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Are There Graphs Whose Shortest Path Structure Requires Large Edge Weights?

Authors Aaron Bernstein, Greg Bodwin, Nicole Wein



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Aaron Bernstein
  • Rutgers University, New Brunswick, NJ, USA
Greg Bodwin
  • University of Michigan, Ann Arbor, MI, USA
Nicole Wein
  • Simons Institute, Berkeley, CA, USA

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Aaron Bernstein, Greg Bodwin, and Nicole Wein. Are There Graphs Whose Shortest Path Structure Requires Large Edge Weights?. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 12:1-12:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.ITCS.2024.12

Abstract

The aspect ratio of a (positively) weighted graph G is the ratio of its maximum edge weight to its minimum edge weight. Aspect ratio commonly arises as a complexity measure in graph algorithms, especially related to the computation of shortest paths. Popular paradigms are to interpolate between the settings of weighted and unweighted input graphs by incurring a dependence on aspect ratio, or by simply restricting attention to input graphs of low aspect ratio. This paper studies the effects of these paradigms, investigating whether graphs of low aspect ratio have more structured shortest paths than graphs in general. In particular, we raise the question of whether one can generally take a graph of large aspect ratio and reweight its edges, to obtain a graph with bounded aspect ratio while preserving the structure of its shortest paths. Our findings are: - Every weighted DAG on n nodes has a shortest-paths preserving graph of aspect ratio O(n). A simple lower bound shows that this is tight. - The previous result does not extend to general directed or undirected graphs; in fact, the answer turns out to be exponential in these settings. In particular, we construct directed and undirected n-node graphs for which any shortest-paths preserving graph has aspect ratio 2^{Ω(n)}. We also consider the approximate version of this problem, where the goal is for shortest paths in H to correspond to approximate shortest paths in G. We show that our exponential lower bounds extend even to this setting. We also show that in a closely related model, where approximate shortest paths in H must also correspond to approximate shortest paths in G, even DAGs require exponential aspect ratio.

Subject Classification

ACM Subject Classification
  • Theory of computation → Shortest paths
Keywords
  • shortest paths
  • graph theory
  • weighted graphs

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