Separating internal and external dynamics of complex systems

TL;DR

This paper introduces a method to distinguish internal from external dynamics in complex systems by analyzing simultaneous component activity, aiding in understanding the origins of fluctuations across various real-world systems.

Contribution

The paper presents a novel approach to separate internal and external influences in complex systems using multichannel activity data, applicable across diverse fields.

Findings

Internet and computer chips have robust internal dynamics.

Highway and Web traffic are primarily driven by external demand.

Method effectively identifies fluctuation origins in real systems.

Abstract

The observable behavior of a complex system reflects the mechanisms governing the internal interactions between the system's components and the effect of external perturbations. Here we show that by capturing the simultaneous activity of several of the system's components we can separate the internal dynamics from the external fluctuations. The method allows us to systematically determine the origin of fluctuations in various real systems, finding that while the Internet and the computer chip have robust internal dynamics, highway and Web traffic are driven by external demand. As multichannel measurements are becoming the norm in most fields, the method could help uncover the collective dynamics of a wide array of complex systems.