Implementação em FPGA de Detectores Baseados em Filtragem Casada e Redes Neurais em Ambientes de Física Experimental de Altas Energias

Abstract

This work presents an implementation of two detection algorithms in FPGA in an experimental high energy physics environment, namely the hadronic calorimeter (TileCal) of the ATLAS detector at CERN. It focuses on the design of detectors based on a matched filter and an artificial neural network. The results show that the neural detector outperforms the matched filter for the considered application.