Classifying the CP properties of the ggH coupling in H+2j production

TL;DR

This paper uses machine learning to analyze Higgs production with two jets, focusing on CP properties of the Higgs-gluon coupling, and proposes methods to improve experimental limits on CP violation in Higgs interactions.

Contribution

It introduces a novel approach exploiting phase space regions with CP sensitivity in Higgs plus two jets production using machine learning techniques.

Findings

Potential to improve current experimental limits on CP violation.

Identification of key observables for CP violation disentanglement.

Projected limits on CP-violating top-Yukawa coupling are competitive.

Abstract

The Higgs-gluon interaction is crucial for LHC phenomenology. To improve the constraints on the CP structure of this coupling, we investigate Higgs production with two jets using machine learning. In particular, we exploit the CP sensitivity of the so far neglected phase space region that differs from the typical vector boson fusion-like kinematics. Our results indicate that further improvements in the current experimental limits could be achievable using our techniques. We also discuss the most relevant observables and how CP violation in the Higgs-gluon interaction can be disentangled from CP violation in the interaction between the Higgs boson and massive vector bosons. Assuming the absence of CP-violating Higgs interactions with coloured beyond-the-Standard-Model states, our projected limits on a CP-violating top-Yukawa coupling are competitive with more direct probes like top-associated Higgs production and limits from a global fit.