Near-linear Size Hypergraph Cut Sparsifiers

Yu Chen; Sanjeev Khanna; Ansh Nagda

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arXiv · 2009.04992

Near-linear Size Hypergraph Cut Sparsifiers

Yu Chen·Sanjeev Khanna·Ansh Nagda

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Abstract

Cuts in graphs are a fundamental object of study, and play a central role in the study of graph algorithms. The problem of sparsifying a graph while approximately preserving its cut structure has been extensively studied and has many applications. In a seminal work, Bencz\'ur and Karger (1996) showed that given any $n$-vertex undirected weighted graph $G$ and a parameter $\varepsilon \in (0,1)$, there is a near-linear time algorithm that outputs a weighted subgraph $G'$ of $G$ of size $\tilde{O}(n/\varepsilon^2)$ such that the weight of every cut in $G$ is preserved to within a $(1 \pm \varepsilon)$-factor in $G'$. The graph $G'$ is referred to as a {\em $(1 \pm \varepsilon)$-approximate cut sparsifier} of $G$. A natural question is if such cut-preserving sparsifiers also exist for hypergraphs. Kogan and Krauthgamer (2015) initiated a study of this question and showed that given any weighted hypergraph $H$ where the cardinality of each hyperedge is bounded by $r$, there is a polynomial-time algorithm to find a $(1 \pm \varepsilon)$-approximate cut sparsifier of $H$ of size $\tilde{O}(\frac{nr}{\varepsilon^2})$. Since $r$ can be as large as $n$, in general, this gives a hypergraph cut sparsifier of size $\tilde{O}(n^2/\varepsilon^2)$, which is a factor $n$ larger than the Bencz\'ur-Karger bound for graphs. It has been an open question whether or not Bencz\'ur-Karger bound is achievable on hypergraphs. In this work, we resolve this question in the affirmative by giving a new polynomial-time algorithm for creating hypergraph sparsifiers of size $\tilde{O}(n/\varepsilon^2)$.

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Yu Chen, Sanjeev Khanna, Ansh Nagda. 2020-09-10. Near-linear Size Hypergraph Cut Sparsifiers. https://arxiv.org/abs/2009.04992

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