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Weakly supervised anomaly detection with event-level variables

Liam Brennan1,*, Tamas Almos Vami1,†, Oz Amram2,‡, Sanjana Sekhar3, Yuta Takahashi4, Louis Moureaux5, Manuel Sommerhalder5, Petar Maksimovic3, Tianji Cai6,7 et al.

Nathaniel Craig1,8

  • *Contact author: Liam.Robert.Brennan@cern.ch
  • †Contact author: Tamas.Almos.Vami@cern.ch
  • ‡Contact author: Oz.Amram@cern.ch
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Phys. Rev. D 112, 055040 – Published 26 September, 2025

DOI: https://doi.org/10.1103/rk29-518p

Abstract

We introduce a new topology for weakly supervised anomaly detection searches, diobject plus X. In this topology, one looks for a resonance decaying to two standard model particles produced in association with other anomalous event activity (X). This additional activity is used for classification. We demonstrate how anomaly detection techniques which have been developed for dijet searches focusing on jet substructure anomalies can be applied to event-level anomaly detection in this topology. To robustly capture event-level features of multiparticle kinematics, we employ new physically motivated variables derived from the geometric structure of a collision’s phase space manifold. As a proof of concept, we explore the application of this approach to several benchmark signals in the di-τ and di-μ plus X final states. We demonstrate that our anomaly detection approach can reach discovery-level significances for signals that would be missed in a conventional bump-hunt approach.

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Phys. Rev. D 112, 055040– Published 26 September, 2025
  • Received 17 April 2025
  • Accepted 25 August 2025
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