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Beam Measurements and Machine Learning at the CERN Large Hadron Collider

Authors :
Stefano Redaelli
Benoit Salvant
F. Blanc
Roberto Prevete
Matteo Solfaroli Camillocci
Jorg Wenninger
F. Giordano
Massimo Giovannozzi
Tatiana Pieloni
Elena Fol
Loic Coyle
Gabriella Azzopardi
Xavier Buffat
Pasquale Arpaia
Rogelio Tomás
Gianluca Valentino
Michael Schenk
Frederik Van Der Veken
Belen Salvachua
Publication Year :
2021

Abstract

Particle accelerators are among the most complex instruments conceived by physicists for the exploration of the fundamental laws of nature. Of relevance for particle physics are the high-energy colliders, such as the CERN Large Hadron Collider (LHC), which hosts particle physics experiments that are probing the Standard Model predictions and looking for signs of physics beyond the standard model. This paper presents a review of the recent Machine Learning activities carried out on beam measurements performed at the CERN Large Hadron Collider. This paper has been accepted for publication in IEEE Instrumentation and Measurement Magazine and in the published version no abstract is provided.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....024bf8116196a46fab9d5ecaacadd7a1