Skip to content
DraconiticResearch
Search Sources API
181,716 studies31 sourcesUpdated 17 min ago
PreprintCC BY 4.0arXiv

Anomaly detection for multijet scenarios

  • Gregor Kasieczka
  • Sung Hak Lim
  • Louis Moureaux
  • Tore von Schwartz
  • David Shih
  • Chitrakshee Yede
Open at sourcePDFDOICite

Abstract

Signals of physics beyond the Standard Model continue to resist discovery at the LHC. Recent years have seen the proliferation of new anomaly detection techniques, promising discovery with significantly fewer model assumptions than traditional approaches. Strategies based on weak supervision have been especially successful, but so far were largely limited in scope by their reliance on a resonance manifesting a decay into a pair of jets. In this work, we demonstrate that a well-established idea from jet substructure physics - recursive soft drop - in combination with the CATHODE technique for anomaly detection can be used to simultaneously perform anomaly detection for signals with an arbitrary number of jets in the final state, greatly increasing the scope of such searches.

Related

  1. 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
  2. Resonance-aware electroweak Sudakov reweighting for multijet-merged predictions
    Lenart Jerala, Rikkert Frederix, Miha Muškinja +3
    arXivPreprintarXiv licenceFull textHigh-energy & particle physicsarXiv
  3. 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
  4. Predictive Maintenance at the Edge: An Embedded Anomaly Detection Pipeline Trained with Quantum Optimization
    Filipe Chagas Ferraz
    arXivPreprintarXiv licenceFull textQuantum physics & quantum informationarXiv
  5. Quantum anomaly detection in real scarce data
    Emanuele Casciaro, Fabio Mascherpa, Alfonso Amendola +1
    arXivPreprintCC BY 4.0Full textQuantum physics & quantum informationarXiv

Cite

BibTeXRIS
BibTeX
@misc{kasieczka2026anomaly,
  title = {{Anomaly detection for multijet scenarios}},
  author = {Gregor Kasieczka and Sung Hak Lim and Louis Moureaux and Tore von Schwartz and David Shih and Chitrakshee Yede},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2609.00132},
  eprint = {2609.00132},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.00132},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Anomaly detection for multijet scenarios
AU  - Gregor Kasieczka
AU  - Sung Hak Lim
AU  - Louis Moureaux
AU  - Tore von Schwartz
AU  - David Shih
AU  - Chitrakshee Yede
PY  - 2026
DA  - 2026/10/14
PB  - arXiv
DO  - 10.48550/arxiv.2609.00132
UR  - https://arxiv.org/abs/2609.00132
AB  - Signals of physics beyond the Standard Model continue to resist discovery at the LHC. Recent years have seen the proliferation of new anomaly detection techniques, promising discovery with significantly fewer model assumptions than traditional approaches. Strategies based on weak supervision have been especially successful, but so far were largely limited in scope by their reliance on a resonance manifesting a decay into a pair of jets. In this work, we demonstrate that a well-established idea from jet substructure physics - recursive soft drop - in combination with the CATHODE technique for anomaly detection can be used to simultaneously perform anomaly detection for signals with an arbitrary number of jets in the final state, greatly increasing the scope of such searches.
ER  -