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Optimisation of the ATLAS $b$-tagging algorithms for the 2017-2018 LHC data-taking
This contribution describes the performance of the ATLAS $b$-tagging algorithms for the 2017-18 datataking at the LHC. Novel taggers based on soft muons from semi-leptonic decays of the $b$/$c$-hadrons and a RecurrentNeural Network based on track parameters have been integrated into the final high-l...
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| Lenguaje: | eng |
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2017
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| Acceso en línea: | https://dx.doi.org/10.22323/1.314.0733 http://cds.cern.ch/record/2286993 |