Abstract
We consider the problem of maintaining an approximate maximum integral matching in a dynamic graph , while the adversary makes changes to the edges of the graph. The goal is to maintain a -approximate maximum matching for constant , 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 . Motivated by the fact that the 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 update time decremental algorithm for this problem in \emph{bipartite graphs}. However, beating 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 update time algorithm that maintains a -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 update time algorithm for general graphs in the \emph{incremental} (insertion-only) model, our result essentially completes the picture for partially dynamic matching.
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