file