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T: Fachverband Teilchenphysik

T 103: Methods in Particle Physics V (Event Reconstruction, PID)

T 103.3: Vortrag

Freitag, 4. April 2025, 09:30–09:45, VG 4.101

Machine Learning Assisted Reconstruction of Hadron-Collider Events using Mini-Jets — •Josef Murnauer¹, Stefan Kluth¹, Daniel Britzger¹, and Roman Kogler² — ¹Max-Planck-Institut für Physik, Garching — ²DESY, Hamburg

Reconstructing impactful physical observables from hadron collider data represents challenges due to combinatorial ambiguities and experimental effects. We propose a novel approach using mini-jets (R=0.1) as the sole reconstructed objects, employing a deep neural network for observable determination. This method condenses full event information into a manageable size, demonstrating superior efficiency and generality compared to classical algorithms for future LHC analyses.

Keywords: Machine Learning; Top Quark Physics; Reconstruction