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https://www.um.edu.mt/library/oar/handle/123456789/96688| Title: | Beam measurements and machine learning at the CERN Large Hadron Collider |
| Authors: | Arpaia, Pasquale Azzopardi, Gabriella Blanc, Frederic Buffat, Xavier Coyle, Loic Fol, Elena Giordano, Francesco Giovannozzi, Massimo Pieloni, Tatiana Prevete, Roberto Redaelli, Stefano Salvachua, Belen Salvant, Benoit Schenk, Michael Solfaroli Camillocci, Matteo Tomas, Rogelio Valentino, Gianluca Van der Veken, Frederik Wenninger, Jorg |
| Keywords: | Machine learning Deep learning (Machine learning) Large Hadron Collider (France and Switzerland) Colliders (Nuclear physics) Particle beams -- Instruments |
| Issue Date: | 2021-11 |
| Publisher: | IEEE |
| Citation: | Arpaia, P., Azzopardi, G., Blanc, F., Buffat, X., Coyle, L., Fol, E., ... & Wenninger, J. (2021). Beam measurements and machine learning at the CERN Large Hadron Collider. IEEE Instrumentation & Measurement Magazine, 24(9), 47-58. |
| 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. |
| URI: | https://www.um.edu.mt/library/oar/handle/123456789/96688 |
| Appears in Collections: | Scholarly Works - FacICTCCE |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Beam measurements and machine learning at the CERN Large Hadron Collider.pdf Restricted Access | 1.26 MB | Adobe PDF | View/Open Request a copy |
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