Using Machine Learning techniques in phenomenological studies on flavour physics
Resumen: An updated analysis of New Physics violating Lepton Flavour Universality, by using the Standard Model Effective Field Lagrangian with semileptonic dimension six operators at ¿ = 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.
Idioma: Inglés
DOI: 10.1007/JHEP07(2022)115
Año: 2022
Publicado en: Journal of High Energy Physics 2022, 7 (2022), 115 [43 pp.]
ISSN: 1126-6708

Factor impacto JCR: 5.4 (2022)
Categ. JCR: PHYSICS, PARTICLES & FIELDS rank: 6 / 29 = 0.207 (2022) - Q1 - T1
Factor impacto CITESCORE: 10.3 - Physics and Astronomy (Q1)

Factor impacto SCIMAGO: 0.859 - Nuclear and High Energy Physics (Q2)

Financiación: info:eu-repo/grantAgreement/ES/AEI/CEX2019-000918-M
Financiación: info:eu-repo/grantAgreement/ES/AEI/PID2019-105614GB-C22
Financiación: info:eu-repo/grantAgreement/ES/DGIID-DGA/2015-E24-2
Financiación: info:eu-repo/grantAgreement/ES/MINECO-FEDER/PGC2018-095328-B-I00
Financiación: info:eu-repo/grantAgreement/ES/MINECO/FPA2015-65745-P
Tipo y forma: Article (Published version)
Área (Departamento): Área Física Teórica (Dpto. Física Teórica)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.


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 Record created 2022-10-20, last modified 2024-03-19


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