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From optimal observables to machine learning: an effective-field-theory analysis of e+e − → W+W − at future lepton colliders

Abstract We apply machine-learning techniques to the effective-field-theory analysis of the e + e − → W + W − processes at future lepton colliders, and demonstrate their advantages in comparison with conventional methods, such as optimal observables. In particular, we show that machine-learning meth...

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Autors principals: Shengdu Chai, Jiayin Gu, Lingfeng Li
Format: Artigo
Idioma:Inglês
Publicat: SpringerOpen 2024-05-01
Col·lecció:Journal of High Energy Physics
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Accés en línia:https://doi.org/10.1007/JHEP05(2024)292
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