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On the cut dimension of a graph

Published 10 Nov 2020 in cs.CC, cs.DS, and math.CO | (2011.05085v2)

Abstract: Let G=(V,w)G = (V,w) be a weighted undirected graph with mm edges. The cut dimension of GG is the dimension of the span of the characteristic vectors of the minimum cuts of GG, viewed as vectors in 0,1<sup>m{0,1}<sup>m. For every n≥2n \ge 2 we show that the cut dimension of an nn-vertex graph is at most $2n-3$, and construct graphs realizing this bound. The cut dimension was recently defined by Graur et al.\ \cite{GPRW20}, who show that the maximum cut dimension of an nn-vertex graph is a lower bound on the number of cut queries needed by a deterministic algorithm to solve the minimum cut problem on nn-vertex graphs. For every n≥2n\ge 2, Graur et al.\ exhibit a graph on nn vertices with cut dimension at least $3n/2 -2$, giving the first lower bound larger than nn on the deterministic cut query complexity of computing mincut. We observe that the cut dimension is even a lower bound on the number of \emph{linear} queries needed by a deterministic algorithm to solve mincut, where a linear query can ask any vector x∈R<sup>(n2)x \in \mathbb{R}<sup>{\binom{n}{2}} and receives the answer w<sup>T</sup>xw<sup>T</sup> x. Our results thus show a lower bound of $2n-3$ on the number of linear queries needed by a deterministic algorithm to solve minimum cut on nn-vertex graphs, and imply that one cannot show a lower bound larger than this via the cut dimension. We further introduce a generalization of the cut dimension which we call the ℓ1\ell_1-approximate cut dimension. The ℓ1\ell_1-approximate cut dimension is also a lower bound on the number of linear queries needed by a deterministic algorithm to compute minimum cut. It is always at least as large as the cut dimension, and we construct an infinite family of graphs on n=3k+1n=3k+1 vertices with ℓ1\ell_1-approximate cut dimension $2n-2$, showing that it can be strictly larger than the cut dimension.

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