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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
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Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 16 through 30 of 63 found.

A Revolutionary Organic Habitable UniVerse

Animate Cosmos > Organic > Chemistry

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)

Animate Cosmos > Intelligence

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)

Animate Cosmos > Astrobiology

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)

Animate Cosmos > Astrobiology

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.

Animate Cosmos > exoearths

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.

Ecosmomics: A Survey of Nonlinear Complex Network Sciences

Cosmic Code

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)

Cosmic Code > nonlinear > networks

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)

Cosmic Code > nonlinear > networks

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)

Cosmic Code > nonlinear > networks

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)

Cosmic Code > nonlinear > networks

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)

Cosmic Code > nonlinear > Algorithms

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)

Cosmic Code > nonlinear > Algorithms

Kaznatcheev, Artem. Evolution is Exponentially More Powerful with Frequency-Dependent Selection. . An Oxford University computer scientist posts a latest appreciation of how living systems appear to evolve and develop as stochastic explore and educate optimization processes. In any event, the insight admits a deep mathematical presence of operative programs, which are modified along the way. See also Computational Complexity as an Ultimate Constraint on Evolution by AK in Genetics (212/245, 2019).

In 2009 (Leslie) Valiant (search) proposed to treat Darwinian evolution as a special kind of computational learning by way of statistical queries which represent a genotype’s fitness over a distribution of challenges. His model noted various environments that are “adaptable-to” from those that are not, but omits vital ecological interactions between different evolving agents. Here I extend an algorithmic Darwinism to include the ecological exigiences of frequency-dependent selection as a population-dependent bias and develop a game landscape view of evolution so to generalize the popular fitness landscape. The evolutionary game dynamics of finite populations are essential for finding a short adaptive path to the global fitness peak during the second stage of the adaptation process. This highlights the rich interface between computational learning theory, evolutionary games, and long-term evolution. (Abstract excerpt)

Artem K. website Prior to Oxford, I was at the Department of Integrated Mathematical Oncology at Moffitt Cancer, and at McGill University where I developed my interest in evolutionary dynamics, computer science, mathematical oncology and computational learning theory. In regard, I marvel at the world through algorithmic lenses. My theoretical work aims to ground the extended evolutionary synthesis in algorithmic game theory, computational learning theory, and combinatorial optimization.

Cosmic Code > nonlinear > Rosetta Cosmos

Chen, Hongjia, et al. Scaling Laws and Dynamics of Hashtags on Twitter. arXiv:2004.12707. University of Sydney systems linguists including Eduardo Altmann discern yet another case of nature’s universal mathematic patterns and dynamics at formative presence even is these hyper-active Internet communications.

In this paper we quantify the statistical properties and dynamics of the frequency of hashtag use on Twitter. Hashtags are special words used in social media to attract attention and to organize content. Looking at the collection of hashtags used in a period of time, we identify the scaling laws for their frequency distribution (Zipf's law), the number of unique hashtags as a function of sample size (Heaps' law), and the fluctuations around expected values (Taylor's law). While these scaling laws appear to be universal, their volume and nature depends strongly on time, with bursts at the minute scale, fat-tailed noise, and long-range correlations. Here we view hashtags as memes and quantify emerging properties of their collective interaction including scaling laws and time scales. (Excerpt)

Cosmic Code > nonlinear > 2015 universal

Buendia, Victor, et al. Feedback Mechanisms for Self-Organization to the Edge of a Phase Transition. arXiv:2006.03020. University of Granada, Columbia University, and Rutgers University bioscientists including Migeul Munoz continue to explore and finesse the various ways that nature’s newly found propensity to seek and attain an optimum dynamic balance between reciprocal modes or stages can be seen to take and express.

Scale-free outbursts of activity are commonly observed in physical, geological, and biological systems. The idea of self-organized criticality (SOC) suggests that natural systems can self-tune to a critical state with its concomitant power-laws and scaling. Theoretical progress now explains SOC by relating its critical properties to those of a non-equilibrium phase transition that separates an active state in which dynamical activity reverberates indefinitely, from an absorbing or quiescent state where activity eventually ceases. Here, we consider a related concept: self-organized bistability (SOB). We review similarities and differences between SOC and SOB under a common theoretical framework, and discuss "self-organized quasi-criticality" and "self-organized collective oscillations", with the aim of providing feedback mechanisms for self-organization to the edge of a phase transition. (Abstract excerpt)

In summary, we have reviewed within a common and unified framework different types of mechanisms for the self-organization to the vicinity of phase transitions. We hope that this work help clarify the literature on the subject, and contribute to new and exciting developments in physics and other disciplines. This could be especially important in biology, where the idea that living systems can obtain important functional advantages by operating at the edge of two alternative/complementary types of phases/state has attracted a great deal of attention and excitement. (21)

Cosmic Code > nonlinear > 2015 universal

Nosonovsky, Michael and Prosun Roy. Scaling in Collodial and Biological Networks. Entropy. 22/6, 2020. We cite this contribution by University of Wisconsin bioengineers as another good example of how worldwide collaborations are finding a consistency of active topologies which form into similar nested recurrences across material, biochemical, cellular, metabolic to neural and communicative domains. By a philoSophia 2020 vision, a revolutionary organic genesis ecosmos seems well underway to being quantified.

Scaling and dimensional analysis is applied to networks that describe various physical systems. Some of these networks possess fractal, scale-free, and small-world properties. First, we consider networks arising from granular and colloidal systems due to pairwise interaction between the particles. Many networks found in colloidal science possess self-organizing properties and/or self-organized criticality. Then, we discuss the allometric laws in branching vascular networks, artificial neural networks, cortical neural networks, as well as immune networks. Scaling relationships in complex networks of neurons, which are organized in the neocortex in a hierarchical manner, suggest that the characteristic time constant is independent of brain size when interspecies comparison is conducted. The information content, scaling, dimensional, and topological properties of these networks are discussed. (Abstract excerpt)

The brain networks possess many characteristics typical to other networks, including over‐frequency and power‐law activities, avalanches, small‐world, scale‐free, and fractal topography. It is particularly interesting to look for the correlation between the spatial distribution (for example, hubs) and temporal organization (frequency spectrum) of human brain cognitive activities. Such research is being conducted by many groups, for example, the study of the DMN during such activities as the comprehension of a text in a natural language versus contemplating it (the “language of thought”). The information content of the neural networks can be studied using the standard characteristics of the information theory, such as the Shannon entropy. It may provide ways to distinguish between DNA‐encoded information and information generated during the embryonal and post‐embryonal development, which may be driven by the self‐organizing process. (22)

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