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Simulating the LHCb hadron calorimeter with generative adversarial networks
Generative adversarial networks are known as a tool for fast simulation of data. Our aim is to research and develop a physical application of these tools by simulating LHCb hadron calorimeter (HCAL) in order to speed up the Monte Carlo datasets production.
Autores principales: | , , |
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Lenguaje: | eng |
Publicado: |
2019
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1393/ncc/i2019-19197-3 http://cds.cern.ch/record/2834891 |