Better Jet Clustering Algorithms
Yu. L. Dokshitzer, G. D. Leder, S. Moretti, B. R. Webber
Abstract
We investigate modifications to the k-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.
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