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