| Article | |
| Title | Real time crystal collimation monitoring at the CERN Large Hadron Collider |
| Author(s) | Ricci, Gianmarco (Rome U. ; CERN) ; Mostacci, Andrea (Rome U. ; CERN) ; Mirarchi, Daniele (CERN) ; Matheson, Eloise (CERN) ; D'Andrea, Marco (CERN ; INFN, Legnaro) ; Di Castro, Mario (CERN) ; Cai, Rongrong (CERN) ; Redaelli, Stefano (CERN) |
| Publication | 2024 |
| Number of pages | 4 |
| In: | JACoW IPAC 2024 (2024) TUPS42 |
| In: | 15th International Particle Accelerator Conference (IPAC 2024), Nashville, TN, United States, 19 - 24 May 2024, pp.TUPS42 |
| DOI | 10.18429/JACoW-IPAC2024-TUPS42 |
| Subject category | Accelerators and Storage Rings |
| Accelerator/Facility, Experiment | CERN LHC |
| Abstract | At the CERN Large Hadron Collider (LHC), bent crystals play a crucial role in efficiently redirecting ion-beam halo particles toward secondary collimators used for absorption. This innovative method leverages millimeter-sized crystals to achieve deflection equivalent to a magnetic field of hundreds of Tesla at LHC’s highest energies. This advancement significantly enhances the machine’s cleaning performance. Nevertheless, ensuring the ongoing effectiveness of this process requires maintaining optimal angular alignment of the crystals against the circulating beam. This study aims to improve the monitoring of crystal collimation to provide a tool that detects deviations from the optimal channeling orientation during beam operation. These deviations may arise not only from crystal movements but also from fluctuations in beam dynamics. The ability to adapt and compensate for these changes is crucial for ensuring consistent and stable performance of crystal collimation during LHC operations. To achieve this, a feed-forward neural network (FNN) was trained using data simulated with the SixTrack-FLUKA Coupling reproducing the pattern of losses obtained during the 2023 ion run. The findings reveal that while the network can learn from the dataset, it lacks the ability to supervise the crystal devices effectively. Thus, it underscores the challenge of accurately classifying when the crystal is optimally aligned with the circulating beam during operation. |
| Copyright/License | CC-BY-4.0 |
Corresponding record in: Inspire
Record created 2024-10-09, last modified 2024-10-10
