← 研踪 PaperTrailarXiv:2611.16313 · v1
Optimal-Size Strong Connectivity Preservers under Two Edge Failures in Subcubic Time
首次提交 2026-11-12 13:18
版本更新 2026-11-12 13:18
雷达观测 2026-11-13 14:16
摘要
A -edge-failure strong connectivity preserver of a directed graph on vertices is a spanning subgraph that has the same strongly connected components as the input after each set of at most edge deletions. The lower-bound construction of Baswana, Choudhary, and Roditty [BCR18], adapted to strong connectivity in [CC20], gives the previous best bound of necessary edges. Hoppenworth, Saranurak, and Wang [HSW25] prove an upper bound, leaving a logarithmic gap for fixed . We close this gap by giving an explicit strongly connected graph on vertices with edges, every one of which is necessary in a two-failure preserver. Together with the upper bound of [HSW25], this proves that the optimal size in the worst case is for every fixed , whereas it is for [GIP20]. The same graph has a one-failure preserver with at most edges. We also give a randomized algorithm that either returns a spanning subgraph or reports failure. For every fixed , with probability at least it returns a correct preserver for with edges, in time and space. Here is the matrix multiplication exponent over a fixed finite field.
作者备注:43 pages
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v1 · 2026-11-12 13:18 · 最新观测版本
Optimal-Size Strong Connectivity Preservers under Two Edge Failures in Subcubic Time
A -edge-failure strong connectivity preserver of a directed graph on vertices is a spanning subgraph that has the same strongly connected components as the input after each set of at most edge deletions. The lower-bound construction of Baswana, Choudhary, and Roditty [BCR18], adapted to strong connectivity in [CC20], gives the previous best bound of necessary edges. Hoppenworth, Saranurak, and Wang [HSW25] prove an upper bound, leaving a logarithmic gap for fixed . We close this gap by giving an explicit strongly connected graph on vertices with edges, every one of which is necessary in a two-failure preserver. Together with the upper bound of [HSW25], this proves that the optimal size in the worst case is for every fixed , whereas it is for [GIP20]. The same graph has a one-failure preserver with at most edges. We also give a randomized algorithm that either returns a spanning subgraph or reports failure. For every fixed , with probability at least it returns a correct preserver for with edges, in time and space. Here is the matrix multiplication exponent over a fixed finite field.
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