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B-flavor tagging at Belle II

F. Abudin??n, Н. Акопов, A. Aloisio, V. Babu, Sw. Banerjee, M. Bauer, J. V. Bennett, F. U. Bernlochner, M. Bessner, S. Bettarini, T. Bilka, S. Bilokin, D. Biswas, D. Bodrov, J. Borah, M. Bra??ko, P. Branchini, A. Budano, M. Campajola, G. Casarosa, C. Cecchi, R. Cheaib, V. Chekelian, C. Chen, Y. Q. Chen, H. -E. Cho, S. Cunliffe, G. De Nardo, G. De Pietro, R. de Sangro, S. Dey, A. Di Canto, F. Di Capua, T. V. Dong, G. Dujany, P. Ecker, M. Eliachevitch, T. Ferber, F. Forti, E. Ganiev, A. Gaz, Michael H. Gelb, J. Gemmler, R. Godang, P. Goldenzweig, E. Graziani, K. Hara, A. D. Hershenhorn, T. Higuchi, E. Hill, M. Hohmann, T. Humair, G. Inguglia, H. Junkerkalefeld, Robert Karl, Yuji Katō, Thomas M. Keck, C. Kiesling, C. -H. Kim, S. Kohani, I. Komarov, T. M. G. Kraetzschmar, P. Kri??an, J. F. Krohn, T. Kuhr, J. Kumar, K. Kumara, S. Kurz, S. Lacaprara, C. La Licata, M. Laurenza, K. Lautenbach, S. C. Lee, K. Lieret, L. Li Gioi, Q. Y. Liu, S. Longo, M. Maggiora, E. Manoni, C. Mariñas, A. Martini, F. Meier, M. Merola, F. Metzner, M. Milesi, K. Miyabayashi, G. B. Mohanty, F. Mueller, C. Murphy, E. R. Oxford, S. -H. Park, A. Passeri, F. Pham, L. E. Piilonen, S. Pokharel, M. T. Prim, C. Pulvermacher, P. Rados, M. Ritter, A. Rostomyan

2022CINECA IRIS Institutial research information system (University of Pisa)30 citationsDOIOpen Access PDF

Abstract

We 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 gamma(4S) resonance with the Belle II detector at the SuperKEKB collider. We measure the total effective tagging efficiency to be epsilon(eff) = (30.0 +/- 1.2(stat) +/- 0.4(syst))% for a category-based algorithm and epsilon(eff) = (28.8 +/- 1.2(stat) +/- 0.4(syst))% for a deep-learning-based algorithm.

Topics & Concepts

AlgorithmPhysicsDatabaseComputer scienceParticle physics theoretical and experimental studiesParticle Detector Development and PerformanceHigh-Energy Particle Collisions Research
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