Speaker
Thomas Matthew Critchley
(Universite de Geneve (CH))
Description
In place of traditional cut and count methods, machine learning techniques offer powerful ways to optimise our searches for new physics. At the FCC-ee, we will probe the highest intensities and energies ever seen at a lepton collider, opening the possibly for discovery of massive right-handed neutrino states. In this work, existing searches for HNLs at the FCC-ee are optimised using a BDT and a DNN. We report an increase in the sensitivity of the considered parameter space by as much as two orders of magnitude in the couplings.
Primary authors
Anna Sfyrla
(Universite de Geneve (CH))
Pantelis Kontaxakis
(Universite de Geneve (CH))
Thomas Matthew Critchley
(Universite de Geneve (CH))
