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

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

Tkacik, Gasper and Aleksandra Walczak. Information Transmission in Genetic Regulatory Networks: A Review. Journal of Physics: Condensed Matter. 23/15, 2011. In regard I heard physicist Nigel Goldenfeld (search) at the University of Massachusetts, Amherst in October 2013 announce that “Biology is the physics of the 21st century.” This report in an Institute of Physics (IOP) journal by Institute of Science and Technology, Austria, and CRNS-Ecole Normale Superieure, Paris theorists could be a good example of this turn, among an increasing number in traditional physics periodicals. It illustrates the realization, and grand promise, that one whole uniVerse must exist and be engaged this way whence physical and living systems can cross inform and fertilize each other. See also, e.g., a paper by Walczak, et al in Cooperative Societies about the nonlinear dynamics of bird flocks.

Genetic regulatory networks enable cells to respond to changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits has deepened our understanding of what kinds of computations genetic regulatory networks can perform, and with what reliability. These advances have motivated researchers to look for connections between the architecture and function of genetic regulatory networks. Transmitting information between a network's inputs and outputs has been proposed as one such possible measure of function, relevant in certain biological contexts. Here we summarize recent developments in the application of information theory to gene regulatory networks. We first review basic concepts in information theory necessary for understanding recent work. We then discuss the functional complexity of gene regulation, which arises from the molecular nature of the regulatory interactions. We end by reviewing some experiments that support the view that genetic networks responsible for early development of multicellular organisms might be maximizing transmitted 'positional information'. (Abstract)

Gašper Tkačik is a theoretical physicist who studies information processing in living systems. He uses tools from statistical physics of disordered systems and from information theory to investigate biological systems such as networks of neurons or genes. The unifying hypothesis driving his research has been that information processing networks have evolved or adapted to maximize the information transmitted from their inputs to the outputs, given the biophysical noise and resource constraints. He works closely with experimentalists and analyzes data sets that record simultaneously the behavior of many network components. Results of his work gave insight into the principles of genetic regulation in early morphogenesis of Drosophila and of information coding in retinal ganglion cells. In the future, he plans to expand his activities to study collective behavior and cellular self-organization. (GT website)

Aleksandra Walczak The precision and reproducibility of cellular processes poses a challenge to many-body physics and our understanding of the physical principles that control the emergent properties of biological systems. In my research I study the behaviour of such strongly coupled nonlinear systems that are not in equilibrium, mostly inspired by existing biological solutions. My main interest lies in the description of systems on the cellular scale - understanding the link between function, development and evolvability of conserved pathways and their elements. My recent focus has been on a number of concrete, not disjoint, topics: gene regulatory networks, the immune system and population genetics. (AW website)

Tkacik, Gasper, et al. Thermodynamics for a Network of Neurons: Signatures of Criticality. arXiv:1407.5946. A team from Austria, France, and the USA including Thierry Mora and William Bialek apply statistical mechanics concepts to an analysis of cerebral function and cogitation. Compare with a concurrent, similar paper by Sequn, Goh, et al about urban people movements.

The activity of a neural network is defined by patterns of spiking and silence from the individual neurons. Because spikes are (relatively) sparse, patterns of activity with increasing numbers of spikes are less probable, but with more spikes the number of possible patterns increases. This tradeoff between probability and numerosity is mathematically equivalent to the relationship between entropy and energy in statistical physics. We construct this relationship for populations of up to N=160 neurons in a small patch of the vertebrate retina, using a combination of direct and model-based analyses of experiments on the response of this network to naturalistic movies. We see signs of a thermodynamic limit, where the entropy per neuron approaches a smooth function of the energy per neuron as N increases. The form of this function corresponds to the distribution of activity being poised near an unusual kind of critical point. Networks with more or less correlation among neurons would not reach this critical state. (Abstract)

Trabesinger, Andreas, ed. Complexity. Nature Physics. 8/1, 2012. A general introduction to this special Insight section which focuses on and champions a decade and more of wide and deep progress in “network science.” Along with articles herein by Barabasi, Newman, and Vespignani, are “Between Order and Chaos” by James Crutchfield, and “Networks Formed from Interdependent Networks” by Jianxi Gao, Sergey Buldyrev, Eugene Stanley, and Shlomo Havlin. Within our Natural Genesis 2012 survey, here is a good example of the on-going worldwide discovery of a vital theory of “everywhere” that portends a universe to human genesis. With archetypal network “nodes and links,” or the “agents and interactions” of self-organizing adaptive systems, at what point, by what imagination within a true biological cosmos, can this realization be translated as the semblance and result of its actual parent to child “genetic code?”

Valani, Rahil and David Paganin. Deterministic Active Matter Generated Using Strange Attractors. arXiv:2110.03776. University of Adelaide and Monash University physicists provide a further mathematical finesse to explain a natural spontaneity which fosters and results in life-like movements across many substantial conditions.

Strange attractors are induced by governing differential or integro-differential equations associated with non-linear dynamical systems, but they can also drive such dynamics. When such equations contain stochastic forcing, they may be replaced by deterministic chaotic driving via an overall strange attractor. We outline a flexible deterministic means for chaotic strange-attractor driven dynamics, and illustrate its utility for modeling active matter. Similar phenomena may be modeled in this manner, such as run-and-tumble particles, run-reverse-flick motion, clustering, jamming and flocking. (Abstract)

Vespignani, Allessandro. Modelling Dynamical Processes in Complex Socio-Technical Systems. Nature Physics. 8/1, 2012. A Northeastern University, Boston, and Institute for Scientific Interchange, Torino, physicist further documents the seamless continuity from cosmos to civilization of the same prototypical, infinitely recurrent, network patterns and processes. What seems to accrue is an infinite nest that can only be explained as the exemplary effect of a natural genetic program.

Questions concerning how pathogens spread in population networks, how blackouts can spread on a nationwide scale, or how efficiently we can search and retrieve data on large information structures are generally related to the dynamics of spreading and diffusion processes. Social behaviour, the spread of cultural norms, or the emergence of consensus may often be modelled as the dynamical interaction of a set of connected agents. Phenomena as diverse as ecosystems or animal and insect behaviour can all be described as the dynamic behaviour of collections of coupled oscillators. Although all these phenomena refer to very different systems, their mathematical description relies on very similar models that depend on the definition and characterization of a large number of individuals and their interactions in spatially extended systems. (32)

The study of dynamical processes and the emergence of macrolevel collective behaviour in complex systems follows a conceptual route essentially similar to the statistical physics approach to non-equilibrium phase transitions. (32-33) One of the most important features affecting dynamical processes in real-world networks is the presence of dynamic self-organization and the lack of characteristic scales – typical hallmarks of complex systems. Although those characteristics have long been acknowledged as a relevant factor in determining the properties of dynamical processes, many real-world networks exhibit levels of heterogeneity that were not anticipated until a few years ago. (34)

Vicsek, Tamas and Anna Zafeiris. Collective Motion. arXiv:1010.5017. Eotvos University, Budapest, biophysicists offer in 47 pages a theoretical and experimental survey of this robust phenomena found across the natural kingdoms. From “non-living systems, to macromolecules, bacteria colonies, cells, insects, fish, birds, mammals, and onto human beings” a recurrent universality of interacting entities for the benefit of both individual and grouping occurs. As a result, a merger between statistical physics and nonlinear science appears increasingly viable.

We review the observations and the basic laws describing the essential aspects of collective motion - being one of the most common and spectacular manifestation of coordinated behavior. As such, these models allow the establishing of a few fundamental principles of flocking. In particular, it is demonstrated, that in spite of considerable differences, a number of deep analogies exist between equilibrium statistical physics systems and those made of self-propelled (in most cases living) units. In both cases only a few well defined macroscopic/collective states occur and the transitions between these states follow a similar scenario, involving discontinuity and algebraic divergences.

Wall, Michael, ed. Quantitative Biology: From Molecular to Cellular Systems. Boca Raton: CRC Press, 2012. Due by September, a volume in the Chapman & Hall/CRC Mathematical & Computational Biology Series. Typical chapters are Free Energies, Landscapes, and Fitness in Evolution Dynamics BY Robert Austin, System Design Principles, Michael Savage, Chance and Memory by Theodore Perkins, Andrea Weiße, and Peter Swain, and Information Theory and Adaptation, Ilya Nemenman, noted above.

The book is organized into three sections: Fundamental Concepts covers bold ideas that inspire novel approaches in modern quantitative biology. It offers perspectives on evolutionary dynamics, system design principles, chance and memory, and information processing in biology. Methods describes recently developed or improved techniques that are transforming biological research. It covers experimental methods for studying single-molecule biochemistry, small-angle scattering from biomolecules, subcellular localization of proteins, and single-cell behavior. It also describes theoretical methods for synthetic biology and modeling random variations among cells. Molecular and Cellular Systems focuses on specific biological systems where modern quantitative biology methods are making an impact. It incorporates case studies of biological systems for which new concepts or methods are increasing our understanding. Examples include protein kinase at the molecular level, the genetic switch of phage lambda at the regulatory system level, and Escherichia coli chemotaxis at the cellular level. (Publisher)

Weber, Christoph, et al. Physics of Active Emulsions. Reports on Progress in Physics. 82/6, 2019. As nature comes to life, MPI Physics of Complex Systems and Imperial College London biophysicists provide new appreciations of this broad class of colloidal, multi-droplet chemicals so to reveal their innate mobility. See also a Novel Physics Arising from Phase Transitions in Biology at arXiv:1809.11117.

In summary, we have discussed a new class of physical systems which we refer to as active emulsions. These emulsions are relevant to cell biology. They may allow to develop novel applications in the field of chemical engineering or aqueous computing and could help explain how life could have emerged from an inanimate mixture composed of set of simple chemically active molecules. However, the class of active emulsions also challenge our theoretical understanding of spatially heterogeneous systems driven far away from thermal equilibrium and can be used to refine existing theoretical concepts. In particular, active emulsions are characterised by non-equilibrium fluxes that maintain these system away from thermal equilibrium. (37)

White, Simon. Fundamentalist Physics: Why Dark Energy is Bad for Astronomy. Reports on Progress in Physics. 70/6, 2007. An astrophysicist at the Max Planck Institute worries that the integral approach of celestial observations will be compromised if it becomes too influenced by an experimental bent to look for a single reductive theory. Only an intentional synthesis of both micro and macro viewpoints can resolve.

Astrophysicists are universalists, democratic in perceiving interest in all aspects of the cosmos, while high-energy physicists are fundamentalists, cleaving to the pursuit of the single Truth. (889)

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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