Embedding graphs in non-Euclidean geometries
The mathematics of embeddings of graphs in non-Euclidean geometric spaces.
Most network visualization methods essentially embed graphs in either 2 or 3 dimensional Euclidean spaces (although hyperbolic spaces have been used in a minor way). The aim of the visualization mapping is to choose an embedding that optimizes one or more of a set of criteria, such as:a. Minimizing the number of edge crossingsb. Maximizing resolutionc. Maximizing symmetryThis project aims to make a mathematical study of embeddings of graphs in non-Euclidean spaces, using analogues of the usual visualization criteria for Euclidean embeddings. In particular, we will study embeddings in finite geometries.
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The opportunity ID for this research opportunity is: 399
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