Beschreibung:
<jats:p>Belle II is a particle-physics experiment at the intensity frontier focused on probing non Standard Model physics through precision measurements of quark-flavor and <jats:bold><jats:italic>τ</jats:italic></jats:bold>-lepton dynamics. Determining the flavor of neutral <jats:bold><jats:italic>B</jats:italic></jats:bold> mesons, i.e. their quark composition, is a crucial task which is addressed using flavor tagging algorithms. Due to the novel high-luminosity conditions and the increased beam backgrounds at Belle <jats:bold>II</jats:bold>, an improved flavor tagging algorithm had to be developed to ensure the success of the Belle II physics program.</jats:p>
<jats:p>The new Belle <jats:bold>II</jats:bold> flavor tagger exploits the flavor-specific signatures of <jats:bold><jats:italic>B <jats:sup>0</jats:sup></jats:italic></jats:bold> decays employing boosted decision trees and neural networks. It identifies <jats:bold><jats:italic>B <jats:sup>0</jats:sup></jats:italic></jats:bold>-decay products providing flavor-specific signatures and combines the information from all possible signatures into a final output. The algorithm has been validated by comparing its performance on simulated events with its performance on collision events collected by the predecessor experiment Belle.</jats:p>
<jats:p>To explore the advantages of state-of-the-art deep-learning techniques, the Belle II collaboration developed a deep-learning-based flavor tagger. This algorithm tags the flavor of <jats:bold><jats:italic>B <jats:sup>0</jats:sup></jats:italic></jats:bold> mesons without identifying flavor specific signatures using a deep-learning neural network. The validation on Belle data of this algorithm is currently ongoing.</jats:p>