Indexing metadata

Intrinsic Coupling on Riemannian Manifolds and Polyhedra


 
Dublin Core PKP Metadata Items Metadata for this Document
 
1. Title Title of document Intrinsic Coupling on Riemannian Manifolds and Polyhedra
 
2. Creator Author's name, affiliation, country Max-K. von Renesse; Technical University Berlin
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) Coupling; Gradient Estimates; Central Limit Theorem
 
3. Subject Subject classification 60J60; 60J45,58J50
 
4. Description Abstract Starting from a central limit theorem for geometric random walks we give an elementary construction of couplings between Brownian motions on Riemannian manifolds. This approach shows that cut locus phenomena are indeed inessential for Kendall's and Cranston's stochastic proof of gradient estimates for harmonic functions on Riemannian manifolds with lower curvature bounds. Moreover, since the method is based on an asymptotic quadruple inequality and a central limit theorem only it may be extended to certain non smooth spaces which we illustrate by the example of Riemannian polyhedra. Here we also recover the classical heat kernel gradient estimate which is well known from the smooth setting.
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s) Research Center SFB 611 at Bonn University of German Research Council (DFG)
 
7. Date (YYYY-MM-DD) 2004-06-08
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier http://ejp.ejpecp.org/article/view/205
 
10. Identifier Digital Object Identifier 10.1214/EJP.v9-205
 
11. Source Journal/conference title; vol., no. (year) Electronic Journal of Probability; Vol 9
 
12. Language English=en
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
15. Rights Copyright and permissions The Electronic Journal of Probability applies the Creative Commons Attribution License (CCAL) to all articles we publish in this journal. Under the CCAL, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles published in EJP, so long as the original authors and source are credited. This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available.

Summary of the Creative Commons Attribution License

You are free
  • to copy, distribute, display, and perform the work
  • to make derivative works
  • to make commercial use of the work
under the following condition of Attribution: others must attribute the work if displayed on the web or stored in any electronic archive by making a link back to the website of EJP via its Digital Object Identifier (DOI), or if published in other media by acknowledging prior publication in this Journal with a precise citation including the DOI. For any further reuse or distribution, the same terms apply. Any of these conditions can be waived by permission of the Corresponding Author.