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Computer Vision and Application to the Classification of the Hadronic Decay Modes of the Tau Lepton with the ATLAS detector
In this report, we examine the use of deep learning neural networks for the classification of hadronic decays. Through a series of two-dimensional, convolutional neural network, we use Monte-Carlo simulated tau lepton decays to train a classification algorithm. We classify the decays into five mai...
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Lenguaje: | eng |
Publicado: |
2018
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2634314 |
Sumario: | In this report, we examine the use of deep learning neural networks for the classification of hadronic decays. Through a series of two-dimensional, convolutional neural network, we use Monte-Carlo simulated tau lepton decays to train a classification algorithm. We classify the decays into five main modes: letting ``p'' stand for a charged pion, and ``n" stand for a neutral pion, the five modes are as follows: 1p0n, 1p1n, 1pXn, 3p0n, and 3pXn |
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