Quark and Gluon Tagging at the LHC

TL;DR

This paper investigates jet substructure observables at the LHC to distinguish light-quark jets from gluon jets, demonstrating that multivariate methods and simple variable combinations can achieve high discrimination efficiency.

Contribution

It introduces a comprehensive analysis of jet substructure variables and identifies effective multivariate and simple variable-based discriminants for quark-gluon tagging.

Findings

Multivariate approach filters out over 95% of gluon jets while retaining more than half of light-quark jets.

A combination of charge track multiplicity and girth achieves similar discrimination results.

Study is based on Monte Carlo simulations, with potential for improved real-data performance.

Abstract

Being able to distinguish light-quark jets from gluon jets on an event-by-event basis could significantly enhance the reach for many new physics searches at the Large Hadron Collider. Through an exhaustive search of existing and novel jet substructure observables, we find that a multivariate approach can filter out over 95% of the gluon jets while keeping more than half of the light-quark jets. Moreover, a combination of two simple variables, the charge track multiplicity and the $p_T$-weighted linear radial moment (girth), can achieve similar results. While this pair appears very promising, our study is only Monte Carlo based, and other discriminants may work better with real data in a realistic experimental environment. To that end, we explore many other observables constructed using different jet sizes and parameters, and highlight those that deserve further theoretical and experimental scrutiny. Additional information, including distributions of around 10,000 variables, can be found on this website http://jets.physics.harvard.edu/qvg .