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 more powerful beam collider, operating with 13~TeV of energy collision and 25~ns of bunch-crossing interval. A Toroidal LHC AparatuS (ATLAS) is the largest LHC experiment, composed by several subsystems that merge their information to reconstruct each collision. When collisions occur, subproducts are produced and measured by complex devices such as the calorimeter system that absorbs and samples the energy from these subproducts. Typically, a high-energy calorimeter is highly segmented, comprising thousands of dedicated readout channels. The present work evaluates the performance of two algorithms that operate in the ATLAS Tile Calorimeter (TileCal): the OF2 (Optimal Filter) and COF (Constrained Optimal Filter), which was recently proposed to deal with the signal superposition (pile-up) that is present in LHC operation at high subparticle generation rates (high-luminosity). 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 estimation error 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, which is currently employed in the TileCal system.