Szczegóły publikacji
Opis bibliograficzny
Second generation machine learning based algorithm for long-lived particles reconstruction in upgraded LHCb experiment / Sabin HASHMI // Acta Physica Polonica. B, Proceedings Supplement ; ISSN 1899-2358. — 2022 — vol. 15 no. 3 art. no. 3-A36, s. 3-A36.1–3-A36.8. — Bibliogr. s. 3-A36.8, Abstr. — Publikacja dostępna online od: 2022-09-09. — 28th Cracow Epiphany Conference on Recent Advances in Astroparticle Physics : Cracow, Poland, 10–14 January, 2022
Autor
Dane bibliometryczne
| ID BaDAP | 144946 |
|---|---|
| Data dodania do BaDAP | 2023-02-07 |
| Tekst źródłowy | URL |
| DOI | 10.5506/APhysPolBSupp.15.3-A36 |
| Rok publikacji | 2022 |
| Typ publikacji | referat w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Acta Physica Polonica, B, Proceedings Supplement |
Abstract
The paper presents the developments and preliminary results related to the implementation of a Machine Learning based Algorithm for reconstruction of the long-lived particles in an upgraded LHCb experiment. The analysis is based on a Monte-Carlo simulation prepared for LHC Run 3 data-taking conditions. Studied tracks are reconstructed with an official LHCb software application Moore in configuration that is very close to the one that will be operated as a part of the final software trigger system.
