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Main Authors: Chhimpa, Rahul, Singh, Abha, Yadav, Avinash Chand
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2501.03705
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author Chhimpa, Rahul
Singh, Abha
Yadav, Avinash Chand
author_facet Chhimpa, Rahul
Singh, Abha
Yadav, Avinash Chand
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2501_03705
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Correlation time in extremal self-organized critical models
Chhimpa, Rahul
Singh, Abha
Yadav, Avinash Chand
Statistical Mechanics
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.
title Correlation time in extremal self-organized critical models
topic Statistical Mechanics
url https://arxiv.org/abs/2501.03705