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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

2. Computational Systems Physics: Self-Organization

Jensen, Henrik and Elsa Arcaute. Complexity, Collective Effects, and Modeling of Ecosystems. Annals of the New York Academy of Sciences. Vol. 1195, 2010. In an edition entitled Ecological Complexity and Sustainability, Imperial College London mathematicians proceed with a dual purpose of showing how a “Tangled Nature” can in fact be explicated by an adept apply of complex system theories. They go on to perceptively note that such nonlinear phenomena is much the same subject as treated by statistical mechanics. This fertile melding across scales from galaxies to Gaia which is well underway, e.g., Dirk Helbing and Claudino Castellano herein, then portends more than another methodology. Rather what is implied is a new kind of universe distinguished by an independent, implicate spontaneity that explicate, natural phenotypes from molecules to a metropolis emerge from and exemplify. These worldwide collaborations over the past few years can now robustly qualify a cosmic Copernican revolution from a moribund Ptolemaic multiverse to a procreative genesis synthesis.

We discuss the relevance of studying ecology within the framework of Complexity Science from a statistical mechanics approach. Ecology is concerned with understanding how systems level properties emerge out of the multitude of interactions among large numbers of components, leading to ecosystems that possess the prototypical characteristics of complex systems. We argue that statistical mechanics is at present the best methodology available to obtain a quantitative description of complex systems, and that ecology is in urgent need of "integrative" approaches that are quantitative and nonstationary. We describe examples where combining statistical mechanics and ecology has led to improved ecological modeling and, at the same time, broadened the scope of statistical mechanics. (E19 Abstract)

Complex Systems consist of a large number of interacting components. The interactions give rise to emergent hierarchical structures. Statistical Mechanics seeks to understand how properties at systems level emerge from the level of the system-components and their interactions. (E19) This will allow us to demonstrate how macroevolution can be modeled as emerging from the interacting microevolution, which consists of individual organism influencing each other and undergoing reproduction which is prone to mutation. (E20)

Josephson, Brian. Biological Aspects of Fundamental Reality. http://sms.cam.ac.uk/media/715532. A video lecture by the Nobel laureate on October 28, 2009 at the Freiburg Institute for Advanced Studies. The main thesis is that life can and ought to be theoretically seen as a fundamental feature of cosmic nature, not as an alien or secondary anomaly. But after three decades on the physics staff at Cambridge University, he understandably proceeds by trying to tease out of the standard model such novel propensities for cooperative, emergent complexity that will not be found in the LHC. Thus, life is seen to exist beyond particles alone as “relational systems suffused with informational webs.” A more animate physics of our universe may then arise from deeper, different dimensions than quirky quanta.

But Josephson, a fine, sincere fellow, who I met once in 2006, notes that his expansive ideas do not curry favor with his “hostile” physics department. As this site tries to document, nothing less than a Copernican revolution from a Ptolemaic, barren, mechanical multiverse to a universal reality that is inherently organic in kind would seem to do. In which case excuses do not have to be made for an increasingly fertile materiality from which, as Josephson notes, regnant beings may evolve so as to become J. A. Wheeler’s intended observers needed to bring this self-creating genesis into full florescence.

Reductionism is the dominant paradigm of many fields of modern science. The main assumption is that a complex system can be explained in terms of the sum of its parts. On the basis of this idea we can conclude that all the natural phenomena can be explained in terms of some fundamental law of physics. However, this reductionist approach fails when applied to very complex systems such as biological ones. Thus, new paths to the formulation of a theory of everything could include complexity as the basic element.

On the basis of this concept, Prof. Brian D. Josephson offered in his lecture a different "non-orthodox" biological prospective for understanding the laws of nature. His approach is based on the concept that “life" is a new fundamental aspect of reality. Unitary elements behave in several complex ways such as reforming, reshaping, dissolving etc. All these elements represent the basic bricks of a new — although yet unshaped — approach that could lead our knowledge beyond the "standard model". (Talk Abstract)

Karl, Markus, et al. Tuning Universality Far from Equilibrium. Nature Scientific Reports. 3/2394, 2013. With Boris Nowak and Thomas Gasenzer, Ruprecht-Karls-Universitat, Heidelberg physicists show how open systems in this regime have a deep propensity for common scale-free dynamics and topologies at each and every natural stage and instance. The main point carrying through the article is that such similar phenomena appear everywhere as seemingly “independent” of certain specific detail.

Possible universal dynamics of a many-body system far from thermal equilibrium are explored. A focus is set on meta-stable non-thermal states exhibiting critical properties such as self-similarity and independence of the details of how the respective state has been reached. It is proposed that universal dynamics far from equilibrium can be tuned to exhibit a dynamical phase transition where these critical properties change qualitatively. This is demonstrated for the case of a superfluid two-component Bose gas exhibiting dfferent types of long-lived but non-thermal critical order. Scaling exponents controlled by the ratio of experimentally tuneable coupling parameters offer themselves as natural smoking guns. The results shed light on the wealth of universal phenomena expected to exist in the far-from-equilibrium realm. (Abstract)

The concept of universality has been extremely successful in classifying and characterising equilibrium states of matter. For example, there are different types of order in a magnetic material separated by a second-order phase transition at which the relevant physical properties become independent of the microscopic details of the system. This constitutes universality and allows to characterise an extensive range of different phenomena in terms of just a few classes governed by the same critical properties. In view of the intensifying discussion on the dynamics of many-body systems it is a pressing question whether also far away from the thermal limit the character of dynamical evolution can become independent of the microscopic details. (1)

Kelty-Stephen, Damian and James Dixon. When Physics is Not "Just Physics": Complexity Science Invites New Measurement Frames for Exploring the Physics of Cognitive and Biological Development. Critical Reviews in Biomedical Engineering. 40/6, 2012. By a parting of paths centuries ago, physics and biology went separate ways in their studies of moribund matter and quickening life. Here Harvard University and University of Connecticut ecological psychologists contribute to their growing reintegration and reunion in an increasingly holistic genesis universe from singularity to sentience.

The neurobiological sciences have struggled to resolve the physical foundations for biological and cognitive phenomena with a suspicion that biological and cognitive systems, capable of exhibiting and contributing to structure within themselves and through their contexts, are fundamentally distinct or autonomous from purely physical systems. Complexity science offers new physics-based approaches to explaining biological and cognitive phenomena. In response to controversy over whether complexity science might seek to "explain away" biology and cognition as "just physics," we propose that complexity science serves as an application of recent advances in physics to phenomena in biology and cognition without reducing or undermining the integrity of the phenomena to be explained. We highlight that physics is, like the neurobiological sciences, an evolving field and that the threat of reduction is overstated. We propose that distinctions between biological and cognitive systems from physical systems are pretheoretical and thus optional. We review our own work applying insights from post-classical physics regarding turbulence and fractal fluctuations to the problems of developing cognitive structure. Far from hoping to reduce biology and cognition to "nothing but" physics, we present our view that complexity science offers new explanatory frameworks for considering physical foundations of biological and cognitive phenomena. (Abstract)

Kibble, Tom and Ajit Srivastava. Condensed Matter Analogues of Cosmology. Journal of Physics: Condensed Matter. 25/400301, 2013. Imperial College, London, and Institute of Physics, Bhubaneswar, India, physicists introduce an issue on recent correspondences in form and process found across these micro and macro realms. Examples are “The Multiverse Transition in Superfluid 3He” by Yury Bunkov, and Causality and Non-Equilibrium Second-Order Phase Transitions in Inhomogeneous Systems” by Adolfo del Campo, Tom Kibble, and Wojciech Zurek. Leading loci in the American southwest are the Center for Nonlinear Studies, Los Alamos Laboratory, and Texas A & M University, Computational Physics Group. For these articles, and many arXiv postings, their essence is a profusion of nonlinear, self-organized criticalities that repeat in kind from fractal galaxies and geologies to natural biota and social media, so as to imply a dynamic universality drawn from an independent source. Might we then just wonder at a worldwide human acumen able to study such expanse and depth, and altogether begin to realize it is one integral, vital, ultimately self-witnessing creation.

It is always exciting when developments in one branch of physics turn out to have relevance in a quite different branch. It would be hard to find two branches farther apart in terms of energy scales than early-universe cosmology and low-temperature condensed matter physics. Nevertheless ideas about the formation of topological defects during rapid phase transitions that originated in the context of the very early universe have proved remarkably fruitful when applied to a variety of condensed matter systems. The mathematical frameworks for describing these systems can be very similar. This interconnection has led to a deeper understanding of the phenomena in condensed matter systems utilizing ideas from cosmology.

Kohestani, Havva and Alessandro Giuliani. Organization Principles of Biological Networks. BioSystems. Online March, 2016. In another paper which could well represent an international collaboration and scientific synthesis, University of Tabriz, Iran, and National Institute of Health, Italy, theorists identify a wide array of common network features. These include number of nodes, shortest paths, degree of connections, net density, clustering coefficient, net centrality, diameter, heterogeneity, modularity, transmission load, and so on. This distillation is drawn from lattice, Barabasi-Albert, Erdos-Renyi, social, neural and brain, metabolic, protein interaction, amino-acid, gene regulatory, and cancer metabolic networks. On the basis of this exemplary invariance, a separate, universal source domain can now be recognized and specified.

Kolakowska, Alice. Deciphering Dynamical Patterns of Growth Processes. European Journal of Physics. 30/1353, 2009. A Florida Institute of Technology physicist contends that since similar nonlinear phenomena seem to occur everywhere from universe to human, in ways much akin to the field of statistical mechanics, undergraduate physics curriculums ought now to include this significant expansion.

Many large-scale complex systems exhibit similar dynamical patterns. Examples include man-made structures such as, e.g., the Internet, social networks, programming dependences in computer operating system or stock market. Nature-made complex structures provide examples from the animate world such as, e.g., heart-beat patterns, growth of cell colonies and living tissues, or dynamical patterns in fish population: and, numerous mechanistic examples coming from the inanimate world such as, e.g., earthquake patterns, avalanches or dynamics of magnetization in a sample material. What may those diverse systems have in common? Elementary components of one system are quite different to the components of another system, and so is the physical nature of interactions between elementary components. Despite these transparent differences, when the systems of enormously large numbers of elementary components are analysed statistically they amazingly demonstrate similar statistical patterns or scaling laws. (1353-1354)

Koonin, Eugene. The Logic of Chance: The Nature and Origin of Biological Evolution. Upper Saddle River, NJ: FT Press Science, 2011. The National Center for Biotechnology Information, Evolutionary Genomics Research Group director, molecular biologist gathers many articles and thoughts into a work that epitomizes the vying cosmic revolutions. A Preface espouses a “postmodern” evolutionary synthesis of “constrained randomness” so to join a vicarious multiverse with intrinsic patterns that yet seem to underlie genomic activities. Although well intended, thus begins the array of contradictions that beset us today. Postmodernism is noted for its ban of any “metanarrative,” which a stochastic, chancy multiverse assumed by Koonin implies. Yet he perceptively goes on to propose deep affinities between evolutionary dynamics and statistical physics. Both natural realms proceed via many elements in interaction, from which arises an orderly result. It is thus inferred that “universal laws” must exist for such generative effect. Several of Koonin’s papers, often with colleagues, herein tend to favor an independent source. But life’s contingent ascent against the second law is explainable within an infinity of universes. Once again, in so many words, “chance and necessity,” but the ultimate question is again not asked or answered.

The characteristic exponents of the three broad functional classes of genes show little variation across prokaryotic lineages, suggesting that the differential evolutionary dynamics of genes with different functions reflect fundamental “laws” of evolution of cellular organization – or, in other words, distinct, strong constraints on the functional composition of genomes. Eukaryotic genes show similar, if less pronounced, patterns of power law gene scaling. All things considered, these distinct scaling laws represent another set of universals of genome evolution. (97) The parallels between evolutionary biology and statistical physics appear to be both detailed and fundamental to the degree that the conclusion seems to be justified that this is not an analogy, but rather a manifestation of the general statistical principles (it is tempting to call them “laws”) of the behavior of large ensembles of weakly interacting entities. (102)

Koorehdavoudi, Hana and Paul Bogdan. A Statistical Physics Characterization of the Complex Systems Dynamics. Nature Scientific Reports. 6/27602, 2016. As the quotes explain, in a good example of the living networks turn in physical theories, University of Southern California engineers advance an algorithmic quantification of active complexities from spatio-temporal interactions. See also herein a 2017 entry Reliable Multi-Fractal Characterization of Weighted Complex Networks by Bogdan and Yuankun Xue in this journal (7/7487).

Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. (Abstract excerpts)

The remaining of this paper is organized as follows: In the first section of results, we present our framework to extract the possible states in the collective motion and the strategy to build the corresponding energy landscape for transitions between them. To demonstrate the benefits of our approach, we first apply this strategy to quantify the energy landscape of a self-organizing model of a simulated group of agents based on local interactions among its individuals. Next, we define the missing information for the group structure. In the second section, we apply the same framework to three natural groups of swimming bacteria, flying pigeons and ants and study their energy landscapes. We define emergence, self-organization, and quantify the complexity of a collective motion based on
these newly introduced metrics. (2)

Kresic, Ivor, et al.. Generating Multiparticle Entangled States by Self-Organization of Driven Ultracold Atoms. arXiv:2208.10111. As the Abstract conveys, Vienna University of Technology and University of Strathclyde, Scotland physicists expand the frontier presence of spontaneous orderings into atomic depths to an extent that nature’s every depth and breadth seems to exhibit and be moved by these one, same phenomena.

We study a methodology for guiding the dynamical evolution of ultracold atomic motional degrees of freedom towards multiparticle entangled Dicke-like states, via nonlinear self-organization under external driving. In the first model the external drive is an oscillating magnetic field, leading to self-organization by interatomic scattering. In the second model the drive is a pump laser, leading to self-organization by photon-atom scattering in a ring cavity. We demonstrate highly efficient generation of multiparticle entangled states of atomic motion and discuss prospective experimental realizations of the models. Our results highlight the potential for using the self-organization of atomic motion in quantum technological applications.

Krioukov, Dmitri, et al. Network Cosmology. Nature Scientific Reports. 2/793, November, 2012. As the quotes express, mathematical physicists Krioukov, along with Maksim Kitsak, Robert Sinkovits, David Rideout, David Meyer, University of California, San Diego, and Marian Boguna, University of Barcelona, deftly apply the generic scale-free network phenomena that distinguishes everywhere else in nature and society to the realm of celestial topologies and dynamics. As a result, by a finesse of de Sitter spacetime theories, even cosmic reaches are revealed to seamlessly draw upon, apply and exemplify these universal formative principles.

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. (Abstract)

We show here that there exists a very simple but completely unexpected connection between networks and cosmology. In cosmology, de Sitter spacetime plays a central role as the exact solution of Einstein’s equations for an empty universe, to which our universe asymptotically converges. Here we show that graphs encoding the large-scale causal structure of de Sitter spacetime and our universe have structure common to many complex networks, and that the large-scale growth dynamics of these causal graphs and complex networks are asymptotically the same. (1)

In short, past light cones of new nodes, shown by green in Fig. 2, are asymptotically equal to the corresponding hyperbolic discs, shown by red. The green light cone bounds the set of nodes to which node P connects as a new causet element. The red hyperbolic disc bounds the set of nodes to which P connects as a new node in the hyperbolic network model that accurately describes the growth of real networks. Since these two sets are asymptotically the same, we conclude that not only the structure, but also the growth dynamics of complex networks and de Sitter causets are asymptotically identical. (5)

Kwapien, Jaroslaw and Stanislaw Drozdz. Physical Approach to Complex Systems. Physics Reports. 515/3-4, 2012. By virtue of this 153 page treatise, Kwapien, Complex Systems Theory Group, Polish Academy of Sciences, and Drozdz, Institute of Computer Science, Cracow University of Technology, could be fairly seen to broach a 21st cosmic revolution from the homeland of Nicolai Copernicus. A retrospective of the nonlinear sciences is now possible, as the authors accomplish, of their incipient occasion in the 1980s, wide divergence through the 1990s and early 2000s, to their convergent clarification. A case is made that physics, with its quest for fundamental theories and laws, is well suited for this task. From this vantage can be viewed, often in local terms and emphasizing certain aspects, how each dedicated field of nature and society from galaxies to Gaia, has reinvented themselves by way of a dynamical, integral emergence. This is treated by first citing prime attributes such as self-organization, criticality, hierarchical structure, scale invariance, nested networks, fractal geometries, and so on. So put, their presence can be drawn from and exemplified by, for example, quantitative linguistics, financial markets, and the “archetypal” human brain. All of which, one might muse, implies a radically different creative cosmos.

These expansive studies over past years could be seen to sort into two phases or methods. Much of the work was to find evidences of complex phenomena, as noted, in each realm and stage from cosmos to civilization, as this website documents. From these advances could then be distilled, by obvious inference, a common, independent, source. Apropos, I visited the Santa Fe Institute in 1987, heard a talk by Harold Morowitz, with Stuart Kauffman in the audience, when its incentive was the grail hope of uncovering and deciphering such a natural, reliable consistency. This proved elusive over intervening years as work fractionated but from 2005 on, merging with statistical physics, a universal recurrence of much depth and breath has been achieved. This paper is strong theoretical statement in regard, auguring an epochal discovery by humankind of nature’s implicate, creative agency, revealed by its ubiquitous manifestation. A large next step, within a natural genesis universe, is to perceive all this phenomena as a cosmic to children Genetic Code.

Typically, complex systems are natural or social systems which consist of a large number of nonlinearly interacting elements. These systems are open, they interchange information or mass with environment and constantly modify their internal structure and patterns of activity in the process of self-organization. However, the most striking property of such systems is the existence of emergent phenomena which cannot be simply derived or predicted solely from the knowledge of the systems’ structure and the interactions among their individual elements. This property points to the holistic approaches which require giving parallel descriptions of the same system on different levels of its organization. There is strong evidence - consolidated also in the present review - that different, even apparently disparate complex systems can have astonishingly similar characteristics both in their structure and in their behaviour. One can thus expect the existence of some common, universal laws that govern their properties. (Abstract, 1)

Now based on the phenomenon of emergence we may formulate a working definition of a complex system; this definition will be used throughout the present work. According to it, a complex system is a system built from a large number of nonlinearly interacting constituents, which exhibits collective behavior and, due to an exchange of energy or information with the environment, can easily modify its internal structure and patterns of activity. (3) In this section we shall review a few of the most characteristic properties of the structure and behaviour of the systems which are commonly referred to as complex. Presenting such a review is possible because of the fact that complex systems differing in morphology, being built from distinct elements on a microscopic level, and even occupying of the hierarchical organization of matter can exhibit amazingly similar macroscopic structure and also similar behaviour in specific situations. This may constitute a manifestation of universality of the physical phenomena underlying existence of such systems. (6)

Scale Invariance. There is another common property of complex systems which is related to the hierarchical structure discussed above: a lack of characteristic scale. This means that both the structure of, and processes taking place inside such systems are the same over a broad range of spatial and temporal scales. (11)

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