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We report on the R&D for a first prototype of a silicon tracker based on an alternative approach for fast track finding. The working principle is inspired from neurobiology, in particular by the processing of visual images by the brain as it happens in nature. It is based on extensive parallelisation of data distribution and pattern recognition. In this work we present the design of a practical device that consists of a telescope based on single-sided silicon detectors; we describe the data acquisition system and the implementation of the track finding algorithms using available digital logic of commercial FPGA devices. Tracking performance and trigger capabilities of the device are discussed along with perspectives for future applications.
We present the results of a detailed simulation of the artificial retina pattern-recognition algorithm, designed to reconstruct events with hundreds of charged-particle tracks in pixel and silicon detectors at LHCb with LHC crossing frequency of $40,
We present the results of an R&D study for a specialized processor capable of precisely reconstructing events with hundreds of charged-particle tracks in pixel and silicon strip detectors at $40,rm MHz$, thus suitable for processing LHC events at the
Real-time track tracking in high energy physics experiments at colliders running at high luminosity is very challenging for trigger systems. To perform pattern-recognition and track fitting in online trigger system, the artificial Retina algorithm ha
When testing and calibrating particle detectors in a test beam, accurate tracking information independent of the detector being tested is extremely useful during the offline analysis of the data. A general-purpose Silicon Beam Tracker (SBT) was const
We present results of an R&D study for a specialized processor capable of precisely reconstructing, in pixel detectors, hundreds of charged-particle tracks from high-energy collisions at 40 MHz rate. We apply a highly parallel pattern-recognition alg