In recent years, the study of collective dynamics in complex systems has expanded beyond traditional pairwise network models to include non-pairwise interactions represented through hypergraphs, simplicial complexes, and other higher-order structures. These frameworks capture group interactions such as multi-species ecological interactions, higher-order neuronal couplings, and collective decision-making processes that cannot be faithfully represented using ordinary graphs. As a result, higher-order networks have become indispensable for understanding the emergent behavior of systems ranging from coupled oscillators and neural circuits to sociotechnical and biological systems.
While classical network theory has provided deep insights into synchronization, spreading processes, percolation, and robustness, recent discoveries show that non-pairwise interactions can fundamentally alter these dynamical processes. They may lead to richer and more intricate phenomena, including hierarchical and partial synchronization, abrupt transitions, enhanced or suppressed contagion, multi-stability, chimera like patterns, and novel forms of collective behavior not observed in purely pairwise settings. Despite these advances, a comprehensive framework that unifies the dynamics arising from both pairwise and higher-order interactions is still emerging and remains an exciting frontier of research.
This topic aims to advance our understanding of how the structure, topology, and interaction order whether static, temporal, multiplex, or heterogeneous influence the dynamics of complex systems. We seek contributions that uncover fundamental mechanisms, develop analytical frameworks, or employ large-scale numerical simulations to reveal new dynamical phenomena on networks and hypergraphs.
Key themes of interest include, but are not limited to:
• Collective dynamics and synchronization in systems with mixed pairwise and non-pairwise interactions • Modeling contagion, spreading, and diffusion processes in higher-order network structures • Random walks, transport, and search dynamics on hypergraphs and simplicial complexes • Interaction-driven competition, cooperation, and evolutionary dynamics on complex networks • Opinion formation, consensus mechanisms, and social influence in static and temporal networks • Cascading failures, resilience, and robustness in networked systems with higher-order couplings
By integrating analytical, computational, and simulation-based approaches, this topic seeks to bridge theory and application across applied mathematics, physics, biology, neuroscience, epidemiology, and the social sciences. Ultimately, it aims to uncover the fundamental principles governing how collective behavior emerges in systems where interactions extend beyond the pairwise paradigm.
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