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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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Detalles Bibliográficos
Autor principal: Saxton, Torrey Adam
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:http://cds.cern.ch/record/2634314
Descripción
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