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High energy experimental data can be viewed as a sampling of the relevant phase space. We point out that one can apply Voronoi tessellations in order to understand the underlying probability distributions governing the relevant phenomena. Characteristic features embedded in the data can then be discovered by studying the properties of Voronoi cells. We particularly focus on detecting kinematic “edges”, taking the examples of two- and three-dimensional data for concreteness. To this end, we propose algorithms motivated by some analytic results derived for perfect lattices, and show that the relevant methods can be further improved with the addition of a few Voronoi relaxation steps via Lloyd’s method.

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