DNN analysis of pp → WR → ℓNR → ℓℓjj at LHC Run 2 and HL-LHC improves exclusion limits on m_WR and m_NR for unmixed, maximal-mixing, and PMNS-like scenarios over cut-based methods and probes the |Ve1|–|Vμ1| plane.
Hayrapetyanet al.(CMS), JHEP06, 183 (2024), arXiv:2403.04584 [hep-ex]
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Probing lepton flavor mixing in $W_R$ searches with machine learning at the LHC
DNN analysis of pp → WR → ℓNR → ℓℓjj at LHC Run 2 and HL-LHC improves exclusion limits on m_WR and m_NR for unmixed, maximal-mixing, and PMNS-like scenarios over cut-based methods and probes the |Ve1|–|Vμ1| plane.