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Matches in Ghent University Academic Bibliography for { <https://biblio.ugent.be/publication/01H2MQ6DTF5RAW02QA2JDBA6MH> ?p ?o. }

• 01H2MQ6DTF5RAW02QA2JDBA6MH classification A1.
• 01H2MQ6DTF5RAW02QA2JDBA6MH date "2022".
• 01H2MQ6DTF5RAW02QA2JDBA6MH language "eng".
• 01H2MQ6DTF5RAW02QA2JDBA6MH type journalArticle.
• 01H2MQ6DTF5RAW02QA2JDBA6MH hasPart 01H2MRNQHMS5WVFZ9PEG63D8JD.pdf.
• 01H2MQ6DTF5RAW02QA2JDBA6MH subject "Physics and Astronomy".
• 01H2MQ6DTF5RAW02QA2JDBA6MH doi "10.1088/1748-0221/17/07/P07023".
• 01H2MQ6DTF5RAW02QA2JDBA6MH issn "1748-0221".
• 01H2MQ6DTF5RAW02QA2JDBA6MH issue "7".
• 01H2MQ6DTF5RAW02QA2JDBA6MH volume "17".
• 01H2MQ6DTF5RAW02QA2JDBA6MH abstract "A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (tau(h)) that originate from genuine tau leptons in the CMS detector against tau(h) candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a tau(h) candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine tau(h) to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient tau(h) reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved tau(h) reconstruction method are validated with LHC proton-proton collision data at root s = 13 TeV.".
• 01H2MQ6DTF5RAW02QA2JDBA6MH author 01F433D2-F0EE-11E1-A9DE-61C894A0A6B4.
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• 01H2MQ6DTF5RAW02QA2JDBA6MH author 322F4500-E289-11E6-BC5A-1943AE28A064.
• 01H2MQ6DTF5RAW02QA2JDBA6MH author 481d1d32-4c85-11eb-808e-8ab49d8c46c1.
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• 01H2MQ6DTF5RAW02QA2JDBA6MH author C0D62136-E687-11E2-AD28-C2B310BDE39D.
• 01H2MQ6DTF5RAW02QA2JDBA6MH author C69762EA-02FD-11E4-89C9-5E074B2F559A.
• 01H2MQ6DTF5RAW02QA2JDBA6MH author CCD81336-4F36-11E4-A93C-06A6B5D1D7B1.
• 01H2MQ6DTF5RAW02QA2JDBA6MH author F4E76394-F0ED-11E1-A9DE-61C894A0A6B4.
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