Measurements in the highly Lorentz-boosted regime provoke increased interest in probing the Higgs boson properties and in searching for particles beyond the standard model at the LHC. In the CMS Collaboration, various boosted-object tagging algorithms, designed to identify hadronic jets originating from a massive particle decaying to (Formula presented) or (Formula presented), have been developed and deployed across a range of physics analyses. This paper highlights their performance on simulated events, and summarizes novel calibration techniques using proton-proton collision data collected at (Formula presented) during the 2016–2018 LHC data-taking period. Three dedicated methods are used for the calibration in multijet events, leveraging either machine learning techniques, the presence of muons within energetic boosted jets, or the reconstruction of hadronically decaying high-energy Z bosons. The calibration results, obtained through a combination of these approaches, are presented and discussed.

Hayrapetyan, A., Tumasyan, A., Adam, W., Andrejkovic, J., Benato, L., Bergauer, T., et al. (2025). Performance of heavy-flavour jet identification in Lorentz-boosted topologies in proton-proton collisions at (Formula presented). JOURNAL OF INSTRUMENTATION, 20(11) [10.1088/1748-0221/20/11/P11006].

Performance of heavy-flavour jet identification in Lorentz-boosted topologies in proton-proton collisions at (Formula presented)

Xiao J.;Brivio F.;Cetorelli F.;De Guio F.;Dinardo M. E.;Gerosa R.;Ghezzi A.;Govoni P.;Guzzi L.;Lucchini M. T.;Malberti M.;Moroni L.;Paganoni M.;Palluotto S.;Perego A.;Pinolini B. S.;Pizzati G.;Ragazzi S.;Tabarelli de Fatis T.;
2025

Abstract

Measurements in the highly Lorentz-boosted regime provoke increased interest in probing the Higgs boson properties and in searching for particles beyond the standard model at the LHC. In the CMS Collaboration, various boosted-object tagging algorithms, designed to identify hadronic jets originating from a massive particle decaying to (Formula presented) or (Formula presented), have been developed and deployed across a range of physics analyses. This paper highlights their performance on simulated events, and summarizes novel calibration techniques using proton-proton collision data collected at (Formula presented) during the 2016–2018 LHC data-taking period. Three dedicated methods are used for the calibration in multijet events, leveraging either machine learning techniques, the presence of muons within energetic boosted jets, or the reconstruction of hadronically decaying high-energy Z bosons. The calibration results, obtained through a combination of these approaches, are presented and discussed.
Articolo in rivista - Articolo scientifico
calibration and fitting methods; cluster finding; Pattern recognition; Performance of High Energy Physics Detectors;
English
12-nov-2025
2025
20
11
P11006
open
Hayrapetyan, A., Tumasyan, A., Adam, W., Andrejkovic, J., Benato, L., Bergauer, T., et al. (2025). Performance of heavy-flavour jet identification in Lorentz-boosted topologies in proton-proton collisions at (Formula presented). JOURNAL OF INSTRUMENTATION, 20(11) [10.1088/1748-0221/20/11/P11006].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/605121
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