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

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

Newman, Mark. Communities, Modules and Large-scale Structure in Networks. Nature Physics. 8/1, 2012. The University of Michigan, Center for the Study of Complex Systems, mathematician is a leading theorist, advocate and explainer of this grand perception of a whole integral dimension of cosmos, life, persons, and culture beyond reduced, isolate things alone. In an Insight – Complexity section, a recent emphasis arising from these studies is the common tendency to form semi-autonomous modular communities, indeed an array of nested networks that much increases robust survival. His latest book Networks: An Introduction (Oxford, 2010) is a standard source.

Nieves, Veronica, et al. Maximum Entropy Distributions of Scale-Invariant Processes. Physical Review Letters. 105/118701, 2010. Postdoc physicist Nieves, grad student Jingfeng Wang and Rafael Bras, Dean of Engineering (newly Georgia Tech Provost), University of California, Irvine, and grad student Elizabeth Wood, MIT, find that circa 2010 nature’s grand self-similarity, as many other recent papers attest, is robustly evident from cosmos to civilization, and can indeed be modeled in its universal mode by such physical principles.

Organizations of many variables in nature such as soil moisture and topography exhibit patterns with no dominant scales. The maximum entropy (ME) principle is proposed to show how these variables can be statistically described using their scale-invariant properties and geometric mean. The ME principle predicts with great simplicity the probability distribution of a scale-invariant process in terms of macroscopic observables. The ME principle offers a universal and unified framework for characterizing such multiscaling processes. (Abstract, 118701)

Such scale-invariant behavior resulting from self-organization emerges as the most probable and macroscopically reproducible state. It turns out that the geometric mean provides essential information for shaping river networks. (118701-4) The geometric mean is also identified as an important parameter, in addition to the moments, in characterizing multiscaling incremental processes of soil moisture and topography. ….this analysis supports the assertion that the ME theory is a universal and unified framework to characterize those processes governed by scale-invariant laws. (118701-4)

Pan, Raj Kumar and Sitabhra Sinha. Modularity Produces Small-World Networks with Dynamical Time-Scale Separation. EPL (Europhysics Letters). 85/68006, 2009. Institute of Mathematical Sciences, C. I. T. Campus, Chennai, India systems scientists contend that including the ubiquitous presence of modular network substructures in SWNs can reveal a universality that holds across natural phenomena from physical Ising spin-orderings to metabolisms to societies. Now this paper, any many others like it, can illustrate the two extant ways of perceiving such phenomena. As this site records, such nonlinear dynamics can either be noted and studied as instantiated from galaxies to Gaia, or as this distillation unto an independent propensity. The authors go on to say that such commonalities can be applied to contain disease epidemics, as they similarly express this geometry.

Parkar, Devendra et al. Evolving Collective Behavior in Self-Organizing Particle Systems. arXiv:2404.05915.. arXiv:2404.05915. Arizona State University computational biologists describe novel ways to quantify how lively entities and member groupings can spontaneously emerge into being and becoming. Again one might begin to realize that we Earthlings may be altogether finding a greater independent, cocreative existence in and of which all of our lives have a phenomenal source and significance.

Biological and social complex systems are now understood to arise from many local interactions which drive emergent collective behavior. But how they learning how produce a desired condition remains a challenge. In this paper, we present EvoSOPS, an evolutionary framework that searches landscapes of stochastic distributed algorithms for those that achieve a specified target behavior. These select algorithms govern self-organizing particle systems (SOPS) comprised of individuals with nearby sensings and movement. Finally, we distill insights from the diverse, best-fitness genomes produced for aggregation across EvoSOPS runs to demonstrate how the program can bootstrap future theoretical investigations into SOPS algorithms for new behaviors. (Excerpt)

Peat, David. Trapped in a World View. New Scientist. January 5, 2008. The physicist and author proposes that cultural forms of language can, unbeknownst, determine what kind of reality is seen. In Europe, where modern physics began and proceeded, a ‘noun’ or object emphasis holds whereof electrons, e.g., are akin to billiard balls with a distinct position and velocity. But this vernacular is unable to express or include equally relevant dynamical processes between what are in actuality condensations. As a contrast, the Algonquian Indian language is ‘verb’ based which can readily convey an ‘indigenous’ nature as an integral, living, spiritual presence. Now this is not trivial. Much of our scientific impasse today, with physics and cosmology languishing back in time, out in space, and down into matter, could be traced to a linguistic inability to fathom and describe an organic genesis. Instead a sterile mechanical materialism reigns. Or one might say trying to explain a maternal gestation unto nativity by way of or to a paternal mindset.

Peng, Ji, et al. Signal Propagation in Complex Networks. Physics Reports. May, 2023. Ten global theorists including Matjaz Perc and Jurgen Kurths provide an extensive Volume 1017 on this propensity of natural, personal and societal interconnectivities, each in some cerebral way, to take on dynamic, oscillatory, multiplex communications. So into these 2020s, the more we can altogether learn, understand, avail, guide, manage about these agencies and realities the better.

Collective behavior is the hallmark of complex systems, and as such, it has attracted much attention during the past two decades. It is an emergent phenomenon that is due to the interactions between many units that make up complex systems, be it neurons in the brain or ants in an anthill, as well as due to external disturbances that often act upon them. Most importantly, collective behavior is often universal in nature, such that models describing. (Introduce)

Perc, Matjaz. Beauty in Artistic Expressions through the Eyes of Networks and Physics. Journal of the Royal Society Interface. March 11, 2020. The University of Maribor, Slovenia complexity theorist has become a leading expositor in Europe and beyond through a steady flow of papers (search) about physical, biologic to social areas. Here he applies the latest findings, as the abstract notes, to cultural phases to show how each in turn can be modeled by the same dynamic mathematics. So to say in 2020, a grand implication presents itself via an integral survey from statistical physics to literary corpora. As illustrated by flavour tastes, artistic styles, musical modes, how children learn, and more, it is evident that an iconic universality of particle/wave, node/link, DNA/AND, me/We, yin/yang complements in a whole system triality has been verified. This entry well conveys a revolutionary discovery in our midst of a participatory universe to wuman epitome genesis co-creation.

Beauty is subjective, it cannot be defined in absolute terms. But we all know or feel when something is beautiful to us. And in such instances, methods of statistical physics and network science can be used to quantify and better understand what evokes that pleasant experience. From the complexity and entropy of art paintings to an array of food flavors, research at the interface of art, physics and network science abounds. We review the existing literature, focusing on culinary, visual, musical and literary arts. We also touch upon cultural history and culturomics, as well as connections between physics and social sciences in general. We find that synergies between these fields yield entertaining results that can often be enjoyed by layman and experts alike. (Abstract excerpt)

Perotti, Juan, et al. Emergent Self-Organized Complex Network Topology out of Stability Constraints. Physics Review Letters. 103/108701, 2009. With nature becoming untangled by way of such dynamic geometries, researchers at the Universidad Nacional de Cordoba, Argentina, and Northwestern University, USA, are able to distill and discern universal, independent characteristics that repeat everywhere from genes to websites.

Although most networks in nature exhibit complex topologies, the origins of such complexity remain unclear. We propose a general evolutionary mechanism based on global stability. This mechanism is incorporated into a model of a growing network of interacting agents in which each new agent's membership in the network is determined by the agent's effect on the network's global stability. It is shown that out of this stability constraint complex topological properties emerge in a self-organized manner, offering an explanation for their observed ubiquity in biological networks. (Abstract, 108701)

Pietronero, Luciano. Complexity Ideas from Condensed Matter and Statistical Physics. Europhysics News. 39/6, 2008. The STATPHYS 23 (Google) conference held in Rome, July 2007 is seen as initiating a fertile merger of this older field with the new sciences of nonlinear dynamics, since it became evident they studied the same phenomena from different approaches. In this note, a senior University of Rome physicist provides a succinct introduction to a combined “Physics of Complex Systems.” But a further scope is added by seeing a turn from a long reduction phase to particles or “bricks” only to getting on with their integral (re)assembly or “architecture.” Pietronero points out that these advances are uncovering grand affinities whence the same “self-organized fractal growth dynamics” from material aggregates to galactic clusters. A need going forward is the attainment of agreed, clear terminologies.

The basic idea is that nature is organized in a hierarchical way and that there are individual elements and collective emergent properties every time one moves from a level of the hierarchy to the next one. The later development of the renormalization group has provided a formalism which permits to interpret these intuitions within a rigorous framework. Examples of these various levels can be quarks and nuclear physics, atoms, molecules, proteins, the emergence of life and on up to the macroscopic scales and the entire universe. The idea is that each discipline refers to the step between one level and the next one. In this process the essential concepts are the basic elements and their interactions. These lead to emergent properties and collective behaviours which cannot be identified from the original elements. (26)

The study of complex systems refers to the emergence of collective properties in systems with a large number of parts in interaction among them. These elements can be atoms or macromolecules in a physical or biological context, but also people, machines or companies in a socio-economic context. The science of complexity tries to discover the nature of the emerging behaviour of complex systems, often invisible to the traditional approach, by focusing on the structure of the interconnections and the general architecture of systems, rather than on the individual components. It is a change of perspective in the forma mentis of scientists rather than a new scientific discipline. Traditional science is based on a reductionistic reasoning for which, if one knows the basic elements of a system, it is possible to predict its behaviour and properties. It is easy to realize, however, that for a cell or for the socio-economic dynamics one faces a new situation in which the knowledge of the individual parts is not sufficient to describe the global behaviour of the structure. Starting from the simplest physical systems, like critical phenomena in which order and disorder compete, these emergent behaviours can be identified in many other systems, from ecology to the immunitary system, to the social behaviour and economics. The science of complexity has the objective of understanding the properties of these systems. (28)

Pyo, Andrew, et al. Proximity to Criticality Predicts Surface Properties of Biomolecular Condensates. PNAS. 120/23, 2023. This mid 2023 entry by Princeton and Johns Hopkins University biologists including Ned Wingreen is a good example of the wide and deep convergent synthesis that is presently underway. The paper notably views the title biological functions as primarily due to deep self-organizing energies as they serve ti generate life’s oriented developmental evolution. A further vital finding is its constant propensity to seek and reside at an optimum critical point.

In we also cite concurrent physical instances such as Self-Organized Patterning on Azo Molecular Glass Film via Optical Near-Field Effect and Self-Organization of Ferroelectric Domains Reinforced via Ultrasonic Vibration both in the Nature journal Communications Materials (May 2023). To continue with nature’s dynamic universality, see Statistical thermodynamics of self-organization in the adaptive immune system by Jozsef Prechl, (2306.04665), From Autopoiesis to Self-Organization: Toward an Enactive Model of Biological Regulation by Tom Froese, et al (bioRxiv. June 9, 2023), Programmable Self-organization of heterogeneous microrobot collectives by Steven Ceron in PNAS (120/24, 2023) and Critical Scaling of Whole-Brain Resting-State Dynamics by Adrian Ponce-Alvarez, et al in Communications Biology (June 2023).

Self-organization through the phase separation of biomolecular condensates is ubiquitous in living cells. What general principles relate these macroscopic properties to the underlying microscopic features of biomolecules? By using universal ratios of thermodynamic quantities in the vicinity of a critical point, condensate physical properties can be inferred from a small number of thermodynamic parameters. We confirm that the range of validity of the critical region is large enough to cover the physiologically relevant range in living cells. (Pyo Significance excerpt)

Overall, these results suggest that the framework of critical phenomena can be utilized as a principled approach to understand the effect of microscopic features on the macroscopic properties of many biomolecular condensates. (Pyo 2)

The universality of behavior near a critical point provides an inherently principled way to relate microscopic features to macroscopic properties. Within a model for biomolecular phase separation, this affinity infers that polymer sequences influence surface tension by shifting the distance to the critical point. Notably, these interdependent scaling laws are not limited to a particular model system but are generally applicable within the 3D Ising universality class. (Pyo 5, 6)

Radicchi, Filippo, et al. Renormalization Flows in Complex Networks. Physical Review E. 79/026104, 2009. An example of a paper in this large journal for “statistical, nonlinear, and soft matter (that’s us) physics” which can illustrate, at once, a movement to become more receptive of and engaged with dynamical living systems, along with the impediments of abstract terminologies that are not well defined. All of which hightlights the need for a clear, common vernacular in physics itself, within the complexity sciences, and amongst them. We quote a Wikipedia post for “Renormalization Groups.”

In theoretical physics, renormalization group (RG) refers to a mathematical apparatus that allows one to investigate the changes of a physical system as one views it at different distance scales. In particle physics it reflects the changes in the underlying force laws as one varies the energy scale at which physical processes occur. A change in scale is called a "scale transformation" or "conformal transformation." The renormalization group is intimately related to "conformal invariance" or "scale invariance," a symmetry by which the system appears the same at all scales (so-called self-similarity).

Rodriguez, Quentin. Idealizations and Analogies. arXiv:2110.12712. A University of Clermont Auvergne physicist comments on a paper by Robert Batterman (Universality and RG Explanations in Perspectives in Science (27/1, 2019.) and others to explain and endorse nature’s tendency to seek and reside at a critically poised condition wherever possible. (Search Sara Green and RB 2021 for more.) Our take is to note that into late 2021, such perceptions of an infinite repetitive balance between more or less order or coherence is becoming well verified.

The "universality" of critical phenomena is much discussed in the philosophy of scientific philosophy of physics. Lange and Reutlinger recently opposed Batterman concerning the role of some deliberate distortions in unifying a large class of phenomena, regardless of microscopic constitution. In recent regard, an essential explanatory role for "commonalities" rather than that of idealizations has been proposed. Here we show that the differences between the universality of critical phenomena and two paradigmatic cases of a "commonality strategy" (ideal gas and harmonic oscillator) serve to clarify the issue. These benchmarks of critical phenomena reveals the importance of the various analogies which underlie their assumptions. (Abstract excerpt)

Critical phenomena and universality: In the last decades, CP in statistical and condensed matter physics have received much attention in the philosophy of scientific explanation and in the topic of emergence and reduction. This special type of phase transition, i.e., a sudden macroscopic reorganization of matter at thermodynamic equilibrium,1 has drawn physicists’ attention toward a specific feature they have named universality. Here, this term assumes a technical meaning: a property of a certain system is said to be universal if, in the vicinity of a phase transition, it behaves in the same way as other systems around their own phase transition, even if the microscopic constitution of these systems, the nature of their phase transition or the temperature of this phase transition are completely different. (2)

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