IV. Ecosmomics: Independent Complex Network Systems, Computational Programs, Genetic Ecode Scripts

A. A Procreative Ecode: An Ecosmome to Geonome Complementary Hereditary Endowment

Romanczuk, Pawel and Bryan Daniels. Phase Transitions and Criticality in the Collective Behavior of Animals. arXiv:2211.03879. Humboldt University and Arizona State University (see websites) post a chapter for the 2023 Volume VII of the World Scientific series Order, Disorder, and Criticality. An especial notice is that it is edited by Yuri Holovatch (search) at the Laboratory for Statistical Physics of Complex Systems (194.44.208.227/~hol/), National Academy of Science in Ukraine, see notes below. This subject entry has its own distinction as an early integral synthesis of 21st century nonlinear science which proceeds to join an older complex adaptive system format with newly-realized, consequent self-organized criticalities. After these novel appreciations are described as they exemplify across every natural and social domain, the paper goes on to trace their deep rootings in active statistical physics phenomena.

Collective behaviors exhibited by animal groups, such as fish schools, bird flocks, or insect swarms are valid examples of self-organization in biology. Concepts and methods from statistical physics have lately been used as a theoretic reason for such collective effects in living systems. In addition, it has been implied that animal groupings should operate close to a phase transition as a (pseudo-)critical point to optimize their capability for collective computation. In this chapter, we will discuss the current state of research on the "criticality hypothesis", along with how to measure distance from criticality. We highlight the emerging view that explores the benefits of living systems being able to tune to an optimal distance from criticality. (Abstract)

Collective behavior exhibited by large animal aggregations such as swarms of insects, schools of fish, and flocks of birds are ubiquitous examples of biological self-organization. Physicists now investigate parallels between large animal collectives and statistical phenomena where local interactions between simpler components can lead to adaptive macroscopic properties. This functional behavior relies on distributed information available to entities within complex biological systems such as proteins in cells, neurons in brains onto animal and human groups. (2)

As laid out in this chapter, phase transition and criticality theories are highly relevant for understanding the interplay of self-organization and active organism behaviors. The “criticality hypothesis", whence complex biological system seek to optimize their collective computation capabilities, can provide a unifying principle across life’s life’s nested scales. Our consideration aligns with recent calls within evolutionary biology and ecology for novel ideas that can be grounded in a theoretical physics perspective. A truly bidirectional exchange between physics and biology thus opens new avenues of research for better fundamental understandings. (21)

The first volume of Order, Disorder and Criticality was published by World Scientific in 2004 and, over time, it gave rise to this book series. Its chapter content originated from the Ising (Ernst 1900-1998) Lectures workshops that occurred annually in Lviv in the Ukraine. The volumes initially aimed to provide topical surveys related to phase transitions and criticality in theoretical studies. As they appeared, it grew to natural phenomena beyond statistical physics such as complex biological systems composed of many interacting components that display collective behavior above their individual parts. (Yuri Holovatch)

Schaposnik, Laura, et al. Animal Synchrony and Agent’s Segregation. arXiv:2212.07505. Into late 2022, a paper by University of Chicago, Illinois and Oxford University (Robin Dunbar) biobehavior researchers to appear in the Proceedings A of the Royal Society proceeds to add a a further causal mathematic basis whereby creaturely activities in diverse assemblies can be well modeled as reciprocal, self-organized critical, relations. By our notice, this is the first time (on schedule) that Kuramoto (cited), chimera-like oscillations have been applied to and seen in formative effect across to life’s multi-organism phase. See also Relating Size and Functionality in Human Social Networks through Complexity by Bruce West, Robin Dunbar, et al in PNAS (117/31, 2022) for another approach which can perceive and quantify critical behaviors of active groups.

In recent years it has become evident that a lack of coordination imposes constraints on the size of stable groups that highly social mammals can live in. Here we examine the forces that keep animals together as a herd and others that drive them apart. For example, different phenotypes (e.g. genders) have various rates of gut fill, causing them to spend more or less time performing activities. By modeling a group as a set of semi-coupled oscillators, we show that its members may become decoupled until the group breaks apart. We show that when social bonding creates a stickiness, or gravitational pull, between pairs of individuals, fragmentation is reduced. (Abstract)

Shpurov, Ivan and Tom Froese. Evidence of Critical Dynamics in Movements of Bees inside a Hive. Entropy. 24/12, 2022. As scientific realizations in later 2022 report an increasing notice of a vital self-organized critically from quantum to neural and social realms, as this new section reports, for a Statistical Physics of Collective Behavior issue edited by Bryan Daniels (see below), Okinawa Institute of Science and Technology cognitive theorists (search Froese) even perceive and report how this optimum behavioral phenomena is present in insect activities.

Social insects such as honey bees exhibit complex behavioral patterns whose distributed coordination enables decision-making at the colony level. It has been proposed that a high-level description of their collective behavior might share commonalities with the dynamics of neural processes in brains. Here, we investigated this proposal by focusing on how brains are poised at the edge of a critical phase transition which fosters increased computational power and adaptability. We found that certain characteristics of the activity of the bee hive system are consistent with the Ising model when it operates at a critical temperature, and that the system’s behavioral dynamics share features with the human brain in the resting state. (Abstract)

Understanding how the adaptive behavior of groups is controlled by the individuals within them is a major challenge for 21st century science. From proteins in a cell to neurons in a brain, and from fish in a school to people in society, we know how most entities perform and interact, but mapping this to adaptive behavior at the aggregate scale is difficult. Statistical physics has long approached similar problems in non-living systems, connecting macroscopic theories to the microscopic details. This Special Issue will explore these themes using concepts such as coarse graining, renormalization, scaling, phase transitions, collective instabilities, broken symmetries, dynamical modes, free energy, critical phenomena, and more. Our aim is to build predictive theories o describe the collective behavior of proteins, bacteria, neurons, insects, mammals, fish, robots, computers, artificial neural networks, species, people, societies, and ideas. (Byron Daniels Entropy)

Shpurov, Ivan, et al. Beehive scale-free emergent dynamics.arXiv:2311.17114.. arXiv:2311.17114.. IS and Tom Froese, Okinawa Institute of Science and Technology and Dante Chialvo, Center for Complex Systems and Brain Sciences,
Universidad Nacional de Gral, Buenos Aires, contribute one more social insect empirical verification of nature’s universal preference to seek and stay close to an optimum, chimera-like poise of opposite states. A further appreciation is a proposal that this behavior is an expression of a statistical physics ground.

It has been repeatedly reported that the collective dynamics of social insects exhibit universal emergent properties similar to other complex systems. In this note, we study a literature data set in which the positions of thousands of honeybees in a hive are individually tracked over multiple days. The results show that the hive dynamics exhibit long-range spatial and temporal correlations in the occupancy density fluctuations. The variations in the occupancy unveil a non-monotonic function between density and bees' flow, reminiscent of the car traffic dynamic near a jamming transition at which the system performance is optimized. (Abstract)

The collective phenomena exhibited by social insects and animals have long inspired complex systems scientists. Large collective behavioral structures, such as hives, swarms, bird flocks, etc., emerge out of local interactions. The resulting complex global structures are several orders of magnitude larger than the individuals who communicate. Often, the dynamics of these disparate phenomena exhibit scale-invariant properties both in space and time which are common across the species, an observation that could be studied from the perspective of statistical physics. (1)

Smyth, William, et al. Self-Organized Criticality in Geophysical Turbulence. Nature Scientific Reports. 9/3747, 2019. Into 2019, it is becoming strongly evident that a genesis universe evolves and develops by repetitions and iterations of the same dynamic phenomena in kind everywhere. Here Oregon State University oceanographers describe such a tendency to reach a critical balance even in these geologic and atmospheric phases.

Turbulence in geophysical flows tends to organize itself so that the mean flow remains close to a stability boundary in parameter space. That characteristic suggests self-organized criticality (SOC), a statistical property that has been identified in a range of complex phenomena including earthquakes, forest fires and solar flares. This note explores the relationship between forced, sheared, stratified turbulence in oceans, atmospheres and other geophysical fluids and those of SOC. Self-organization to the critical state is demonstrated in a wide range of ocean turbulence, which also follows a power-law distribution indicating self-similarity. (Abstract capsule)

Song, Tiancheng, et al. Unconventional Superconducting Quantum Criticality in Monolayer WTe2.. arXiv:2303.06540. Into the mid 2020s, fifteen Princeton University and National Institute for Materials Science and Nanoarchitectonics, Japan researchers proceed to find an inherent tendency for optimum critical behavior even in this substantial realm. See also Self-similarity of the third type in ultra relativistic blastwave by Tamar Faran, et al at arXiv:2402.07978 for another instance of deeply ingrained critical behavior.

The superconductor to metal transition in two dimensions (2D) provides a platform for study quantum phase transitions (QPTs) and critical phenomena but many questions remain. Extending Nernst experiments down to millikelvin temperatures, we identify a superconducting quantum critical point (QCP) in spin Hall insulator made of tungsten ditelluride (WTe2). These findings, which have no prior analogue, call for careful examinations of the mechanism of the QCP, including the possibility of a QPT between ordered phases in the monolayer. Our experiments open a new avenue for studying quantum critical matter. (Abstract)

Tadic, Bosilijka. Cyclical Trends of Network Load Fluctuations in Traffic Jams. Dynamics. 2/4, 2022. We cite this entry by the veteran Solvenian complexity theorist (search) as an example into these 2020s of how a mathematical awareness of a separate domain that underlies and structures human social activities can provide natural (genetic-like) informed guidance for better results.

The transport of information packets in complex networks is a prototype system for the study of traffic jamming, a nonlinear dynamic phenomenon that arises with increased use and limited road capacity. An intrinsic framework helps to reveal how the macroscopic build-ups from microscopic forces, depending on the posting rate, navigation rules, and network form. We find that near congestion thresholds, traffic fluctuations show a temporal pattern described by cyclical trends with multifractal features. (Excerpt)

Tang, Xun and Huifang Ye. Xun and Huifang Ye. Metaphorical Language Change Change is Self-Organized Criticality. arXiv:2211.10709. Huazhong University of Science and Technology, Wuhan system linguists extend later 2022 perceptions of a ubiquitous SOC so to highlight its innate coherence of two complementary modes. Here linguistic domains are seen as distinguished by this universal scale-free form and facility. As the abstract states, the authors record an historic recognition of how even narrative writings and spoken conversation can equally be seen to avail these archetypal benefits.

One way to resolve the actuation problem of language change is to provide a statistical profile of metaphorical constructions and generative rules. Based the view of language as a complex system and the dynamic view of metaphor, this paper argues that language change qualifies as a self-organized criticality state and the linguistic expressions can be profiled as a fractal correlation. Synchronously, metaphorical usages self-organize into a self-similar, scale-invariance with a power-law distribution. We verify this by statistical analyses of twelve randomly selected Chinese lexicon in a large-scale diachronic corpus. (Abstract)

Tian, Yang, et al. Theoretical Foundations of Studying Criticality in the Brain. Network Neuroscience. 6/4, 2022. For a special Connectivity, Cognition and Consciousness issue, Tsinghua University, Beijing, University of Paris, and Chinese Academy of Science researchers theoretically explain, clarify and advance how the dynamic presence of self-organized phenomena is being found to play a central creative role.

The brain criticality hypothesis is one of the most active topics in neuroscience and biophysics. This work develops a unified framework to reformulate the physics theories of four basic types of brain criticality, ordinary criticality (OC), quasi-criticality (qC), self-organized criticality (SOC), and self-organized quasi-criticality (SOqC), into more accessible and neuroscience-related forms. This framework may help resolve potential controversies in studying the brain criticality hypothesis, especially those arising from the misconceptions about the theoretical foundations of brain criticality. (Author)

Tsakmakidis, Kosmos, et al. Quantum Coherence-driven Self-Organized Criticality and Nonequilibrium Light Localization. Science Advances. May, 2018. UC Berkeley research physicists discern one more actual presence of nature’s optimum dynamic phase ineven at this deepest energetic stage. As a reflection, when I began these studies long ago (e.g., 1987 at the Santa Fe Institute to hear Harold Morowitz) the SO universality of the second quote was a remote hope. Today, in these critical condition 2020s, due to John Beggs and many others, it is vital that our worldwise natural philosopher sapience once again is able at last to perceive and realize what an epochal, numinous discovery has been achieved.

Self-organized criticality emerges in dynamical complex systems driven out of equilibrium and characterizes a wide range of classical phenomena in physics, geology, and biology. We report on a quantum coherence–controlled self-organized critical transition observed in the light localization behavior of a coherence-driven nanophotonic configuration. Our system is composed of a gain-enhanced plasmonic heterostructure controlled by a coherent drive, in which photons close to the stopped-light regime interact in the presence of the active nonlinearities. In this system we observe quantum coherence–controlled self-organized criticality in the emergence of light localization arising from the synchronization of the photons. (Excerpt)

The self-organization of many nonequilibrium complex systems toward an “ordered” state is a profound concept in basic science, ranging from biochemistry to physics.. Examples include the group movement of flocks of birds (, motions of human crowds, neutrino oscillations in the early universe, and the formation of shapes (morphogenesis) in biological organisms. An intriguing trait of this nonequilibrium, driven-dissipative systems is that their self-organization can lead them to a phase transition and to critical behavior — a phenomenon known as self-organized criticality. (1)

Vidielia, Blai, et al. Engineering Self-Organized Criticality in Living Cells. Nature Communications. 12/4415, 2021. Seven Barcelona system scientists including Ricard Sole identify and explain how cellular processes do, in fact, avail this optimum condition for their active viability. This novel appreciation is then carried forth as a way to better conceive new, beneficial biologic formations. And once again this leading edge paper goes on to note that this fittest resolve is likewise being found everywhere else so to prove a natural, one bigender code, universality.

Complex dynamical fluctuations, from intracellular noise, brain dynamics or computer traffic typically display bursting dynamics situated at a critical state between order and disorder. Living close to the critical point has adaptive advantages to an extent that it has been conjectured that life’s evolution could select for these critical states. In regard we consider the case of living cells to see if they reside in at a self-organized criticality (SOC) state. To do so we present an engineered gene network which actually displays SOC behavior, namely the proteolytic degradation of E. coli cells by means of a negative feedback loop that reduces congestion. Our critical motif is built from a two-gene circuit, where SOC can be successfully implemented. (Abstract excerpt)

Critical states are known to be part of the cognitive equipment of multicellular organisms from simple, non-neural placozoans to neural systems and animal collectives. The SOC motif might be an efficient way of generating phenotypic diversity in a microbial population and can be relevant to expand the space of synthetic biology computational designs into collective intelligence. Finally, given the analogies between our system and critical traffic in parallel computer networks, an extension of our approach could involve a 3D spatially explicit system and the development of statistical physics models of critical intracellular activity. (8)

Villani, Marco, et al. Evolving Always-Critical Networks. Life. 10/3, 2020. In this year of binocular clarity, systems physicists MV and Roberto Serra, University of Modena, and Salvatore Magri and Andrea Roli, University of Bologna, along with colleagues can well describe an optimum condition of self-organized criticality that active systems seek and prefer to reside at. As this section reports, some two decades of global research have now settled upon this vital iconic “criticality principle” from brains to genomes to quantum phases. The occasion at last achieves a resolve and proof that a reciprocal mutuality between apart/together, conserve/create, and so on is nature’s best beneficial balance (except politics which blindly pit one complement vs. the other). See also Dynamical Criticality: Overview and Open Questions by this team (Andrea Roli, et al) in the Journal of Systems Science and Complexity (31/647, 2018).

Living beings share several common features at the molecular level, but there are as yet few large-scale “operating rules” for all organisms. An interesting candidate is the “criticality” principle, which claims that biological evolution favors those regimes that are intermediaries between ordered and disordered states, “at the edge of chaos”. The reasons why this should be the case are discussed such as gene regulatory networks (GRN) which do in fact reside at the critical boundaries. In order to explore an “always-critical” state, we resort to simulated evolution via genetic algorithms which show that new individuals do indeed develop critical GRNs. (Abstract excerpt)

Therefore, critical states are in between ordered and disordered ones. The criticality principle states that these states are at an advantage with respect either to chaotic states, since they are more stable and controllable, or to ordered states, since they can better change in response to different conditions, without being stuck in the same state. If this is indeed the case, evolution should have modified the parameters in such a way that living beings are found near critical states—a statement that is, in principle, amenable to experimental verification. (2)

Let us revisit now the CP that has been introduced and discussed in Section 1, which claims that some dynamical states are advantaged with respect to other states, and that evolution drives living beings towards these “critical” states, which are neither fully ordered nor fully disordered. (13)

Systems that exhibit complex behaviours are often found in a dynamical condition which is poised between order and disorder. This observation is the essence of the criticality hypothesis, which states that such an active balance can attain the highest level of computational capabilities and an optimal trade-off between robustness and flexibility. Recent results in cellular and evolutionary biology, neuroscience and computer science have heightened interest in a preferred criticality state as a candidate general law in adaptive complex systems. (Roli, et al Abstract)

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