Anomaly detection from mass unspecific jet tagging Aguilar Saavedra, Juan Antonio I thank F.R. Joaquim and J. Seabra for previous collaboration in the MUST development, and J.H. Collins and D. Shih for advice in the generation of Monte Carlo events of Ref. []. This work has been supported by MICINN project PID2019-110058GB-C21 and by FCT project CERN/FIS-PAR/0004/2019. 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. 2022-03-07T09:13:20Z 2022-03-07T09:13:20Z 2022-02-11 journal article 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] http://hdl.handle.net/10481/73174 10.1140/epjc/s10052-022-10058-w eng http://creativecommons.org/licenses/by/3.0/es/ open access Atribución 3.0 España Springer Science and Business Media Deutschland GmbH