Physics of complex systems: emergent properties, criticality and dynamical networks

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Physical, geophysical, chemical, living and man-made systems often show behaviors that cannot be understood by studying their building blocks or constituents to ever finer detail but that are emergent. The concept of emergence can be summarized by the statement that there exists an entity (e.g. an organism) which is more than the sum of its parts. This is often used as the defining property of a complex system. Many of these complex systems can be represented as a collection of dynamical units coupled via complex architectures. Complex network theory offers a unified description of these complex systems and has been invaluable in discovering unifying characteristics and principles despite the intrinsic differences between systems. Understanding these emergent characteristics and principles, their stability and the self-organization processes leading to them is one of the central quests of modern physics. Prominent examples include seismicity and neural signaling or biological signaling processes in general, with immense importance for society. A detailed understanding of seismicity is required to ensure successful seismic hazard assessment and to explore the possibility of successful earthquake prediction. A detailed understanding of the brain is essential to tackle brain related diseases such as Alzheimer's and epilepsy. The research program "Physics of complex systems: Emergent properties, criticality and dynamical networks" will establish new general concepts and data analysis tools to characterize and understand complex systems, will identify generic and universal properties by analyzing model systems and large scale data sets, and will collaborate with leading experimental groups to develop accurate theories for specific classes of systems. The phenomena under consideration include earthquake triggering in lab, natural and human-made settings as well as neuronal dynamics. We expect that our research will close a critical knowledge gap in our understanding of material failure, which is essential for progress in predicting the failure point. The proposed research will also allow us to develop probabilistic forecasting schemes suitable for seismicity induced by fluid injections. In addition, we anticipate that our unique study of the emergent properties in neuronal systems will enable us to make significant contributions to drug development related to neuronal diseases. This highlights the conceptual importance and far-reaching applications of this research program, promoting interdisciplinary approaches in general and the application of modern tools of statistical physics, nonlinear dynamics and complex network theory to fields outside the classical realm of physics in particular. At the same time, the research program will train highly qualified personnel and provide them with a unique, modern and interdisciplinary skill set benefiting the Canadian industry and Canada as a whole.