Optimal transport event representation for anomaly detection
Abstract
We introduce optimal transport (OT) as a physics-based intermediate event representation for weakly supervised anomaly detection. With only 0.5% injection of resonant signals in the LHC Olympics benchmark datasets, the OT-augmented feature set achieves nearly twice the significance improvement of the standard high-level observables using an idealized setup, while end-to-end deep learning on low-level four-momenta is less effective in this low-signal regime. The observed gains persist across signal types and classifiers considered in this study, suggesting that structured, physics-informed representations can provide a useful complement to existing approaches for anomaly detection.
Fields of Study & Subjects
Particle physics theoretical and experimental studies
Particle Detector Development and Performance
Anomaly Detection Techniques and Applications
Publication details
- Journal / source
- Physical review. D/Physical review. D.
- Publisher
- American Physical Society (APS)
- Volume
- 114
- Issue
- 1
- Publication date
- 24 June 2026
- Language
- EN