Reconstruction of unconverted photons in the presence of high pileup at the CMS Phase-2 High Granularity Endcap Calorimeter

The CMS Collaboration foresees the installation of a novel endcap calorimeter, named High-Granularity CALorimeter (HGCAL), to sustain the harsher conditions of the High-Luminosity LHC (HL-LHC). The new calorimeter will predominantly use silicon sensors to achieve sufficient radiation tolerance and will exploit highly granular information to achieve high performance object reconstruction and mitigate the effects of the pile up. These sensors will sample the electromagnetic and hadronic particle showers with fine lateral granularity and provide 5D measurements of energy, position, and timing. A versatile reconstruction framework (TICL: The Iterative CLustering) is being developed within the CMS Software CMSSW to fully exploit the features of the novel detector, such as its granularity and precise timing. To attain maximal flexibility, TICL allows the composition of different combinations of modules that can be chained together as a reconstruction step, to form one iteration of TICL. In view of the expected pressure on the computing capacity in the HL-LHC era, the algorithms and their data structures are designed to be executed on GPUs. A new version of TICL (TICLv4) has been recently released with many improvements, including a new pattern recognition algorithm with the purpose of a more robust reconstruction of particle showers in the detector. In the high-pile up environment expected at the HL-LHC, reconstructed showers can have additional contamination from pile up attached to them, leading to the need of an algorithm to clean them. The note will focus on the performance of the electromagnetic reconstruction of TICLv4 in presence of pile up with a specific focus on the cleaning algorithm.