Muon identification using multivariate techniques in the CMS experiment 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 (2024) | ||
| Makale Dili | İngilizce | Basım Tarihi | 02-2024 |
| Cilt / Sayı / Sayfa | 19 / 2 / – | DOI | 10.1088/1748-0221/19/02/P02031 |
| Makale Linki | http://www.scopus.com/inward/record.url?eid=2-s2.0-85186624167&partnerID=MN8TOARS | ||
| UAK Araştırma Alanları |
Fen Bilimleri ve Matematik
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| Özet |
| The identification of prompt and isolated muons, as well as muons from heavy-flavour hadron decays, is an important task. We developed two multivariate techniques to provide highly efficient identification for muons with transverse momentum greater than 10 GeV. One provides a continuous variable as an alternative to a cut-based identification selection and offers a better discrimination power against misidentified muons. The other one selects prompt and isolated muons by using isolation requirements to reduce the contamination from nonprompt muons arising in heavy-flavour hadron decays. Both algorithms are developed using 59.7 fb-1 of proton-proton collisions data at a centre-of-mass energy of √(s)=13 TeV collected in 2018 with the CMS experiment at the CERN LHC. |
| Anahtar Kelimeler |
| Muon spectrometers | Particle identification methods | Particle tracking detectors |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 13 |
| Scopus | 9 |
| Google Scholar | 7 |