Machine Learning approach for the search of heavy diboson resonances in semi-leptonic final state at √s = 13 TeV with the ATLAS detector

Auricchio, S. (2022) Machine Learning approach for the search of heavy diboson resonances in semi-leptonic final state at √s = 13 TeV with the ATLAS detector. Il nuovo cimento C, 45 (5). pp. 1-4. ISSN 1826-9885

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Abstract

A Recurrent Neural Network-based approach has been adopted for the classification of the production mechanisms in the search of heavy resonances decaying in two bosons. The search is performed using proton-proton collision data recorded with the ATLAS detector from 2015 to 2018. The investigated final state is semi-leptonic, where one boson decays in two leptons and the other decays hadronically. No excesses have been found in data with respect to the background-only hypothesis. Upper bounds on the production cross sections of heavy scalar, vector or tensor resonances are derived in the mass range 300–5000 GeV.

Item Type:	Article
Subjects:	500 Scienze naturali e Matematica > 530 Fisica
Depositing User:	Marina Spanti
Date Deposited:	31 Jan 2023 13:54
Last Modified:	31 Jan 2023 13:54
URI:	http://eprints.bice.rm.cnr.it/id/eprint/22149

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