Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
---|---|---|
Article Number | 02014 | |
Number of page(s) | 8 | |
Section | T2 - Offline computing | |
DOI | https://doi.org/10.1051/epjconf/201921402014 | |
Published online | 17 September 2019 |
https://doi.org/10.1051/epjconf/201921402014
Local reconstruction algorithms in the cathode strip chambers of CMS
University of California, Riverside,
USA
* e-mail: mirena.paneva@cern.ch
Published online: 17 September 2019
The design of the CMS detector is optimized for muon measurements. The muon system consists of gas ionization detector technologies. Cathode Strip Chambers (CSC) with both tracking and triggering capabilities are installed in the forward region. The first stage of muon reconstruction uses information from individual muon chambers and is thus called local reconstruction, in contrast to a subsequent global reconstruction where the information from all detectors is combined. First, 2-dimensional spatial points (rechits) describing where a muon crosses the CSC layers are built from the electrical signals induced by the charged particle traversing the chamber. Next, from the reconstructed hits, straight-line track segments are built within each chamber. Local reconstruction becomes particularly challenging at high instantaneous luminosities, which are expected at the HL-LHC. The high rate of particles traversing the detectors leads to increased rate of spurious rechits and segments thus increasing the combinatorial backgrounds. In this respect, work on improving the current and developing new algorithms is essential and is in progress. This document presents the existing local reconstruction algorithms used in the CMS cathode strip chambers. Their performance as well as ongoing efforts towards HL-LHC improvements are discussed.
© The Authors, published by EDP Sciences, 2019
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.
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