Critical Transitions In a Model of a Genetic Regulatory System

We consider a model for substrate-depletion oscillations in genetic systems, based on a stochastic differential equation with a slowly evolving external signal. We show the existence of critical transitions in the system. We apply two methods to numerically test the synthetic time series generated by the system for early indicators of critical transitions: a detrended fluctuation analysis method, and a novel method based on topological data analysis (persistence diagrams).Comment: 19 pages, 8 figure

If you're a fish, what can you know about the water?

The authors of this paper have been engaged in Systems Thinking, Systems Practice and Systems Teaching for many years. In this paper they reflect on their experience of engaging systemically with their own organisation in order to bring about change. Re-structuring the Systems Department of the UK's Open University to create new sites for emergence of fresh ideas, interests and enthusiasms raised questions about meaning and purpose as well as theoretical questions about practice. The authors describe their own attempts to answer these questions and to manage their own evolving understandings and emotionings by reflecting on some critical incidents

Universal properties of many-body delocalization transitions

We study the dynamical melting of "hot" one-dimensional many-body localized systems. As disorder is weakened below a critical value these non-thermal quantum glasses melt via a continuous dynamical phase transition into classical thermal liquids. By accounting for collective resonant tunneling processes, we derive and numerically solve an effective model for such quantum-to-classical transitions and compute their universal critical properties. Notably, the classical thermal liquid exhibits a broad regime of anomalously slow sub-diffusive equilibration dynamics and energy transport. The subdiffusive regime is characterized by a continuously evolving dynamical critical exponent that diverges with a universal power at the transition. Our approach elucidates the universal long-distance, low-energy scaling structure of many-body delocalization transitions in one dimension, in a way that is transparently connected to the underlying microscopic physics.Comment: 12 pages, 6 figures; major changes from v1, including a modified approach and new emphasis on conventional MBL systems rather than their critical variant

Highly Optimized Tolerance: Robustness and Power Laws in Complex Systems

We introduce highly optimized tolerance (HOT), a mechanism that connects evolving structure and power laws in interconnected systems. HOT systems arise, e.g., in biology and engineering, where design and evolution create complex systems sharing common features, including (1) high efficiency, performance, and robustness to designed-for uncertainties, (2) hypersensitivity to design flaws and unanticipated perturbations, (3) nongeneric, specialized, structured configurations, and (4) power laws. We introduce HOT states in the context of percolation, and contrast properties of the high density HOT states with random configurations near the critical point. While both cases exhibit power laws, only HOT states display properties (1-3) associated with design and evolution.Comment: 4 pages, 2 figure

Evolving Systems: Adaptive Key Component Control and Inheritance of Passivity and Dissipativity

We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. Autonomous assembly of large, complex flexible structures in space is a target application for Evolving Systems. A critical requirement for autonomous assembling structures is that they remain stable during and after assembly. The fundamental topic of inheritance of stability, dissipativity, and passivity in Evolving Systems is the primary focus of this research. In this paper, we develop an adaptive key component controller to restore stability in Nonlinear Evolving Systems that would otherwise fail to inherit the stability traits of their components. We provide sufficient conditions for the use of this novel control method and demonstrate its use on an illustrative example

To Trust or Not to Trust? Developing Trusted Digital Spaces through Timely Reliable and Personalized Provenance

Organizations are increasingly dependent on data stored and processed by distributed, heterogeneous services to make critical, high-value decisions. However, these service-oriented computing environments are dynamic in nature and are becoming ever more complex systems of systems. In such evolving and dynamic eco-system infrastructures, knowing how data was derived is of significant importance in determining its validity and reliability. To address this, a number of advocates and theorists postulate that provenance is critical to building trust in data and the services that generated it as it provides evidence for data consumers to judge the integrity of the results. This paper presents a summary of the STRAPP (trusted digital Spaces through Timely Reliable And Personalised Provenance) project, which is designing and engineering mechanisms to achieve a holistic solution to a number of real-world service-based decision-support systems