Machine learning the Higgs boson-top quark CP phase

Autor: Rahool Kumar Barman, Dorival Gonçalves, Felix Kling
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Physical Review
Physical review / D 105(3), 035023 (2022). doi:10.1103/PhysRevD.105.035023
DOI: 10.3204/PUBDB-2021-04062
Popis: Physical review / D 105(3), 035023 (2022). doi:10.1103/PhysRevD.105.035023
We explore the direct Higgs boson-top CP measurement via the $pp ��� t\bar{t}h$ 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 $t\bar{t}h$ multiparticle 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, semileptonic, and dileptonic top pair final states in association with $h�������$, we obtain that the HL-LHC can probe the Higgs boson-top coupling modifier and CP phase, respectively, up to $|��_t|���8% and |��|���13��$ at $68%$ C.L.
Published by Inst., Melville, NY
Databáze: OpenAIRE