Calorimetry with deep learning: particle simulation and reconstruction for collider physics

Calorimetry with deep learning: particle simulation and reconstruction for collider physics

Abstract Using detailed simulations of calorimeter showers as training data, we investigate the use of deep learning algorithms for the simulation and reconstruction of single isolated particles produced in high-energy physics collisions. We train neural networks on single-particle shower data at th...

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Bibliographic Details
Main Authors: Dawit Belayneh, Federico Carminati, Amir Farbin, Benjamin Hooberman, Gulrukh Khattak, Miaoyuan Liu, Junze Liu, Dominick Olivito, Vitória Barin Pacela, Maurizio Pierini, Alexander Schwing, Maria Spiropulu, Sofia Vallecorsa, Jean-Roch Vlimant, Wei Wei, Matt Zhang
Format: Article
Language:English
Published: SpringerOpen 2020-07-01
Series:European Physical Journal C: Particles and Fields
Online Access:http://link.springer.com/article/10.1140/epjc/s10052-020-8251-9

Internet

http://link.springer.com/article/10.1140/epjc/s10052-020-8251-9

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