SAIP2025

Particle Flow Algorithm (PFA) development for forward jet reconstruction with the ATLAS ITk detector setup at the HL-LHC

8 Jul 2025, 12:10

20m

Solomon Mahlangu House (University of the Witwatersrand, Johannesburg)

Oral Presentation Track B - Nuclear, Particle and Radiation Physics Nuclear, Particle and Radiation Physics-2

Speaker

Thabo James Lepota (School of Physics and Institute for Collider Particle Physics, University of the Witwatersrand)

Description

The ATLAS experiment at the High-Luminosity Large Hadron Collider (HL-LHC) will require advanced reconstruction techniques, particularly in the forward region, to cope with increased pile-up. This work presents a Particle Flow Algorithm (PFA) development for the ITk detector, focusing on tower clusters rather than traditional topological clusters in the η = ⟨0 − 1.5⟩ region. The forward region indicates η = ⟨2 − 4⟩. The strategy integrates tracker momentum measurements with calorimeter energy deposits through cell-based subtraction, prioritising energy density layers to resolve overlaps between tracking and calorimetric data. By employing tower clusters, which aggregate calorimeter cells into fixed η × ϕ grids, we aim to improve computational efficiency while maintaining spatial granularity critical for forward jet reconstruction. The framework processes Event Summary Data (ESD), containing raw detector-level information (tracker hits, calorimeter clusters), and it is processed into Analysis Object Data (AOD), a condensed format storing high-level physics objects (jets, leptons) optimised for analysis. The algorithm refines energy subtraction and calibration by implementing Gaussian fitting of ⟨E/p⟩ distributions across calorimeter layers, mitigating pile-up effects in the forward region. This approach addresses the high-pileup HL-LHC environment, balancing precision in jet energy resolution with computational scalability for the ITk detector’s upgraded granularity.