Papers › Evaluating the Impact of Detector Design on Jet Flavor Tagging for Future Colliders
Evaluating the Impact of Detector Design on Jet Flavor Tagging for Future Colliders
Dimitrios Ntounis, Loukas Gouskos, Caterina Vernieri
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
Jet flavor tagging is of utmost importance for unlocking the full physics potential of any future collider experiment. The performance of any jet flavor identification algorithm depends both on its underlying architecture and on the detector's design and capabilities. In this work, we present an analysis of the dependence of jet tagging algorithm performance on three detector designs being considered for future e⁺e⁻ colliders. To fully exploit the potential of these detector concepts, we utilize a graph neural network-based jet tagging algorithm. In addition, we evaluate the impact on the jet tagging performance of variations in the tracking and calorimeter systems for one of these detector concepts, the SiD detector, as well as the dependence on the center-of-mass energy.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections