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Related Experiment Video

Updated: Apr 25, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Controlling extreme events on complex networks.

Yu-Zhong Chen¹, Zi-Gang Huang², Ying-Cheng Lai³

¹School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, USA.

Scientific Reports

|August 19, 2014

Summary

This summary is machine-generated.

Making complex networks mobile can suppress extreme events. An optimal mobility level minimizes the probability of catastrophic collective behavior, offering new control strategies.

Related Experiment Videos

Last Updated: Apr 25, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Area of Science:

Complex systems
Network science
Dynamical systems

Background:

Extreme events in complex networked systems can have severe consequences.
Controlling these events is crucial for practical applications.
Transportation dynamics serve as a model for studying such phenomena.

Purpose of the Study:

To investigate methods for suppressing extreme events in complex networks.
To explore the impact of network mobility on event probability.
To develop a theoretical understanding of event control mechanisms.

Main Methods:

Utilizing transportation dynamics on complex networks as a model system.
Analyzing the effect of network mobility on the occurrence of extreme events.
Deriving an analytic theory to explain the observed phenomena.
Validating theoretical findings through numerical simulations.

Main Results:

Introducing mobility to a network effectively suppresses extreme events.
A resonance-like phenomenon was observed, indicating an optimal mobility level.
This optimal mobility minimizes the probability of extreme events.
An analytic theory quantitatively explains the control mechanism.

Conclusions:

Network mobility is a viable strategy for controlling extreme events.
The identified optimal mobility offers a precise method for event suppression.
Findings have implications for cybersecurity and other complex systems.