| Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
|---|---|---|
| Article Number | 02015 | |
| Number of page(s) | 10 | |
| Section | Online Computing | |
| DOI | https://doi.org/10.1051/epjconf/202429502015 | |
| Published online | 06 May 2024 | |
https://doi.org/10.1051/epjconf/202429502015
Impact of the high-level trigger for detecting long-lived particles at LHCb
1 EPFL (Ecole Polytechnique Fédérale de Lausanne), Switzerland.
2 IFIC (Instituto de Física Corpuscular), University of Valencia-CSIC, Valencia, Spain.
3 TIFR (Tata institute of fundamental research), DHEP (Department of High Energy Physics), Mumbai, India.
4 Taras Shevchenko National University of Kyiv, Ukraine.
Published online: 6 May 2024
Long-lived particles (LLPs) are very challenging to search for with current detectors and computing requirements due to their very displaced vertices. This study evaluates the ability of the trigger algorithms used in the Large Hadron Collider beauty (LHCb) experiment to detect long-lived particles and attempts to adapt them to enhance the sensitivity of this experiment to undiscovered long-lived particles. One of the challenges in the track reconstruction is to deal with the large amount of combinatorics of hits. A dedicated algorithm has been developed to cope with the large data output. When fully implemented, this algorithm would greatly increase the efficiency for any long-lived particle reconstruction in the forward region, for the Standard Model of particle physics and beyond.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.