Track reconstruction in the CMS tracker
By T. Speer, W. Adam, Rudolf Frühwirth, A. Strandlie, T. Todorov, M. Winkler. 2006
155 citations recorded by the source corpus.
An overview of the track reconstruction algorithms used in the tracker of the CMS experiment at the LHC is presented. At the LHC, track reconstruction will be a very challenging task due to the high number of tracks foreseen. In addition to the standard Kalman filter, which serves as the basis for track reconstruction, several non-linear algorithms have been implemented.
Subfields: Computer Vision and Pattern Recognition, Nuclear and High Energy Physics
View Paper: https://www.semanticscholar.org/paper/dba79a084c53136ebf50ea7e0c40d8d2de723985
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Cms Collaboration
- Jean-Roch Vlimant
- Matthew Fisher
- Y. Liu
- Pushpalatha C. Bhat
- Frans Meijers
- Loukas Gouskos
- Alexey Kamenev
In Nuclear and High Energy Physics
- Cms Collaboration
- Atlas Collaboration
- Fabio Maltoni
- M. Raidal
- K. Kannike
- Philip C. Harris
- É. Conte
- Nhan Tran
Citations in the corpus
- Particle-flow reconstruction and global event description with the CMS detector (2017, methodology): “A combinatorial track finder based on Kalman Filtering (KF) [29] was used to reconstruct these tracks in three stages: initial seed generation with a”
- CMS tracking performance results from early LHC operation (2010, methodology): “The standard track reconstruction at CMS is performed by the combinatorial track finder (CTF) [28].”
- Transverse-momentum and pseudorapidity distributions of charged hadrons in pp collisions at $\sqrt{s} = 0.9 $ and 2.36 TeV (2010, methodology): “[17, 18], but was further optimized for primary-track reconstruction in minimum bias events.”