Indexing metadata

Complex Determinantal Processes and $H1$ Noise


 
Dublin Core PKP Metadata Items Metadata for this Document
 
1. Title Title of document Complex Determinantal Processes and $H1$ Noise
 
2. Creator Author's name, affiliation, country Brian Rider; University of Colorado, Boulder
 
2. Creator Author's name, affiliation, country Balint Virag; University of Toronto
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) determinantal process; random matrices; invariant point process; noise limit
 
3. Subject Subject classification 60D05; 30F99
 
4. Description Abstract For the plane, sphere, and hyperbolic plane we consider the canonical invariant determinantal point processes $\mathcal Z_\rho$ with intensity $\rho d\nu$, where $\nu$ is the corresponding invariant measure. We show that as $\rho\to\infty$, after centering, these processes converge to invariant $H^1$ noise. More precisely, for all functions $f\in H^1(\nu) \cap L^1(\nu)$ the distribution of $\sum_{z\in \mathcal Z} f(z)-\frac{\rho}{\pi} \int f d \nu$ converges to Gaussian with mean zero and variance $ \frac{1}{4 \pi} \|f\|_{H^1}^2$.
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s) NSF, Sloan Foundation, NSERC, Connaught Grant, Canada Resarch Chair Program
 
7. Date (YYYY-MM-DD) 2007-10-09
 
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/446
 
10. Identifier Digital Object Identifier 10.1214/EJP.v12-446
 
11. Source Journal/conference title; vol., no. (year) Electronic Journal of Probability; Vol 12
 
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.