Experimental Proof of the Theory of Interdependent Networks: Novel Superconducting Phase Transitions
Prof. Shlomo Havlin, Bar-Ilan University
A theoretical framework for the percolation of interdependent networks will be presented. In interdependent networks, such as infrastructures, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This may happen recursively and can lead to a cascade of failures and to a sudden fragmentation of the system. This is in contrast to a single network where the percolation transition due to failures is continuous. I will present analytical solutions based on the percolation theory, for the functional network and cascading failures, for a network of n interdependent networks. Our analytical results show that the percolation theory of a single network studied for over 90 years is just a limited case, n=1, of the general and a significantly richer case of n>1. I will also show that interdependent networks embedded in space are extremely vulnerable and have significantly richer behavior compared to non-embedded networks. In particular, it will be shown that a novel phase appears where localized attacks of a microscopic critical size lead to cascading failures that dynamically propagate like nucleation and yield an abrupt macroscopic phase transition. I will finally show that the abstract interdependent percolation theory and its novel behavior in networks of networks can be realized and proven in controlled experiments performed by Aviad Frydman on real physical systems. I will present recent experiments that support the interdependent network theory performed in laboratory measurements of interdependent superconducting networks. Here, a novel abrupt phase transition is observed due to microscopic interactions between the macroscopic systems. This is in contrast to an isolated system that shows a continuous phase transition.
References
Control of co-evolutionary opinion and action dynamics in cyber-physical-human networks
Prof. Ming Cao, University of Groningen
Cyber-physical-human networks (CPHN) occur in a wide range of application domains, ranging from autonomous robotics to the smart grid and sustainable technologies. The size and scale of CPHN and the role that the human (or humans) play vary significantly, and yet all such systems have complexities which make control and regulation a significant challenge. Engineers and practitioners face both classical and emergent challenges when dealing with CPHN. In this talk, I first review modeling techniques, especially those from game theory, for some emerging CPHN of increasing research interest. Then I will focus on how such game models can be effectively used to analyze the complex co-evolutionary dynamics of opinions and actions in the collective decision making processes. I will also demonstrate how control actions can be introduced through the human interactions with the cyber-physical part of the system.
Cascading transitions in psycho-social systems
Prof. Han van der Maas, University of Amsterdam
Tipping points or phase transitions separate stable states in psycho-social systems. Examples are quitting smoking, radicalization, and dropping-out of school. Two knowledge gaps prevent our ability to predict and control these tipping points. First, we miss explanatory mathematical models of such non-linear processes. Second, we ignore the multilevel character of psycho-social transitions. I contend that important changes in many psycho-social systems are cascading transitions, where individual transitions trigger or are triggered by social transitions. The cascade of radicalization of individuals in the context of political polarization in societies is an example of such a multilevel process. Being able to predict and control cascading transitions in psycho-social systems would be a major scientific breakthrough.