arXiv · 2109.07405
Using Machine Learning techniques in phenomenological studies in flavour physics
Abstract
An updated analysis of New Physics violating Lepton Flavour Universality, by using the Standard Model Effective Field Lagrangian with semileptonic dimension six operators at $\Lambda = 1\,\mathrm{TeV}$ 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.
Explore related subjects
Keep this discovery
Jorge Alda, Jaume Guasch, Siannah Penaranda. 2021-09-15. Using Machine Learning techniques in phenomenological studies in flavour physics. https://doi.org/10.1007/jhep07(2022)115
Cite the original work for its findings. Save a collection to share your selection of sources.