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Related Experiment Video

Updated: Jun 19, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Branching process in a stochastic extremal model.

S S Manna1

  • 1Max-Planck-Institute für Physik Komplexer Systeme, D-01187 Dresden, Germany.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|October 2, 2009
PubMed
Summary
This summary is machine-generated.

This study explores a modified Bak-Sneppen model (SBSM) for ecological evolution. The research finds that SBSM exhibits similar critical behavior to the original model on standard graphs but differs on scale-free networks.

Related Experiment Videos

Last Updated: Jun 19, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Area of Science:

  • Ecological modeling
  • Evolutionary dynamics
  • Statistical physics

Background:

  • The Bak-Sneppen model (BSM) is a key model for studying self-organized criticality in ecological systems.
  • Understanding how evolutionary dynamics affect ecosystem stability is crucial.
  • Previous models often assume a fixed mutation rate or zone.

Purpose of the Study:

  • To investigate a stochastic version of the Bak-Sneppen model (SBSM) with restricted mutation zones.
  • To analyze the critical behavior of SBSM across different network structures (dimensions and scale-free graphs).
  • To explore modifications to the mutation process and their impact on self-organized criticality.

Main Methods:

  • Simulations of the stochastic Bak-Sneppen model (SBSM) with a mutation zone of size M=2.
  • Analysis of critical behavior in different dimensions (d=1, 2) and on scale-free graphs.
  • Investigating probabilistic updates of the mutation zone to further reduce M.

Main Results:

  • SBSM shows critical behavior identical to the original BS model in dimensions d=1 and 2.
  • On scale-free graphs, SBSM exhibits a non-zero critical fitness value in the thermodynamic limit with mean-field-like critical behavior.
  • Probabilistically updating the mutation zone to M<2 also reproduces the original BS model's behavior.

Conclusions:

  • The stochastic Bak-Sneppen model (SBSM) maintains critical properties similar to the original model under specific conditions.
  • Scale-free networks introduce significant deviations in critical fitness and behavior within SBSM.
  • A conjecture is proposed that SBSM on arbitrary graphs with a branching factor > 1 leads to a self-organized critical state.