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 tt¯→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.

Zwalinski, L., Zou, W., Zormpa, O., Zorbas, T.G., Zoch, K., Zoccoli, A., et al. (2025). A continuous calibration of the ATLAS flavour-tagging classifiers via optimal transportation maps. THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS, 85(11) [10.1140/epjc/s10052-025-14682-0].

A continuous calibration of the ATLAS flavour-tagging classifiers via optimal transportation maps

Cerri A.;
2025-01-01

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 tt¯→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.
2025
Zwalinski, L., Zou, W., Zormpa, O., Zorbas, T.G., Zoch, K., Zoccoli, A., et al. (2025). A continuous calibration of the ATLAS flavour-tagging classifiers via optimal transportation maps. THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS, 85(11) [10.1140/epjc/s10052-025-14682-0].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1317759