https://doi.org/10.1051/epjconf/202429509024
Machine Learning for New Physics Searches in B → K*0µ+µ− Decays
1 University of Hawai‘i at Mānoa, Honolulu, HI 96822, USA
2 Indian Institute of Technology Gandhinagar, Gujarat 382055, India
* e-mail: sdubey@hawaii.edu
Published online: 6 May 2024
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*0µ+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 δ C9 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.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
