English

Machine learning the Higgs boson-top quark CP phase

High Energy Physics - Phenomenology 2022-05-17 v2 High Energy Physics - Experiment

Abstract

We explore the direct Higgs-top CP measurement via the ppttˉhpp\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 ttˉht\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 hγγh\to \gamma\gamma, we obtain that the HL-LHC can probe the Higgs-top coupling modifier and CP-phase, respectively, up to κt8%|\kappa_t|\lesssim 8\% and α13|\alpha|\lesssim 13^{\circ} at 68%68\%~CL.

Keywords

Cite

@article{arxiv.2110.07635,
  title  = {Machine learning the Higgs boson-top quark CP phase},
  author = {Rahool Kumar Barman and Dorival Gonçalves and Felix Kling},
  journal= {arXiv preprint arXiv:2110.07635},
  year   = {2022}
}

Comments

Published version in PRD, 12 pages, 5 figures

R2 v1 2026-06-24T06:53:57.304Z