Skip to content
DraconiticResearch
Search Sources API
194,220 studies31 sourcesUpdated 54 min ago
PreprintarXiv licencearXiv

Anomaly Detection in Bunch Oscillations for Early Warning of Sudden Beam Loss at SuperKEKB

Abstract

Sudden beam loss (SBL) events at the SuperKEKB collider result in the loss of a large fraction of the stored beam within just a few revolutions, on a timescale comparable to or shorter than the 20-30 μs latency of the existing abort system. Such events have damaged collimators and threaten Belle II subdetectors. Bunch Oscillation Recorders (BORs) capture transverse bunch positions at each revolution, which often show sizable oscillations that precede significant beam current loss. We test whether these precursors can be detected earlier than a charge-based reference that mimics the existing abort sensors. We apply several oscillation-based anomaly detection algorithms to 208 SBL events recorded in the low-energy ring during the 2024 run period, ranging from simple rolling statistics to machine learning models trained to forecast bunch oscillation. On 173 events not used for training or calibration, the best-balanced model (DeepLSTM) triggers before the charge-based reference in 86-90% of events across five training seeds, with a mean lead time of 25-30 μs. The only trigger classified as a false alarm fires on an oscillation that begins about 60 turns before the abort and persists until the beam is lost, making it more likely an early precursor than a spurious trigger. These results establish bunch oscillations as a viable early abort trigger and motivate a shadow-mode deployment to measure the false-alarm rate in continuous operation.

Related

  1. Warning of infrastructure deformation anomaly through probabilistic analysis of InSAR observations
    Hao Kuai, Na Hao, Pantelis Karamitopoulos +2
    arXivPreprintCC BY 4.0Full textStatisticsComputational physicsarXiv
  2. Anomaly detection for multijet scenarios
    Gregor Kasieczka, Sung Hak Lim, Louis Moureaux +3
    arXivPreprintCC BY 4.0Full textComputational physicsHigh-energy & particle physicsarXiv
  3. Domain Adaptation against Background Sculpting in Anomaly Detection at the LHC
    Vincent Benne, Marie Hein, Michael Krämer +3
    arXivPreprintCC BY 4.0Full textHigh-energy & particle physicsarXiv
  4. Model-independent searches and anomaly detection at the CMS experiment
    Tamas Almos Vami, for the CMS Collaboration
    arXivPreprintCC BY 4.0Full textHigh-energy & particle physicsarXiv
  5. Predictive Maintenance at the Edge: An Embedded Anomaly Detection Pipeline Trained with Quantum Optimization
    Filipe Chagas Ferraz
    arXivPreprintarXiv licenceFull textQuantum physics & quantum informationarXiv
BibTeX
@misc{haigh2026anomaly,
  title = {{Anomaly Detection in Bunch Oscillations for Early Warning of Sudden Beam Loss at SuperKEKB}},
  author = {H. Haigh and P. Horak and G. Inguglia and C. Krause and G. Mitsuka and H. Nakayama and R. Nomaru and M. Tobiyama},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.17241},
  eprint = {2610.17241},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.17241},
}
RIS
TY  - UNPB
TI  - Anomaly Detection in Bunch Oscillations for Early Warning of Sudden Beam Loss at SuperKEKB
AU  - H. Haigh
AU  - P. Horak
AU  - G. Inguglia
AU  - C. Krause
AU  - G. Mitsuka
AU  - H. Nakayama
AU  - R. Nomaru
AU  - M. Tobiyama
PY  - 2026
DA  - 2026/10/12
PB  - arXiv
DO  - 10.48550/arxiv.2610.17241
UR  - https://arxiv.org/abs/2610.17241
AB  - Sudden beam loss (SBL) events at the SuperKEKB collider result in the loss of a large fraction of the stored beam within just a few revolutions, on a timescale comparable to or shorter than the 20-30 μs latency of the existing abort system. Such events have damaged collimators and threaten Belle II subdetectors. Bunch Oscillation Recorders (BORs) capture transverse bunch positions at each revolution, which often show sizable oscillations that precede significant beam current loss. We test whether these precursors can be detected earlier than a charge-based reference that mimics the existing abort sensors. We apply several oscillation-based anomaly detection algorithms to 208 SBL events recorded in the low-energy ring during the 2024 run period, ranging from simple rolling statistics to machine learning models trained to forecast bunch oscillation. On 173 events not used for training or calibration, the best-balanced model (DeepLSTM) triggers before the charge-based reference in 86-90% of events across five training seeds, with a mean lead time of 25-30 μs. The only trigger classified as a false alarm fires on an oscillation that begins about 60 turns before the abort and persists until the beam is lost, making it more likely an early precursor than a spurious trigger. These results establish bunch oscillations as a viable early abort trigger and motivate a shadow-mode deployment to measure the false-alarm rate in continuous operation.
ER  -