Quantifying the performance of jet algorithms at LHC

TL;DR

This paper introduces a method to evaluate the effectiveness of jet clustering algorithms at the LHC, focusing on reconstructing heavy particle decays and optimizing algorithm choices.

Contribution

It presents a new strategy for quantifying jet algorithm performance, including robustness against pileup, with applications to hypothetical heavy particle decays.

Findings

Optimal jet algorithm parameters identified for Z' and Higgs decays.

Performance estimates remain stable under high-luminosity pileup.

Method provides a systematic way to compare jet algorithms.

Abstract

In the present contribution we introduce a strategy to quantify the performance of modern infrared and collinear safe jet clustering algorithms in processes which involve the reconstruction of heavy object decays. We determine optimal choices for fictional narrow $Z'\to q\bar{q}$ and $H\to gg$ over a range of masses, providing examples of simple quark-jet and gluon-jet samples respectively. We show also that our estimates are robust against the presence of high-luminosity pileup.