Treffer: A nearly optimal algorithm for deciding connectivity queries in smooth and bounded real algebraic sets

Title:
A nearly optimal algorithm for deciding connectivity queries in smooth and bounded real algebraic sets
Contributors:
Polynomial Systems (PolSys), Laboratoire d'Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), David R. Cheriton School of Computer Science, University of Waterloo Waterloo, ANR-11-BS03-0011,GEOLMI,Geométrie et algèbre des inégalités matricielles linéaires avec applications en commande(2011)
Source:
ISSN: 0004-5411.
Publisher Information:
CCSD
Association for Computing Machinery
Publication Year:
2017
Document Type:
Fachzeitschrift article in journal/newspaper
Language:
English
Relation:
info:eu-repo/semantics/altIdentifier/arxiv/1307.7836v2; ARXIV: 1307.7836v2
DOI:
10.1145/2996450
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edsbas.E5E09817
Database:
BASE

Weitere Informationen

Major revision, accepted for publication to Journal of the ACM ; International audience ; A roadmap for a semi-algebraic set $S$ is a curve which has a non-empty and connected intersection with all connected components of $S$. Hence, this kind of object, introduced by Canny, can be used to answer connectivity queries (with applications, for instance, to motion planning) but has also become of central importance in effective real algebraic geometry, since it is used in higher-level algorithms. In this paper, we provide a probabilistic algorithm which computes roadmaps for smooth and bounded real algebraic sets. Its output size and running time are polynomial in $(nD)^{n\log(d)}$, where $D$ is the maximum of the degrees of the input polynomials, $d$ is the dimension of the set under consideration and $n$ is the number of variables. More precisely, the running time of the algorithm is essentially subquadratic in the output size. Even under our assumptions, it is the first roadmap algorithm with output size and running time polynomial in $(nD)^{n\log(d)}$.