Detector monitoring with artificial neural networks at the CMS experiment at the CERN Large Hadron Collider

Reliable data quality monitoring is a key asset in delivering collision data suitable for physics analysis in any modern large-scale high energy physics experiment. This paper focuses on the use of artificial neural networks for supervised and semi-supervised problems related to the identification o...

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Detalles Bibliográficos
Autores principales: Pol, Adrian Alan, Cerminara, Gianluca, Germain, Cecile, Pierini, Maurizio, Seth, Agrima
Lenguaje:eng
Publicado: 2018
Materias:
Data Analysis and Statistics
Computing and Computers
Detectors and Experimental Techniques
Other
physics.data-an
cs.LG
physics.ins-det
stat.ML
Acceso en línea:https://dx.doi.org/10.1007/s41781-018-0020-1
http://cds.cern.ch/record/2683825

Internet

https://dx.doi.org/10.1007/s41781-018-0020-1
http://cds.cern.ch/record/2683825

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