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Roei Tov

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TCS Journal 2023 Journal Article

Approximate distance oracles with improved stretch for sparse graphs

  • Liam Roditty
  • Roei Tov

Thorup and Zwick [1] introduced the notion of approximate distance oracles, a data structure that produces for an n-vertex, m-edge weighted undirected graph G = ( V, E ), distance estimations in constant query time. They presented a distance oracle of size O ( k n 1 + 1 / k ) that given a pair of vertices u, v ∈ V at distance d ( u, v ) produces in O ( k ) time an estimation that is bounded by ( 2 k − 1 ) d ( u, v ), i. e. , a ( 2 k − 1 ) -multiplicative approximation (stretch). Thorup and Zwick [1] presented also a lower bound based on the girth conjecture of Erdős. For sparse unweighted graphs (i. e. , m = O ˜ ( n ) ) the lower bound does not apply. Pǎtraşcu and Roditty [2] used the sparsity of the graph and obtained a distance oracle that uses O ˜ ( n 5 / 3 ) space, has O ( 1 ) query time and a stretch of 2. Pǎtraşcu et al. [3] presented infinitely many distance oracles with fractional stretch factors that for graphs with m = O ˜ ( n ) converge exactly to the integral stretch factors and the corresponding space bound of Thorup and Zwick. It is not known, however, whether graph sparsity can help to get a stretch which is better than ( 2 k − 1 ) using only O ˜ ( k n 1 + 1 / k ) space. In this paper we answer this open question and prove a separation between sparse and dense graphs by showing that using sparsity it is possible to obtain better stretch/space tradeoffs than those of Thorup and Zwick. We show that for every k ≥ 2 there is a distance oracle of size O ˜ ( k m 1 + 1 / k ) that produces in O ( k ) time an estimation d ⁎ ( u, v ) that satisfies d ( u, v ) ≤ d ⁎ ( u, v ) ≤ ( 2 k − 1 ) d ( u, v ) − 4, for k > 2, and d ( u, v ) ≤ d ⁎ ( u, v ) ≤ 3 d ( u, v ) − 2, for k = 2. Another contribution of this paper is a refined stretch analysis of Thorup and Zwick distance oracles that allows us to obtain a better understanding of this important data structure. We present simple conditions for every w ∈ V that characterize the exact scenarios in which every query that involves w produces an estimation of stretch strictly better than 2 k − 1, even in the case of dense graphs. We complement this contribution with an experiment on real world graphs. The main finding in the experiment is that different real world graphs are likely to satisfy the required conditions and hence the stretch of Thorup and Zwick distance oracles is much better than its worst case bound in these real world graphs.

SODA Conference 2018 Conference Paper

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

  • Jakub Pachocki
  • Liam Roditty
  • Aaron Sidford
  • Roei Tov
  • Virginia Vassilevska Williams

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: • Multiplicative Approximations in Nearly Linear Time: We give an algorithm that in Õ ( m ) time computes an Õ (1)-multiplicative approximation of the girth as well as an Õ (1)-multiplicative roundtrip spanner with Õ ( n ) edges with high probability (w. h. p). • Nearly Tight Additive Approximations: For unweighted graphs and any a ∊ (0, 1) we give an algorithm that in Õ ( mn 1– a ) time computes an O ( n a )-additive approximation of the girth, w. h. p. We show that the runtime 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.

v2026.09.13