Probing heavy ion collisions using quark and gluon jet substructure with machine learning

TL;DR

This paper explores how machine learning and advanced jet substructure techniques can distinguish quark and gluon jets in heavy ion collisions, revealing medium effects on jet properties and improving understanding of quark-gluon plasma.

Contribution

It introduces the telescoping deconstruction framework and applies deep learning to classify jets, providing new tools for probing medium modifications in heavy ion collisions.

Findings

Quark-gluon discrimination performance decreases in heavy ion collisions due to soft radiation.

TD observables reveal fundamental properties of jet modifications in medium.

Deep CNNs benchmark jet classification performance in complex environments.

Abstract

Understanding the inner working of the quark-gluon plasma requires complete and precise jet substructure studies in heavy ion collisions. In this proceeding we discuss the use of quark and gluon jets as independent probes, and how their classification allows us to uncover regions of QCD phase space sensitive to medium dynamics. We introduce the telescoping deconstruction (TD) framework to capture complete jet information and show that TD observables reveal fundamental properties of quark and gluon jets and their modifications in the medium. We draw connections to soft-drop subjet distributions and illuminate medium-induced jet modifications using Lund diagrams. The classification is also studied using a physics-motivated, multivariate analysis of jet substructure observables. Moreover, we apply image-recognition techniques by training a deep convolutional neural network on jet images to benchmark classification performances. We find that the quark gluon discrimination performance worsens in \textsc{Jewel}-simulated heavy ion collisions due to significant soft radiation affecting soft jet substructures. This work suggests a systematic framework for jet studies and facilitates direct comparisons between theoretical calculations and measurements in heavy ion collisions.