Computer Science – Information Theory
Scientific paper
2011-11-23
Computer Science
Information Theory
Scientific paper
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 scale-free network of Ising-spins, a prototypical complex system, and present an answer to the unexplained phenomenon that real systems with a heterogeneous topology are mainly controlled by nodes with fewer connections. 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 reveals that the framework of information processing improves our understanding of complex systems at large.
Apolloni Andrea
Quax Rick
Sloot Peter M. A.
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