Better Jet Clustering Algorithms

TL;DR

The paper investigates improvements to JADE-type jet clustering, focusing on the Durham $k_ot$ algorithm, to reduce non-perturbative corrections while preserving infrared safety. It introduces two refinements: angular ordering (A) by separating the clustering order from the test, and soft freezing (C) to prevent mis-clustering of soft wide-angle radiation. Fixed-order and resummed analyses show that A shifts some three-jet configurations toward two jets and C further redistributes rates to four jets, with improved scale stability. Monte Carlo studies with HERWIG confirm reduced hadronization effects for A and especially C, particularly at small $y_{ ext{cut}}$, validating their practical advantage for probing perturbative/non-perturbative QCD interfaces. Collectively, the results support adopting the Cambridge algorithm as a robust, lower-correction alternative to the original Durham scheme.

Abstract

We investigate modifications to the $k_\perp$-clustering jet algorithm which preserve the advantages of the original Durham algorithm while reducing non-perturbative corrections and providing better resolution of jet substructure. We find that a simple change in the sequence of clustering (combining smaller-angle pairs first), together with the `freezing' of soft resolved jets, has beneficial effects.