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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 $Lambda = 1,mathrm{TeV}$ 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.
LHCb found hints for physics beyond the Standard Model (SM) in $Bto K^*mu^+mu^-$, $R(K)$ and $B_stophimu^+mu^-$. These intriguing hints for NP have recently been confirmed by the LHCb measurement of $R(K^*)$ giving a combined significance for NP abov
Disruption prediction and mitigation is of key importance in the development of sustainable tokamakreactors. Machine learning has become a key tool in this endeavour. In this paper multiple machinelearning models will be tested and compared. A partic
Several experiments observed deviations from the Standard Model (SM) in the flavour sector: LHCb found a $4-5,sigma$ discrepancy compared to the SM in $bto smu^+mu^-$ transitions (recently supported by an Belle analysis) and CMS reported a non-zero m
We give a brief introduction to flavour physics. The first part covers the flavour structure of the Standard Model, how the Kobayashi-Maskawa mechanism is tested and provides examples of searches for new physics using flavour observables, such as mes
The determination of the fundamental parameters of the Standard Model (and its extensions) is often limited by the presence of statistical and theoretical uncertainties. We present several models for the latter uncertainties (random, nuisance, extern