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Electronic Journal of Combinatorics
Article . 2024 . Peer-reviewed
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Article . 2024
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https://dx.doi.org/10.48550/ar...
Article . 2024
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Article . 2024
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Note on the Spectra of Steiner Distance Hypermatrices

Note on the spectra of Steiner distance hypermatrices
Authors: Joshua Cooper 0002; Zhibin Du;

Note on the Spectra of Steiner Distance Hypermatrices

Abstract

The Steiner distance of a set of vertices in a graph is the fewest number of edges in any connected subgraph containing those vertices. The order-$k$ Steiner distance hypermatrix of an $n$-vertex graph is the $n \times \cdots \times n$ ($k$ terms) array indexed by vertices, whose entries are the Steiner distances of their corresponding indices. In the case of $k=2$, this reduces to the classical distance matrix of a graph. Graham and Pollak showed in 1971 that the determinant of the distance matrix of a tree only depends on its number $n$ of vertices. Here, we show that the hyperdeterminant of the Steiner distance hypermatrix of a tree vanishes if and only if (a) $n \geq 3$ and $k$ is odd, (b) $n=1$, or (c) $n=2$ and $k \equiv 1 \pmod{6}$. Two proofs are presented of the $n=2$ case - the other situations were handled previously - and we use the argument further to show that the distance spectral radius for $n=2$ is equal to $2^{k-1}-1$. Some related open questions are also discussed.

Keywords

Distance in graphs, Graphs and linear algebra (matrices, eigenvalues, etc.), FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), G.2.2, 05C12 (Primary) 05C50, 15A69 (Secondary), Enumeration in graph theory, distance spectral radius

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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