Extreme events and event size fluctuations in biased random walks on networks.
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Summary
This work studies extreme events in a generalized random walk model in which the walk is preferentially biased by the network topology, and shows that extremely large fluctuations in event sizes are possible on small degree nodes when the walkers are biased toward the hubs.
- Type
- article
- Published
- 2011-12-09
- Cited by
- 43
- References
- 16
- Access
- Open access
- OpenAlex
- https://openalex.org/W1971128028
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:17040940
Keywords
Random walk, Extreme value theory, Node (physics), Event (particle physics), Mathematics
References
Cited by
- Structural robustness of scale-free networks against overload failures.
- Rare events statistics of random walks on networks: localisation and other dynamical phase transitions
- Convergence of large-deviation estimators.
- Controlling extreme events on complex networks
- Effects of target routing model on the occurrence of extreme events in complex networks
- Quantification and prediction of extreme events in a one-dimensional nonlinear dispersive wave model
- Overload Network Failures: An Approach from the Random-Walk Model
- Extreme events in multilayer, interdependent complex networks and control
- Controlling extreme events on complex
- Diffusions conditioned on occupation measures
- A probabilistic decomposition-synthesis method for the quantification of rare events due to internal instabilities
- Network fragility to overload failures: influence of the scale-free property
- Decentralized network control, optimization and random walks on networks
- A statistical physics approach to different problems in network theory
- Phase Transition in Recovery Process of Complex Networks
- How important are hubs for the generation of extreme events in networks of excitable units?
- Dependence of extreme events on spatial location.
- Robustness of complex networks to cascading failures induced by Poisson fluctuating loads
- Large deviations of random walks on random graphs.
- Fractal and Small-World Networks Formed by Self-Organized Critical Dynamics
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