Optimized probes of $CP$-odd effects in the $t \bar{t} h$ process at hadron colliders

TL;DR

This paper develops optimized $CP$-odd observables for the $pp o tar{t}h$ process at colliders, using machine learning and phase-space optimization to enhance sensitivity to $CP$-violating interactions involving the top quark and Higgs boson.

Contribution

It introduces a simple linear combination of $CP$-odd observables that matches the sensitivity of complex ML models for probing $CP$ violation in top-Higgs interactions.

Findings

Optimized observables improve sensitivity to $CP$-odd effects.

Projected sensitivities at HL-LHC, HE-LHC, and FCC-hh.

Linear combination performs comparably to ML models.

Abstract

We use machine learning (ML) and non-ML techniques to study optimized $CP$-odd observables, directly and maximally sensitive to the $CP$-odd $i \tilde \kappa \bar t \gamma^5 t h$ interaction at the LHC and prospective future hadron colliders using the final state with a Higgs boson and a top quark pair, $pp\to t\bar t h$, followed by semileptonic $t$ decays. We perform phase-space optimization of manifestly $CP$-odd observables ($\boldsymbol \omega$), sensitive to the sign of $\tilde \kappa$, and constructed from experimentally accessible final state momenta. We identify a simple optimized linear combination $\boldsymbol \alpha\cdot \boldsymbol\omega$ that gives similar sensitivity as the studied fully fledged ML models. Using $\boldsymbol\alpha\cdot \boldsymbol\omega$ we project the expected sensitivities to $\tilde \kappa$ at HL-LHC, HE-LHC, and FCC-hh.