The Iterative Clustering framework for the CMS HGCAL Reconstruction

Abstract To sustain the harsher conditions of high-luminosity LHC [1], CMS Collaboration [2] is designing a novel endcap calorimeter system [3]. The new will predominantly use silicon sensors to achieve sufficient radiation tolerance and maintain highly granular information in readout help mitigate effects pile up. In regions characterized by lower levels, small scintillator tiles with individual SiPM on-tile are employed. A unique reconstruction framework (TICL: Iterative CLustering) being developed within Software CMSSW fully exploit granularity other significant detector features, such as particle identification precision timing, view mitigating up very dense environment HL-LHC. TICL has been thought heterogeneous computing mind: algorithms their data structures designed be executed on GPUs. addition, geometry agnostic have provide fast navigation searching capabilities. Seeding capabilities (also exploiting coming from detectors), dynamic cluster masking, energy calibration, main components framework. allow for maximal flexibility, allows composition different combinations modules that can chained together an iterative fashion.