New approaches using machine learning for fast shower simulation in ATLAS

Modeling the detector response to collisions is one of the most CPU expensive and time-consuming aspects in the LHC. The current ATLAS baseline, GEANT4, is highly CPU intensive. With the large collision dataset expected in the future, CPU usage becomes critical. During the LHC Run-1, a fast calorime...

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Detalles Bibliográficos
Autores principales: Hasib, Ahmed, Schaarschmidt, Jana, Gadatsch, Stefan, Golling, Tobias, Salamani, Dalila, Ghosh, Aishik, Rousseau, David, Cranmer, Kyle, Stewart, Graeme, Louppe, Gilles Claude
Lenguaje:eng
Publicado: 2018
Materias:
Particle Physics - Experiment
Acceso en línea:http://cds.cern.ch/record/2628624

Internet

http://cds.cern.ch/record/2628624

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