Online Track Vertex Reconstruction Method Based on an Artificial Neural Network for MPGD

Abstract

In this paper, an online vertex reconstruction algorithm based on an artificial neural network (ANN) was proposed for the micro-pattern gaseous detector (MPGD). A simulation based on Geant4 was performed to generate the training and testing samples for the two cascade neural networks. Compared with a center-of-mass reconstruction, the proposed method shows better precision and much higher efficiency. Furthermore, a scheme for implementing the proposed algorithm on a Field-Programmable Gate Array (FPGA) chip is also presented to demonstrate that the algorithm could be integrated in a modern data acquisition (DAQ) system for online imaging techniques.