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

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

Beiro, Mariano, et al. Signs of Criticality in Social Explosions. arXiv:2305.01944. University of Buenos Aires, Singapore University of Social Sciences, Nanyang Technological University, Singapore, Complexity Science Hub Vienna (Stefan Thurner) and International Valencian University, Spain systems theorists describe a unique, extensive project which has found that even this hyper-active, multi-faceted public intensity tends toward, exhibits and is distinguished a self-organized ciriticalities which endow near-optimum communicative conditions.

The success of an on-line movement could be defined by a shift to off-line street actions of protests. One may view these macro-behaviors as spontaneous interactions, which will give rise to common simplifications on several statistics. Here, we go on to observe of signs of criticality in such dynamic public demonstrations. Namely, the same power-law exponents are found whenever the distributions are calculated, either due to the same windows-time or the number of hashtags. By means of network arrays, we show that the systems take on two correlations with high or low values of modularity. The importance of analysing systems near a critical point is that any small disturbance can escalate and induce large-scale -- nationwide -- chain reactions. (Abstract excerpt)

Butler, Travis and Georgi Georgiev. Self-Organization in Stellar Evolution: Size-Complexity Rule. arXiv:2202.02318. Assumption University, Worcester, MA physicists (search GG) post a strong notice to date of nature’s deep propensity to organize itself into dynamic, invariant states everywhere. In this astral case, how stars form is seen as an another exemplary result. An historic importance then becomes an implied mathematic source code which exists in generative effect independently of any certain scale or instance. In regard, such recurrent features in kind from celestial to cultural phases are cited as a 2022 presence and proof of a true universality. As our Earthuman epic reaches a consummate moment, this entry, A Physics Perspective on Collective Animal Behavior (N. Ouellette 2022), and many others are coming altogether so to reveal and discover a cocreative uniVerse to wumanVerse familial genesis.

Complexity Theory is highly interdisciplinary, therefore any regularities must hold on all levels of organization, independent on the nature of the system. An open question in science is how complex systems self-organize to produce emergent structures and properties by way of non-equilibrium thermodynamics. There is a quantity-quality transition which holds across natural systems, which is often known as the size-complexity rule. We apply this standard to stars to compare them with other complex systems so to find universal patterns of self-organization independent of the substrate. This rule goes under different names in different disciplines and systems of different nature, such as the area-speciation rule, economies of scale, scaling relations in biology and for cities, and many others. (Abstract excerpt)

Cambrainha, Gustavo, et al. Criticality at work: scaling in the mouse cortex enhances performance. arXiv:2410.23508. Into this year, Universidade Federal de Pernambuco, Recife, Brazil neuroscientists combine sophisticated imaging studies with deep physical theories to achieve a strong validation of an optimum cerebral self-organized critical poise. See also Rapid cooling of the Cassiopeia A neutron star due to superfluid quantum criticality at arXiv:2410.21945 for a remote instance of this same phenomena. These latest findings of nature’s whole scale, sweet spot universality will be a prime aspect of a 2025 ecosmic synthesis.

The critical brain hypothesis posits that neural systems operate near a phase transition which optimizes the transmission, storage, and processing of information. While the scale invariance and non-Gaussian dynamic hallmarks of criticality have been observed in brain activity, a direct link between this certain state and cognitive performance remains to be fully proven. Here, we use a renormalisation group approach to examine the primary cortex of mice on a visual task. We show that non-trivial scaling is associated with enhanced acuity, with pronounced scaling observed during successful completion. These results add further evidence that critical dynamics are vital for cortical processing and best behavior. (Abstract)

Castro, Daniel, et al. Interdependent scaling exponents in the human brain. arXiv:2411.09098. Universidade Federal de Pernambuco, Recife, Brazil and Dutch Institute for Emergent Phenomena, University of Amsterdam neuroscientists add a physical depth to complex network system studies by way of renormalization theories. By so doing, a further exposition and evidence of pervasive self-organized criticalities which enhance cerebral functions and faculties is achieved. See also In and Out of Criticality? State-Dependent Scaling in the Rat Visual Cortex by Daniel Castro, et al in PRX Life (2/023008, 2024).

We apply renormalization group (RG) theories to resting-state fMRI imagings of brain activity in a large population. By recursively coarse-graining the data, we compute scaling exponents for the series variance, log probability of silence, and covariance eigenvalues. We find a significant correlation of exponent values with the gray matter volume and cognitive performance. Akin to scaling relations near critical points in thermodynamics, our findings suggest that scalar interdependencies are intrinsic to brain organization and may also exist in other complex systems. (Abstract)

A key insight from RG theory is that scaling exponents — quantities describing the behavior of physical observables near a phase transition — are interdependent. Their exponents determine the universality class, so systems with widely different microscopic details can share the same macroscopic critical behavior. (1) Finally, given that our approach relies on time series data analysis, it also opens the possibility of finding scaling interdependencies in other complex systems exhibiting multiscale dynamics. Exploring these systems could advance the general understanding of universality and pave the way towards identifying key underlying mechanisms governing complex system behavior. (4)

Castro, Daniel. et al. In and Out of Criticality? State-Dependent Scaling in the Rat Visual Cortex. PRX Life. 2/023008, 2024. In this new Physical Review journal, eight Universidade Federal de Pernambuco, Recife, Brazil and University of Minho, Braga, Portugal system physicians add a latest appreciation of how our cerebral processes indeed do seem to bounce around a best performance balance.

A presumed proximity to a critical point is believed to endow the brain with scale-invariant statistics to confer advantages for information processing, storage, and transmission. To assess scaling and cortical states, we apply a renormalization group method to data recordings from the anesthetized rat's visual cortex. Under anesthesia, cortical states shift across synchronization levels defined by population spiking rate variability. We find that scaling signatures only appear as spiking frequency surpasses a threshold. Our results suggest that a wide range of cortical states corresponds to small deviations around a critical point, with the system fluctuating in and out of criticality, spending roughly three-quarters of the experiment duration within a scaling regime. (Abstract excerpt)

Chen, Lei, et al. Metallic Quantum Criticality Enabled by Flat Bands in a Kagome Lattice. arXiv:2307.09431.. As the quotes convey, Rice University Center for Quantum Materials, Vienna University of Technology and SUNY Stony Brook physicists including Jennifer Cano and Silke Paschen delve deeply into these substantial realms and scientific features to reveal still another exemplary statement of nature’s optimum self-organized balance. See also Quantum Criticality Enabled by Intertwined Degrees of Freedom by this group for a broader version in PNAS. (120/30, 2023.)

Strange metals arise in a variety of platforms for strongly correlated electrons, ranging from the cuprates, heavy fermions to flat band systems. We study a Hubbard model on a kagome lattice so as to construct a Kondo lattice description. We identify a Mott transition with a quantum critical point at which quasiparticles a strange metallicity emerges. Our theoretical work opens up a new route for realizing beyond-Landau quantum criticality and novel quantum phases that it nucleates. (Excerpts)

For the first time, we have theoretically realized a metallic quantum critical point enabled by the flat bands of a kagome lattice, with properties that parallel the well established strange metallicity of heavy fermion systems. (28) Our findings also reveal new interconnections among a variety of correlated electron platforms, and point to new platforms for beyond-Landau quantum criticality. (30)

Chen, Luyao, et al. AI of Brain and Cognitive Sciences: From the Perspective of First Principles. arXiv:2301.08382. Sixteen Chinese length scholars under the auspices of the AI of Brain and Cognitive Sciences Research Group, Beijing Academy of Artificial Intelligence, and Beijing University post an array of chapters, per the first quote, in an effort to advance AI abilities by better appreciations of how our own cerebral faculties have actually formed and well function. Our main interest is Criticality: Bringing New Perspectives to the Brain and AI, which gathers and presents an extensive, latest survey as this realization lately gains a wide, quantified acceptance. The two longer quotes are from this section.

This paper collects six such first principles summarized by the research team, “AI of Brain and Cognitive Sciences”, in the Beijing Academy of Artificial Intelligence (BAAI). They are attractor network, criticality, random network, sparse coding, relational memory, and perceptual learning. On each topic, we review its biological background, fundamental property, potential application to AI, and future development.

The framework of criticality is a powerful tool to understand and analyze complex systems because many systems in physics and nature are in a critical state. In the past 20 years, researchers found that biological neural networks in the brain operate close to a critical state, which provides a new perspective on studying brain dynamics. It is known that the critical state is important for brain activities/functions because it optimizes numerous aspects of information transmission, storage, and processing. In addition, some brain diseases are believed to be related to the deviation from the critical state, which also opens a new window for diagnosing and treating these diseases. In the field of artificial intelligence, the framework of the critical state is used to analyze and guide both the structural design and weight initialization of deep neural networks, suggesting that operating close to a critical state may be considered one of the fundamental principles governing computations in neural networks. (9)

The critical state gives us a new perspective to study biological and artificial neural networks. At present, the framework of criticality has not only been used to understand neural dynamics and brain diseases but also to analyze the operation of deep neural networks and guide the design for further improvement. Through theoretical analysis and numerical simulations, we know that the critical state of the network can be controlled by some simple control parameters, such as branching ratio, spectral radius, and input-output Jacobian singular values. This makes it possible to analyze or tune the overall behavior of complex networks through statistics that are easy to observe. We believe that the framework of criticality will play an even more important role in helping us better understand the constraints applied to artificial neural networks and to design better architectures as well as dynamical rules to improve its performance in complex information processing. (14)

Chen, Qianyang and Mikhail Prokopenko. Why collective behaviours self-organise to criticality: A primer on information-theoretic and thermodynamic utility measures. arXiv:2409.15668. Centre for Complex Systems, University of Sydney physicists (search MP) contribute a further qualification of nature’s apparent whole scale persistence to arrange itself across every infinity by way of this critical poise, best balance, optimum state of more or less order. See also Biological Arrow of Time by Mikhail Prokopenko, et al (arXiv:2409.12029) for another instantiation as a revolutionary ecosmic natural genesis universe just now becomes a profound reality.

Collective behaviours are frequently observed to self-organise to criticality. Existing models such as Self-organised Criticality (SOC) occur across disciplines but in our view do not fully explain. Here we propose an information-driven approach with predictive content, empowerment, and active inference, as well as thermodynamic efficiencies. By interpreting the Ising model as a perception-action loop, we compare how intrinsic utilities shape collective behaviour. Finally, we define a Principle of Super-efficiency whereby collective behaviours arrive at a critical regime as an optimal balance with respect to the entropy reduction relative to the thermodynamic costs. (Abstract)

Self-organisation is a process where a system spontaneously develops new structured patterns or functions, without control by an external force. From a physics perspective, the effect is viewed as entropy reduction or increase in order in an open system. In a biological sense, self-organisation is defined as a pattern-formation process that relies on interactions among many lower-level components. Three key aspects are Spontaneous order: the system evolves into a more coherent state; Emergent transition to a more collective behaviour and Local interactions and long-range correlations: system components operate on local information but exhibit long-range connectivity. (1)

The Ising model is a mathematical expression of ferromagnetism in statistical mechanics. It consists of discrete variables that represent atomic "spins" in one of two states arranged in a lattice allowing each spin to interact with its neighbors. The model allows the identification of phase transitions as a simplified model of reality.

Cheraghalizadeh, J., et al. Simulating Cumulus Clouds Based on Self-Organized Criticality. arXiv:2211.06111. University of Mohaghech Ardabili, Iran and ETH Zurich physicists advance recent findings that even such weather conditions can be found to take on and exhibit this intrinsic phenomenal preference. In regard, this widespread, exemplary occasion of a SOC viability strongly indicates an independent source which is universally inl manifest effect.

Recently it was shown that self-organized criticality is an important ingredient of the dynamics of cumulus clouds (Physical Review E, 103(5), 2021). Here we introduce a new algorithm to simulate cumulus clouds in two-dimensional square lattices, based on the cohesive energy of wet air parcels and a sandpile-type diffusion of cloud segments. We observed that the cloud fields that we obtain from our model are fractal, with the outer perimeter having a fractal dimension. (Excerpt)

Ciaunica, Anna, et al. Nested Selves: Self-Organization and Shared Markov Blankets in Prenatal Development in Humans.. PsyArixiv Preprints, May 2023. We review this post by AC, University of Lisbon, Michael Levin, Tufts University, Fernando Rosas, University of Sussex, and Karl Friston, University College London (search each) as they move on to a unique perception that life’s embryonic stage can be rightly viewed as a self-organizing process. Into 2023, this occasion becomes evident within a biological self-making milieu and a newly fertile physical basis. So once more, along with Autorino and Petridou, a true evolutionary gestation takes credence as a genesis synthesis.

The immune system is a central component of organismic function in humans. This paper addresses self-organisation of a biological system in relation to — and nested within — an other biological system in pregnancy. Indeed, the hierarchical relationship in pregnancy reflects an earlier autopoietic process in the embryo by which the number of individuals in a single blastoderm is determined by cell-cell interactions. Specifically, we consider the role of the immune system in biological self-organisation in addition to neural/brain systems that furnish us with a sense of self. In pregnancy, two immune systems need to exchange resources and information to maintain viable self-regulation of nested systems. We then propose mechanisms that scaffold tise complex relationship through the lens of the Active Inference, with a focus on shared Markov blankets. (Abstract excerpt))

Ciss, Mamadou, et al. Description of the Cattle and Small Ruminants Trade Network in Senegal.. arXiv:2301.11784. We cite as another instance by Senegalese, French and British system veterinaries of how a mature awareness of common, implicate nonlinear lineaments in universal effect can provide an implicate guidance even for the distribution and maintenance of indigenous herd animals.

Livestock mobility of small and large ruminants, is a main pillar of production and trade in West Africa. These movements cover several thousand kilometers and connect the whole West African region. But this activity also leads to the diffusion of many animal and zoonotic diseases. In this paper, we present a procedure based on temporal network theory to identify possible sentinel locations using two indicators: vulnerability (i.e. the probability of being reached by the disease) and time of infection (i.e. the time of first arrival of the disease). (Excerpt)

Deco, Gustavo, et al. Complex harmonics reveal low-dimensional manifolds of critical brain dynamics.. Physical Review E. 111/014410, 2025. Universitat Pompeu Fabra, Barcelona and Oxford University open another window to view a neural nature which attains a twintelligence (herein a reciprocal poise) and effective cognizance by way of this complementarity and familiarity. See also Emergence of Power-Law Avalanches from Collective Stochastic Dynamics of Adaptive Neurons by Lik-Chun Chan, et al in PRX Life (3/013013, 2025).

The brain needs to perform time-critical computations to ensure survival, for which nonlocal, distributed computation at the whole-brain level make possible by self-organized criticality. These responses accord with Schrödinger's wave equation, so as to form a complex harmonics decomposition (CHARM) framework to express the complex network dynamics that are the key computational engines of critical brain dynamics. (Excerpt)

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