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Göttingen 2025 – scientific programme

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T: Fachverband Teilchenphysik

T 24: Higgs Physics III (boson final states)

T 24.6: Talk

Tuesday, April 1, 2025, 17:30–17:45, ZHG104

Quantum tomography using machine learning to infer incomplete information in HWW→ℓνℓν — Carsten Burgard1, Vince Croft2, Andre Sopczak3, •Andrii Vak3, and Lennart Völz11TU Dortmund University — 2Leiden University — 3Czech Technical University in Prague

Potential entanglement originating from the scalar nature of the Higgs boson can translate to variables that could be accessible at collider experiments such as ATLAS at the LHC. The entanglement is mediated through the parity violation from weak decay vertices, affecting for example the angular properties of the dilepton system in HWW→ℓνℓν decays. Thus, the analysis of multiple neutrinos in the final state is interesting for quantum tomography measurements. This study uses advanced machine learning methods for regression and inference of missing kinematic information.

Keywords: quantum entanglement; Higgs boson decay; missing energy; collider experiments

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