Speaker
Gang Li
(Sun Yat-Sen University)
Description
In this talk, I will discuss the LHC reach for probing the right-handed neutrino mixing matrix via the Keung–Senjanović process, $pp \to W_R \to \ell N_R \to \ell\ell jj$, focusing on both same-sign and opposite-sign dilepton final states with different lepton flavor combinations. I will show that machine learning technique significantly enhances the sensitivities to the masses of $W_R$ and $N_R$, as well as to the lepton flavor mixing parameters. I will also discuss how this collider search complements low-energy searches for charged lepton flavor violation.
Primary author
Gang Li
(Sun Yat-Sen University)
