We report on new flavor tagging algorithms developed to determine the quark-flavor content of bottom ( ) 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 decays with flavor-specific final states reconstructed in a data set corresponding to an integrated luminosity of 62.8 fb−1
, collected at the resonance with the Belle II detector at the SuperKEKB collider. We measure the total effective tagging efficiency to be
εeff=(30.0±1.2(stat)±0.4(syst))%
for a category-based algorithm and
εeff=(28.8±1.2(stat)±0.4(syst))%
for a deep-learning-based algorithm
