A. Ecode 2023: EarthKinder Discovers a Universal, Independent Ecosmome to Geomome Exemplary Endowment
Pereverzev, Sergey. Dark Matter Searches and Energy Accumulation and Release in Materials. arXiv:2212.13964. This presentation at the 14th International Conference on Identification of Dark Matter (Vienna 2022) by a Lawrence Livermore experimental physicist describes highly complex, diverse experiments which show how self-organized critical phenomena is inherently pervasive all manner of material and energetic phases.
This presentation at the 14th International Conference on Identification of Dark Matter (Vienna 2022) by a Lawrence Livermore experimental physicist describes highly complex, diverse experiments which show how self-organized critical phenomena is inherently pervasive all manner of material and energetic phases.
Provata, Astero.. From Turing Patterns to Chimera States in the 2D Brusselator Model. arXiv:2212.01297. A National Center for Scientific Research, Athens (bio below) physicist contributes a latest explanation about these spatial and temporal conditions which appear across a widening array of life’s natural and social phenomena. A novel contribution is their aptness to shift from a morphogenetic phase to a self-organized critical activity. On a personal note, I had lunch with Ilya Prigogine in a group in 1987 at a conference. Some 35 years on, into these 2020s the complexity sciences have come to and settled on this common non-equilibrium occasion, a true universality in kind.
The Brusselator has been used as a prototype model for autocatalytic reactions, and for the Belouzov-Zhabotinsky reaction. When coupled at the diffusive limit, the it undergoes a bifurcation resulting in the formation of classical Turing patterns such as spots, stripes and spirals. In the present study we use generic nonlocally coupled Brusselators and show that in the diffuse limit of the coupling range, the Turing effects are recovered, while for intermediate coupling ranges and appropriate parameter values chimera states are produced. This study demonstrates how the parameters of a typical nonlinear oscillator can be tuned so that the coupled system passes from spatially stable structures to dynamical spatiotemporal chimera modes. (Abstract)
Proverbio, Daniele, et al. Buffering in Cell Regulation Motifs Close to Criticality. arXiv:2212.08600. As late 2022 scientific studies proceed to find a widening propensity across life’s metabolic, and cerebral phases to achieve and benefit from dynamic sensitivities, University of Luxembourg theorists show how these a these nuanced responses can also foster a ecological resilience.
Bistable biological regulatory systems need to cope with stochastic noise to fine-tune their function close to bifurcation points. Here, we study stability properties of this regime in generic systems to demonstrate that cooperative interactions buffer noise-induced regime shifts. Our generic framework, based on minimal models, can be used to extract robustness and variability properties of more complex models and empirical data close to criticality. (Abstract)
Rao, Ankit, et al. Self-Assembled Meuromorphic Networks at Self-Organized Criticality in Ag-hBN Platform. arXiv:2301.01619. Eight India Institute of Science and University of Groningen researchers describe an involved physical material method by which to attain, demonstrate and explain this optimum performance condition.
Networks and systems which exhibit brain-like behavior can analyze information from noisy data with low power consumption due to the critical nature and complex interconnectivity of their neuronal-like network. We show that a system comprised of hexagonal Boron Nitride (hBN) films contacted with Silver (Ag), that can uniquely host two different self-assembled networks, which are self-organized at criticality (SOC). This system shows bipolar resistive switching between high resistance (HRS) and low resistance states (LRS). The temporal avalanche dynamics in both these states exhibit power-law scaling,
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 (220.127.116.11/~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)
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)
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)
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)
TABLE OF CONTENTS |
GENESIS VISION |
LEARNING PLANET |