2024/10/16 by J. Kvita, P. Baroň, Kvita, Jiří +9 · 1 citation
Physics and Astronomy · #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #High-Energy Particle Collisions Research #Quantum Chromodynamics and Particle Interactions
paper · pdf · doi:10.48550/arxiv.2410.13904
openalex publication_date 2024/10/16 · openalex created_date 2024/11/02 · openalex updated_date 2026/07/28
We apply both cut-based and machine learning techniques using the same inputs to the challenge of hadronic jet substructure recognition, utilizing classical subjettiness variables within the Delphes parameterized detector simulation framework. We focus on jets generated in simulated proton-proton collisions, identifying those consistent with the decay signatures of top quarks or W bosons. Such jets are employed in four-top quark events in fully hadronic final states stemming from both the Standard Model as well as from a new physics process of a hypothetical scalar resonance y0 decaying into a pair of top quarks. We reconstruct the resonance invariant mass and compare it properties over the falling background using the two tagging approaches, with implications to LHC searches.