The understanding of interacting dynamics is important for the characterization of real-world/nnetworks. In general real-world networks are heterogeneous in the sense that each node of the/nnetwork is a dynamics with di erent properties. For coupled non-identical dynamics symmetric/ninteractions are not straightforwardly de ned from the coupling strength values. Thus, a challenging/nissue is whether we can de ne a symmetric interaction in this asymmetric setting. To address this/nproblem we introduce ...
The understanding of interacting dynamics is important for the characterization of real-world/nnetworks. In general real-world networks are heterogeneous in the sense that each node of the/nnetwork is a dynamics with di erent properties. For coupled non-identical dynamics symmetric/ninteractions are not straightforwardly de ned from the coupling strength values. Thus, a challenging/nissue is whether we can de ne a symmetric interaction in this asymmetric setting. To address this/nproblem we introduce the notion of the coupling impact. The coupling impact considers not only/nthe coupling strength but also the energy of the individual dynamics which is conveyed via the/ncoupling. To illustrate this concept, we follow a data-driven approach by analyzing signals from pairs/nof coupled model dynamics using two di erent connectivity measures. We nd that the coupling/nimpact, but not the coupling strength, correctly detects a symmetric interaction between pairs of/ncoupled dynamics regardless of their degree of asymmetry. Therefore, this approach allows to reveal/nthe real impact that one dynamics has on the other and hence to de ne symmetric interactions in/npairs of non-identical dynamics.
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