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Unbinned multivariate observables for global SMEFT analyses from machine learning
<!--HTML-->Theoretical interpretations of particle physics data, such as the determination of the Wilson coefficients of the Standard Model Effective Field Theory (SMEFT), often involve the inference of multiple parameters from a global dataset. Optimizing such interpretations requires the ide...
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| Lenguaje: | eng |
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2022
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| Acceso en línea: | http://cds.cern.ch/record/2844699 |