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Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 31 through 45 of 115 found.


Cosmomics: A Genomic Source Code in Procreative Effect

Cosmic Code

Sole, Ricard and Sergei Valverde. Evolving Complexity: How Tinkering Shapes Cells, Software and Ecological Networks. arXiv:1907.05528. Barcelona systems theorists (search) provide a 21st century retrospective survey of their studies and this revolutionary witness by a worldwide faculty of a cosmos to creature to cognition proto-evolution which is suffused by a common multiplex anatomy and physiology. In 2019 this phenomenal animate reality is set within a scenario that implies a dynamic interplay of endemic self-organizing principles and constraints, along with many candidates subject to chancy selective forces. The main gist draws upon Francois Jacob’s 1977 Evolution and Tinkering paper (French Nobel geneticist, see Science 196/1161) to emphasize how nature seems to constantly repurpose organelle components as life strives to develop and emerge. Some four decades later, by way of novel network connectivities a balanced synthesis of non-random rules and working adaptations can be broached.

A prime trait of complex systems is that they can be represented as a network of interacting parts. These organizational propensities are the main source of higher-level properties, which are not reducible to the individual parts. Can the topological features of these webs provide insight into their evolutionary origins? Both biological and artificial networks are heterogeneous and sparse, and exhibit small-world modular or hierarchical patterns. Against the standard selection-optimization argument, some networks reveal the inevitable generation of complex patterns resulting from reuse which can be modelled using duplication-rewiring rules. These give rise to scale-free and modular architectures observed in the real case studies.

Tinkering is a universal mechanism that drives not only biological evolution but also the large-scale dynamics of some technological designs. Here we examine the evidence for tinkering in cellular, technological and ecological webs and its impact in shaping their architecture and deeply affecting their functional properties. Our analysis suggests to seriously reconsider the role played by selection forces or design principles as main drivers of network evolution. (Abstract)

The fabric of complexity is made of networks. The presence of collective-level, system properties necessarily requires a description grounded in a map of connections between individual parts. Such view has been around much longer than is usually acknowledged within the field of Network Science. Long before small worlds and scale-free structures were identified, the importance of interactions and their embodiment within graphs was already in place in ecology and neuroscience. Classic studies on trophic webs and their stability had an enormous impact on our understanding of communities. Similarly, since (Santiago) Ramon y Cajal the realization that cognition was associated to complex webs
has been percolating through the entire field. (1)

It has been suggested (Sole et al., 2003) that inspecting the organisation of complex networks can reveal the evolutionary design or evolutionary principles that shaped them. In a nutshell, identifying the generative rules responsible for their topology could be used to find their origins and the contributions of randomness, architectural constraints or self-organisation. In other words, the paths followed by each system can be deeply limited by fundamental principles of mathematical nature. In this paper, we will review the evidence for this idea and its deep implications for our understanding of network complexity. This includes the presence of mechanisms of network growth that are dominated by extensive reuse of extant components. Such a ”tinkering” process was early suggested by the French biologist Francois Jacob and has enormous importance in evolution. (3)

The findings described above strongly support the idea that the proteome map contains a considerable amount of statistical correlations that are a byproduct of the duplication-rewiring set of rules. The presence of modularity or non-random distributions of motifs cannot be taken (alone) as a signature of selection. This finding, as shown below, is far from accidental. (5)

Cosmic Code > Algorithms

Aerts, Diederik, et al. Quantum Entanglement in Physical and Cognitive Systems. arXiv:1903.09103. A seven person team based at Brussels Free University with other postings in Switzerland, the UK and Chile enter their latest work-in-progress toward a theoretical and conceptual, quantum and classical, physical and biological, cosmic integrative whole. Into mid 2019, per the second quote, as new understandings join quantum and human phenomena, we can begin to glimpse a universal Copernican revolution. Physics and people are at last reunited, which in turn implies a lively, literate ecosmos. On this eprint site, over a hundred papers by D. Aerts, this group, and many colleagues can be accessed going back to 2008. An example is The Emergence and Evolution of Integrated Worldviews by DA with Liane Gabora at 1001.1399. Another current posting is Quantum-Theoretic Modeling in Computer Science at 1901.04299 and Quantum Entanglement in Corpuses of Documents 1810.12114.

We provide a general description of the phenomenon of entanglement in bipartite systems, as it manifests in micro and macro physical systems, as well as in human cognitive processes. We do so by observing that when genuine coincidence measurements are considered, the violation of the 'marginal laws', in addition to the Bell-CHSH inequality, is also to be expected. The situation can be described in the quantum formalism by considering the presence of entanglement not only at the level of the states, but also at the level of the measurements. (Abstract excerpt)

But nowadays the predictions of quantum theory are no longer put into question, not only as regards entanglement, which has been shown to be preservable over distances of a thousand kilometers, but also with respect to many other effects such the delocalization of large organic molecules. On the other hand, the debate about the profound meaning of the theory never stopped, and in fact has constantly renewed and expanded over the years, so much so that one can envisage this will produce in the end a Copernican-like revolution in the way we understand the nature of our physical reality. Such a debate, however, is not confined to physicists or philosophers of science, but also reached new fields of investigation, in particular that of psychology, due to the development of that research domain called ‘quantum cognition.’ (2)

Quantum entanglement is a physical phenomenon that occurs when pairs or groups of particles are generated, interact, or share spatial proximity in ways such that the quantum state of each particle cannot be described independently of the state of the others, even when the particles are separated by a large distance.

In physics, the CHSH inequality can be used in the proof of Bell's theorem, which states that certain consequences of entanglement in quantum mechanics cannot be reproduced by local hidden variable theories. Experimental verification of violation of the inequalities is seen as experimental confirmation that nature cannot be described by local hidden variables theories. CHSH stands for John Clauser, Michael Horne, Abner Shimony, and Richard Holt, who described it in 1969.

Cosmic Code > Algorithms

Beltran, Lester and Suzette Geriente. Quantum Entanglement in Corpuses of Documents. arXiv:1810.12114. Brussels Free University, Interdisciplinary Studies Group researchers led by Diederik Aerts explore how recent clarifications and integrative expansions of quantum theory can reveal how such deep phenomena is actively present even in human literary writings. As if a library of cosmos (taking license), in addition to fractal network complexities, our textual linguistic corpora is found to possess a physical affinity and generative source. And we note, by turns, this extant cosmos becomes graced by a natural narrative (more license). See also Quantum-Theoretic Modeling in Computer Science by these authors and group at 1901.04299 for a later finesse. A parallel effort goes on in Bob Coecke’s Oxford University group, such as The Mathematics of Text Structure at 1904.03478.

Cosmic Code > Algorithms

Fernandez, Jose and Francisco Vico. AI Methods in Algorithmic Composition. Journal of Artificial Intelligence Research. Volume 48, 2013. This entry by University of Malaga, Spain computer scientists is cited in A. Wagner’s Life Finds a Way (2019) to show how evolution seems guided by source programs which can be modeled by artificial neural networks. By such perceptions, the natural presence of iterative cellular automata and self-similar patterns can be noticed. Its mathematical form and flow also appear as a musical or written composition. In regard, are we coming upon an proactive ecosmos which is composing itself by way of sapient species as our global own? Please visit F. Vico’s website to read about his “Melomics” or genetics of melody project.

Algorithmic composition is the partial or total automation of the process of music composition by using computers. Since the 1950s, different computational techniques related to Artificial Intelligence have been used for algorithmic composition, including grammatical representations, probabilistic methods, neural networks, symbolic rule-based systems, constraint programming and evolutionary algorithms. This survey aims to be a comprehensive account of research on algorithmic composition, presenting a thorough view of the field for researchers in Artificial Intelligence. (Abstract)

The purpose of this survey is to review and bring together existing research on a specific style of Computational Creativity: algorithmic composition. Interpreted literally, algorithmic composition is a self-explanatory term: the use of algorithms to compose music. (1)

Cosmic Code > Algorithms

Sloss, Andrew and Steven Gustafson. 2019 Evolutionary Algorithm Review. arXiv:1906.08870. Bellevue, WA software scientists post a thorough survey as the field of artificial intelligence, broadly conceived, becomes ever more biological in its basis. By turns, life’s genetically programmed development is broached as an “Idealized Darwinism.” Section 5.1 is an Auto-Constructive Evolution, while 5.2 is Deep Neuroevolution and 5.3 Self-Replicating Neural Networks.

In this review, we explore a new taxonomy of evolutionary algorithms and classifications that look at five main areas: the ability to manage the control of the environment with limiters, how to explain and repeat the search process, understandings of input and output causality within a solution, the ability to manage algorithm bias due to data or user design, and lastly, and how to add corrective measures. As many reviews of evolutionary algorithms exist, after motivating this new taxonomy, we briefly classify a broad range of algorithms and identify areas of future research. (Abstract excerpt)

Cosmic Code > Algorithms

Wolpert, David, et al, eds. The Energetics of Computing in Life and Machines. Santa Fe: Santa Fe Institute Press, 2018. These highly technical proceedings from SFI seminars consider more efficient computational methods by way a better, deeper integration with vital principles and procedures. For example see Overview of Information Theory and Stochastic Thermodynamics of Computation by Wolpert (search), Information Processing in Chemical Systems by Peter Stadler, et al, and Automatically Reducing Energy consumption of software by Stephanie Forrest, et al.

Why do computers use so much energy? What are the fundamental physical laws governing the relationship between the precise computation run by a system, whether artificial or natural, and how much energy that computation requires? Can we learn how to improve efficiency in computing by examining how biological computers manage to be so efficient? The time is ripe for a new synthesis of systems physics, computer science, and biochemistry. This volume integrates pure and applied concepts from these diverse fields, with the goal of cultivating a modern, nonequilibrium thermodynamics of computation.

Cosmic Code > 2015 universal

Nagata, Shintaro and Macoto Kikuchi. Emergence of Cooperative Bistability and Robustness of Gene Regulatory Networks. . An Osaka University biochemist and a biophysicist report that the common bistability state (Wikipedia) of dynamical systems can likewise be recognized in this genomic mode, whence GRNs reside in two coordinated, genes on and off, positions at once. See also a slide presentation Simultaneous emergence of Cooperative Response and Mutational Robustness in Gene Regulatory Networks by the authors at www.cp.cmc.osaka-u.ac.jp/~kikuchi/presentation/CCS2018.

Gene regulatory networks (GRNs) are complex systems in which many genes mutually regulate their expressions for changing the cell state adaptively to environmental conditions. The GRNs utilized by living systems possess several kinds of robustness which here means that they do not lose their functions when exposed to mutation or noises. In this study, we explore the fitness landscape of GRNs and investigate how the robust feature emerges in the "well-fitted" GRNs. Thus the more sensitively a GRN responds to the input, the fitter it is. To do this, they exhibit bistability, which necessarily emerges as the fitness becomes high. These properties are universal irrespective of the evolutionary pathway, because we did not perform evolutionary simulations. (Abstract excerpt)

The emergence of the new fixed points can be considered as an innovation or a big evolutionary jump. Then, what can we infer about the evolution based on them? The cooperative bistability and the robustness against noises are the consequence of the high fitness. Thus, we can say that this evolutional jump occurs inevitably as the fitness increases irrespective of the evolutionary pathway. We may identify this as the universality of evolution. (9)

Cosmic Code > 2015 universal

Norman, Andreas and Lukasz Rudnicki. Quantum Correlations and Complementarity of Vectorial Light Fields. arXiv:1904.07533. We review this entry by MPI Science of Light researchers much more in Quantum Organics, especially for its introduction of a “triality” concept to join and unite complements.

Cosmic Code > 2015 universal

Peruzzo, Fabio, et al. Spatial Patterns Emerging from a Stochastic Process near Criticality. arXiv:1907.08852. Into the year 2019, University of Leeds mathematicians including Sandro Azaele (search), draw upon a wealth of 21st century science so as to assert that living systems across every natural and social phase can be seen to seek and reach a preferred state of critical balance. As many other entries prove, this finding bodes well for a discovery of the universal complex recurrence of a dynamic complementarity. This constant phenomena arises from “nonlinearities of interacting agents,” that is nodal, particulate entities and relational, wave-like links, which are rooted in the physical cosmos, as it come to life again.

There is mounting empirical evidence that many communities of living organisms display key features which closely resemble those of physical systems at criticality. We here introduce a model framework for the dynamics of a community of individuals which undergoes local birth-death, immigration and local jumps on a regular lattice. We study these properties when the system is close to its critical point. Within a physically relevant regime dominated by fluctuations, it is possible to calculate analytically the probability density function of the number of individuals living in a given volume, which captures the close-to-critical behavior of the community across spatial scales. We discuss how this model in the critical-like regime is in agreement with several biodiversity patterns observed in tropical rain forests. (Abstract)

Cosmic Code > 2015 universal

Wolchover, Natalie. The Universal Law that Aims Time’s Arrow. Quanta. August 1, 2019. A new look at a ubiquitous phenomenon has uncovered unexpected fractal behavior that could give us clues about the early universe and the arrow of time. The science journalist reports on a confluence of findings which seem to quantify and affirm an intrinsic cosmic self-similarity. By way of a natural philosophia view, if of a mind to perceive, a worldwide human quest may at last be closing on a phenomenal discovery. As long intimated, an infinite recurrence of the same pattern and process in kind really does exist and emerge on its own. As a nascent sapiensphere can prove and realize this, organic nature’s genome-like source code can reach, as planned, our intentional, procreative furtherance.

Notable papers are Prescaling and Far from Equilibrium Hydrodynamics in the Quark-Gluon Plasma by Alekson Mazeliauskas and Jurgen Berges in Physical Review Letters (122/122301, 2019), Universal Dynamics Far from Equilibrium by C. M. Schmied, et al at arXiv:1810.08143, Observation of Universal Dynamics in a Spinor Gas by Max Prufer, et al in Nature (563/217, 2018) and Prescaling in a Far from Equilibrium Bose Gas by C. M. Schmied, et al in Physical Review Letters (122/170404, 2019). See also Bubble Experiment finds Universal Laws by Charlie Wood in Quanta for July 31, 2019.

In the new work, researchers see far-from-equilibrium systems undergoing fractal-like universal scaling across both time and space. Take the birth of the universe. After cosmic inflation, the hypothetical oscillating, space-filling condensate would have quickly transformed into a dense field of quantum particles all moving with the same characteristic speed. (Jurgen) Berges and his colleagues conjecture that these non-equilibrium particles then exhibited fractal scaling governed by universal scaling exponents as they began the thermal evolution of the universe.

Cosmic Code > networks

Moreno, Yamir and Matjaz Perc, eds. Focus on Multileyer Networks. New Journal of Physics. Circa 2018,, 2019. University of Zaragoza, Spain and University of Maribor, Slovenia physicists open a special collection with this title, as the quote notes. We note, for example, Inter-Layer Competition in Adaptive Multiplex Network by Elena Pitsik (20/075004) and Communicability Geometry of Multiplexes by Ernesto Estrada (21/015004, 2019).

In the later past century and early 2000's, the availability of data about real-world systems made it possible to study the topology of large networks. This work has revealed the structure, dynamics and functions of complex networks, as well as new models for synthetic networks. During the last 5 years, also backed up by new results, scientists have realized that many systems and processes cannot be described with single-layer nets since they have a multilayer geometry made up of many layers. The study of these multiplex networks has pointed out that their structure, dynamics, and evolution exhibit non-trivial relationships and interdependencies that give rise to new phenomena. (Scope)

Cosmic Code > networks

Radicchi, Filippo, et al. Classical Information Theory of Networks. arXiv:1908.03811. FR, Indiana University, with Dmitri Krioukov and Harrison Hartle, Northeastern University, and Ginestra Bianconi, Queen Mary University of London finesse a better synthesis of implicit network communicative content with nature’s ubiquitous multiplex geometries. The broad motive is a better way to recognize evident commonalities as they vitalize and inform both genomic and neuromic phases.

Heterogeneity is an important feature which characterizes real-world networks. The diverse concept provides a convenient way to analyze and enhance systemic features such as robustness, synchronization and navigability. However, a unifying information theory to explain the natural emergence of heterogeneity in complex networks does not yet exist. Here, we develop a theoretical framework by showing that among degree distributions that can generate random networks, the one emerging from the principle of maximum entropy exhibits a power law. The pertinent features of real-world air transportation networks are well described by the proposed framework. (Abstract excerpt)

The principle of maximum entropy states that the unique probability distribution, encoding all the information available about a system but not any other information, is the one with largest information entropy. Available information about the system corresponds to constraints under which entropy is maximized. The principle of maximum entropy has found applications in many different disciplines, including physics, computer science, geography, finance, molecular biology, neuroscience, learning, deep learning, etc. (1)

Cosmic Code > networks

Rakshit, Sarbendu, et al. Transitions from Chimeras to Coherence: An Analytical Approach by Means of the Coherent Stability Function. arXiv:1908.01063. Indian Statistical Institute, Kolkata, Amirkabir University of Technology, Tehran and University of Maribor, Slovenia (Matjaz Perc) further quantify the dynamic cerebral presence of such dual, simultaneous, more or less orderly phases. Circa 2019, the paper is a good instance of the global collaborative breadth and depth of scientific endeavors.

The study of transitions from chimeras to coherent states remains a challenge. Here we derive the necessary conditions for this shift by a coherent stability function approach. In chimera states, there is typically at least one group of oscillators that evolves in a drifting, random manner, while other groups of oscillators follow a smoother, more coherent profile. We use leech neurons, which exhibit a coexistence of chaotic and periodic tonic spiking depending on initial conditions, coupled via non-local electrical synapses, to demonstrate our approach. We explore various dynamical states with the focus on the transitions between chimeras and coherence, fully confirming the validity of the coherent stability function. (Abstract)

Cosmic Code > networks

Suvakov, Milovan, et al. Hidden Geometries in Networks Arising from Cooperative Self-Assembly. Nature Scientific Reports. 8/1987, 2018. In these later 2010s of daily global scientific discourse, Jozef Stefan Institute, Slovenia physicists including Bosiljka Tadic (search) delve deeper into nature’s phenomenal, generative topologies so as to find further dimensions. We seek to report this frontier work, along with companion studies, as growing evidence of an independent, mathematical source code in creative, exemplary effect everywhere. As a result, relatively inorganic and living systems are found to organize or assemble themselves into similarly quickening scales and activities. By these perceptions, a universal reciprocity via a particulate nodal component and a relational connectivity mode or phase, which altogether carry vital information and form a triune whole, can be identified. See also Functional Geometry of Human Connectomes in this journal (9/12060, 2019), and Simplicial Complexes and Complex Systems by Vsevolod Salnikov, et al in the European Journal of Physics (40/014001, 2018).

Multilevel self-assembly involving small structured groups of nano-particles provides new routes to novel functional materials with a sophisticated architecture. In addition to inter-particle forces, the geometrical shapes are decisive factors. A comprehensive understanding of these processes is thus vital for the design of assemblies of desired properties. Here, we introduce a computational model for cooperative self-assembly with the attachment of structured groups of particles described by simplexes (connected pairs, triangles, tetrahedrons and higher order cliques) within a growing network. Our results show that higher Q-connectedness of the appearing simplicial complexes can arise due to geometric factors alone and that it can be efficiently modulated by changing the chemical potential and the polydispersity of the binding simplexes. (Abstract excerpt)

Cosmic Code > networks

Wang, Wei, et al. Coevolution Spreading in Complex Networks. arXiv: 1901.02125. In a 115 page paper with 334 references, informatics researchers based at the University of Electronic and Technology of China apply the latest complexity theories to further quantify this vital phase of composite social behavior, disease, health, and other aspects. The paper now appears in Physics Reports. (Online July 29, 2019).

The propagations of diseases, behaviors and information in real systems are rarely independent of each other, for they coevolve with strong interactions. The study of dynamic spatiotemporal patterns and critical phenomena of networked coevolution spreading can provide theoretical foundations to control epidemics, predict collective behaviors in social systems, and so on. In this review, we draw upon the perspectives of statistical mechanics and network science such as critical phenomena, phase transitions, interacting mechanisms, and network topology for four representative types of biological contagions, social contagions, epidemic–awareness, and epidemic–resources. (Abstract excerpt)

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