Work

Disentangling Clustering Effects in Jet Algorithms

Year: 2012
Type: preprint
Abstract: Clustering algorithms build jets though the iterative application of single particle and pairwise metrics. This leads to phase space constraints that are extremely complicated beyond the lowest orders in perturbation theory, and in practice they must be implemented numerically. This complication presents a significant barrier to gaining an analytic understanding of the perturbative structure of jet cross sections. We present a novel framework to express the jet algorithm's phase space constraints as a function of clustered groups of particles, which are the possible outcomes of the algorithm. This approach highlights the analytic properties of jet observables, rather than the explicit constraints on individual final state momenta, which can be unwieldy at higher orders. We derive the form of the n-particle phase space constraints for a jet algorithm with any measurement. We provide an expression for the measurement that makes clustering effects manifest and relates them to constraints from clustering at lower orders. The utility of this framework is demonstrated by using it to understand clustering effects for a large class of jet shape observables in the soft/collinear limit. We apply this framework to isolate divergences and analyze the logarithmic structure of the Abelian terms in the soft function, providing the all-orders form of these terms and showing that corrections from clustering start at next-to-leading logarithmic order in the exponent of the cross section.
Language: English
Open Access status: green
OpenAlex ID: W24884274
Cites: 28
Cited by: 17
Related to: 10