Telescoping Jets: Multiple Event Interpretations with Multiple R's

Abstract

Jets at high energy colliders are complicated objects to identify. Even if jets are widely separated, there is no reason for jets to have the same size. A single reconstruction, or interpretation, of each event can only extract a limited amount of information. Motivated by the recently proposed Qjet algorithms, which give multiple interpretations for each event using nondeterministic jet clustering, we propose a simple, fast and powerful method to give multiple event interpretations by varying the parameter R in the jet definition. With multiple interpretations we can redefine the weight of each event in a counting experiment to be the fraction of interpretations passing the experimental cuts, instead of 0 or 1 in a conventional analysis. We show that the statistical power of an analysis can be dramatically increased. In particular, we can have a 46% improvement in the statistical significance for the Higgs search with an associated Z boson (ZH\rightarrow ν{\bar ν}b {\bar b}) at the 8 TeV LHC.

4 pages, 6 figures, 1 table

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• PYTHIA 6.4 Physics and Manual
• Jet substructure as a new Higgs search channel at the LHC
• Top-tagging: A Method for Identifying Boosted Hadronic Tops
• Techniques for improved heavy particle searches with jet substructure
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• Probing heavy ion collisions using quark and gluon jet substructure with machine learning
• Parameter Inference from Event Ensembles and the Top-Quark Mass
• Deep Learning Jet Substructure from Two-Particle Correlation
• Telescoping jet substructure
• Augmenting Collider Searches and Enhancing Discovery Potentials through Stochastic Jet Grooming
• Heavy ion jet physics studies using precision jet substructure and quark-gluon jet classification