Nature processes information. We observe this from physical systems, which register information in the system state, transfer information through interactions, and lose information due to thermal noise. Being able to quantify this information processing could lead to a unifying framework for a better understanding of complex systems. In this letter we present a formalism to describe to what extent a macroscopic system is affected by the microstates of its constituents. We study this numerically for a heterogeneous network of Ising-spins, and suggest an answer to the unexplained phenomenon that real systems with a heterogeneous topology are mainly controlled by nodes with fewer connections [Liu, Y.-Y. et al., Nature 473, 7346 (2011)]. Counter to intuition we find that due to selective information dissipation, not the hubs but rather the intermediately connected nodes are remembered best by the system. Our study suggests that the concept of inherent information processing may lead to a better understanding of the emergent behavior of complex systems.
['Rick Quax', 'Andrea Apolloni', 'Peter M. A. Sloot']
Information processing reveals how microscopic components affect the macroscopic system-state in complex networks