Optimal Vertex-Cut Sparsification of Quasi-Bipartite Graphs

preprint2022arXivOpen access

Abstract

In vertex-cut sparsification, given a graph G=(V,E)G=(V,E) with a terminal set T⊆VT\subseteq V, we wish to construct a graph G′=(V′,E′)G'=(V',E') with T⊆V′T\subseteq V', such that for every two sets of terminals A,B⊆TA,B\subseteq T, the size of a minimum (A,B)(A,B)-vertex-cut in G′G' is the same as in GG. In the most basic setting, GG is unweighted and undirected, and we wish to bound the size of G′G' by a function of k=∣T∣k=|T|. Kratsch and Wahlström [JACM 2020] proved that every graph GG (possibly directed), admits a vertex-cut sparsifier G′G' with O(k3)O(k^3) vertices, which can in fact be constructed in randomized polynomial time. We study (possibly directed) graphs GG that are quasi-bipartite, i.e., every edge has at least one endpoint in TT, and prove that they admit a vertex-cut sparsifier with O(k2)O(k^2) edges and vertices, which can in fact be constructed in deterministic polynomial time. In fact, this bound naturally extends to all graphs with a small separator into bounded-size sets. Finally, we prove information-theoretically a nearly-matching lower bound, i.e., that Ω~(k2)\tildeΩ(k^2) edges are required to sparsify quasi-bipartite undirected graphs.

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