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Emergence of a multilayer structure in adaptive networks of phase oscillators
Institution:1. Faculty of Nonlinear Processes, Saratov State University, Astrakhanskaya 83, Saratov 410012, Russia;2. REC ’Nonlinear Dynamics of Complex Systems’, Saratov State Technical University, Politechnicheskaja 77, Saratov 410054, Russia;3. Laboratory of Biological Networks, Center for Biomedical Technology, 28923 Pozuelo de Alarcón, Spain;4. Complex Systems Group & GISC, URJC, 28933 Móstoles, Spain;5. CNR – Institute of Complex Systems, Via Madonna del Prato, 10, 50019 Sesto Fiorentino (FI), Italy;6. The Italian Embassy in Tel Aviv, Trade Tower, 25, Hamered St., 68125 Tel Aviv, Israel;1. Centre for Nonlinear Science & Engineering, School of Electrical & Electronics Engineering, SASTRA University, Thanjavur 613 402, India;2. School of Physics, Indian Institute of Science Education and Research, Thiruvanandapuram 695016, India;3. Centre for Nonlinear Dynamics, School of Physics, Bharathidasan University, Tiruchirapalli 620 024, India;4. Potsdam Institute for Climate Impact Research, Potsdam 14473, Germany;5. Institute of Physics, Humboldt University, Berlin 12489, Germany;6. Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen AB24 3UE, United Kingdom
Abstract:We report on self-organization of adaptive networks, where topology and dynamics evolve in accordance to a competition between homophilic and homeostatic mechanisms, and where links are associated to a vector of weights. Under an appropriate balance between the intra- and inter- layer coupling strengths, we show that a multilayer structure emerges due to the adaptive evolution, resulting in different link weights at each layer, i.e. different components of the weights’ vector. In parallel, synchronized clusters at each layer are formed, which may overlap or not, depending on the values of the coupling strengths. Only when intra- and inter- layer coupling strengths are high enough, all layers reach identical final topologies, collapsing the system into, in fact, a monolayer network. The relationships between such steady state topologies and a set of dynamical network’s properties are discussed.
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