Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
---|---|---|
Article Number | 03014 | |
Number of page(s) | 7 | |
Section | Offline Computing | |
DOI | https://doi.org/10.1051/epjconf/202429503014 | |
Published online | 06 May 2024 |
https://doi.org/10.1051/epjconf/202429503014
Faster simulated track reconstruction in the ATLAS Fast Chain
1 University of Massachusetts Amherst, Amherst, MA, USA
2 Stony Brook University, Stony Brook, NY, USA
3 Université de Genève, Geneva, Switzerland
4 University of Cambridge, Cambridge, UK
* e-mail: wleight@cern.ch
Published online: 6 May 2024
The production of simulated datasets for use by physics analyses consumes a large fraction of ATLAS computing resources, a problem that will only get worse as increases in the instantaneous luminosity provided by the LHC lead to more collisions per bunch crossing (pile-up). One of the more resource-intensive steps in the Monte Carlo production is reconstructing the tracks in the ATLAS Inner Detector, which takes up about 60% of the total detector reconstruction time. This talk discusses a novel technique called track overlay, which substantially speeds up the Inner Detector reconstruction. In track overlay the pile-up Inner Detector tracks are reconstructed ahead of time and overlaid onto the Inner Detector tracks from the simulated hard-scatter event. We present our implementation of this track overlay approach as part of the ATLAS Fast Chain simulation, as well as a method for deciding in which cases it is possible to use track overlay in the reconstruction of simulated data without performance degradation, and in which it is preferable to use the current approach.
© 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.