
IV. Ecosmomics: Independent, UniVersal, Complex Network Systems and a Genetic CodeScript Source4. Universality Affirmations: A Critical Complementarity Jagielski, Maciej, et al. Theory of Earthquakes Interevent Times Applied to Financial Markets. arXiv:1610.08921. With Ryszard Kutner and Didier Sornette, European theorists describe an inherent mathematical correspondence between these disparate geological and societal realms, which is then seen as a universal quality of abrupt dynamic phenomena. We analyze the probability density function (PDF) of waiting times between financial loss exceedances. The empirical PDFs are fitted with the selfexcited Hawkes conditional Poisson process with a long power law memory kernel. The Hawkes process is the simplest extension of the Poisson process that takes into account how past events influence the occurrence of future events. By analyzing the empirical data for 15 different financial assets, we show that the formalism of the Hawkes process used for earthquakes can successfully model the PDF of interevent times between successive market losses. (Abstract) Jofre, Paula, et al. Cosmic Phylogeny: Reconstructing the Chemical History of the Solar Neighborhood with an Evolutionary Tree. arXiv:1611.02575. Cambridge University, Universidad Diego Protales, Chile, and Oxford University scientists, including Robert Foley, explore promising ways to apply life’s developmental topologies across chemical and stellar realms. An allusion is made to an analogous celestial genome, whose resultant webworks suggest an “astrocladistics.” Using 17 chemical elements as a proxy for stellar DNA, we present a full phylogenetic study of stars in the solar neighbourhood. This entails applying a clustering technique that is widely used in molecular biology to construct an evolutionary tree from which three branches emerge. These are interpreted as stellar populations which separate in age and kinematics and can be thus attributed to the thin disk, the thick disk, and an intermediate population of probable distinct origin. Combining the ages of the stars with their position on the tree, we are able to quantify the mean rate of chemical enrichment of each of the populations, and thus show in a purely empirical way that the star formation rate in the thick disk is much higher than in the thin disk. Our method offers an alternative approach to chemical tagging methods with the advantage of visualising the behaviour of chemical elements in evolutionary trees. This offers a new way to search for `common ancestors' that can reveal the origin of solar neighbourhood stars. (Abstract) Kalinin, Nikita, et al. Selforganized Criticality and Pattern Emergence through the Lens of Tropical Geometry. Proceedings of the National Academy of Sciences. I115/E8135, 2018. National Research University, St. Petersburg, IBM Watson Research Center, University of Toulouse, Institute of Science and Technology, Austria, and CINVESTAV, Mexico system mathematicians provide another way to perceive and quantify nature’s constant propensity to reach an a balance beam of more or less relative order in every topological form and function. In actuality, each instantiated complement of the dual, reciprocal condition then resides in both modes at once (particle/wave). See also Introduction to Tropical Series by the authors at arXiv:1706.03062. A simple geometric continuous model of selforganized criticality (SOC) is proposed. This model belongs to the field of tropical geometry and appears as a scaling limit of the classical sandpile model. We expect that our observation will connect the study of SOC and pattern formation to other fields (such as algebraic geometry, topology, string theory, and many practical applications) where tropical geometry has already been successfully used. (Significance) Klamser, Pascal and Pawel Romanczuk. Collective Predator Evasion: Putting the Criticality Hypothesis to the Test. PLoS Computational Biology. March, 2021. Humboldt University, Berlin, computational neuroscientists conduct analytical studies of how and why animal groupings as they cope with survival issues seem to tend toward a dynamic critical state. Their work goes on to study the role that selforganizing forces play in facilitating this optimum viability. Collective intelligence relies on efficient processing of information. Complex systems theory suggests that this activity is optimal at the border between order and disorder, i.e. at a critical point. However, for animal collectives fundamental questions remain open regarding selforganization towards criticality. Using a spatially explicit model of collective predator avoidance, we show that schooling prey performance is indeed optimal at criticality, but is not due to a collective response. Rather it occurs because of the emergent dynamical group structure. More importantly, this structural sensitivity makes the critical state evolutionary highly unstable in the context of predatorprey interactions, and demonstrates the decisive importance of spatial selforganization in collective animal behavior. (Author summary) Kolodrubetz, Michael. Quenching Our Thirst for Universality. Nature. 563/191, 2018. A UT Dallas systems physicist introduces three papers in this issue: Observation of Universal Dynamics in a Spinor Bose Gas Far from Equilibrium (Prufer, 217), Universal Prethermal Dynamics of Bose Gases Quenched to Unitarity (Eiger, 221) and Universal Dynamics in an Isolated OneDimensional Bose Gas Far from Equilibrium (Erne, 225), that verify in different places and ways the natural presence of ubiquitous, infinitely iterated, formative patterns and active processes. Although we live in a world of constant motion, physicists have focused largely on systems in or near equilibrium. In the past few decades, interest in nonequilibrium systems has increased, spurred by developments that are taking quantum mechanics from fundamental science to practical technology. Physicists are therefore tasked with an important question: what organizing principles do nonequilibrium quantum systems obey? Herein Prüfer et al, Eigen et al, and Erne et al report experiments that provide a partial answer to this question. The studies show, for the first time, that ultracold atomic systems far from equilibrium exhibit universality, in which measurable experimental properties become independent of microscopic details. (MK) Kossio, Felipe, et al. Growing Critical: SelfOrganized Criticality in a Developing Neural System. arXiv:1811.02861. As it becomes well known that brains seek and best perform in a state of mutual balance between more or less orderly complements, University of Bonn, Radboud University and King Juan Carlos University, Madrid neuroinformatic researchers describe experimental evidence that developmental brain maturations likewise proceed toward this optimum condition. Experiments in various neural systems found avalanches: bursts of activity with characteristics typical for critical dynamics. A possible explanation for their occurrence is an underlying network that selforganizes into a critical state. We propose a simple spiking model for developing neural networks, showing how these may "grow into" criticality. Avalanches generated by our model correspond to clusters of widely applied Hawkes processes. We analytically derive the cluster size and duration distributions and find that they agree with those of experimentally observed neuronal avalanches. (Abstract) Laurent, HebertDufresne, et al. Complex Networks as an Emerging Property of Hierarchical Preferential Attachment. Physical Review E. 92/6, 2015. University of Laval, Quebec and University of Barcelona physicists open this survey on the state of complexity science by tracing its advent to a 1962 paper The Architecture of Complexity by the pioneer theorist Herbert Simon in the Proceedings of the American Philosophical Society (106/467). Some half century later, as this 2015 section documents, the Grail goal of one, same, infinitely iterated, selforganizing system has been proven from quantum to human to cosmic realms, so as to imply a common, independent, universally manifest, source. Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of complex systems can be modeled as an organization of many embedded levels (potentially infinite in number), all of them following the same universal growth principle known as preferential attachment. More importantly, we show how real complex networks can be interpreted as a projection of our model, from which their scale independence, their clustering, their hierarchy, their fractality and their navigability naturally emerge. Our results suggest that complex networks, viewed as growing systems, can be quite simple, and that the apparent complexity of their structure is largely a reflection of their unobserved hierarchical nature. (Abstract) Lin, Henry and Max Tegmark. Critical Behavior from Deep Dynamics: A Hidden Dimension in Natural Language. arXiv:1606.06737. A Harvard University prodigy and a MIT polymath (Google names) team up to propose in mid 2016 a theoretical union across the expanse of uniVerse and humanVerse. Again, as the sections Universality Affirmations, Rosetta Cosmos, and others lately attest, this scientific verification from an array of technical finesses finds these same physical principles at work in cultural literature, which in turn implies an intrinsic textual essence. In regard, “close analogies” are cited between recursive grammars and statistical physics, which can be tracked by an informational quality. Wikipedia postings, human genomes and cosmic materiality are thus written in and convey the same linguistic script. We show that although many important data sequences  from texts in different languages to melodies and genomes  exhibit critical behavior, where the mutual information between symbols decays roughly like a power law with separation, Markov processes generically do not, their mutual information instead decaying exponentially. This explains why natural languages are very poorly approximated by Markov processes. We also present a broad class of models that naturally produce critical behavior. They all involve deep dynamics of a recursive nature, as can be implemented by treelike or recurrent deep neural networks. This model class captures the essence of recursive universal grammar as well as recursive selfreproduction in physical phenomena such as turbulence and cosmological inflation. We derive an analytic formula for the asymptotic power law and elucidate our results in a statistical physics context: 1dimensional models (such as a Markov models) will always fail to model natural language, because they cannot exhibit phase transitions, whereas models with one or more "hidden" dimensions representing levels of abstraction or scale can potentially succeed. (Abstract) Lin, Henry and Max Tegmark. Critical Behavior in Physics and Probabilistic Formal Languages. Entropy. 19/7, 2017. Harvard and MIT polymath physicists offer a good instance of a late 2010s universality whence this same complexity trace is seen to occur from music compositions, Wikipedia text, human genomes to physical dynamics. Such common phenomena can then be given a grammatical linguistic character, which is affine to neural net and computational learning processes. The article is included in an Information Theory collection of the prolific online journal, which along with many similar efforts, tries to express this deepest quality of a universe to human articulation. We show that the mutual information between two symbols, as a function of the number of symbols between the two, decays exponentially in any probabilistic regular grammar, but can decay like a power law for a contextfree grammar. This result about formal languages is closely related to a wellknown result in classical statistical mechanics that there are no phase transitions in dimensions fewer than two. It is also related to the emergence of power law correlations in turbulence and cosmological inflation through recursive generative processes. We elucidate these physics connections and comment on potential applications of our results to machine learning tasks like training artificial recurrent neural networks. (Abstract) Lorenzo, Salvatore, et al. Quantum Critical Scaling under Periodic Driving. Nature Scientific Reports. 7/5672, 2017. (arXiv:1612.02259) Into these later 2010s, University of Palermo, Milan, Calabria, and Cologne physicists distill the presence of universally recurrent phenomena, for example a propensity of quantum systems to seek and reach a critically poised state. Universality is key to the theory of phase transitions, stating that the equilibrium properties of observables near a phase transition can be classified according to few critical exponents. These exponents rule an universal scaling behaviour that witnesses the irrelevance of the model’s microscopic details at criticality. Here we discuss the persistence of such a scaling in a onedimensional quantum Ising model under sinusoidal modulation in time of its transverse magnetic field. We show that scaling of various quantities (concurrence, entanglement entropy, magnetic and fidelity susceptibility) endures up to a stroboscopic time proportional to the size of the system. Our results suggest that relevant features of the universality do hold also when the system is brought outofequilibrium by a periodic driving. (Abstract) Lugo, Haydee, et al. Chimera and Anticoordination States in Learning Dynamics. arXiv:1812.05603. We cite this entry by Spanish economists because they go on to suggest ways that this recently realized tendency of physical, electronic and neural systems to become poised between more or less order could be similarly evident in personal and social activities. Its early on, but we add that by perceptive extensions like this, its traditional version best known as yin/yang dynamics can at last gain a modern, 21st century scientific confirmation. In many reallife situations, individuals are motivated to achieve both social acceptance or approval and strategic objectives of coordination. Since these modes may take place in different environments, a twolayer network works well for its analysis. From an evolutionary approach, we focus on asymptotic solutions for alltoall interactions across and inside the layers and for initial distributions of strategies. We report the existence of chimera states in which two collective states coexist in the same network. We trace back the emergence of chimera states and global anticoordination states to the agents inertia against social pressure. (Abstract excerpt) Mac Carron, Padraig and Ralph Kenna. Universal Properties of Mythological Networks. Europhysics Letters EPL. 99/28002, 2012. As the quotes describe, Coventry University physicists apply condensed matter theories in the form of complex systems to the historic corpus of epic fabled and storied mythic literatures. The second quote is a also exemplifies how such papers now open as the range and reach of nonlinear phenomena extends across every natural and social domain. As a result, a true cosmos to culture “universality” is at last becoming evident and proven. As in statistical physics, the concept of universality plays an important, albeit qualitative, role in the field of comparative mythology. Here we apply statistical mechanical tools to analyse the networks underlying three iconic mythological narratives with a view to identifying common and distinguishing quantitative features. Of the three narratives, an AngloSaxon and a Greek text are mostly believed by antiquarians to be partly historically based while the third, an Irish epic, is often considered to be fictional. Here we use network analysis in an attempt to discriminate real from imaginary social networks and place mythological narratives on the spectrum between them. (Abstract)
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