Speaker
Nicola Neri
(Università degli Studi e INFN Milano (IT))
Description
We report on the status of the R&D of the first prototype of a silicon 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 real time tracking and can be designed to work for HEP applications, i.e. high rates and large detectors, providing offline-like track quality results with a sub-μs latency. The tracking system prototype consists of a telescope with 8 planes of single-sided silicon strip detectors that are readout using custom ASICs providing hit position and pulse height. The “artificial retina” algorithm has been implemented using commercial FPGAs and it is organized in three main blocks: a switch for the parallel distribution of the hits, a pool of processing units for the digital processing of the hits and pattern recognition, and a block for track parameter calculations. We will discuss the implementation of the “artificial retina” algorithm in the FPGAs, the performance of the device, and the first prototype results.
Author
Nicola Neri
(Università degli Studi e INFN Milano (IT))
