Understanding Ultrafast Instabilities in a Global Cyber-Physical System

Abstract: Most future CPS systems will represent a complex, messy mix of hardware, software and human interactions - and may produce dangerous instabilities quicker than some external controller can react. The specific focus and motivation of this project concerns modeling and understanding the dynamics of such CPS that are large and evolve in a decentralized way due to changing market conditions, yielding a system comprising many heterogeneous components that may have incompatible communication protocols (e.g. subsets of actuators and sensors built by different manufacturers and/or operated by competing entities). The number operating at any one time may also fluctuate, creating a time-dependent ecology comprising anywhere from a few hundred to several million distinct pieces of hardware, software or mechanical components. Since much of the future 'CPS ecology' will be driven by technological advances in optoelectronics, which itself is racing toward the nanosecond operating scale, the overall CPS operation may produce undesirable behaviors on timescales lying beyond human response times, meaning that the CPS cannot be overridden in real time by any human-in-the-loop. In short, the CPS may operate quicker than any human regulator or moderator can respond. Such sudden extremes can also occur on the slower scales of minutes and days, as long as the underlying nucleating activity is sufficiently hidden within the CPS system and hence takes longer for any human-in-the-loop to find than it does to occur. This raises the following key scientific questions which are of core interest to the safety and security of all large-scale CPS implementations: What is the nature of such emergent instabilities? How can they be described mathematically in a way that gives insight and quantitative results that are applicable across CPS systems, and are also scalable to CPS systems of any size? Our methodology to approach such questions is that of generalized statistical mechanics from physics, in which the details of individual nodes become washed out in favor of a focus on the correlations that develop between components - even though these components may be actively competing rather than cooperating. We focus on developing a rigorous yet practical mathematical description of extreme behaviors in societal CPS ecologies comprising arbitrarily large numbers of heterogeneous components (sensors/actuators). By contrast, most existing theoretical descriptions of CPS systems focus on the optimal behavior of a well-defined CPS system with finite size and a known, fixed number of components. We have already developed reasonably generic, scalable models that are minimal in their structure and amenable to mathematical analysis, yet highly non-trivial in terms of their ability to produce complex dynamics of the type observed empirically across a wide variety of real-world complex systems and networks. Our modeling approach considers a dynamical multi-agent game which spontaneously produces large, unexpected (and hence unsafe or insecure) behaviors. The model features an arbitrary number of heterogeneous, adaptive sensor-actuator components which feed in information from the outside (sensor) and take an action (actuator). Though developed in a simplified environment, the findings of the model should hold in far more general situations since they depend on a just a few commonly encountered system features. In Year 3, we are focusing on 3 major application areas [1-10]: (1) CPS and social media online, (2) how less sophisticated components in a CPS can actually be beneficial, with a focus on navigation toward a target, and (3) initial exploration of the impact of having decision-making humans in the loop. More generally, this project promises new science not just for applications of CPS, but also for the core question of dynamical behavior of CPS complex systems. Broader impacts also include the promise of enhanced safety and security across a wide variety of societal CPS systems, from financial networks, smart energy buildings and cities, to autonomous vehicle design, both at individual and swarm level. Products from this year of 2018 to date, include:

1. "David Versus Goliath: Fundamental Patterns and Predictions in Modern Wars and Terrorist Campaigns", PLOS ONE (in press, 2018); Michael Spagat, Neil F Johnson, Stijn van Weezel
2. "Impact on the topology of power-law networks from anisotropic and localized access to information", Phys. Rev E (in press, 2018); Zhenfeng Cao, Zhou He, and Neil F. Johnson
3. "Generalized gelation theory describes onset of online extremist support", Phys. Rev. Lett. 121, 048301 (2018); P.D. Manrique, M.Zheng, Z. Cao, E.M. Restrepo, N.F. Johnson
4. "Pulsed Generation of Quantum Coherences and Non-classicality in Light-Matter Systems", Frontiers in Physics 6:92. doi: 10.3389/fphy.2018.00092 (2018); Fernando Javier Gomez-Ruiz, Oscar Leonardo Acevedo, Ferney Rodriguez, Luis Quiroga, Neil Johnson
5. "Decentralized competition produces nonlinear dynamics akin to klinotaxis", Complexity 2018, Article ID 9803239 (2018) https://doi.org/10.1155/2018/9803239; Pedro Manrique, Mason Klein, Yao Sheng Li, Chen Xu, Pak Ming Hui and Neil F. Johnson
6. "Universality and correlations in individuals wandering through an online extremist space". Phys. Rev. E 97, 032315 (2018); Z. Cao, M. Zheng, Y. Vorobyeva, C. Song, N.F. Johnson
7. "Individual heterogeneity generates explosive system network dynamics", Phys. Rev. E 97, 032311 (2018); Pedro D. Manrique, Neil F. Johnson
8. "Complexity in individual trajectories toward online extremism", Complexity 2018, Article number 3929583 (2018); Z. Cao, M. Zheng, Y. Vorobyeva, C. Song, N.F. Johnson
9. "Multiscale dynamical network mechanisms underlying aging from birth to death", Sci. Rep. 8, 3552 (2018); M. Zheng, Z. Cao, Y. Vorobyeva, P. Manrique, C. Song, N.F. Johnson
10. "Dynamics of entanglement and the Schmidt gap in a driven light-matter system". J. Phys. B: At. Mol. Opt. Phys. 51, 024001 (2018); Fernando Javier Gomez-Ruiz, Juan Jose Mendoza-Arenas, Oscar Acevedo, Ferney J Rodriguez, Luis Quiroga and Neil F Johnson

Explanation of Demonstration: We demonstrate 2 exciting new CPS results obtained this year from our research: (1) The discovery and detection of potentially dangerous gel formation within large CPS systems that include populations of humans and bots interacting through social media. This is shown in the demo as an evolving network. (2) The discovery that large delocalized CPS systems can get closer to a target by having components that are not too sophisticated. Put another way: we show that increasing the sophistication of CPS components too much becomes detrimental to the CPS system performance and efficiency.