We make several advances broadly related to the maintenance of electrical flows in weighted graphs undergoing dynamic resistance updates, including: 1. More efficient dynamic spectral vertex sparsification, achieved by faster length estimation of random walks in weighted graphs using Morris counters [Morris 1978, Nelson-Yu 2020]. 2. A direct reduction from detecting edges with large energy in dynamic electric flows to dynamic spectral vertex sparsifiers. 3. A procedure for turning algorithms for estimating a sequence of vectors under updates from an oblivious adversary to one that tolerates adaptive adversaries via the Gaussian-mechanism from differential privacy. Combining these pieces with modifications to prior robust interior point frameworks gives an algorithm that on graphs with $m$ edges computes a mincost flow with edge costs and capacities in $[1, U]$ in time $\widetilde{O}(m^{3/2-1/58} \log^2 U)$. In prior and independent work, [Axiotis-M\k{a}dry-Vladu FOCS 2021] also obtained an improved algorithm for sparse mincost flows on capacitated graphs. Our algorithm implies a $\widetilde{O}(m^{3/2-1/58} \log U)$ time maxflow algorithm, improving over the $\widetilde{O}(m^{3/2-1/328}\log U)$ time maxflow algorithm of [Gao-Liu-Peng FOCS 2021].
翻译:我们取得了与维持正在动态阻力更新的加权图中电流有关的若干进展,其中包括:1. 使用Morris counts[1978年,纳尔逊-尤尔2020年]对加权图中的随机行走进行更快的长度估计,从而实现更高效的动态光谱顶点封闭。 2. 从探测动态电流中具有巨大能量的边缘直接减少至动态光谱顶点封闭器。3. 将估算矢量序列的算法从一个模糊的对数转换为一个从一个模糊的对数到一个从不同隐私的高山机能中容忍适应对手的程序。将这些片段与先前稳健健的内点框架合并起来,在以美元边缘计算一个小成本流的算法,以$(1, U1, U) (m3/2-58/58}\log%2美元。在以前和独立的工作中,[Axiotiti-Pr_Mlus-Vladu FOS 2021] 也获得了一个改进的时序算法。