,
Kuowen Chen
,
Shengquan Du
,
Arnold Filtser
,
Seth Pettie
,
Daniel Skora
Creative Commons Attribution 4.0 International license
In this paper we consider the problem of approximating Euclidean distances by the infinite integer grid graph. Although the topology of the graph is fixed, we have control over the edge-weight assignment w : E → ℝ_{≥ 0}, and hope to have grid distances be asymptotically isometric to Euclidean distances, that is: For all grid points u,v, dist_w(u,v) = (1± o(1))‖u-v‖₂. We give three methods for solving this problem, each attractive in its own way.
- Our first construction is based on an embedding of the recursive, non-periodic pinwheel tiling of Radin and Conway [Charles Radin, 1994; Radin and Sadun, 1996; John H. Conway and Charles Radin, 1998] into the integer grid. Distances in the pinwheel graph are asymptotically isometric to Euclidean distances, but no explicit bound on the rate of convergence was known. We prove that the multiplicative distortion of the pinwheel graph is (1 + 1/Θ(log^ξ log D)), where D is the Euclidean distance and ξ = Θ(1). The pinwheel tiling approach is conceptually simple, but can be improved quantitatively.
- Our second construction is based on a hierarchical arrangement of highways. It is simple, achieving stretch (1 + 1/Θ(D^{1/9})), which converges doubly exponentially faster than the pinwheel tiling approach.
- The first two methods are deterministic, with rigorous guarantees. An even simpler approach is to sample the edge weights independently and randomly from a common distribution D. Whether there exists a distribution D^* that makes grid distances Euclidean, asymptotically and in expectation, is major open problem in the theory of first passage percolation. Previous experiments show that when D is a Fisher distribution (which is continuous), grid distances are within 1% of Euclidean distances. We demonstrate experimentally that this level of accuracy can be achieved by a simple 2-point distribution that assigns weights 0.41 or 4.75 with probability 44% and 56%, respectively.
@InProceedings{cai_et_al:LIPIcs.SoCG.2026.27,
author = {Cai, Zixi and Chen, Kuowen and Du, Shengquan and Filtser, Arnold and Pettie, Seth and Skora, Daniel},
title = {{The Squishy Grid Problem}},
booktitle = {42nd International Symposium on Computational Geometry (SoCG 2026)},
pages = {27:1--27:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-418-5},
ISSN = {1868-8969},
year = {2026},
volume = {367},
editor = {Ahn, Hee-Kap and Hoffmann, Michael and Nayyeri, Amir},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2026.27},
URN = {urn:nbn:de:0030-drops-258333},
doi = {10.4230/LIPIcs.SoCG.2026.27},
annote = {Keywords: grid graph, Euclidean distance, metric embedding, first passage percolation}
}