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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/189626
Using Machine Learning techniques in phenomenological studies on flavour physics
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An updated analysis of New Physics violating Lepton Flavour Universality, by using the Standard Model Effective Field Lagrangian with semileptonic dimension six operators at Λ = 1 TeV is presented. We perform a global fit, by discussing the relevance of the mixing in the first generation. We use for the first time in this context a Montecarlo analysis to extract the confidence intervals and correlations between observables. Our results show that machine learning, made jointly with the SHAP values, constitute a suitable strategy to use in this kind of analysis.
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ALDA, J., GUASCH INGLADA, Jaume and PEÑARANDA RIVAS, Siannah. Using Machine Learning techniques in phenomenological studies on flavour physics. Journal of High Energy Physics. 2022. Vol. 2022, num. 115, pags. 1-42. ISSN 1126-6708. [consulted: 11 of June of 2026]. Available at: https://hdl.handle.net/2445/189626