Anomaly detection from mass unspecific jet tagging
Metadatos
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Springer Science and Business Media Deutschland GmbH
Fecha
2022-02-11Referencia bibliográfica
Aguilar-Saavedra, J.A. Anomaly detection from mass unspecific jet tagging. Eur. Phys. J. C 82, 130 (2022). [https://doi.org/10.1140/epjc/s10052-022-10058-w]
Patrocinador
Ministerio de Ciencia e Innovación PID2019-110058GB-C21; Fundació Catalana de Trasplantament CERN/FIS-PAR/0004/2019Resumen
We introduce a novel anomaly search method
based on (i) jet tagging to select interesting events, which are
less likely to be produced by background processes; (ii) comparison of the untagged and tagged samples to single out features (such as bumps produced by the decay of new particles)
in the latter. We demonstrate the usefulness of this method
by applying it to a final state with two massive boosted jets:
for the new physics benchmarks considered, the signal significance increases an order of magnitude, up to a factor of
40. We compare to other anomaly detection methods in the
literature and discuss possible generalisations.