000003545 001__ 3545
000003545 005__ 20230512090633.0
000003545 037__ $$aBELLE2-POSTER-CONF-2023-002
000003545 041__ $$aeng
000003545 100__ $$aShawn Dubey
000003545 245__ $$aMachine Learning for New Physics in B → K ∗µ+µ− Decays
000003545 260__ $$aCHEP 2023$$c2023-05-01
000003545 300__ $$amult. p
000003545 520__ $$aWe report the status of a neural network regression model trained to extract new physics (NP) parame- ters in Monte Carlo (MC) data. We utilize a new EvtGen NP MC generator to generate B → K ∗ µ+ µ− events according to the deviation of the Wilson Coef- ficient C9 from its SM value, δC9 . We train a three- dimensional ResNet regression model, using images built from the the angular observables and the invari- ant mass of the di-muon system, to extract values of δC9 directly from MC data samples. This work is in- tended for future analyses at the Belle II experiment but may also find applicability at other experiments.
000003545 700__ $$aAlexei Sibidanov
000003545 700__ $$aThomas E. Browder
000003545 700__ $$aShahab Kohani
000003545 700__ $$aRusa Mandal
000003545 700__ $$aSaurabh Sandilya
000003545 700__ $$aRahul Sinha
000003545 700__ $$aSven E. Vahsen
000003545 8560_ $$fsdubey@hawaii.edu
000003545 8564_ $$uhttps://docs.belle2.org/record/3545/files/BELLE2-POSTER-CONF-2023-002.pdf$$zUpdated on 05/05/2023