ALICE measures the radial jet-energy flow observable Δp_T in Pb-Pb (5.02 TeV) and pp (13 TeV) collisions and reports narrowing of the energy distribution in heavy-ion collisions at 3.5-4.5σ significance.
Kogleret al., Rev
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abstract
Jet substructure has emerged to play a central role at the Large Hadron Collider, where it has provided numerous innovative ways to search for new physics and to probe the Standard Model, particularly in extreme regions of phase space. In this article we focus on a review of the development and use of state-of-the-art jet substructure techniques by the ATLAS and CMS experiments.
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Proof-of-principle for hadron-in-fat-jet AI tagging that yields an expected 95% CL limit of B(W±→π±γ) < 2.78×10^{-5} at 450 fb^{-1}.
Explainability techniques applied to LundNet show that assigned node importance correlates with classical jet substructure observables such as N-subjettiness ratios and energy correlation functions, with shifts across transverse-momentum regimes.
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Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane
Explainability techniques applied to LundNet show that assigned node importance correlates with classical jet substructure observables such as N-subjettiness ratios and energy correlation functions, with shifts across transverse-momentum regimes.