III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

2. Computational Systems Physics: Self-Organization, Active Matter

Wissner-Gross, Alexander and Cameron Freer. Causal Entropic Forces. Physical Review Letters. 110/168702, 2012. For some context, I began my curious readings about a half century ago. In the early 1960s, with the DNA double helix recently found, a big bang origin proven in 1965, we valiant earthlings seemed at odds with, not at home in or lost in, a vast, roiling galactic cosmos. It is a huge achievement to now note studies as this by Harvard University and University of Hawaii theorists, and many others herein, that are able to view and join human and universe in a seamless continuum by way of innate, dynamical, procreative properties. As a nonlinear self-organizing, complexity science explains an increasingly fertile material milieu, might a “systems cosmology” be appropriate for a natural genesis universe.

Recent advances in fields ranging from cosmology to computer science have hinted at a possible deep connection between intelligence and entropy maximization, but no formal physical relationship between them has yet been established. Here, we explicitly propose a first step toward such a relationship in the form of a causal generalization of entropic forces that we find can cause two defining behaviors of the human “cognitive niche”—tool use and social cooperation—to spontaneously emerge in simple physical systems. Our results suggest a potentially general thermodynamic model of adaptive behavior as a nonequilibrium process in open systems. (Abstract)

To the best of our knowledge, these tool use puzzle and social cooperation puzzle results represent the first successful completion of such standard animal cognition tests using only a simple physical process. The remarkable spontaneous emergence of these sophisticated behaviors from such a simple physical process suggests that causal entropic forces might be used as the basis for a general—and potentially universal—thermodynamic model for adaptive behavior. Namely, adaptive behavior might emerge more generally in open thermodynamic systems as a result of physical agents acting with some or all of the systems’ degrees of freedom so as to maximize the overall diversity of accessible future paths of their worlds (causal entropic forcing). (168702-4)

These results have broad physical relevance. In condensed matter physics, our results suggest a novel means for driving physical systems toward self-organized criticality. In particle theory, they suggest a natural generalization of entropic gravity. In econophysics, they suggest a novel physical definition for wealth based on causal entropy. In cosmology, they suggest a path entropy-based refinement to current horizon entropy-based anthropic selection principles that might better cope with black hole horizons. Finally, in biophysics, they suggest new physical measures for the behavioral adaptiveness and sophistication of systems ranging from biomolecular configurations to planetary ecosystems. (168702-5)

Yeung, Chi Ho and David Saad. Networking – A Statistical Physics Perspective. Journal of Physics A: Mathematical and Theoretical. 46/10, 2013. Nonlinearity and Complexity Research Group, Aston University, Birmingham, UK researchers offer a Topical Review of the many junctures of this ubiquitous biological propensity with an inherently dynamic physical reality. Once again life’s roots are found to run deeper into an increasingly fertile natural ground. As the second quote avers, while not yet seen akin to a Systems Physics, an epochal revolution is underway.

Networking encompasses a variety of tasks related to the communication of information on networks; it has a substantial economic and societal impact on a broad range of areas including transportation systems, wired and wireless communications and a range of Internet applications. As transportation and communication networks become increasingly more complex, the ever increasing demand for congestion control, higher traffic capacity, quality of service, robustness and reduced energy consumption requires new tools and methods to meet these conflicting requirements. The new methodology should serve for gaining better understanding of the properties of networking systems at the macroscopic level, as well as for the development of new principled optimization and management algorithms at the microscopic level. Methods of statistical physics seem best placed to provide new approaches as they have been developed specifically to deal with nonlinear large-scale systems. This review aims at presenting an overview of tools and methods that have been developed within the statistical physics community and that can be readily applied to address the emerging problems in networking. (Abstract)

The Non-linearity and Complexity Research Group has high international visibility in the areas of pattern analysis, probabilistic methods, non-linear dynamics and the application of methods from statistical physics to the analysis of complex systems. The underpinning methodology used includes principled approaches from probabilistic modelling, Bayesian statistics, statistical mechanics and non-linear stochastic and deterministic differential equations. Particularly significant application domains include Biomedical Information Engineering and Signal Processing, Health Informatics, Environmental Modelling and Weather Forecasting, Error-correcting Codes and Multi-user Communication, Complex Systems and Networks, Solitons and Optical Fibers, and Chaos and turbulence. (Aston University)

Zeravcic, Zorana, et al. Toward Living Matter with Colloidal Particles. Reviews of Modern Physics. 89/031001, 2017. Zeravcic, CNRS, Paris, with Vinothan Manoharan and Michael Brenner, Harvard, contribute an array of sophisticated insights as physical materiality becomes increasingly imbued with innate organic structures and movements. A persistent tendency to achieve self-replicative and metabolic states is evident. One may add that in turn well infers an animate, procreative ecosmos.

A fundamental unsolved problem is to understand the differences between inanimate matter and living matter. Although this question might be framed as philosophical, there are many fundamental and practical reasons to pursue the development of synthetic materials with the properties of living ones. There are three fundamental properties of living materials that we seek to reproduce: The ability to spontaneously assemble complex structures, the ability to self-replicate, and the ability to perform complex and coordinated reactions that enable transformations impossible to realize if a single structure acted alone. The conditions that are required for a synthetic material to have these properties are currently unknown. This Colloquium examines whether these phenomena could emerge by programming interactions between colloidal particles, an approach that bootstraps off of recent advances in DNA nanotechnology and in the mathematics of sphere packings. (Abstract excerpt)

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