Euclidean Embeddings of Acyclic Hypergraph Line Metrics
This paper studies Euclidean embeddings of higher-order line metrics arising from hypergraphs and improves the worst-case Euclidean distortion from Θ(log n) to Θ(√log log n) for α-acyclic hypergraphs.
This paper improves the worst-case Euclidean distortion for α-acyclic hypergraphs, which was not previously known.
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Applications
- →Computer networks
- →Data analysis
To understand this paper, make sure you know these concepts first:
- Graph theoryfind papers →
- Euclidean geometryfind papers →
Abstract
More Like ThisWe study Euclidean embeddings of higher-order line metrics arising from hypergraphs. For a fixed threshold \(s\geq 1\), the \(s\)-line graph \(L_s(H)\) has one vertex for each hyperedge of \(H\), with two hyperedges adjacent when they intersect in at least \(s\) vertices; its shortest-path metric is the native \(s\)-line metric. In the unrestricted setting, every finite graph occurs as the \(s\)-line graph of some hypergraph, so the worst-case Euclidean distortion is \(Θ(\log n)\). We show that \(α\)-acyclicity yields a sharp improvement to \(Θ(\sqrt{\log\log n})\). Although the canonical join tree of an \(α\)-acyclic hypergraph may have arbitrarily large stretch relative to the native metric, we prove that for every \(s\), the \(s\)-line graphs of \(α\)-acyclic hypergraphs are exactly the dually chordal graphs. Using their constant-factor spanning-tree approximations together with classical tree-embedding bounds, we obtain an \(O(\sqrt{\log\log n})\) Euclidean embedding bound. We then show this is asymptotically tight by realizing every finite tree as the \(s\)-line graph of an \(α\)-acyclic hypergraph. Thus, the worst-case distortion is \(Θ(\sqrt{\log\log n})\), including for hypergraphs of rank at most \(3s+1\).