Indexing metadata

Erdos-Renyi random graphs + forest fires = self-organized criticality


 
Dublin Core PKP Metadata Items Metadata for this Document
 
1. Title Title of document Erdos-Renyi random graphs + forest fires = self-organized criticality
 
2. Creator Author's name, affiliation, country Balazs Rath; Budapest University of Technology
 
2. Creator Author's name, affiliation, country Balint Toth; Budapest University of Technology
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) forest fire model, Erdos-Renyi random graph, Smoluchowski coagulation equations, self-organized criticality
 
3. Subject Subject classification 60K35
 
4. Description Abstract We modify the usual Erdos-Renyi random graph evolution by letting connected clusters 'burn down' (i.e. fall apart to disconnected single sites) due to a Poisson flow of lightnings. In a range of the intensity of rate of lightnings the system sticks to a permanent.
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s) This research was partially supported by the OTKA (Hungarian National Research Fund) grants K 60708 and TS 49835.
 
7. Date (YYYY-MM-DD) 2009-06-15
 
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/653
 
10. Identifier Digital Object Identifier 10.1214/EJP.v14-653
 
11. Source Journal/conference title; vol., no. (year) Electronic Journal of Probability; Vol 14
 
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.