Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Computing Delaunay triangulations in R d involves evaluating the so-called in_sphere predicate that determines if a point x lies inside, on or outside the sphere circumscribing d + 1 points p0;:::;pd. This predicate reduces to evaluating the sign of a multivariate polynomial of degree d + 2 in the coordinates of the points x;p0;:::;pd. Despite much progress on exact geometric computing, the fact that the degree of the polynomial increases with d makes the evaluation of the sign of such a polynomial problematic except in very low dimensions. ,  propose a new approach that is based on the witness complex, a ak form of the Delaunay complex introduced by Carlsson and de Silva. The witness complex Wit(L;W ) is defined from two sets L and W in some metric space X: a finite set of points L on which the complex is built, and a set W of witnesses that serves as an approximation of X. A fundamental result of de Silva states that Wit(L;W ) = Del(L) if W = X = R d . ,  give conditions on L that ensure that the witness complex and the Delaunay triangulation coincide when W is a finite set, and  introduce a new perturbation scheme to compute a perturbed set L 0 close to L such that Del(L 0 ) = Wit(L 0 ;W ). Our perturbation algorithm is a geometric application of the Moser-Tardos constructive proof of the Lovasz local lemma. The only numerical operations  use are (squared) distance comparisons (i.e., predicates of degree 2). The time-complexity of the algorithm is sublinear in jWj. Interestingly, although the algorithm does not compute any measure of simplex quality, a lor bound on the thickness of the output simplices can be guaranteed.
['Jean-Daniel Boissonnat', 'Ramsay Dyer', 'Arijit Ghosh']
I am writing a research paper on a idea A probabilistic approach to reducing the algebraic complexity of computing Delaunay triangulations
[{"from": "human", "value": "I am writing a research paper on a idea A probabilistic approach to reducing the algebraic complexity of computing Delaunay triangulations"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Computing Delaunay triangulations in R d involves evaluating the so-called in_sphere predicate that determines if a point x lies inside, on or outside the sphere circumscribing d + 1 points p0;:::;pd. This predicate reduces to evaluating the sign of a multivariate polynomial of degree d + 2 in the coordinates of the points x;p0;:::;pd. Despite much progress on exact geometric computing, the fact that the degree of the polynomial increases with d makes the evaluation of the sign of such a polynomial problematic except in very low dimensions. ,  propose a new approach that is based on the witness complex, a ak form of the Delaunay complex introduced by Carlsson and de Silva. The witness complex Wit(L;W ) is defined from two sets L and W in some metric space X: a finite set of points L on which the complex is built, and a set W of witnesses that serves as an approximation of X. A fundamental result of de Silva states that Wit(L;W ) = Del(L) if W = X = R d . ,  give conditions on L that ensure that the witness complex and the Delaunay triangulation coincide when W is a finite set, and  introduce a new perturbation scheme to compute a perturbed set L 0 close to L such that Del(L 0 ) = Wit(L 0 ;W ). Our perturbation algorithm is a geometric application of the Moser-Tardos constructive proof of the Lovasz local lemma. The only numerical operations  use are (squared) distance comparisons (i.e., predicates of degree 2). The time-complexity of the algorithm is sublinear in jWj. Interestingly, although the algorithm does not compute any measure of simplex quality, a lor bound on the thickness of the output simplices can be guaranteed."}]