Energy Reconstruction Performance in the ATLAS Tile Calorimeter Operating at High Event Rate Conditions Using LHC Collision Data

The discovery of particles that shape our universe pushes the scientific community to increasingly build sophisticated equipments. Particle accelerators are one of these complex machines that put known particle beams on a collision course at speeds close to that of light. The Large Hadron Collider (LHC) is the world's largest and most powerful beam collider, operating with 13~TeV of energy collision and 25~ns of bunch-crossing interval. ATLAS is the largest LHC experiment, comprising several subsystems which provide data fusion to reconstruct each collision. When collisions occur, subproducts are produced and measured by the calorimeter system, which absorbs these subproducts. Typically, a high-energy calorimeter is highly segmented, comprising thousands of dedicated readout channels. The present work evaluates the performance of two cell energy reconstruction algorithms that operate in the ATLAS Tile Calorimeter (TileCal): the baseline algorithm OF2 (Optimal Filter) and COF (Constrained Optimal Filter), which was recently proposed to deal with the signal superposition (pile-up) that is, increscent, present in LHC operation. In order to evaluate the energy estimation efficiency, real data acquired during the nominal LHC operation at high luminosity condition were used. The statistics from the energy estimation is employed to compare the performance achieved by each method. The results show that the COF method presents a better performance than the OF2 method, pointing out benefits from using this alternative estimation method.