Brian #Josephson (2016)

Lecture and Discussion: #Emergent #Self-Organising Activity as the true #foundation of #Reality

http://www.mediatheque.lindau-nobel.org/videos/36145/lecture-emergent-self-organising-activity

Abstract

The presumptions underlying quantum mechanics make it relevant to a limited range of situations only1; furthermore, its statistical character means that it provides no answers to the question ‘what is really going on?’. In line with Barad’s discussions of the way quantum measurements introduce definiteness into previously indefinite situations, it is hypothesised that the underlying mechanics has parallels with human activities. We are led to consider a subtle type of order, different from those commonly encountered in the discipline of physics, and yet comprehensible in terms of concepts considered by Barad and Yardley such as oppositional dynamics or ‘intra-actions’2. The emergent organisation implies that nature is no longer fundamentally meaningless.

We are led to consider a subtle type of order, different from those commonly encountered in the discipline of physics, and yet comprehensible in terms of concepts considered by Barad and Yardley such as oppositional dynamics or ‘intra-actions’. The emergent organisation implies that nature is no longer fundamentally meaningless.

NB: the slides for this lecture are available separately at
http://www.tcm.phy.cam.ac.uk/~bdj10/Documents/Lindau2016-slides.pdf.

Clarifications added after lecture: agencies can be viewed as dynamical systems, so we are dealing with models involving interacting dynamical systems. The 'congealing of agencies' to whch Barad refers can equated to the presence of regulatory mechanisms restricting the range of possibilities open to the agencies concerned.

The difference between #reversible and #irreversible events has particular explanatory value in #complex_systems (such as living organisms, or ecosystems). According to the biologists Humberto Maturana and Francisco Varela, living organisms are characterized by autopoiesis, which enables their continued existence. More primitive forms of self-organizing systems have been described by the physicist and chemist Ilya Prigogine. In the context of complex systems, events which lead to the end of certain #self-organising processes, like death, extinction of a species or the collapse of a meteorological system can be considered as irreversible. Even if a clone with the same organizational principle (e.g. identical DNA-structure) could be developed, this would not mean that the former distinct system comes back into being. Events to which the self-organizing capacities of organisms, species or other complex systems can adapt, like minor injuries or changes in the physical environment are reversible. However, #adaptation depends on import of negentropy into the organism, thereby increasing irreversible processes in its environment. Ecological principles, like those of sustainability and the precautionary principle can be defined with reference to the concept of reversibility.

https://en.wikipedia.org/wiki/Irreversible_process#Complex_systems

📝 Sensitive dependence of network dynamics on network structure

Takashi Nishikawa, Jie Sun, Adilson E. Motter

https://arxiv.org/pdf/1611.01164v1

📌 ABSTRACT
The relation between network structure and dynamics is determinant for the behavior of complex systems in numerous domains. An important longstanding problem concerns the properties of the networks that optimize the dynamics with respect to a given performance measure. Here we show that such optimization can lead to sensitive dependence of the dynamics on the structure of the network. Specifically, we demonstrate that the stability of the dynamical state, as determined by the maximum Lyapunov exponent, can exhibit a cusp-like dependence on the number of nodes and links as well as on the size of perturbations applied to the network structure. As mechanisms underlying this sensitivity, we identify discontinuous transitions occurring in the complement of optimal networks and the prevalence of eigenvector degeneracy in these networks. These findings establish a unified characterization of networks optimized for dynamical stability in diffusively coupled systems, which we illustrate using Turing instability in activator-inhibitor systems, synchronization in power-grid networks, and several other examples. Our results suggest that the network structure of a complex system operating near an optimum can potentially be fine-tuned for a significantly enhanced stability compared to what one might expect from simple extrapolation. On the other hand, they also suggest constraints on how close to the optimum the system can be in practice. Finally, the results have potential implications for biophysical networks, which have evolved under the competing pressures of optimizing fitness while remaining robust against perturbations.

#Adaptation and #Self-Organizing Systems (nlin.AO); Physics and Society (physics.soc-ph)