arXiv · 2505.13063
A continuous calibration of the ATLAS flavour-tagging classifiers via optimal transportation maps
Abstract
A calibration of the ATLAS flavour-tagging algorithms using a new calibration procedure based on optimal transportation maps is presented. Simultaneous, continuous corrections to the $b$-jet, $c$-jet, and light-flavour jet classification probabilities from jet-tagging algorithms in simulation are derived for $b$-jets using $t\bar t \to eμννbb$ data. After application of the derived calibration maps, closure between simulation and observation is achieved for jet flavour observables used in ATLAS analyses of Large Hadron Collider (LHC) Run 2 proton-proton collision data. This continuous calibration opens up new possibilities for the future use of jet flavour information in LHC analyses and also serves as a guide for deriving high-dimensional corrections to simulation via transportation maps, an important development for a broad range of inference tasks.
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ATLAS Collaboration. 2025-11-13. A continuous calibration of the ATLAS flavour-tagging classifiers via optimal transportation maps. https://doi.org/10.1140/epjc%2Fs10052-025-14682-0
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