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arXiv · 1506.07876

Separated at Birth: Jet Maximization, Axis Minimization, and Stable Cone Finding

Jesse Thaler
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Abstract

Jet finding is a type of optimization problem, where hadrons from a high-energy collision event are grouped into jets based on a clustering criterion. As three interesting examples, one can form a jet cluster that (1) optimizes the overall jet four-vector, (2) optimizes the jet axis, or (3) aligns the jet axis with the jet four-vector. In this paper, we show that these three approaches to jet finding, despite being philosophically quite different, can be regarded as descendants of a mother optimization problem. For the special case of finding a single cone jet of fixed opening angle, the three approaches are genuinely identical when defined appropriately, and the result is a stable cone jet with the largest value of a quantity J. This relationship is only approximate for cone jets in the rapidity-azimuth plane, as used at the Large Hadron Collider, though the differences are mild for small radius jets.

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Jesse Thaler. 2015-06-25. Separated at Birth: Jet Maximization, Axis Minimization, and Stable Cone Finding. https://doi.org/10.1103/physrevd.92.074001

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