Physics Seminar: Shawn Dubey

Speaker: Shawn Dubey, University of Hawaii

Title: Machine Learning for New Physics in B ¿ K*µ+µ- Decays

Abstract: We report the status of a neural network regression model trained to extract new physics (NP) parameters in Monte Carlo (MC) data. We utilize a newEvtGen NP MC generator to generate B ¿ K*µ+µ- events according to the deviation of the Wilson Co-efficient C9 from its SM value, dC9, for different dC9values. We train a three-dimensional ResNet regression model, using images built from the the angular observables and the square of the invariant mass ofthe di-muon system, to extract values of dC9 directly from MC data samples. This work is intended for future analyses at the Belle II experiment but may alsofind applicability at other experiments.