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Approximating Cycles in Directed Graphs: Fast Algorithms for Girth and Roundtrip Spanners

机译:近似循环在有向图中:周长和往返跨越扳手的快速算法

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The girth of a graph, i.e. the length of its shortest cycle, is a fundamental graph parameter. Unfortunately all known algorithms for computing, even approximately, the girth and girth-related structures in directed weighted m-edge and n-node graphs require Ω(min{n~ω, mn}) time (for 2 ≤ ω < 2.373). In this paper, we drastically improve these runtimes as follows: (1) Multiplicative Approximations in Nearly Linear Time: We give an algorithm that in O(m) time computes an O(1)-multiplicative approximation of the girth as well as an O(1)-multiplicative roundtrip spanner with O(n) edges with high probability (w.h.p). (2) Nearly Tight Additive Approximations: For unweighted graphs and any a ∈ (0,1) we give an algorithm that in O(mn~(1-α)) time computes an O(n~a)-additive approximation of the girth, w.h.p. We show that the run-time of our algorithm cannot be significantly improved without a breakthrough in combinatorial boolean matrix multiplication. We also show that if the girth is O(n~a), then the same guarantee can be achieved via a deterministic algorithm. Our main technical contribution to achieve these results is the first nearly linear time algorithm for computing roundtrip covers, a directed graph decomposition concept key to previous roundtrip spanner constructions. Previously it was not known how to compute these significantly faster than Ω(mn) time. Given the traditional difficulty in efficiently processing directed graphs, we hope our techniques may find further applications.
机译:图形的周长,即其最短周期的长度是一个基本图表参数。遗憾的是,所有已知的计算算法,甚至大约大约,周长和周长相关的结构,在指向加权M-EDGE和N节点图需要ω(min {nΩ,mn})时间(2≤Ω<2.373)。在本文中,我们大大改善了这些运行时,如下:(1)几乎线性时间内的乘法近似:我们给出了一种在O(m)时间计算的算法计算周长的O(1)-mlowive近似值以及o (1) - 具有高概率(WHP)的O(n)边缘的多次往返扳手。 (2)近乎紧张的附加附加近似:对于未加权的图表和任何∈(0,1),我们提供了一种在O(MN〜(1-α))时间计算的算法计算O(n〜a)的废弃近似周长,WHP.我们表明,在组合布尔矩阵乘法中,我们的算法的运行时间不能显着提高。我们还表明,如果周长是O(n〜a),那么通过确定性算法可以实现相同的保证。我们主要的技术贡献实现这些结果是第一个用于计算往返封面的近似线性时间算法,前往往返扳手构造的定向图分解概念键。此前,目前尚不知道如何计算这些明显比ω(MN)时间更快。鉴于有效处理有效的图表的传统困难,我们希望我们的技术可以找到进一步的应用程序。

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