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dc.contributor.authorAguilar Saavedra, Juan Antonio 
dc.date.accessioned2022-03-07T09:13:20Z
dc.date.available2022-03-07T09:13:20Z
dc.date.issued2022-02-11
dc.identifier.citationAguilar-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]es_ES
dc.identifier.urihttp://hdl.handle.net/10481/73174
dc.descriptionI 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.es_ES
dc.description.abstractWe 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.es_ES
dc.description.sponsorshipMinisterio de Ciencia e Innovación PID2019-110058GB-C21es_ES
dc.description.sponsorshipFundació Catalana de Trasplantament CERN/FIS-PAR/0004/2019es_ES
dc.language.isoenges_ES
dc.publisherSpringer Science and Business Media Deutschland GmbHes_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.titleAnomaly detection from mass unspecific jet tagginges_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1140/epjc/s10052-022-10058-w
dc.type.hasVersionVoRes_ES


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