Combining Resonant and Tail-based Anomaly Detection

2023/09/22 by Gerrit Bickendorf, Manuel Drees, Gregor Kasieczka +2 · 1 voice · 1 citation
Physics and Astronomy · #hep-ph #hep-ex

paper · pdf · doi:10.1103/physrevd.109.096031

arxiv published 2023/09/22 · arxiv updated 2024/05/28

Abstract

In many well-motivated models of the electroweak scale, cascade decays of new particles can result in highly boosted hadronic resonances (e.g. Z/W/h). This can make these models rich and promising targets for recently developed resonant anomaly detection methods powered by modern machine learning. We demonstrate this using the state-of-the-art CATHODE method applied to supersymmetry scenarios with gluino pair production. We show that CATHODE, despite being model-agnostic, is nevertheless competitive with dedicated cut-based searches, while simultaneously covering a much wider region of parameter space. The gluino events also populate the tails of the missing energy and H_T distributions, making this a novel combination of resonant and tail-based anomaly detection.

Cited by

• Model-Agnostic Signal Discovery with Machine Learning: Bridging the Gap Between Theory and Practice

Discussions

• What's better than one new paper on #anomaly detection to start the week?  Two new papers on anomaly detection of course!  Out now: arxiv.org/abs/2309.12918 & arxiv.org/abs/2309.13111 [bsky, 0 points, 0 comments]

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