Titel: Search for B → K𝑣𝑣 decays with a machine learning method at the Belle II experiment
Sprache: Englisch
Autor*in: Praz, Cyrille
Schlagwörter: Particle Physics; Belle II experiment; Rare decay; Electroweak penguin; Machine learning
GND-Schlagwörter: PhysikGND
ElementarteilchenphysikGND
Belle-II-DetektorGND
B-MesonGND
Maschinelles LernenGND
Erscheinungsdatum: 2022
Tag der mündlichen Prüfung: 2022-08-23
Zusammenfassung: 
This thesis documents a search for the rare decay of a B meson into a K meson and a pair of neutrinos at the Belle II experiment, which is located along the SuperKEKB energy-asymmetric electron-positron collider. This decay has never been observed, its branching fraction is predicted with accuracy in the standard model of particle physics, and is a good probe of physics beyond the standard model. A novel method to search for this decay, the inclusive tagging, is developed on a data sample corresponding to an integrated luminosity of 189 fb−1 collected at the Υ(4S) resonance, and a complementary sample of 18 fb−1 collected 60 MeV below the resonance. For this integrated luminosity, the expected upper limits on the branching fraction of B+→K+νν̄ and B0→KS0νν̄ are determined from simulation to be 1.0×10−5 and 1.8×10−5 at the 90% confidence level, respectively. When the method is applied to data samples of 63 fb−1 collected at the Υ(4S) resonance and 9 fb−1 collected 60 MeV below the resonance, no significant signal is observed, and an upper limit on the branching fraction of B+→K+νν̄ is determined to be 4.1×10−5 at the 90% confidence level.
URL: https://ediss.sub.uni-hamburg.de/handle/ediss/9793
URN: urn:nbn:de:gbv:18-ediss-102932
Dokumenttyp: Dissertation
Betreuer*in: Glazov, Alexander
Tackmann, Kerstin
Enthalten in den Sammlungen:Elektronische Dissertationen und Habilitationen

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