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| Master Thesis | PUBDB-2026-01966 |
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2026
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Please use a persistent id in citations: doi:10.3204/PUBDB-2026-01966
Abstract: A study for the associated production of a Higgs boson with a top quark pair $(t\bar{t}H)$ in the fully hadronic final state is presented, focusing on the H → $b\bar{b}$ decay channel using proton-protoncollision data collected by the CMS experiment during Run 3 in 2024. Resolving the jet-parton assignment task in this high jet multiplicity environment represents a major source of combinatorial ambiguity. To address this limitation, a multivariate approach based on Symmetry-Preserving Attention Networks (SPANeT) is implemented to optimize the event reconstruction. Evaluated on simulated signal samples, the network achieves a Higgs boson acceptance of 63% and an assignment efficiency of 57% in the inclusive baseline category. This marks a significant improvement by nearly a factor of three compared to the 21% efficiency obtained via traditional geometric matching methods based on angular proximity (∆R). Finally, the network’s susceptibility to systematic biases is validated using a pure $ t\bar{t}$ + bb background control sample. While the model successfully reconstructs the signal topology, a noticeable mass-sculpting effect is observed in the background spectrum. To mitigate this effect in future analysis workflows, an impartial training scheme utilizing multi-mass signal samples is proposed to decorrelate the network’s predictions from the target Higgs boson mass.
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