3 papers
cs.DC2025
SkimROOT: Accelerating LHC Data Filtering with Near-Storage Processing
Narangerelt Batsoyol, Jonathan Guiang, Diego Davila +4
Data analysis in high-energy physics (HEP) begins with data reduction, where vast datasets are filtered to extract relevant events. At the Large Hadron Collider (LHC), this process…
hep-ex2024
Line Segment Tracking: Improving the Phase 2 CMS High Level Trigger Tracking with a Novel, Hardware-Agnostic Pattern Recognition Algorithm
Emmanouil Vourliotis, Philip Chang, Peter Elmer +11
Charged particle reconstruction is one the most computationally heavy components of the full event reconstruction of Large Hadron Collider (LHC) experiments. Looking to the future,…
physics.ins-det2024
Improving tracking algorithms with machine learning: a case for line-segment tracking at the High Luminosity LHC
Jonathan Guiang, Slava Krutelyov, Manos Vourliotis +10
In this work, we present a study on ways that tracking algorithms can be improved with machine learning (ML). We base this study on the line segment tracking (LST) algorithm that w…