New Deterministic Approximation Algorithms for Fully Dynamic Matching
  We present two deterministic dynamic algorithms for the maximum matching problem. (1) An algorithm that maintains a $(2+\epsilon)$-approximate maximum matching in general graphs with $O(\text{poly}(\log n, 1/\epsilon))$ update time. (2) An algorithm that maintains an $\alpha_K$ approximation of the {\em value} of the maximum matching with $O(n^{2/K})$ update time in bipartite graphs, for every sufficiently large constant positive integer $K$. Here, $1\leq \alpha_K < 2$ is a constant determined by the value of $K$. Result (1) is the first deterministic algorithm that can maintain an $o(\log n)$-approximate maximum matching with polylogarithmic update time, improving the seminal result of Onak et al. [STOC 2010]. Its approximation guarantee almost matches the guarantee of the best {\em randomized} polylogarithmic update time algorithm [Baswana et al. FOCS 2011]. Result (2) achieves a better-than-two approximation with {\em arbitrarily small polynomial} update time on bipartite graphs. Previously the best update time for this problem was $O(m^{1/4})$ [Bernstein et al. ICALP 2015], where $m$ is the current number of edges in the graph. 
Sayan Bhattacharya and Monika Henzinger and Danupon Nanongkai
cs.DS