Separating internal and external dynamics of complex systems.

Area of Science:

• Complex systems science
• Network dynamics
• Statistical physics

Background:

• Observable behavior of complex systems arises from internal interactions and external influences.
• Distinguishing internal dynamics from external fluctuations is crucial for understanding system behavior.
• Multichannel measurements are increasingly common across scientific disciplines.

Purpose of the Study:

• To develop a method for separating internal dynamics from external fluctuations in complex systems.
• To systematically identify the origins of fluctuations in diverse real-world systems.
• To demonstrate the broad applicability of multichannel measurements in complex systems analysis.

Main Methods:

• Simultaneous monitoring of multiple system components.
• Analysis of internal dynamics versus external perturbations.
• Application of the method to various complex systems, including the Internet, computer chips, highway traffic, and Web traffic.

Main Results:

• The developed method successfully separates internal dynamics from external fluctuations.
• Internet and computer chip systems exhibit robust internal dynamics.
• Highway and Web traffic dynamics are primarily driven by external demand.
• The findings highlight differing mechanisms governing complex systems.

Conclusions:

• The proposed method provides a systematic way to determine the origin of fluctuations in complex systems.
• This technique can differentiate between internally driven and externally influenced system behaviors.
• The approach has the potential to reveal collective dynamics across a wide range of complex systems as multichannel measurements become standard.