000002686 001__ 2686
000002686 005__ 20220403125241.0
000002686 037__ $$aBELLE2-PUB-TE-2021-002
000002686 041__ $$aeng
000002686 100__ $$aFernando Abudinen
000002686 245__ $$aB-flavor tagging at Belle II
000002686 260__ $$a$$c2021-09-14
000002686 300__ $$a42
000002686 520__ $$aWe report on new flavor-tagging algorithms developed to determine the quark-flavor content of bottom (B) mesons at Belle II. The algorithms provide essential inputs for measurements of quark-flavor mixing and charge-parity violation.  We validate and evaluate the performance of the algorithms using hadronic B decays with flavor-specific final states reconstructed in a data set corresponding to an integrated luminosity of 62.8 fb$^{-1}$, collected at the Y(4S) resonance with the Belle II detector at the SuperKEKB collider. We measure the total effective tagging efficiency to be $\varepsilon_{\rm eff} = (30.0 \pm 1.2(stat) \pm 0.4(syst))\%$ for a category-based algorithm and $\varepsilon_{\rm eff} = (28.8 \pm 1.2(stat) \pm 0.4(syst))\%$ for a deep-learning-based algorithm.
000002686 6531_ $$aFlavor tagging,
000002686 6531_ $$aBzero-AntiBzero mixing,
000002686 6531_ $$aCP violation,
000002686 6531_ $$aCKM angles,
000002686 6531_ $$aMultivariate analysis,
000002686 6531_ $$aMachine learning,
000002686 6531_ $$aDeep learning
000002686 700__ $$aColm Murphy
000002686 700__ $$aTakeo Higuchi
000002686 8560_ $$ffernando.abudinen@cern.ch
000002686 8564_ $$uhttps://docs.belle2.org/record/2686/files/BELLE2-PUB-TE-2021-002.pdf