Shayma Wahdan, on behalf of the ATLAS collaboration
SciPost Phys. Proc. 18, 019 (2026) ·
published 29 January 2026
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These proceedings present a search for flavour-changing neutral-current (FCNC) interaction involving the top quark, Higgs boson and either the up or the charm quark, using 140 $\text{fb}^{-1}$ of 13 TeV proton--proton collision data from the ATLAS detector at the Large Hadron Collider. Two channels are considered: the production of top quark-antiquark pair with one top decaying via FCNC, and the associated production of a top quark and Higgs boson. Final states contain either two same-charge leptons, or three leptons of which two have the same charge. Observed (expected) upper limits on the branching rations are determined as $\mathcal{B}(t\to Hu)<2.8 (3.0) × 10^{-4}$ and $\mathcal{B}(t\to Hc)<3.3 (3.8) × 10^{-4}$.
SciPost Phys. 19, 155 (2025) ·
published 16 December 2025
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The ATLAS experiment at the Large Hadron Collider explores the use of modern neural networks for a multi-dimensional calibration of its calorimeter signal defined by clusters of topologically connected cells (topo-clusters). The Bayesian neural network (BNN) approach not only yields a continuous and smooth calibration function that improves performance relative to the standard calibration but also provides uncertainties on the calibrated energies for each topo-cluster. The results obtained by using a trained BNN are compared to the standard local hadronic calibration and to a calibration provided by training a deep neural network. The uncertainties predicted by the BNN are interpreted in the context of a fractional contribution to the systematic uncertainties of the trained calibration. They are also compared to uncertainty predictions obtained from an alternative estimator employing repulsive ensembles.
