Abstract

The LHCb experiment is dedicated to searching for New Physics effects in the heavy flavour sector, precise measurements of CP violation and rare heavy meson decays. Precise tracking and vertexing around the interaction point is crucial in achieving these physics goals. The LHCb VELO (VErtex LOcator) silicon detector is the highest precision vertex detector at the LHC and is located at only 8 mm from the proton beams. The high spatial point precision (up to 4 μm single hit precision) is facilitated by a complex chain of processing algorithms to suppress noise and reconstruct clusters. These are implemented in FPGAs, with over one million individually optimised parameters. A novel approach has been developed to optimise the parameters, integrating their determination into the full software framework of the LHCb experiment. While FPGAs are commonly used in HEP, their parameters are typically set by standalone software. However, the VELO complex processing chain would only achieve optimal performance and full sensitivity monitoring through optimisation integrated with the full reconstruction framework of the experiment. This off-line software framework performs a bit perfect emulation of the FPGAs hardware processing, and is fully integrated into the LHCb software, rather than standalone. The software platform facilitates: developing and understanding the behaviour of the processing algorithms; optimizing the parameters of the algorithms that will be loaded into the FPGAs; and monitoring the performance of the detector. This framework has also been adopted by the Silicon Tracker detector of LHCb. This novel approach has been successfully applied to the collision data taken in 2010 by the LHCb experiment. The initial calibration of the VELO detector has been performed using the emulation suite. The software is used to monitor the noise of the detector, pedestals stability, hit reconstruction performance and other detector parameters.

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