A probabilistic approach to reducing the algebraic complexity of computing Delaunay triangulations
Jean-Daniel Boissonnat, Ramsay Dyer, Arijit Ghosh

TL;DR
This paper introduces a probabilistic method using witness complexes and a perturbation scheme based on the Lovász local lemma to simplify the algebraic complexity of computing Delaunay triangulations in high dimensions.
Contribution
It proposes a novel approach that reduces polynomial degree evaluations in Delaunay triangulation computation by leveraging witness complexes and a perturbation algorithm grounded in probabilistic combinatorics.
Findings
The perturbation algorithm uses only quadratic distance comparisons.
The method achieves sublinear time complexity relative to the size of witness set W.
It guarantees a lower bound on the thickness of the resulting simplices.
Abstract
Computing Delaunay triangulations in involves evaluating the so-called in\_sphere predicate that determines if a point lies inside, on or outside the sphere circumscribing points . This predicate reduces to evaluating the sign of a multivariate polynomial of degree in the coordinates of the points . Despite much progress on exact geometric computing, the fact that the degree of the polynomial increases with makes the evaluation of the sign of such a polynomial problematic except in very low dimensions. In this paper, we propose a new approach that is based on the witness complex, a weak form of the Delaunay complex introduced by Carlsson and de Silva. The witness complex is defined from two sets and in some metric space : a finite set of points on which the complex is…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComputational Geometry and Mesh Generation · Topological and Geometric Data Analysis · Data Management and Algorithms
