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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 8: Dynamics of Social and Adaptive Networks II
SOE 8.3: Vortrag
Freitag, 1. Oktober 2021, 11:45–12:15, H6
Desynchronization Transitions in Adaptive Networks — •Rico Berner1,2, Simon Vock3, Serhiy Yanchuk2, and Eckehard Schöll1,4,5 — 1Institut für Theoretische Physik, Technische Universität Berlin, Germany — 2Institut für Mathematik, Technische Universität Berlin, Germany — 3Charité-Universitätsmedizin Berlin, Germany — 4Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität Berlin, Germany — 5Potsdam Institute for Climate Impact Research, Potsdam, Germany
Adaptive networks change their connectivity with time, depending on their dynamical state [R. Berner, E. Schöll and S. Yanchuk, SIAM J. Appl. Dyn. Syst. 18, 2227 (2019)]. While synchronization in structurally static networks has been studied extensively, this problem is much more challenging for adaptive networks. In this work, we develop the master stability approach for a large class of adaptive networks [R. Berner, S. Vock, E. Schöll and S. Yanchuk, PRL 126, 028301 (2021)]. This approach allows for reducing the synchronization problem for adaptive networks to a low-dimensional system, by decoupling topological and dynamical properties. We show how the interplay between adaptivity and network structure gives rise to the formation of stability islands. Moreover, we report a desynchronization transition and the emergence of complex partial synchronization patterns induced by an increasing overall coupling strength. We illustrate our findings using adaptive networks of coupled phase oscillators and FitzHugh-Nagumo neurons with synaptic plasticity.