Machine learning the Higgs-top CP phase

We explore the direct Higgs-top CP measurement via the pp → $t\overline{t}h$ channel at the high-luminosity LHC. We show that a combination of machine learning techniques and efficient kinematic reconstruction methods can boost new physics sensitivity, effectively probing the complex $t\overline{t}h$ multi-particle phase space. Special attention is devoted to top quark polarization observables, uplifting the analysis from a raw rate to a polarization study. Through a combination of hadronic, semi-leptonic, and di-leptonic top pair final states in association with h → γγ, we obtain that the HL-LHC can probe the Higgs-top coupling modifier and CP-phase, respectively, up to |${\kappa }_t$|≲ 8% and |α|≲13° at 68% CL.