Speaker
Description
The upcoming upgrades to the Large Hadron Collider for the HL-LHC era will progressively increase the nominal luminosity, aiming to a reach peak value of $5×10^{34} $ cm$^{-2}$ s$^{-1}$ for the ATLAS and CMS experiments. Higher luminosity will naturally lead to a larger number of proton–proton interactions occurring in the same bunch crossing, with pileup levels that may reach up to 200, creating a significantly more complex environment for track reconstruction.
To cope with these conditions, several experiments have begun redesigning parts of their track reconstruction software so that it can run efficiently on heterogeneous computing architectures. Although these initiatives have yielded promising results, they have generally remained internal to each individual experiment.
In this work, we present CylOn, a standalone tracking framework derived from the CMS Patatrack reconstruction and designed to investigate the portability of its Cellular Automaton approach to different cylindrical tracker layouts operating across multiple backends including CPUs, NVIDIA GPUs and AMD GPUs, and to reconstruct tracks in cylindrical tracker detectors used by different high-energy physics experiments. The framework is applied to a substantially different detector layout, including pixel and short-strip layers, and its physics and computational performance are evaluated under HL-LHC-like pileup conditions.
This effort constitutes a first step toward a unified and experiment-independent reconstruction tool for HL-LHC–like detectors defined only in terms of its fundamental components.