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Abstract

In Run 3 of the LHC, the LHCb experiment faces megahertz-rates of data containing beauty and charm hadron decays. Thus the task of the trigger is not to select any beauty and charm events but to select specific beauty and charm decays interesting for the LHCb physics programme. LHCb has therefore implemented a real-time data analysis strategy to trigger directly on fully-reconstructed events. This is done in two software-trigger stages, the first of which performs a partial event reconstruction on GPUs, while the second stage reconstructs the full event with offline quality on CPUs. This thesis describes LHCb’s CPU-based track reconstruction for Run 3, highlighting the Forward tracking, which is the algorithm that reconstructs trajectories of charged particles traversing the entire tracking system. It is shown that using the capabilities of modern CPUs, the event throughput of the Forward tracking is improved by a factor of 3.5 while reaching reconstruction efficiencies of more than 95% for tracks above 5 GeV/c originating from a B meson.