Correlation time in extremal self-organized critical models
Rahul Chhimpa (),
Abha Singh () and
Avinash Chand Yadav ()
Additional contact information
Rahul Chhimpa: Banaras Hindu University
Abha Singh: Banaras Hindu University
Avinash Chand Yadav: Banaras Hindu University
The European Physical Journal B: Condensed Matter and Complex Systems, 2025, vol. 98, issue 6, 1-8
Abstract:
Abstract We investigate correlation time numerically in extremal self-organized critical models, namely the Bak–Sneppen evolution and the Robin Hood dynamics. The (fitness) correlation time is the duration required for the extinction or mutation of species over the entire spatial region in the critical state. We apply the methods of finite-size scaling and extreme value theory to understand the statistics of the correlation time. We find power-law system size scaling behaviors for the mean, the variance, the mode, and the peak probability of the correlation time. We obtain data collapse for the correlation time cumulative probability distribution, and the scaling function follows the generalized extreme value density close to the Gumbel function. Graphic abstract
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1140/epjb/s10051-025-00988-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:eurphb:v:98:y:2025:i:6:d:10.1140_epjb_s10051-025-00988-1
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/10051
DOI: 10.1140/epjb/s10051-025-00988-1
Access Statistics for this article
The European Physical Journal B: Condensed Matter and Complex Systems is currently edited by P. Hänggi and Angel Rubio
More articles in The European Physical Journal B: Condensed Matter and Complex Systems from Springer, EDP Sciences
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().