几乎最优的超常通流下界的可达性

Lijie Chen, Gillat Kol, Dmitry Paramonov, Raghuvansh R. Saxena, Zhao Song, Huacheng Yu
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引用次数: 17

摘要

我们给出了求解(有向)s-t可达问题的任意o(√logn)次流算法的空间消耗的几乎二次n2−o(1)下界。这意味着任何这样的算法本质上都必须存储整个图。作为推论,我们得到了其他基本问题的几乎二次空间下界,包括最大匹配、最短路径、矩阵秩和线性规划。我们的主要技术贡献是集合隐藏图的定义和构造,这可能是独立的兴趣:我们给出了一种将集合S≤[k]编码为具有n = k1 + o(1)个顶点的有向图的一般方法,从而确定i∈S是否归结为确定对于图中的特定顶点对(si,ti)是否可从si到达。此外,我们证明了我们的图“隐藏”了S,从某种意义上说,没有低空间流算法可以通过少量的传递来学习(几乎)任何关于S的东西。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Almost optimal super-constant-pass streaming lower bounds for reachability
We give an almost quadratic n2−o(1) lower bound on the space consumption of any o(√logn)-pass streaming algorithm solving the (directed) s-t reachability problem. This means that any such algorithm must essentially store the entire graph. As corollaries, we obtain almost quadratic space lower bounds for additional fundamental problems, including maximum matching, shortest path, matrix rank, and linear programming. Our main technical contribution is the definition and construction of set hiding graphs, that may be of independent interest: we give a general way of encoding a set S ⊆ [k] as a directed graph with n = k 1 + o( 1 ) vertices, such that deciding whether i ∈ S boils down to deciding if ti is reachable from si, for a specific pair of vertices (si,ti) in the graph. Furthermore, we prove that our graph “hides” S, in the sense that no low-space streaming algorithm with a small number of passes can learn (almost) anything about S.
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