Amplitude-assisted tagging of longitudinally polarised bosons using wide neural networks

Extracting longitudinal modes of weak bosons in LHC processes is essential to understand the electroweak-symmetry-breaking mechanism. To that end, we propose a general method, based on wide neural networks, to properly model longitudinal-boson signals and hence enable the event-by-event tagging of longitudinal bosons. It combines experimentally accessible kinematic information and genuine theoretical inputs provided by amplitudes in perturbation theory. As an application we consider the production of a Z boson in association with a jet at the LHC, both at leading order and in the presence of parton-shower effects. The devised neural networks are able to extract reliably the longitudinal contribution to the unpolarised process. The proposed method is very general and can be systematically extended to other processes and problems.