Random walks on networks with preferential cumulative damage: generation of bias and aging

Author:

Eraso-Hernandez L K,Riascos A P,Michelitsch T M,Wang-Michelitsch J

Abstract

Abstract In this paper, we explore the reduction of functionality in a complex system as a consequence of cumulative random damage and imperfect reparation, a phenomenon modeled as a dynamical process in networks. We analyze the global characteristics of the diffusive movement of random walkers on networks where the walkers hop considering the capacity of transport of each link. The links are susceptible to damage that generates bias and aging. We describe the algorithm for the generation of damage and the bias in the transport producing complex eigenvalues of the transition matrix that defines the random walker for different types of graphs, including regular, deterministic, and random networks. The evolution of the asymmetry of the transport is quantified with local information in the links and further with non-local information associated with the transport on a global scale, such as the matrix of the mean first passage times and the fractional Laplacian matrix. Our findings suggest that systems with greater complexity live longer.

Publisher

IOP Publishing

Subject

Statistics, Probability and Uncertainty,Statistics and Probability,Statistical and Nonlinear Physics

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fractional advection diffusion asymmetry equation, derivation, solution and application;Journal of Physics A: Mathematical and Theoretical;2024-01-04

2. Influence of cumulative damage on synchronization of Kuramoto oscillators on networks;Journal of Physics A: Mathematical and Theoretical;2023-10-30

3. Evolution of transport under cumulative damage in metro systems;International Journal of Modern Physics C;2023-09-06

4. A measure of dissimilarity between diffusive processes on networks;Journal of Physics A: Mathematical and Theoretical;2023-03-16

5. Optimal exploration of random walks with local bias on networks;Physical Review E;2022-04-25

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