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We report on the performances of a prototype for a specialized processor capable of reconstructing charged-particle tracks in a realistic Large Hadron Collider (LHC) detector, at full readout speed and with sub-microsecond latency. The processor is based on an innovative pattern recognition, called “artificial retina” algorithm, inspired by the vision system of the mammals. A prototype system has...
We present the first results of the prototype of a silicon tracker with trigger capabilities based on a novel approach for fast track finding. The working principle of the "artificial retina" is inspired by the processing of visual images by the brain and it is based on extensive parallelisation of data distribution and pattern recognition. The algorithm has been implemented in commercial...
We present the design for the first prototype of a tracking system with “artificial retina” for fast track finding. The “artificial retina” is a tracking algorithm inspired by neurobiology and based on extensive parallelization of data distribution and pattern recognition. It allows track finding with a latency < 1 µs and with track parameter resolutions that are comparable with offline reconstruction...
As the LHC luminosity is ramped up to 3×1034 cm-2 s-1 and beyond, the high rates, multiplicities, and energies of particles seen by the detectors will pose a unique challenge. Only a tiny fraction of the produced collisions can be stored on tape and immense real-time data reduction is needed. An effective trigger system must maintain high trigger efficiencies for the physics we are most interested...
The fast track processor (FTK) has been proposed for high-quality track finding at very high rates (level-1 output rates) for the LHC experiments. Fast, efficient and precise pattern recognition has been studied using a silicon 6-layer sub-detector, including a subset of the pixel and SCT layers. We tested the FTK algorithms using the ATLAS full simulation. We compare the FTK reconstruction quality...
The silicon vertex trigger (SVT) in the CDF experiment at Fermilab performs fast and precise track finding and fitting at the second trigger level and has been a crucial element in data acquisition for Run II physics. However as luminosity rises, multiple interactions increase the complexity of events and thus the SVT processing time, reducing the amount of data CDF can record. The SVT upgrade aims...
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