Machine learning the Higgs boson-top quark CP phase

Abstract

We explore the direct Higgs-top CP measurement via the $pp\to t\bar{t}h$ 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 $t\bar{t}h$ 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 $h\to {\hat{I}}^3{\hat{I}}^3$, we obtain that the HL-LHC can probe the Higgs-top coupling modifier and CP-phase, respectively, up to $|\hat{I}{º}_t|\lesssim 8\%$ and $|\hat{I}\pm |\lesssim 13^{\circ }$ at $68\%$~CL.

Published version in PRD, 12 pages, 5 figures