Flavour anomalies and Machine Learning: an improved analysis
| Autor: | Alda, Jorge, Mir, Alejandro, Penaranda, Siannah |
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| Rok vydání: | 2024 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | We present an extended analysis of our previous results on flavour anomalies in semileptonic rare $B$-meson decays using an effective field theory approach and assuming that new physics affects only one generation in the interaction basis and non-universal mixing effects are generated by the rotation to the mass basis. A global fit to experimental data is performed, focusing on LFU ratios $R_{D^{(*)}}$ and $R_{J/\psi}$ and branching ratios that exhibit tensions with Standard Model predictions on $B \rightarrow K^{(*)} \nu \bar{\nu}$ decays. We use a Machine Learning Montecarlo algorithm in our analysis. Comparing three different scenarios, we show that the one that introduces only mixing between the second and third quark generations and no mixing in the lepton sector, as well as independent coefficients for the singlet and triplet four fermion effective operators, provides the best fit to experimental data. A comparison with our previous results is performed. Comment: 30 pages, 11 figures, 3 tables |
| Databáze: | arXiv |
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