Decremental Matching in General Graphs

Abstract

We consider the problem of maintaining an approximate maximum integral matching in a dynamic graph $G$, while the adversary makes changes to the edges of the graph. The goal is to maintain a $(1+\hat{I}\mu )$-approximate maximum matching for constant $\hat{I}\mu >0$, while minimizing the update time. In the fully dynamic setting, where both edge insertion and deletions are allowed, Gupta and Peng (see \cite{GP13}) gave an algorithm for this problem with an update time of $O(\sqrt{m}/\hat{I}{\mu }^2)$. Motivated by the fact that the $O_{\hat{I}}\mu (\sqrt{m})$ barrier is hard to overcome (see Henzinger, Krinninger, Nanongkai, and Saranurak [HKNS15]); Kopelowitz, Pettie, and Porat [KPP16]), we study this problem in the \emph{decremental} model, where the adversary is only allowed to delete edges. Recently, Bernstein, Probst-Gutenberg, and Saranurak (see [BPT20]) gave an $O_{\hat{I}}\mu (1)$ update time decremental algorithm for this problem in \emph{bipartite graphs}. However, beating $O(\sqrt{m})$ update time remained an open problem for \emph{general graphs}. In this paper, we bridge the gap between bipartite and general graphs, by giving an $O_{\hat{I}}\mu (1)$ update time algorithm that maintains a $(1+\hat{I}\mu )$-approximate maximum integral matching under adversarial deletions. Our algorithm is randomized, but works against an adaptive adversary. Together with the work of Grandoni, Leonardi, Sankowski, Schwiegelshohn, and Solomon [GLSSS19] who give an $O_{\hat{I}}\mu (1)$ update time algorithm for general graphs in the \emph{incremental} (insertion-only) model, our result essentially completes the picture for partially dynamic matching.

33 pages, 2 figures; comments welcome