Speakers
Description
Jet flavour identification algorithms are of paramount importance to maximise the physics output in e+e- collisions at the Future Circular Collider (FCC-ee). Among the extensive FCC-ee physics program, flavour tagging is crucial for the Higgs, Electroweak and top-quark programs, given the dominance of hadronic decays of the heaviest particles of the Standard Model (SM). A highly efficient discrimination of b, c, strange, and gluon jets allows to access novel decay channels that are not accessible at the LHC, increasing significantly the physics potential of the SM precision measurements and searches for new physics at FCC-ee. In this contribution, we will present the latest results on jet flavour tagging, based on machine learning techniques, applied to concrete FCC-ee physics studies. Beyond an excellent performance on b- and c-quark tagging, the future taggers will be able to discriminate strange quark jets, opening the way to the measurement of the strange-quark Yukawa coupling, as well as observing very rare flavour-changing neutral current processes, such as Z->bs. Potential strategies for calibrating the jet taggers will be also discussed.
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