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Displaying entries 16 through 30 of 86 found.
Animate Cosmos > Information
Language is Physical.
Quantum Information Processing.
At the outset of 21st century perceptions that quantum phenomena has an informational essence, the Argonne National Laboratory mathematical physicist proceeds from Rolf Landauer’s 1990s avowal (search) that physical reality is innately linguistic to scope out this novel expanse. So we have an early glimpse of a creative continuity from quantum realms and substantial matter to life’s rise as it reaches (and becomes manifest as) our loquacious sapience. The early paper is also at arXiv:quant-ph/0210211.
Some aspects of the physical nature of language are discussed. In particular, physical models of language must exist that are efficiently implementable. The existence requirement is essential because without physical models no communication or thinking would be possible. Efficient implementability for creating and reading language is discussed and illustrated with a quantum mechanical model. Linguistic expressions can have meaning, either as an informal or a formal language associated with a mathematical or physical theory. Inclusion of intelligent system in the theory domain means that the theory, e.g., quantum mechanics, must describe in some sense its own validation. Maps of language contents into physical states are discussed. (Abstract excerpts)
Animate Cosmos > Information
It is also quite likely that the ability to think or reason depends on the existence of physical models of language. Without entering into details of this complex subject it seems reasonable to expect that distinct conscious states of the brain correspond to distinct physical states of the brain. This would be expected to be the case independent of how one reasons or thinks (e.g. in picture sequences or word sequences, etc.). If such physical states did not exist, then it is likely that reasoning, thinking and even consciousness would not be possible. That is, physical representations of language are a necessary, but probably not sufficient, condition for the existence of communication, thinking, and possibly even consciousness. (499)
The Demon in the Machine: How Hidden Webs of Information are Solving the Mystery of Life.
London: Allen Lane,
The British physicist and popular author is now at Arizona State University as director of the BEYOND Center for Fundamental Concepts in Science. This latest volume since 2010 draws upon collegial projects and papers, plus meetings with many co-investigators such as Gregory Chaitin, Stuart Kauffman, Steven Benner, David Chalmers to Lee Cronin, Philip Ball, Giulio Tononi, Michael Levin, and more so to range from cosmos to consciousness. The result is a clearest glimpse to date of a 21st century integral reunion of biology and physics, human and universe, via a missing generative, informative principle.
At the outset, two main predecessors are James Clerk Maxwell (1831-1879) whose familiar demon of sorts served as an ordering agency and Erwin Schrodinger (1887-1961, (search) who in his 1943 What is Life? held that some “source code” must be in active effect. At the cusp of 2020, as this site tries to report, a worldwise cumulative intelligence (which is noted (102) in coherent groupings) seems to be coming altogether into a credible synthesis. In regard, the work joins the frontiers of evolutionary creativity, complex self-organization, algorithmic computation, network theory, integrative consciousness, morphogenesis, quantum biology, and further afield. As the second quote says, while olden material physics does not show signs of life, if such a bevy of novel principles is added to cosmic nature, it increasingly reveals an organic essence and human persons whom are indeed written in.
A lot of the ideas I present here originate with my colleague Sara Walker at ASU who has greatly influenced my thinking over the past five years. Sara shares my enthusiasm for seeking a grand unified theory of physics and biology organized around the concept of information. “Life is the next great frontier of physics” she declares. (2)
Animate Cosmos > Information > Quant Info
There is no evidence that the known laws of physics are rigged in favor of life. But what about the new informational laws of the sort I am conjecturing here? My hunch is that would not be so specific as to foreshadow biology as such, but they might favor a broader class of complex information managing systems of which life as we know it would be a striking representative. It’s an uplifting though that the laws of the universe might be intrinsically bio-friendly in this general manner. If the emergence of life, and perhaps mind, are etched into the underlying lawfulness of nature, it would bestow upon our existence as living, thinking beings a type of cosmic-level meaning. (217)
Relation between Observers and Effects of Number Valuation in Science.
A latest entry by the octogenarian Argonne National Laboratory mathematician (search) which continues his lifetime studies of quantum physical reality so as to distill a natural unification. See also a steady 21st century posting of his papers on the e-print site, along with work on quantum information theory.
This paper is a small step towards the goal of constructing a coherent theory of physics and mathematics together. It is based on two ideas, the localization of mathematical systems in space or space time, and the separation of the concepts of number from number value. The presence of a location dependent number value field affects theoretical descriptions of many physical and geometric quantities. The localization of mathematical systems and the separation of number from number value or meaning both emphasize the role of observers. Nothing, including numbers, has value or meaning to an unconscious observer. It is hoped that this work will lead to a better understanding of the relation between the foundations of mathematics and physics, and the role that observers play in this relation. (Abstract Excerpt)
Animate Cosmos > Fractal
Kempkes, Sander, et al.
Design and Characterization of Electrons in a Fractal Geometry.
As the Abstract details, Utrecht University physicists deftly show how even atoms and electrons, in their dynamic forms, naturally take on this iterative patterning. We offer two comments. When this section was first posted in 2004, the presence of a common, natural self-similarity was spurious and patchy. Fifteen years later it has become robustly evident that every universal, atomic, and animate complexity is graced by this infinite iteration. Whomever in the cosmos are we peoples to consider and begin a second materiality by way of “artificial atoms.” See also in the same issue Quantum Fractals by Dario Bercioux and Ainhoa Iriguez.
Here, we show how arrays of artificial atoms can be defined by controlled positioning of CO molecules on a Cu (111) surface, and how these sites couple to form electronic Sierpiński fractals. We characterize the electron wavefunctions at different energies with scanning tunnelling microscopy and spectroscopy, and show that they inherit the fractional dimension. Wavefunctions delocalized over the Sierpiński structure decompose into self-similar parts at higher energy, and this scale invariance can also be retrieved in reciprocal space. Our results show that electronic quantum fractals can be artificially created by atomic manipulation in a scanning tunnelling microscope. Moreover, the rational concept of artificial atoms can readily be transferred to planar semiconductor electronics, allowing for the exploration of electrons in a well-defined fractal geometry, including interactions and external fields. (Abstract)
Animate Cosmos > Fractal
Evolution of the Early Universe in the Scale Invariant Theory.
The Geneva Observatory astronomer (search) expands his collegial quantification of a universally repetitious self-similarity onto the whole evolutionary cosmos. See also The Growth of the Density Fluctuations in the Scale-Invariant Vacuum Theory by AM and Vesselin Gueorguiev at 1811.03495.
Analytical solutions are obtained for the early cosmological phases in the scale invariant models with curvature k=0. The physical properties in the radiative era are derived from conservation laws and compared to those of current standard models. The critical runs of the temperature and of the expansion rate of the scale invariant models with low densities, are quite similar at the time of nucleosynthesis to those of standard models, leading to the same freezing number ratio of neutrons to protons. These results are consistent with the fact that the scale invariant models appear to not require the presence of dark matter. (Abstract)
Animate Cosmos > Fractal
Von Korff, Modest and Thomas Sander.
Molecular Complexity Calculated by Fractal Dimension.
Nature Scientific Reports.
Scientific Computing Drug Discovery, Idorsia Pharmaceuticals, Switzerland researchers achieve another novel recognition that nature’s proclivity to adopt and display a self-similar, iterative essence can be traced even to molecular and atomic forms and sub-structures.
Molecular complexity is an important characteristic of organic molecules for drug discovery. How to calculate molecular complexity has been discussed in the scientific literature for decades. It was known from early on that the numbers of substructures that can be cut out of a molecular graph are of importance. However, it was never realized that the cut-out substructures show self-similarity to the parent structures. Such a series shows self-similarity similar to fractal objects. The fractal dimension of a molecule is a new matter constant that incorporates all features that are currently known to be important for describing molecular complexity.(Abstract)
Animate Cosmos > Astrobiology
During our work on repetitive molecular features we realized that every molecular substructure displays self-similarity to its parent structure. Self-similarity means that an object is similar to a part of itself. Let us derive the concept of self-similarity for organic molecules at the example of n-hexane, a linear alkane. A linear alkane consists of a chain of carbon atoms saturated with hydrogen atoms. Removing one of the two outmost carbon-atoms and the connecting bond creates a new chain with one bond less. To the chain carbon-atom from where the bond was removed, a hydrogen atom has to be added for completing the saturation of the chain. (2)
Kolb, Vera, ed.
Handbook of Astrobiology.
Boca Raton: CRC Press,
The editor is a University of Wisconsin astrochemist and author for these fertile fields. This volume is an 850 page survey to date all about Earth and cosmic life definitions, multifaceted origins, early evolutions, biochemicals and microbes in space, planetary habitability, whence intelligence, exoEarth searches, ethical issues and educative methods. For example Mind in the Universe by David Duner, Where Are They by Nikos Prantzos, The Evolution of Habitability by Charles Lineweaver, et al, The Origin of Life by Iris Fry, Complex Organic Molecules in Space by Sun Kwok, and Communication as the Main Characteristic of Life by Guenther Witzany (search).
Animate Cosmos > exoearths
Gelino, Dawn and Jason Wright.
NASA and the Search for Technosignatures.
The 70 page main report from a September 2018 Workshop on how we Earthlings might look for and validly detect the presence of exo-civilizations with technical capacities. Some sections are Pulsed Radio, Continuous Wave Radio, Laser, Searches, also Limits of Megastructures, Waste Heat for Stars and Galaxies, and much more as our human to Anthropo sapience is just beginning to explore cosmic neighborhoods.
Bornholdt, Stefan and Stuart Kauffman.
Ensembles, Dynamics, and Cell Types: Revisiting the Statistical Mechanics Perspective on Cellular Regulation.
University of Bremen and Institute for Systems Biology, Seattle senior theorists look back 50 years to review Kauffman’s 1969 paper Metabolic Stability and Epigenesis in Randomly Constructed Genetic Nets (Journal of Theoretical Biology, 22/3, Abstract below). His 1993 work The Origins of Order played a major part in establishing the field of complex system studies. This posting continues its Self-Organization and Selection in Evolution subtitle by adding a statistical mechanics basis for biological regulation, along with selective effects. Into 2019 his prescient glimpses are well proven as we now know that gene regulatory networks do seek a self-organized criticality (search Bryan Daniels, Universality, Autocatalytic sections and elsewhere).
Genetic regulatory networks control ontogeny. For fifty years Boolean networks have served as models of such systems, ranging from ensembles of random Boolean networks as models for generic properties of gene regulation to working dynamical models of a growing number of sub-networks of real cells. At the same time, their statistical mechanics has been thoroughly studied. Here we recapitulate their original motivation in the context of current theoretical and empirical research. We discuss ensembles of random Boolean networks whose dynamical attractors model cell types. There is now strong evidence that genetic regulatory networks are dynamically critical, and that evolution is exploring the critical sub-ensemble. The generic properties of this sub-ensemble predict essential features of cell differentiation. Thus, the theory correctly predicts a power law relationship between the number of cell types and the DNA contents per cell, and a comparable slope. (2019 Abstract excerpt)
Proto-organisms probably were randomly aggregated nets of chemical reactions. The hypothesis that contemporary organisms are also randomly constructed molecular automata is examined by modeling the gene as a binary (on-off) device and studying the behavior of large, randomly constructed nets of these binary “genes”. The results suggest that, if each “gene” is directly affected by two or three other “genes”, then such random nets behave with great order and stability; undergo behavior cycles whose length predicts cell replication time as a function of the number of genes per cell; and under the stimulus of noise are capable of differentiating directly from any mode of behavior to at most a few other modes of behavior. The possibility of a general theory of metabolic behavior is suggested. (1969 SK Abstract excerpt)
Thurner, Stefan, et al.
Introduction to the Theory of Complex Systems.
Introduction to the Theory of Complex Systems,
Senior Medical University of Vienna system physicists Stefan Thurner, Peter Klimek and Rudolf Hamel provide a wide-ranging technical survey to date which covers scaling, networks, evolutionary processes, self-organized criticality, non-equilibrium statistical mechanics, information theory, and future advances, see next quote.
The chapter is a mini outlook on the field. The classic achievenments in complexity science are mentioned, and we summarize how the new directions might open new doors into a twenty-first-century science of complex systems. We do that by clarifying the origin of scaling laws, in particular for driven non-equilibrium systems, deriving the statistics of driven systems, categorizing probabilistic complex systems into universality classes, by meaningful generalizations of statistical mechanics and information theory, and finally, by unifying approaches to evolution and co-evolution into a single mathematical framework. We comment on our view of the role of artificial intelligence and our opinion on the future of science of complex systems. (Future of Complex Systems Science excerpt)
Cosmic Code > Algorithms
The Beauty of Mathematics in Computer Science.
Boca Raton: CRC Press,
This popular text in Chinese by a Google Brain USA member (bio below) is here published in English. It’s main message is to show the deep affinities between algorithmic code, scriptural languages and innate mathematic principles
The book covers many topics including Natural language processing, Speech recognition and machine translation, Statistical language modeling, Quantitive measurement of information, Pagerank for web search, Matrix operation and document classification, Mathematical background of big data, and Neural networks and Google’s deep learning.
Cosmic Code > networks
Jun Wu was a research scientist who invented Google’s Chinese, Japanese, and Korean Web Search Algorithms. He wrote official blogs introducing Google technologies in simple languages for Chinese Internet users from 2006-2010. Wu received PhD in computer science from Johns Hopkins University and has been working on natural language processing for more than 20 years.
Alves, Liuz, et al.
The Nested Structural Organization of the Worldwide Trade Multi-Layes Network.
Nature Scientific Reports.
As if a cerebral sapiensphere learning on her/his own, University of Sao Paulo, University of Catania, Italy, Imperial College London, Queen Mary University, London and University of Zaragosa, Spain systems theorists discern the active multiplex connectivities across the eastern and western continents and trader lands. As the quotes allude, once more nature’s independent, universally instantiated complex dynamics and geometries make an appearance.
Nestedness has traditionally been used to detect assembly patterns in meta-communities and networks of interacting species. Attempts have also been made to uncover nested structures in international trade as bipartite networks in which connections are between countries (exporters or importers) and industries. A bipartite representation of trade, however, neglects transactions between industries. To fully capture the organization of the global value chain, we draw on the World Input-Output Database and construct a multi-layer network in which the nodes are the countries, the layers are the industries, and links can be from sellers to buyers within and across industries. Drawing on null models that preserve the countries’ or layers’ distributions in the original multi-layer network, we uncover variations of country- and transaction-based nestedness over time. (Abstract)
Cosmic Code > networks
Our findings suggest that the nested structure of these matrices is similar to the one uncovered in ecological networks Finally, because multi-layer networks can be found across a variety of biological, technological and social systems, we discuss the implications that our proposed approach to measuring nestedness can have beyond trade, for a wide range of empirical domains. (2) Because a variety of empirical domains, from biological to technological and social ones, can be characterized as complex networks in which relationships have a multi-layer representation, our approach also has important implications beyond international trade, and can help gain a better understanding of their structural organization, stability, and growth mechanisms. (12)
Cinardi, Nicola, et al.
Quantum Statistics in Network Geometry with Fractional Flavor.
Systems physicists NC and Andrea Rapisarda, University of Catania, and Ginestra Bianconi, Queen Mary University of London continue to finely season nature’s true anatomy and physiology as it ever arrays in similar kinds from quantum to neuronal realms.
Growing network models have been shown to display emergent quantum statistics when nodes are associated to a fitness value describing the intrinsic ability of a node to acquire new links. Recently it has been shown that quantum statistics emerge also in a growing simplicial complex model called Network Geometry with Flavor which allow for the description of many-body interaction between the nodes. In this case the faces of the simplicial complex are naturally described by the Bose-Einstein, Boltzmann and Fermi-Dirac distribution depending on their dimension. We show that in this case the statistical properties of the faces of the simplicial complex are described by the Bose-Einstein or the Fermi-Dirac distribution only. (Abstract flavor)
Cosmic Code > networks
Harush, Uzi and Baruch Barzel.
Dynamic Patterns of Information Flow in Complex Networks.
We cite this entry by Bar-Ilan University, Israel mathematicians because after some 20 years of node/link multiplex network studies, the detection of common recurrences everywhere must imply “universal laws” in effect. The paper was cited by Paul Davies in The Demon in the Machine as proof that the generative “informative patterns” he and colleagues propose are indeed “coherent things with an independent existence.” (101)
Although networks are extensively used to visualize information flow in biological, social and technological systems, translating topology into dynamic flow continues to challenge us, as similar networks exhibit different flow patterns, driven by other interaction mechanisms. To uncover a network’s actual flow patterns, we use a perturbative formalism, tracking the contribution of all nodes/paths to the flow of information, exposing the rules that link structure and dynamic flow for a broad range of nonlinear systems. We find that the diversity of patterns can be mapped into a single universal function, characterizing the interplay between the system’s topology and its dynamics. (Abstract excerpt)
Cosmic Code > networks
Our results show that despite the diversity of potential interaction mechanisms, the patterns of information flow are governed by universal laws that can be directly linked to the system’s microscopic dynamics. (2) From neuronal signals to gene regulation, complex networks unction by enabling the flow of information between nodes. Understanding the rules that govern this flow is a crucial step toward establishing a theory of network dynamics. (10) In a broader perspective, our predicted universality indicates that the macroscopic flow patterns of complex systems are controlled by only a few relevant parameters of the system’s microscopic dynamics. (10)
Sreedharan, Jithin, et al.
Inferring Temporal Information from a Snapshot of a Dynamic Network.
Nature Scientific Reports.
Purdue University and University of Michigan (Abram Magner) computer researchers finesse nature’s pervasive webwork anatomy and physiology by showing that a small segment can serve in some way as an invariant capsule. The paper opens with the standard litany that the same such phenomena has been found in kind from cells to brains to economies (second quote). See also Network Archaeology by J. Young, et al at arXiv:1803.09191.
The problem of reverse-engineering the evolution of a dynamic network, known broadly as network archaeology, is of much importance in diverse applications. In an analysis of infection spread, it discerns the underlying spatial and temporal processes. For biomolecular interaction networks (e.g., protein interaction networks), it reveals early molecules that are implicated in diseases. In economic networks, it shows the flow of capital and associated actors. It can further help describe the structural and functional evolution of the human brain connectome. In this paper, we model, formulate, and analyze the arrival order of nodes in a dynamic network from a single snapshot. (Abstract)
Complex systems are comprised of interacting entities; e.g., cellular processes are comprised of interacting genes, proteins, and biomolecules; social systems, of individuals and organizations; and economic systems, of financial entities. These systems are modeled as networks, with nodes as entities and edges as their interactions. Typical systems continually evolve to optimize various criteria, including function (e.g., flow of information in social networks, evolution of brain connectomes to specialize function), structure (e.g., evolution of social network structures to minimize sociological stress while maximizing information flow), and survivability (e.g., redundant pathways in genic interactions as evidenced by synthetic lethality screens). (1)