Signal Reconstruction in ATLAS Tile Calorimeter using Run 3 Real Data and Perspectives for the Phase-II Operation

The Tile Barrel Calorimeter (TileCal) is the central section of the hadronic calorimeter of ATLAS at LHC. It comprises approximately 10,000 readout channels where the energy deposited in each channel is read out and the analog pulse is conditioned by a shaper circuit. The output signal is sampled at 40 MHz and the energy is estimated by reconstructing its amplitude through an optimal filtering (OF) algorithm, which performs a dot product operation between the incoming time samples and the OF weights. During Run 3, LHC operates with an average number of interactions per bunch crossing of around 60, producing a significant pile-up effect in the TileCal readout channels. Currently, the OF version used in TileCal does not take into account the signal pile-up information. Therefore, its performance is degraded in pile-up conditions, especially in the most exposed channels. However, the OF method envisages the use of the noise covariance matrix in its optimization procedure which reduces the uncertainties and bias due to the pile-up. Therefore, this work presents a study on the impact of using the signal pile-up information in the optimization procedure that computes the OF weights. For performance evaluation, a comparison with the current OF version is carried out using real data acquired during LHC Run 3 operation. The results show that, depending on the channel occupancy level, an improvement up to 20 % can be achieved when the optimized version of the OF method is used. Furthermore, perspectives for the signal reconstruction task considering the new signal chain scheme foreseen for LHC phase-II operation is described.