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A Revolutionary Organic Habitable UniVerse

Kartvelishvili, Guram, et al. Self-Organized Critical Multiverse. arXiv:2003.12594. As nature’s phenomenal propensity to seek and reside at an optimum, complementary balance between certain particle/wave, conserve/create, me/We states gains notice everywhere, University of Pennsylvania astrophysicists including Justin Khoury scope out ways to detect its effect on this vast expanse. After citations of its wide presence (see quotes), a review of deep parameters from an inflationary start to now are seen to express such a nonlinear poise. In wider regard, as human beings are lately assaulted is so many ways, at the same while a worldwise intelligence discovers a multiUniVerse to EarthVerse of a bipartite, bigender code. As the website documents, this source code seems to be genetic in actual kind as a vital endowment. See also Dynamical Criticality and Higgs Metastability by JK at 1912.06706 and Search Optimization, Funnel Tomography, and Dynamical Criticality on the String Landscape by JK and Onkar Farrikar at 1907.07693. We post several quotes in support

Recently a dynamical selection mechanism for vacua based on search optimization was proposed in the context of false-vacuum eternal inflation on the landscape. The search algorithm is optimal in regions of the landscape where the dynamics are tuned at criticality, with de Sitter vacua having an average lifetime of order their Page time. The purpose of this paper is to shed light on the nature of the dynamical phase transition at the Page lifetime. Through a change of variables the master equation governing the comoving volume of de Sitter vacua is mapped to a stochastic equation for coupled overdamped stochastic oscillators . We show that the displacement fluctuations for the oscillators exhibit a 1/f power spectrum over a broad range of frequencies. A 1/f power spectrum is a hallmark of non-equilibrium systems at criticality. In analogy with neuronal avalanches in the brain, de Sitter vacua at criticality can be thought of as undergoing scale invariant volume fluctuation avalanches. (Abstract excerpt)

The discovery that string theory admits a vast landscape of metastable vacua, together with the mechanism of eternal inflation for dynamically populating these vacua, has led to a paradigm shift in our understanding of fundamental physics. It entails that statistical physics, possibly in conjunction with selection (anthropic) effects, played a role in determining the physical parameters of our universe. Like many other statistical systems, it is natural to expect that the multiverse can exhibit phase transitions. Indeed, it has been shown recently that certain regions of the landscape display non-equilibrium critical phenomena, in the sense that their vacuum dynamics are tuned at dynamical criticality. (1)

Non-equilibrium systems exhibiting 1/f fluctuation spectra are ubiquitous in nature. Examples include neuronal dynamics, heart beat variability, linguistics (Zipf’s law), economic time series (stock market prices), music and art. Thus, complex behavior appears intimately related to dynamical criticality. This has motivated the tantalizing idea of self-organizing criticality. While the subject is not without controversy, it is worth noting that our framework satisfies what are believed to be necessary conditions for self-organized criticality — our landscape region is out-of-equilibrium, open/dissipative, and slowly-driven. (3)

Complex self-organized systems poised at criticality are ubiquitous in the natural world. This has led to the conjecture that dynamical criticality is evolutionarily favored because it offers an ideal trade-off between robust response to external stimuli and flexibility of adaptation to a changing environment. In a forthcoming paper we will study another advantage of dynamical criticality, namely enhanced computational capabilities. Indeed, it has been argued that complex systems maximize their computational capabilities at the phase transition between stable and unstable dynamical behavior — the so-called “edge of chaos”. For instance, cellular automata with certain critical dynamical rules are capable of universal computation, exhibiting long-lived and complex transient structures. (9-10)

Xue, Chi, et al. Scale-invariant Topology and Bursty Branching of Evolutionary Trees Emerge from Niche Construction. Proceedings of the National Academy of Sciences. 117/7679, 2020. University of Illinois genome biologists including Nigel Goldenfeld provide an exercise to show how, by way of statistical physics and network principles, that life’s circuitous, diverse, adaptive course can yet be found to have an intrinsic, self similar topology.

Phylogenetic trees describe both the evolutionary process and community diversity. Recent work has established that they exhibit scale-invariant topology, which quantifies the fact that their branching lies in between balanced binary trees and maximally unbalanced ones. Here, we present a simple, coarse-grained statistical model of niche construction coupled to speciation. Finite-size scaling analysis of the dynamics shows that the resultant phylogenetic tree topology is scale-invariant due to a singularity arising from large niche construction fluctuations that follow extinction events. The same model recapitulates the bursty pattern of diversification in time. (Abstract)

McArdle, Sam, et al. Quantum Computational Chemistry. Review of Modern Physics. 92/015003, 2020. Oxford University and University of Toronto materials scientists post a 51 page, 2020s tutorial as these three major scientific areas flow together and cross-inform each other. A further integration is also made with “classical” approaches, along with algorithmic methods and other skill sets so to compose a unified substantial synthesis.

A promising application of quantum computing is the solving of classically intractable chemistry problems. This may help explain phenomena such as high temperature superconductivity, solid-state physics, transition metal catalysis, and certain biochemical reactions. However, building a sufficient quantum computer for this purpose will be a scientific challenge. This review provides a comprehensive introduction with key methods to demonstrate how to map chemical problems onto a quantum computer, and to solve them. (Abstract excerpt)

Campbell, John O. and Michael Price. Universal Darwinism and the Origins of Order. Georgiev, Georgi, et al, eds. Evolution, Development and Complexity. International: Springer, 2019. In a chapter from a 2017 conference with the book title (search editor), a British Columbia independent researcher and a Brunel University evolutionary psychologist scope out a growing sense that life’s “variance – inheritance – selection” method is even in effect across temporal cosmic to cultural domains. By this view, this scheme becomes a computational, probabilistic iteration whence out of many contingent candidates an “optimum” result might eventually be achieved. The paper then introduces a novel quality that such a universe seems to favor and advance, namely an “accumulated knowledge repository.” As the Abstract and quote note, a five stage scale is cited whereof each phase contains more relative informational content.

In regard, this natural learning process serves to trace and track an oriented course from universe to us peoples, akin to J. A. Wheeler’s bit to it circuit. Although not mentioned, we Earthling interlocutors seem to be involved with its actual discovery, self-selection and literate cocreation. But an imagination of a greater phenomenal reality with an independent, genetic-like self-organization remains elusive to the authors and conference. The manifest knowledge resource, akin to Ken Richardson’s biogrammar (search), does not yet have a tangible identity. As it may at last ascend to our prodigious sapiensphere, maybe a global “geonome” appreciation would be apt.

In this chapter we describe a ‘universal Darwinism’ which proposes that the observable universe results from two types of processes: (1) disorder’s tendency to increase in isolated systems (second law of thermodynamics), and (2) Darwinian selection, which produces orderly entities that can withstand the second law. Darwinian processes generate complex order not just in the biological phase but in all five domains of nature as they exist in a nested hierarchy of cosmological, quantum, biological, neural, and cultural. Each qualifies as a distinct stage by being characterized by a relative ‘knowledge repository’, that is, a cumulative store of information about existence (e.g. a genome).

Knowledge repositories are probabilistic models which make guesses about how to exist, which are then tested by the ‘embodied adapted system’ (e.g. phenotype). The repository then undergoes a Bayesian update, and thus becomes less ignorant and less entropic. These natural inferential systems evolve according to ‘variance – inheritance – selection’ Darwinian dynamics. For each new phase, its repository computationally transforms the substrate of the earlier domain (e.g., cultural repositories orchestrate the neural substrate), to generate new, innovative ways of overcoming the second law. We conclude that Darwinian theory, as an explanation for the origins of complex order in the universe, may be far more fundamental than is conventionally supposed. (Abstract)

We suggest that nature has utilized the selective Darwinian process to accumulate repositories of evolutionary knowledge within several domains of nature. We will discuss five types of autopoietic knowledge repositories, one in each domain of nature: (1) in the cosmological domain, this knowledge repository is represented by the laws and parameters of physics; (2) in the quantum domain, by quantum wave functions; (3) in the biological domain, by genomes (potentially acting in concert with epigenetic effects); (4) in the neural domain, by learned neural models; and (5) in the cultural domain, by cultural models. It is no accident that each natural domain possesses its own repository of accumulated knowledge, because the presence of such a knowledge repository is in fact our criterion for identifying each domain. (4)

Ulanowicz, Robert. Ecological Clues to the Nature of Consciousness. Entropy. 22/6, 2020. The veteran theoretical ecologist (search) was at the University of Maryland Center for Environmental Sciences for many years where, among other projects, he served as a caretaker of Chesapeake Bay. In 1987 Bob and I had lunch with Ilya Prigogine at a conference. In this paper he illumes that Integrated Information and Global Workspace theories of cerebral function with regard to knowing awareness can have an affinity to similar environmental principles and vitalities.

Some dynamics associated with consciousness are shared by other complex macroscopic living systems. Autocatalysis, an active agency in ecosystems, imparts to them a centripetality, the ability to attract resources. It is likely that autocatalysis in the central nervous system gives rise to the phenomenon of selfhood. Similarly, a coherence domain, as constituted in terms of bi-level coordination in ecosystems, stands as an analogy to the simultaneous access the mind has to available information. The result is the feeling that one’s surroundings are present to the individual all at once. Similar research in other fields suggests empirical approaches to the study of consciousness in humans and other higher animals. (Abstract)

Cataldo, Franco, et al. Petroleum, Coal and Other Organics in Space. arXiv:2005.01162. In a paper to appear in a special issue of Astrophysics and Space Science, Italian and French astrochemists discern and extend the pervasive presence of such organic, precursor biochemicals across a conducive spacescape. And we add such spontaneous formations of quite organic, fuel-like components well implies an innate, evolutionary fertility.

The petroleum and coal models of the unidentified infrared emissions (UIE), sometimes referred also as unidentified infrared bands (UIBs) has been reviewed mainly based on the work of the authors with the inclusion of unpublished results. It is shown that the petroleum and coal model of the UIE converges and merges quite well with the MAON (Mixed Aromatic Aliphatic Organic Nanoparticles) model of the UIE. It is shown that the thermal treatment of various substrates like PAHs, alkylated PAHs but also mixed aliphatic/olefinic substrates leads invariable to carbonaceous materials matching the infrared spectrum of anthracite coal or certain petroleum fractions. (Abstract excerpt)

Cleland, Carol. The Quest for a Universal Theory of Life. ambridge: Cambridge University Press, 2019. The veteran University of Colorado philosopher of astrobiology surveys the past and present of unresolved efforts to explain ourselves and the life phenomenon of living systems across local and cosmic matter. With a nod to Aristotle and Darwin, is its essence self-organization or genetic reproduction, how can we ever define and know? But we add, it seems as long as (male) mindset rules that cannot imagine or allow any extant universe at all from which viability arises, no answer will be possible.

Gaudi, B. Scott, et al. The Habitable Exoplanet Observatory Mission Concept Report. arXiv:2001:06683. We note this 500 page mission statement by some 200 astroscientists with a main base at Jet Propulsion Laboratory as a premier example into the 2030s of our collaborative Earthkind personsphere beginning to explore, quantify and spread forth in a revolutionary genesis universe.

Seyler, Lauren, et al. Metabolomics as an Emerging Tool in the Search for Astrobiologically Relevant Biomarkers. Astrobiology. June, 2020. A seven member team from the Woods Hole Oceanographic Institution, Centro de Astrobiología, Madrid, Blue Marble Space Institute, Seattle, and Cal Tech including James Cleaves scope out how such an expansive –omics approach, properly integrated and applied, can well facilitate this grand new exoplanetary phase as Earthlings begin to search for near and far celestial neighbors.

It is now easy to sequence and recover microbial genomes from environmental samples. If transcriptional and translational functions can be assigned to these genomes, it should be possible to understand the molecular inputs and outputs of a microbial community. However, gene-based tools alone are presently insufficient to describe the full suite of chemical reactions and small molecules that compose a living cell. Metabolomic tools have developed quickly and now enable rapid detection and identification of small molecules within biological and environmental samples. These technologies will soon facilitate the detection of novel enzymatic activities, novel organisms, and potentially extraterrestrial life-forms. (Abstract)

Ecosmomics: A Survey of Nonlinear Complex Network Sciences

Zhang, Mengsen, et al. Topological Portraits of Multiscale Coordination Dynamics. Journal of Neuroscience Methods. Vol. 339, 2020. Florida Atlantic University and Stanford University researchers including Scott Kelso and Emmanuelle Tognoli (search) continue to finesse the presence and importance of nature’s scored choreography as it graces, informs and empowers our responsive cerebral performance. We note the mathematic approaches in bold as they find application to an increasing number of disparate many areas, which altogether imply a mindful ecosmic coordination.

Living systems exhibit complex yet organized behavior on multiple spatiotemporal scales. To investigate this phenomena, one needs a meaningful way to quantify the complex dynamics. This work shows how computational algebraic topology and dynamical systems theory can help meet this challenge. We propose, for example, a method to study dynamic topological information using persistent homology, which allows us to effectively construct a multiscale topological portrait of rhythmic coordination. The present work demonstrates how the analysis of multiscale coordination dynamics can benefit from topological methods, thereby paving the way for further systematic quantification of complex, high-dimensional dynamics in living systems. (Abstract excerpt)

Battiston, Federico, et al. Network beyond Pairwise Interactions: Structure and Dynamics. Physics Reports. June, 2020. As network science enters the 2020s, an eight person team from across Europe and the USA including Vito Latora and Alice Patania posts a 109 page, 734 reference tutorial on the “higher-order representation of networks.” These further insights and appreciations involve features such as simplical homology, complexes, motifs, spreading dynamics, evolutionary games and more. With this expansive theory in place, an array of social, biologic, neural and ecological applications are reviewed. See also Growing Scale-Free Simplexes by K. Kovalinko, et al at arXiv:2006.12899. In regard, we record still another 21st century revolutionary discovery of a genesis nature as it reaches mature verification.

The complexity of many biological, social and technological systems stems from the richness of the interactions among their units. Over the past decades, complex systems have been described as networks whose interacting pairs of nodes are connected by links. Yet, in human communication, chemical reactions and ecological systems, interactions can occur in groups of three or more nodes. Here, we present an overview of the emerging field of networks beyond pairwise interactions. We discuss the methods to represent higher-order interactions and present different frameworks used to describe them. We review ways to characterize the structure of these systems such as random and growing simplicial complexes, bipartite graphs and hypergraphs. We conclude with a summary of empirical applications, providing an outlook on current modeling and conceptual frontiers. (Abstract excerpt)

Caetano-Anolles, Gustavo, et al. Emergence of Hierarchical Modularity in Evolving Networks Uncovered by Phylogenomic Analysis. Evolutionary Bioinformatics. 15/1, 2019. University of Illinois, Heidelberg Institute for Theoretical Studies, Gebze Technical University, Turkey, Seoul National University, and European Molecular Biology Laboratory, Germany system biologists (search lead author) advance their phylogenomomic project by showing how this theoretical approach can provide novel explanations of life’s anatomic physiology.

Networks describe how parts associate with each other to form integrated systems which often have modular and hierarchical structure. In biology, network growth involves two processes, one that unifies and the other that diversifies. Here, we propose a biphasic (bow-tie) theory of module emergence. In the first phase, emerging, self-organized interactions join nodal parts into modular linkages. In the second phase, modular variants become components for a new generative cycle of higher level organization. Remarkably, phylogenomic analyses uncover this emergence in the rewiring of metabolomic and transcriptome-informed metabolic networks, the nanosecond dynamics of proteins, and evolving metabolism, elementary functionomes, and protein domain networks. (Abstract)

Gysi, Deisy and Katja Nowick. Construction, Comparison and Evolution of Networks in Life Sciences and Other Disciplines. Journal of the Royal Society Interface. May, 2020. University of Leipzig and Free University of Berlin bioinformatic scholars (View GDs website, who is now with AL Barabasi’s group at Northeastern University) offer a broad survey of the 21st century network revolution that ALB and Reka Albert (search) initiated around 2000. Through the 2010s, almost every physical, biological and social phase has become reconceived, filled out and invigorated by these scale-free connective dynamics. The paper opens with glossary terms such as centrality and clustering to an extent that the common multiplex linkages appear to actively exist on their independent own.

This heretofore unknown anatomy and physiology is then noted from protein, metabolic, genomic, and neural realms onto an evolutionary presence and role so as to join living systems in modular scales. A further topical series covers science learning, cultural media, finance and more. It closes by saying that the same forms and functions can now be seen to repeat in kind at every stage which Geoffrey West cited as a “Universality of Networks” in Niall Ferguson’s Networld 2020 TV special.

Network approaches have become pervasive in many research fields. They allow for a more comprehensive understanding of complex relationships between entities as well as their group-level properties and dynamics. Many networks change over time, be it within seconds or millions of years, depending on the nature of the network. Our focus will be on comparative network analyses in life sciences, where deciphering temporal network changes is a core interest of molecular, ecological, neuropsychological and evolutionary biologists. Further, we will take a journey through disciplines such as social sciences, finance and computational gastronomy to present commonalities and differences in how networks change and can be analysed. (Abstract)

Li, Aming, et al. Evolution of Cooperation on Temporal Networks. Nature Communications. 11/2259, 2020. By a novel application of network science to social activities, an eight person team from Peking University, Northeastern University, Harvard Medical School and Princeton University (Simon Levin) illuminates a deeper natural basis for beneficial behaviors to both members and groups. As the quotes says, these heretofore unknown features can aid better explanations and usage.

Population structure is a key determinant in fostering cooperation among naturally self-interested individuals in microbial populations, social insect groups, and human societies. Prior research has focused on static structures, and yet most interactions are changing in time and form a temporal network. Surprisingly, we find that network temporality actually enhances the evolution of cooperation relative to comparable static networks, despite the fact that bursty interaction patterns generally impede. We resolve this tension by a measure which quantifies the amount of temporality in a network, so to reveal an intermediate level that boosts cooperation. (Abstract excerpt)

Explaining the evolution of durable, widespread cooperative behaviour in groups of self-interested individuals has been a challenge since the time of Darwin. In response, researchers have turned to the critical role played by the underlying interaction networks, in which nodes represent individuals and links represent interactions. It has been shown that the nontrivial population structures represented by both homogeneous and heterogeneous networks permit the formation of stable clusters of cooperators (altruists), with higher individual payoffs while also resisting defectors (egoists). As such, both theoretical analysis and behavioural experiments point to network structure as a key ingredient for the emergence of cooperation. (2)

Hillberry, Logan, et al. Entangled Quantum Cellular Automata (QCA), Physical Complexity, and Goldilocks Rules. arXiv:2005.1763. We cite this entry by a nine member team based at UT Austin, CalTech, and the University of Padova including Nicole Yunger Halpern as a current example of how disparate classical and quantum domains along with mathematic computations are joining up and cross-informing on the way to a phenomenal synthesis. The Abstract and quote convey a essential sense of the frontier project. So into the 2020s can we begin to realize (again) that an extant nature does have its own encoded reality and procreative purpose that we peoples can philosophize about? A good part of the project would be to translate the arcane terms into a human-familial image, which is what this site attempts to do.

Cellular automata are interacting classical bits that display diverse behaviors, from fractals to random-number generators to Turing-complete computation. We introduce entangled quantum cellular automata subject to Goldilocks rules, tradeoffs of the kind underpinning biological, social, and economic complexity. Tweaking digital and analog quantum-computing protocols generates persistent entropy fluctuations; robust dynamical features, including an entangled breather; and network structure and dynamics consistent with complexity. Present-day quantum platforms---Rydberg arrays, trapped ions, and superconducting qubits---can implement Goldilocks protocols, which generate quantum many-body states with rich entanglement and structure. Moreover, the complexity studies reported here underscore an emerging idea in many-body quantum physics: some systems fall outside the integrable/chaotic dichotomy. (Abstract)

We have discovered a physically potent feature of entangled quantum cellular automata: the emergence of complexity under Goldilocks rules. Goldilocks rules balance activity and inactivity. This tradeoff produces new, highly entangled, yet highly structured, quantum states. These states are persistently dynamic and neither uniform nor random. (14) Moreover, we have demonstrated that our QCA time-evolution protocols are implementable in extant digital and analog quantum computers. (14)

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