Jet-Images: Computer Vision Inspired Techniques for Jet Tagging

TL;DR

This paper introduces a computer vision-inspired method for jet tagging in particle physics, using jet-images and Fisher discriminant analysis to improve classification of boosted W boson decays.

Contribution

It presents a novel jet-image technique and preprocessing methods, applying computer vision tools to enhance jet classification performance.

Findings

Improved discrimination between W boson jets and background jets.

Jet-image approach provides new insights into jet substructure.

Method outperforms existing substructure techniques.

Abstract

We introduce a novel approach to jet tagging and classification through the use of techniques inspired by computer vision. Drawing parallels to the problem of facial recognition in images, we define a jet-image using calorimeter towers as the elements of the image and establish jet-image preprocessing methods. For the jet-image processing step, we develop a discriminant for classifying the jet-images derived using Fisher discriminant analysis. The effectiveness of the technique is shown within the context of identifying boosted hadronic W boson decays with respect to a background of quark- and gluon- initiated jets. Using Monte Carlo simulation, we demonstrate that the performance of this technique introduces additional discriminating power over other substructure approaches, and gives significant insight into the internal structure of jets.