EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 337 (2025) EPJ Web Conf., 337 (2025) 01187 References
Open Access
Issue
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
Article Number 01187
Number of page(s) 8
DOI https://doi.org/10.1051/epjconf/202533701187
Published online 07 October 2025
  1. ATLAS Collaboration, ATLAS Software and Computing HL-LHC Roadmap (2022), https://cds.cern.ch/record/2802918 [Google Scholar]
  2. R. Dennard et al., Design of ion-implanted MOSFET’s with very small physical dimensions, IEEE Journal of Solid-State Circuits 9, 256 (1974). https://doi.org/10.1109/JSSC.1974.1050511 [Google Scholar]
  3. B. Yeo et al., Github repository of acts-project/traccc, https://github.com/acts-project/traccc [Google Scholar]
  4. X. Ai et al., A Common Tracking Software Project, Comput. Softw. Big Sci. 6, 8 (2022). https://doi.org/10.1007/s41781-021-00078-8 [CrossRef] [Google Scholar]
  5. P. Gessinger et al., ACTS GPU Track Reconstruction Demonstrator for HEP, Proceedings of the CTD 2022 pp. 46–53 (2023). https://doi.org/10.5281/zenodo.8119864 [Google Scholar]
  6. A. Krasznahorkay et al., traccc - a close to single-source track reconstruction demonstrator for CPU and GPU, https://indico.jlab.org/event/459/contributions/11420/, presented at the 26th International Conference on Computing in High Energy and Nuclear Physics [Google Scholar]
  7. R.E. Kalman, A New Approach to Linear Filtering and Prediction Problems, Journal of Basic Engineering 82, 35 (1960). https://doi.org/10.1115/1.3662552 [CrossRef] [Google Scholar]
  8. R. Frühwirth, Application of Kalman filtering to track and vertex fitting, Nucl. Instr. and Meth. A 262, 444 (1987). https://doi.org/10.1016/0168-9002(87)90887-4 [Google Scholar]
  9. S. Agostinelli et al., Geant4—a simulation toolkit, Nucl. Instr. and Meth. A 506, 250 (2003). https://doi.org/10.1016/S0168-9002(03)01368-8 [CrossRef] [Google Scholar]
  10. P. Gessinger-Befurt, A. Salzburger, J. Niermann, The Open Data Detector Tracking System, Journal of Physics: Conference Series 2438, 012110 (2023). https://doi.org/10.1088/1742-6596/2438/1/012110 [Google Scholar]
  11. Y. Zhang, A. Azad, Z. Hu, FastSV: A Distributed-Memory Connected Component Algorithm with Fast Convergence (2020), pp. 46–57 [Google Scholar]
  12. P. Billoir, Progressive track recognition with a Kalman-like fitting procedure, Computer Physics Communications 57, 390 (1989). https://doi.org/10.1016/0010-4655(89)90249-X [Google Scholar]
  13. P. Billoir, S. Qian, Simultaneous pattern recognition and track fitting by the Kalman filtering method, Nucl. Instr. and Meth. A 294, 219 (1990). https://doi.org/10.1016/0168-9002(90)91835-Y [Google Scholar]
  14. E. Nyström, Über die numerische Integration von Differentialgleichungen, Acta Societatis scientiarum Fennicae (Druck der Finnischen literaturgesellschaft, 1925) [Google Scholar]
  15. L. Bugge, J. Myrheim, Tracking and track fitting, Nuclear Instruments and Methods 179, 365 (1981). https://doi.org/10.1016/0029-554X(81)90063-X [Google Scholar]
  16. E. Lund, L. Bugge, I. Gavrilenko, A. Strandlie, Track parameter propagation through the application of a new adaptive Runge-Kutta-Nyström method in the ATLAS experiment, JINST 4, P04001 (2009). https://doi.org/10.1088/1748-0221/4/04/P04001 [Google Scholar]
  17. E. Lund, L. Bugge, I. Gavrilenko, A. Strandlie, Transport of covariance matrices in the inhomogeneous magnetic field of the ATLAS experiment by the application of a semi-analytical method, JINST 4, P04016 (2009). https://doi.org/10.1088/1748-0221/4/04/P04016 [Google Scholar]
  18. B. Yeo, H. Gray, A. Salzburger, S.N. Swatman, The derivation of Jacobian matrices for the propagation of track parameter uncertainties in the presence of magnetic fields and detector material, Nucl. Instr. and Meth. A 1068, 169734 (2024). https://doi.org/10.1016/j.nima.2024.169734 [Google Scholar]
  19. H.E. Rauch, F. Tung, C.T. Striebel, Maximum likelihood estimates of linear dynamic systems, AIAA Journal 3, 1445 (1965). https://doi.org/10.2514/3.3166 [Google Scholar]
  20. R. Reyes, V. Lomüller, SYCL: Single-source C++ accelerator programming, in International Conference on Parallel Computing (2015) [Google Scholar]
  21. L. Gonella, The ATLAS ITk detector system for the Phase-II LHC upgrade, Nucl. Instr. and Meth. A 1045, 167597 (2023). https://doi.org/10.1016/j.nima.2022.167597 [Google Scholar]
  22. R. Frühwirth et al., Data analysis techniques for high-energy physics; 2nd ed., Cambridge monographs on particle physics, nuclear physics, and cosmology (Cambridge Univ. Press, Cambridge, 2000) [Google Scholar]
  23. R. Frühwirth, A. Strandlie, Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors (Springer Cham, 2021) [Google Scholar]
  24. D.C. Fraser, Ph.D. thesis, Massachusetts Institute of Technology (1967), http://hdl. handle.net/1721.1/13543 [Google Scholar]
  25. NVIDIA Corporation, Triton inference server: An optimized cloud and edge inferencing solution, https://github.com/triton-inference-server [Google Scholar]
  26. S.N. Swatman, A.L. Varbanescu, A. Krasznahorkay, A. Pimentel, Modelling Performance Loss due to Thread Imbalance in Stochastic Variable-Length SIMT Workloads, in 2022 30th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2022), pp. 137–144 [Google Scholar]

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.