Speaker
Description
The reconstruction of electrons and photons in ATLAS, produced from proton-proton collisions at the Large Hadron Collider (LHC), is based on the performance of the Topo-Clustering algorithm developed for electron and photon reconstruction in Run-4. To extract the signal, the algorithm reconstructs three-dimensional energy deposits in the calorimeter by grouping neighbouring cells with signal significance exceeding a noise threshold that depends on the number of pile-up interactions in the event. This approach retains cells with signals near the noise level while maintaining effective noise suppression. The resulting topo-clusters provide information on the shape and location of the energy deposits. Electrons are matched to the topo-clusters from the inner detector tracks and are corrected for the energy lost as they pass through the detector. For a photon, the conversion vertex (where they convert into an electron-positron pair) is matched to the topo-clusters. As a result, the electron and photon objects are reconstructed with their energies calibrated and initial positions corrected. This research investigates the impact of increased pile-up levels of up to 200 simultaneous interactions on the performance of the clustering algorithms, and consequently on electron and photon reconstruction performance.