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Center for Nonlinear Studies |
Complex systems are often described by simple equations that nevertheless lead to a rich variety of behaviors. Discovering and understanding new behaviors is at the forefront of current research on network modeling of complex systems. In this presentation, I will discuss recent work on network phenomena with unprecedented properties that stem from this research. I will motivate the discussion with examples from diverse domains---including microfluidics, metamaterials, biophysics, and control---and substantiate the main results with both theory and experiments. In particular, I will discuss the recently established possibility of converse symmetry breaking, an emergent phenomenon in which stable states of a system are symmetric only when the system itself is not. Systems exhibiting converse symmetry breaking can violate the fundamental and widely held assumption that individual entities are more likely to exhibit the same behavior if they are identical. In such cases, system heterogeneity can serve as an unexpected source of behavioral homogeneity, which is of relevance to processes relying on synchronization, consensus, and coherence. I will discuss applications and implications to fundamental physics as well as biological and technological systems. Ultimately, I hope to convey that our research in network science is not only benefiting from statistical mechanics and nonlinear dynamics, but also fostering foundational discoveries in these areas.
Host: Sergei Tretiak