Szczegóły publikacji
Opis bibliograficzny
Performance of the CMS high-level trigger during LHC Run 2 / A. Hayrapetyan, [et al.], V. AVATI, L. GRZANKA, M. MALAWSKI, [et al.] // Journal of Instrumentation [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 1748-0221. — 2024 — vol. 19 iss. 11 art. no. P11021, s. [1], 1–61. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 38–40, Abstr. — Publikacja dostępna online od: 2024-11-22
Autorzy (2430)
- AGHAvati Valentina
- AGHGrzanka Leszek
- AGHMalawski Maciej
- Hayrapetyan Aram
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 159040 |
|---|---|
| Data dodania do BaDAP | 2025-05-05 |
| Tekst źródłowy | URL |
| DOI | 10.1088/1748-0221/19/11/P11021 |
| Rok publikacji | 2024 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Journal of Instrumentation |
Abstract
The CERN LHC provided proton and heavy ion collisions during its Run 2 operation period from 2015 to 2018. Proton-proton collisions reached a peak instantaneous luminosity of 2.1 × 1034 cm-2s-1, twice the initial design value, at √(s)=13 TeV. The CMS experiment records a subset of the collisions for further processing as part of its online selection of data for physics analyses, using a two-level trigger system: the Level-1 trigger, implemented in custom-designed electronics, and the high-level trigger, a streamlined version of the offline reconstruction software running on a large computer farm. This paper presents the performance of the CMS high-level trigger system during LHC Run 2 for physics objects, such as leptons, jets, and missing transverse momentum, which meet the broad needs of the CMS physics program and the challenge of the evolving LHC and detector conditions. Sophisticated algorithms that were originally used in offline reconstruction were deployed online. Highlights include a machine-learning b tagging algorithm and a reconstruction algorithm for tau leptons that decay hadronically.
