Optimal Vertex-Cut Sparsification of Quasi-Bipartite Graphs

July 04, 2022 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Itai Boneh, Robert Krauthgamer arXiv ID 2207.01459 Category cs.DS: Data Structures & Algorithms Citations 2 Venue arXiv.org Last Checked 4 months ago
Abstract
In vertex-cut sparsification, given a graph $G=(V,E)$ with a terminal set $T\subseteq V$, we wish to construct a graph $G'=(V',E')$ with $T\subseteq V'$, such that for every two sets of terminals $A,B\subseteq T$, the size of a minimum $(A,B)$-vertex-cut in $G'$ is the same as in $G$. In the most basic setting, $G$ is unweighted and undirected, and we wish to bound the size of $G'$ by a function of $k=|T|$. Kratsch and WahlstrΓΆm [JACM 2020] proved that every graph $G$ (possibly directed), admits a vertex-cut sparsifier $G'$ with $O(k^3)$ vertices, which can in fact be constructed in randomized polynomial time. We study (possibly directed) graphs $G$ that are quasi-bipartite, i.e., every edge has at least one endpoint in $T$, and prove that they admit a vertex-cut sparsifier with $O(k^2)$ 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 $\tildeΞ©(k^2)$ edges are required to sparsify quasi-bipartite undirected graphs.
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