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Probing lepton flavor mixing in $W_R$ searches with machine learning at the LHC
Right-handed lepton flavor mixing in the left-right symmetric model directly affects the production and decay of heavy Majorana neutrinos $N_R$, yet its impact on collider searches remains less explored. Using a deep neural network (DNN), we analyze the Keung-Senjanović process $pp \to W_R \to \ell_
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