Performance of heavy-flavour jet identification in Lorentz-boosted topologies in proton-proton collisions at √s=13 TeV
Yazarlar (1)
Prof. Dr. Hasan OĞUL Sinop Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | Journal of Instrumentation (Q3) | ||
| Dergi ISSN | 1748-0221 Dergi Bilgileri (2025) | ||
| Makale Dili | İngilizce | Basım Tarihi | 11-2025 |
| Cilt / Sayı / Sayfa | 20 / 11 / – | DOI | 10.1088/1748-0221/20/11/P11006 |
| Makale Linki | https://iopscience.iop.org/article/10.1088/1748-0221/20/11/P11006/meta | ||
| UAK Araştırma Alanları |
Fen Bilimleri ve Matematik
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| Özet |
| 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 bb̅ or cc̅, 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 √(s) = 13 TeV 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 … |
| Anahtar Kelimeler |
| calibration and fitting methods | cluster finding | Pattern recognition | Performance of High Energy Physics Detectors |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 4 |
| Scopus | 4 |
| Google Scholar | 3 |