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

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

Green, Sara and Robert Batterman. Making Sense of Top-Down Causation: Universality and Functional Equivanence in Physics and Biology. Voosholz, J and M. Gabriel, eds.. Top_Down Causation and Emergence. Cambridge: MIT Press, 2021. In an 80th birthday Festschrift for George Ellis, University of Copenhagen and University of Pittsburgh philosophers make a latest strong case for this natural constructive method, (aka a universe which makes itself.) While doing so, they further affirm a persistent, analogic recurrence in kind across physical and biological phenomena.

Hagan, Michael and Aparna Baskaran. Emergent Self-Organization in Active Materials. Current Opinion in Cell Biology. 38/74, 2016. For the record, we ought to note that just a decade ago, as earlier entries show, a evidential recognition of such cellular spontaneity was rare and in abeyance. Here Brandeis University physicists provide a 2017 example of its common acceptance as metabolic physiology and anatomy becomes an exemplar of nonlinear complexity.

Biological systems exhibit large-scale self-organized dynamics and structures which enable organisms to perform the functions of life. The field of active matter strives to develop and understand microscopically driven nonequilibrium materials, with emergent properties comparable to those of living systems. This review will describe two recently developed classes of active matter systems, in which simple building blocks — self-propelled colloidal particles or extensile rod-like particles — self-organize to form macroscopic structures with features not possible in equilibrium systems. We summarize the recent experimental and theoretical progress on each of these systems, and we present simple descriptions of the physics underlying their emergent behaviors. (Abstract)

Hallatschek, Oskar, et al. Proliferating Active Matter. Nature Reviews Physics. May, 2023. Some 15 years after this field gained recognition (S. Ramaswamy), UC Berkeley, Leipzig University, University of Basel, MIT, University of Edinburgh, and Princeton University researchers including Ned Wingreen provide an extensive, 200 reference survey of a wealth of evidence across all manner of physical and biological phases such as particulate, colloidal, cellular flows and even avian flocks to acquire their own self-organized patterns and processes. Once more in mid 2023 a robust, organic integrity becomes well established.

Active matter locally dissipates energy to produce systematic motion. This Perspective highlights proliferation as a special type of activity that breaks particle number conservation and thereby gives rise to a unique set of collective phenomena characteristic of life. (editor)

The patterns of collective motion created by autonomous particles have fuelled active-matter research for two decades. But so far these studies have focused on candidate entities. In reality, living systems involve the growth and evolution of microbial biofilms, expansion of a tumour, the development from a fertilized egg into an embryo. Here we argue that unique features emerge because proliferation represents a distinct activity that consumes and dissipates energy, injects biomass, and leads to myriad dynamic scenarios. Complex, collective phenomena in these soft-matter phases moves us to propose expansive generation as another direction of active-matter physics, worthy of new dynamical universality classes. (Abstract edits)

Examples of Active Matter Proliferation: Growing cells, shapes and populations have often been studied in mathematical biology at a meanfield level so to observe phenomena in microbiology, development, ecology, epidemiology, group dynamics and evolution. Several generic model systems of active matter collectives have thus emerged. One prototypical example combining soft matter and growth is provided by microbial biofilms on solid, semisolid or liquid substrates into resilient communities. These surface bacteria are abundant in nature composed either of clonal cells or diverse species. Complex physical properties contribute to their expansive presence, evolutionary success and their
important role in human disease. (5)

Havlin, Shlomo, et al. Focus on Complex Networked Systems. www.iop.org/EJ/journal/1367-2630. Accessed December 2007. An introduction to a special section of 20 papers on this subject in the online resource The New Journal of Physics, published by the European Institute of Physics, in association with the American Institute of Physics, in their joint Virtual Journal in Science and Technology program. A salient feature is said to be their recursive, multifractal self-similarity.

Complex networks are becoming manifest in many fields of contemporary science, including mathematics, physics, computer science, biology, engineering, social sciences and economics. As part of a broad movement towards research in complex systems, scientists have recently found a striking degree of self-organization that emerges in networks representing seemingly diverse complex systems. (179) The last decade has witnessed a burst of research activity in the study of large systems made of many non-identical entities, whose interaction or interconnection patterns show complex network-like structures. (179)

Haw, Mark and Otti Croze. Physics Comes to Life. Physics World. February, 2012. A University of Strathclyde chemist and University of Glasgow mathematician contend that recent laboratory studies of aquatic schools of bacteria and algae, as typical many-body systems, require a 21st version of physical theories to explain. May it then be surmised that as statistical physics and complexity science converge, each approach can be deeply and beneficially revised. As a consequence, an ever stronger case bodes for an intrinsically organic cosmos.

Statistical mechanics, one of the 19th century’s most successful scientific theories, describes systems comprising billions of inanimate atoms and molecules. But does this fundamental theory work the same way when applied to swarms of non-equilibrium, self-propelling, environment-exploring swimmers? It turns out that a new “living” statistical mechanics is required to describe many aspects of microswimmer behaviors. (39-40)

Helbing, Dirk, et al, eds. Nonlinear Physics Everywhere From Molecules to Cities. European Physical Journal B. 63/3, 2008. A collection from the European Conference on Complex Systems 2007 in this periodical dedicated to “Condensed Matter and Complex Systems.” A typical paper is Why are Large Cities Faster?: Universal Scaling and Self-Similarity in Urban Organization and Dynamics by Luis Bettencourt, Jose Lobo, and Geoffrey West. An import might be to note two optional modes of study – either to discern the same complex network patterns and processes at each manifest, emergent scale, or trace an inference that this phenomena implies and springs from a common, mathematically creative source.

Herbert-Dufresne, Laurent, et al. Structural Preferential Attachment: Stochastic Process for the Growth of Scale-free, Self-similar Systems. Physical Review E. 85/026108, 2012. Département de Physique, de Génie Physique, et d'Optique, Université Laval, Québec, physicists contribute to this distillation of ubiquitous commonalities across nature and society. As such work proceeds, the presence and instantiation of a cosmic genetic code from galactic clusters to hemispheric civilizations seems ever more evident. For further team work, see A Preferential Attachment Approach to Community Structure at arXiv:1603.035566 which notes the apparent universality of this method.

Many complex systems have been shown to share universal properties of organization, such as scale independence, modularity, and self-similarity. We borrow tools from statistical physics in order to study structural preferential attachment (SPA), a recently proposed growth principle for the emergence of the aforementioned properties. We study the corresponding stochastic process in terms of its time evolution, its asymptotic behavior, and the scaling properties of its statistical steady state. Moreover, approximations are introduced to facilitate the modeling of real systems, mainly complex networks, using SPA. Finally, we investigate a particular behavior observed in the stochastic process, the peloton dynamics, and show how it predicts some features of real growing systems using prose samples as an example. (Abstract)

Hernandez-Bermejo, Benito. Renormalization Group Approach to Power-Law Modeling of Complex Metabolic Networks. Journal of Theoretical Biology. Article in Press, 2010. A Universidad Rey Juan Carlos, Madrid, physicist identifies common parallels between this physical method and nature’s self-similarity, to wit each and all are trying to explain with disparate terms, the one same ubiquitous phenomena.

In the modeling of complex biological systems, and especially in the framework of the description of metabolic pathways, the use of power-law models often provides a remarkable accuracy over several orders of magnitude in concentrations, an unusually broad range not fully understood at present. In order to provide additional insight in this sense, this article is devoted to the renormalization group analysis of reactions in fractal or self-similar media. (Abstract)

This explains also the close relationship of the renormalization group invariant solutions and fractality. In fact, historically the notions of fractal and renormalization group appeared independently, but both were intended to analyze what is invariant under the change of scale of observation: fractal for geometrical objects, and renormalization group for physical quantities. (2)

Heylighen, Francis. The Self-Organization of Time and Causality. Foundations of Science. 15/4, 2010. Within this complexity revolution, the Vrije Universiteit Brussel systems thinker and director of its Evolution, Complexity, & Cognition Group seeks more formally stated, albeit abstract, explanations of a cosmic and earthly nature that evidently seems to be not expiring but somehow winding itself up in a developmental way. In this Autumn 2010 paper, theories can lately be extended to imagine an innately self-arranging and creating universe.

In the case of causality, the variations can be conceived as causal agents that embody different condition-action or cause-effects. In the case of basic laws of physics, the agents are likely to represent elementary particles or fields. Since the agents interact, in the sense that the effect of one’s action forms an initial condition or cause for another one’s subsequent action, they together form a complex dynamical system. These systems are known to necessarily self-organize, in the sense that the overall dynamics settles into an attractor. (355)

As yet, we know too little about the dynamics of such a primordial complex dynamical system to say anything about what kind of causal rules might emerge from such a self-organization at the cosmic scale. However, the general notion of self-organization based on variation and selection suggests some general features of the resulting order, such as the fact that it will be partly contingent, partly predictable, and context-dependent rather than absolute. (355)

Hidalgo, Jorge, et al. Cooperation, Competition and the Emergence of Criticality in Communities of Adaptive Systems. Journal of Statistical Mechanics. March, 033203, 2016. As the quotes describe, a theorist team of Hidalgo and Miguel Munoz, University of Granada and Jacopo Grilli, Samir Suweis, and Amos Maritan, University of Padova (search for prior papers) continues their project to quantify the features and propensities of life’s finely poised dynamic phenomena. As this paper and many others express, in accord with traditional wisdom, a universal balance of harmony and disorder does seem to be evident everywhere.

The hypothesis that living systems can benefit from operating at the vicinity of critical points has gained momentum in recent years. Criticality may confer an optimal balance between too ordered and exceedingly noisy states. Here we present a model, based on information theory and statistical mechanics, illustrating how and why a community of agents aimed at understanding and communicating with each other converges to a globally coherent state in which all individuals are close to an internal critical state, i.e. at the borderline between order and disorder. We study—both analytically and computationally—the circumstances under which criticality is the best possible outcome of the dynamical process, confirming the convergence to critical points under very generic conditions. Finally, we analyze the effect of cooperation (agents trying to enhance not only their fitness, but also that of other individuals) and competition (agents trying to improve their own fitness and to diminish those of competitors) within our setting. (Abstract)

In a recent work with a fresh perspective [29], criticality has been shown to emerge in communities of individuals/agents trying to communicate with each other and creating a collective entity. This approach considers a community of individuals equipped with a (genetic, neural, regulation...) network representing the internal configuration of each individual agent. The state of each of such networks is controlled by some parameters that completely determine the steady state probability distribution function of internal con figurations. It is assumed that the state of each single agent is defined by such a probability distribution. Each individual of the community tries to mimic, i.e. to infer or “understand", the state of others within a community. With unexpected generality, under this dynamics, the community experiences a drift toward the critical point of the network dynamics, i.e. at the edge between ordered and disordered states. (3)

Hidalgo, Jorge, et al. Emergence of Criticality in Living Systems through Adaptation and Evolution: Practice Makes Critical. arXiv:1307.4325. A posting in its Condensed Matter: Statistical Mechanics section by systems physicists Hidalgo and Miguel Munoz, University of Granada, Spain, Jacopo Grilli, Samir Suweis, and Amos Maritan, University of Padova, Italy, and Jaynath Banavar, University of Maryland, USA. In regard, a contribution to this scientific synthesis – a material cosmos which is innately conducive for life, and a universality of critically poised, self-organized, dynamic networks that grace such bodies, brains and societies.

Empirical evidence has proliferated that living systems might operate at the vicinity of critical points with examples ranging from spontaneous brain activity to flock dynamics. Such systems need to cope with and respond to a complex ever-changing environment through the construction of useful internal maps of the world. Here we employ tools from statistical mechanics and information theory to prove that systems poised at criticality are much more efficient in ensuring that their internal maps are good proxies of reality. Analytical and computational evolutionary models vividly illustrate that a community of such systems dynamically self-tunes toward a critical state either as the complexity of the environment increases or even upon attempting to map with fidelity the other agents in the community. Our approach constitutes a general explanation for the emergence of critical-like behavior in complex adaptive systems. (Abstract)

These general ideas can be exploited to construct a quantitative framework, which clearly demonstrates that self-tuning to criticality is a strategy adopted by living systems to effectively represent the external world. The critical point reached in this way represents a borderline between a disordered phase in which perturbations and noise propagate unboundedly and an ordered phase whereas changes are rapidly erased –hindering plasticity– thereby providing an excellent compromise between flexibility and accuracy. (2)

Janson, Natalia. Non-Linear Dynamics of Biological Systems. Contemporary Physics. 53/2, 2012. As a cosmic and vital spontaneities flow together, a Loughborough University, UK, mathematical physicist, with a doctorate from Saratov State University, Russia, contributes a technical tutorial upon exemplary phenomena such as “oscillatory dynamics” in cardiac physiology, respiration, and metabolism. With Ilya Prigogine, Herman Haken, and earlier Leonid Mandelstam as guides, living systems are seen to progressively arise from non-equilibrium, self-organizing thermodynamics.

All living systems, their parts, or their populations, have three properties in common. Firstly, they feed on externally supplied nutrients, regularly remove the products of decay, and exchange signals with the surrounding objects. In other words, they exchange matter, energy, and information with the environment and thus belong to the wide class of open systems. Secondly, even if they do not demonstrate any obvious activity, they constantly lose energy to the external world, and are thus dissipative systems. Thirdly, all living systems are non-linear, which means, broadly speaking, that their response to a sum of external inputs is not equivalent to a sum of their responses to the individual inputs. It is the combination of these three features that lead to the remarkable properties that we observe in living systems, such as the ability to live and survive, and to develop and learn. (137)

Here we look at biological systems from the viewpoint of the discipline known under a variety of names: complexity theory, synergetics, self-organization theory, chaos theory, or nonlinear dynamics – in what follows we will use the latter name. It is based on a vast number of discoveries in mathematics and physics made during as many as five centuries. (137)

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