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1.	Machine Learning for New Physics Searches in B → K∗0 µ+µ− Decays / S. Dubey ; T.E. Browder ; S. Kohani ; R. Mandal ; et al [BELLE2-CONF-PROC-2023-035] 22 September 2023 We report the status of a neural network regression model trained to extract new physics (NP) parameters in Monte Carlo (MC) simulation data. [...] Fulltext: PDF; Detailed record - Similar records
2.	Machine Learning for New Physics in B → K ∗µ+µ− Decays / Shawn Dubey ; Alexei Sibidanov ; Thomas E. Browder ; Shahab Kohani ; et al [BELLE2-POSTER-CONF-2023-002] 01 May 2023 / CHEP 2023 We report the status of a neural network regression model trained to extract new physics (NP) parame- ters in Monte Carlo (MC) data. [...] Fulltext: PDF; Detailed record - Similar records
3.	Search for the decay Bs0 → η' Xss̄ Using a Semi-Inclusive Method at the Belle Experiment / Shawn Dubey ; Thomas E. Browder [BELLE2-PTHESIS-2021-003] Presented on 19 12 2020 PhD 2020 University of Hawaii/ProQuest / Honolulu, HI The decay Bs0 → η' Xss̄ is searched for at Belle, using Belle’s 121.4 fb − 1 integrated luminosity data sample, taken at Υ( 5S ) resonance. [...] Fulltext: PDF; Detailed record - Similar records
4.	Physics at Super B Factory / T. Aushev ; W. Barte ; A. Bondar ; J. Brodzicka ; et al [KEK Report 2009-12] [arXiv:1002.5012] [BELLE2-REPORT-2016-002] 11 February 2010 This report presents the results of studies that investigate the physics reach at a Super B factory, an asymmetric-energy e+e− collider with a design luminosity of 8×10^35 cm−2s−1, which is around 50 times as large as the peak luminosity achieved by the KEKB collider. [...] Fulltext: PDF; Detailed record - Similar records

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