Dynamic $(1+\epsilon)$-Approximate Matching Size in Truly Sublinear Update Time

TL;DR

This paper introduces a fully dynamic algorithm that maintains a near-accurate estimate of maximum matching size in graphs with significantly improved update times, solving a longstanding open problem.

Contribution

It presents the first polynomial improvement over the $O(n)$ update time for approximate maximum matching size in dynamic graphs, with a novel sublinear algorithm for dense graphs.

Findings

Achieves $m^{0.5- ext{constant}}$ update time for approximate matching size

First sublinear algorithm for $(1, ext{epsilon} n)$-approximate maximum matching on dense graphs

Resolves a major open question in dynamic graph algorithms

Abstract

We show a fully dynamic algorithm for maintaining $(1+\epsilon)$-approximate \emph{size} of maximum matching of the graph with $n$ vertices and $m$ edges using $m^{0.5-\Omega_{\epsilon}(1)}$ update time. This is the first polynomial improvement over the long-standing $O(n)$ update time, which can be trivially obtained by periodic recomputation. Thus, we resolve the value version of a major open question of the dynamic graph algorithms literature (see, e.g., [Gupta and Peng FOCS'13], [Bernstein and Stein SODA'16],[Behnezhad and Khanna SODA'22]). Our key technical component is the first sublinear algorithm for $(1,\epsilon n)$-approximate maximum matching with sublinear running time on dense graphs. All previous algorithms suffered a multiplicative approximation factor of at least $1.499$ or assumed that the graph has a very small maximum degree.