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Noise Induced Pattern Switching in Randomly Distributed Delayed Swarms.

Brandon Lindley¹, Luis Mier-Y-Teran-Romero², Ira B Schwartz³

¹US Naval Research Labooratory, Code 6792, Washington, DC 20375 USA, brandon.lindley.ctr@nrl.navy.mil.

Proceedings of the ... American Control Conference. American Control Conference

|November 11, 2014

Summary

This summary is machine-generated.

Noise can surprisingly organize self-propelling particle systems. A critical noise level triggers transitions from less to more organized states, with transition times depending on noise intensity and delay distributions.

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Area of Science:

Physics
Complex Systems
Statistical Mechanics

Background:

Coupled self-propelling particles exhibit complex emergent patterns.
System stability and pattern formation are sensitive to time-delayed coupling.
Time delay distributions significantly influence pattern stability and bifurcation points.

Purpose of the Study:

Investigate the impact of noise on the dynamics of time-delayed self-propelling particle systems.
Analyze noise-induced transitions between different organizational states.
Quantify the critical noise threshold for swarm reorganization.

Main Methods:

Numerical simulations of coupled self-propelling particles with discrete, random time delays.
Systematic variation of noise intensities and delay distribution parameters.
Analysis of system dynamics and state transitions under varying noise levels.

Main Results:

A critical noise threshold was identified, above which systems transition to more organized states.
Noise can induce transitions between less and more organized swarm patterns.
Transition times are dependent on both noise intensity and the characteristics of the delay distribution.

Conclusions:

Noise plays a crucial role in the reorganization dynamics of self-propelled particle systems with time delays.
A specific noise intensity can act as a control parameter to enhance system organization.
Understanding noise-induced transitions is key for predicting and controlling emergent behavior in such systems.