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A. Piucci

Publications and source records attributed to A. Piucci.

5 recordsLinked to original sources

Simulation and performance of an artificial retina for 40 MHz track reconstruction

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 $40\,\rm MHz$. Performances of the artificial retina algorithm are assessed using the official Monte Carlo samples of the LHCb experiment. We found performances for the retina pattern-recognition algorithm comparable with the full LHCb reconstruction algorithm.

physics.ins-det

The artificial retina processor for track reconstruction at the LHC crossing rate

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 algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature, and describe in detail an efficient hardware implementation in high-speed, high-bandwidth FPGA devices. This is the first detailed demonstration of reconstruction of offline-quality tracks at 40 MHz and makes the device suitable for processing Large Hadron Collider events at the full crossing frequency.

physics.ins-det

The artificial retina for track reconstruction at the LHC crossing rate

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 full crossing frequency. For this purpose we design and test a massively parallel pattern-recognition algorithm, inspired to the current understanding of the mechanisms adopted by the primary visual cortex of mammals in the early stages of visual-information processing. The detailed geometry and charged-particle's activity of a large tracking detector are simulated and used to assess the performance of the artificial retina algorithm. We find that high-quality tracking in large detectors is possible with sub-microsecond latencies when the algorithm is implemented in modern, high-speed, high-bandwidth FPGA devices.

physics.ins-det

First prototype of a silicon tracker using an artificial retina for fast track finding

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.

physics.ins-det

A Specialized Processor for Track Reconstruction at the LHC Crossing Rate

We present the results of an R&D study of a specialized processor capable of precisely reconstructing events with hundreds of charged-particle tracks in pixel detectors at 40 MHz, thus suitable for processing LHC events at the full crossing frequency. For this purpose we design and test a massively parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature. We find that high-quality tracking in large detectors is possible with sub-$μ$s latencies when this algorithm is implemented in modern, high-speed, high-bandwidth FPGA devices. This opens a possibility of making track reconstruction happen transparently as part of the detector readout.

physics.ins-det