Machine Learning for New Physics Searches in B → K∗0 µ+µ− Decays

S. Dubey ; T.E. Browder ; S. Kohani ; R. Mandal ; A. Sibidanov ; R. Sinha ; S.E. Vahsen

22 September 2023

Abstract: We report the status of a neural network regression model trained to extract new physics (NP) parameters in Monte Carlo (MC) simulation data. We utilize a new EvtGen NP MC generator to generate B → K∗0 µ+µ− events according to the deviation of the Wilson Coefficient C9 from its SM value, δC9 . We train a three-dimensional ResNet regression model, using images built from the angular observables and the invariant mass of the di-muon system, to extract values of δC9 directly from the MC data samples. This work is intended for future analyses at the Belle II experiment but may also find applicability at other experiments.

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 Record created 2023-09-22, last modified 2023-09-22

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