A third level trigger programmable on FPGA for the gamma/hadron separation in a Cherenkov telescope using pseudo-Zernike moments and the SVM classifier

TL;DR

This paper presents a FPGA-implemented third-level trigger for gamma/hadron separation in Cherenkov telescopes, utilizing pseudo-Zernike image features and SVM classification to improve discrimination accuracy.

Contribution

It introduces a novel FPGA-based implementation of an SVM classifier using pseudo-Zernike features for gamma/hadron separation in Cherenkov telescope data.

Findings

Successful FPGA implementation of the SVM kernel with pseudo-Zernike features

Enhanced gamma/hadron discrimination capability in the MAGIC Experiment

Real-time processing potential for Cherenkov telescope triggers

Abstract

We studied the application of the Pseudo-Zernike features as image parameters (instead of the Hillas parameters) for the discrimination between the images produced by atmospheric electromagnetic showers caused by gamma-rays and the ones produced by atmospheric electromagnetic showers caused by hadrons in the MAGIC Experiment. We used a Support Vector Machine as classification algorithm with the computed Pseudo-Zernike features as classification parameters. We implemented on a FPGA board a kernel function of the SVM and the Pseudo-Zernike features to build a third level trigger for the gamma-hadron separation task of the MAGIC Experiment.