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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

2. A Consilience as Physics, Biology and People Become One

Nastasiuk, Vadim. Emergent Quantum Mechanics of Finances. Physica A. Online February, 2014. On the shores of the Black Sea, a South Ukrainian National Pedagogical University, Odessa, researcher proposes ways that quantum phenomena might be in dynamic effect even for widely removed economic transactions. If a cross-correspondence can be drawn, it would then aid studies of market volatilities. In regard, might a wider palliative discovery at last accrue by which to realize a single, infinitely iterative, genesis, a natural guidance for peoples to move beyond the guns of 2014 and become planetary patriots?

This paper is an attempt at understanding the quantum-like dynamics of financial markets in terms of non-differentiable price–time continuum having fractal properties. The main steps of this development are the statistical scaling, the non-differentiability hypothesis, and the equations of motion entailed by this hypothesis. From perspective of the proposed theory the dynamics of S&P500 index are analyzed. (Abstract)

Nourmohammad, Armita, et al. Universality and Predictability in Molecular Quantitative Genetics. arXiv:1309.3312. Posted November 2013, Nourmohammad, and Torsten Held, Princeton University integrative geneticists, and Michael Lassig, University of Colonge biophysicist, convey the present merger of statistical, condensed matter physics with all aspects of life’s evolution, along with the popular trend to report and affirm a universal recurrence of the same phenomena across every domain and instance. The paper is forthcoming in Current Opinion in Genetics and Development. See also among Lassig’s prior papers “From Fitness Landscapes to Seascapes: Non-Equilibrium Dynamics of Selection and Adaptation” with Ville Mustonen in Trends in Genetics (25/3, 2009).


Molecular traits, such as gene expression levels or protein binding affinities, are increasingly accessible to quantitative measurement by modern high-throughput techniques. Such traits measure molecular functions and, from an evolutionary point of view, are important as targets of natural selection. We review recent developments in evolutionary theory and experiments that are expected to become building blocks of a quantitative genetics of molecular traits. We focus on universal evolutionary characteristics: these are largely independent of a trait's genetic basis, which is often at least partially unknown. We show that universal measurements can be used to infer selection on a quantitative trait, which determines its evolutionary mode of conservation or adaptation. Furthermore, universality is closely linked to predictability of trait evolution across lineages. We argue that universal trait statistics extends over a range of cellular scales and opens new avenues of quantitative evolutionary systems biology. (Abstract)

This article is on universality in molecular evolution. We introduce universality as an emerging statistical property of complex traits, which are encoded by multiple genomic loci. We give examples of experimentally observable universal trait characteristics, and we argue that universality is a key concept for a new quantitative genetics of molecular traits. Three aspects of this concept are discussed in detail. First, universal statistics governs evolutionary modes of conservation and adaptation for quantitative traits, which can be used to infer natural selection that determines these modes. Furthermore, there is a close link between universality and predictability of evolutionary processes. Finally, universality extends to the evolution of higher-level units such as metabolic and regulatory networks, which provides a link between quantitative genetics and systems biology. (1)

In a broad sense, universality means that properties of a large system can become independent of details of its constituent parts. This term has been coined in statistical physics, where it refers to macroscopic properties of large systems that are independent of details at the molecular scale. Universality also arises in evolutionary biology. As in physics, it is a property of systems with a large number of components, and it has strong consequences for experiment and data analysis. (1)

Again, the reason for universality is that changes in one pathway component tend to be buffered by compensatory changes in other components. These compensations can be statistical or systematic, that is, generated by feedback loops in the pathway organization. Universality and predictability of pathway output emerge primarily in complex, higher-level pathways, which have multiple compensatory channels. This suggests the hierarchy of molecular functions is reflected by an evolutionary hierarchy: universality and predictability increase, while stochasticity decreases with increasing level of complexity. (10)

Nurisso, Marco, et al. Higher-order Laplacian Renormalization. arXiv:2401.11298. Turin Polytechnic, Aix-Marseille University and Northeastern University London physicists have come up with a novel approach, as the quotes say, by which this primary theoretical explanation can be applied to better reveal multiplex network forms and functions, along with providing a physical origin.


We propose a cross-order Laplacian renormalization group (X-LRG) scheme for diverse higher-order networks. This formula is a pillar of the theory of scaling, scale-invariance, and universality in physics. An RG scheme based on diffusion dynamics was recently introduced for complex networks with dyadic interactions. Yet despite many polyadic links, we still lack a general RG model for multiplex systems. Our approach uses a diffusion process to group nodes or simplices, which allows us to probe higher-order structures. We apply to synthetic linkages and detect scale-invariant profiles of real-world examples. (Excerpt)

The renormalization group (RG) [1] is a cornerstone of modern theoretical physics because it allows us to study how a physical system depends on the scale of observation, defining universality classes and formalizing the concept of scale-invariance. While the RG has provided valuable insights, extending its framework to complex networks has posed a problem mainly due to the correlations between scales caused by small-world effects. (1)

Finally, our results provide a new lens to address questions on the origin of different high er-order invariant structures in various domains, and on their effects on dynamical processes taking place on them, as well as to the limits they might pose on the predictability and reconstruction of complex systems. (8)

Nussinov, Zohar, et al. Inference of Hidden Structures in Complex Physical Systems by Multi-Scale Clustering. arXiv:1503.01626. American and Indian physicists contend that condensed matter/statistical mechanic studies, which are lately coming to assume an intricately networked nature, have found a persistent tendency to form modular communities. Such whole units, with their own integrity while immersed in multiple layers, are a prime, natural feature. And if we might avail, a much better society could be conceived as many, interlinked communal villages in a local and global organic, physiological milieu.

We survey the application of a relatively new branch of statistical physics--"community detection"-- to data mining. In particular, we focus on the diagnosis of materials and automated image segmentation. Community detection describes the quest of partitioning a complex system involving many elements into optimally decoupled subsets or communities of such elements. We review a multiresolution variant which is used to ascertain structures at different spatial and temporal scales. Significant patterns are obtained by examining the correlations between different independent solvers. Similar to other combinatorial optimization problems in the NP complexity class, community detection exhibits several phases. (Abstract)

Pauls, James, et al. Quantum Coherence and Entanglement in the Avian Compass. Physical Review E. 87/062704, 2013. Reviewed more in Cooperative Societies, Purdue University and LANL physicists including Sabre Kais advance the reconception and unity of physics and life as they find deep similarities and explanations. The artificial quantum-classical barrier is being removed to reveal a creative reiteration in kind and time from universe to human.

Perunov, Nikolai, et al. Statistical Physics of Adaption. arXiv.1412.1875. As the Abstract notes, MIT Physics of Living Systems Group researchers including Jeremy England contribute to the ongoing synthesis of these fields of study which serve to integrate and root life’s evolution, and our collaborative comprehension, within a fertile cosmic ground.

All living things exhibit adaptations that enable them to survive and reproduce in the natural environment that they inhabit. From a biological standpoint, it has long been understood that adaptation comes from natural selection, whereby maladapted individuals do not pass their traits effectively to future generations. However, we may also consider the phenomenon of adaptation from the standpoint of physics, and ask whether it is possible to delineate what the difference is in terms of physical properties between something that is well-adapted to its surrounding environment, and something that is not. In this work, we undertake to address this question from a theoretical standpoint. Building on past fundamental results in far-from-equilibrium statistical mechanics, we demonstrate a generalization of the Helmholtz free energy for the finite-time stochastic evolution of driven Newtonian matter. By analyzing this expression term by term, we are able to argue for a general tendency in driven many-particle systems towards self-organization into states formed through exceptionally reliable absorption and dissipation of work energy from the surrounding environment. (Abstract)

Picoli, Sergio, et al. Universal Bursty Behavior in Human Violent Conflicts. Nature Scientific Reports. 4/4773, 2014. Universidade Estadual de Maringa, Brazil, and Universidad Nacional Autonoma de Mexico, systems physicists quantify that even the most chaotic carnage can yet be seen to exhibit a common structure and activity. However and whenever might we finally altogether come to realize and understand, as so implied, that an independent mathematical source is in formative effect everywhere? Then as so edified be able to at last to declare a truce and break free from this obsession?

Understanding the mechanisms and processes underlying the dynamics of collective violence is of considerable current interest. Recent studies indicated the presence of robust patterns characterizing the size and timing of violent events in human conflicts. Since the size and timing of violent events arises as the result of a dynamical process, we explore the possibility of unifying these observations. By analyzing available catalogs on violent events in Iraq (2003–2005), Afghanistan (2008–2010) and Northern Ireland (1969–2001), we show that the inter-event time distributions (calculated for a range of minimum sizes) obeys approximately a simple scaling law which holds for more than three orders of magnitude. This robust pattern suggests a hierarchical organization in size and time providing a unified picture of the dynamics of violent conflicts. (Abstract)

Despite the fact that human activities and natural phenomena are very different in nature, it has been suggested that both could be described by a common approach. For example, the occurrence of earthquakes has been related to the relaxation of accumulated stress after reaching a threshold as in self-organized criticality (SOC). Analogously, violent events in human conflicts could be associated with a threshold mechanism. In this scenario, a description of human conflicts in terms of SOC seems plausible. Our findings are consistent with this possibility, providing quantitative support for the analogy between patterns in human conflicts and natural phenomena exhibiting SOC. (3)

Popkin, Gabriel. The Physics of Life. Nature. 529/16, 2016. A report on the growing realization of inherent material propensities, via the new field of “active matter” research, to organize and arrange into similar biological forms and motions from proteins to people.

From flocking birds to swarming molecules, physicists are seeking to understand ‘active matter’ – and looking for a fundamental theory of the living world.

Prechl, Jozsef. Statistical thermodynamics of self-organization in the adaptive immune system. arXiv:2306.04665. A senior Eotvos Lorand University, Budapest researcher contributes to the ongoing integral rooting of viable, persistent organisms withi a conducive, substantial milieu which is then seen to spontaneously vivify into a processive animate development. A Table of cardinal features from physical self-organization to an adaptive immunity enlists a thermal energy, dynamic non-linearity, multiple interactions, and more.

A steady flow of energy can be seen to arrange matter and information in particular ways by a process known as self-organization. Adaptive immunity is an instance implemented as a complex adaptive biological system that vivifies and informs itself by the maintenance of a steady state which can be modeled mathematically and physically. Here I summarize arguments for such a statistical thermodynamic interpretation of immune function and key variables that characterize self-organization in the context of biochemical energies, and network structurations. (Abstract)

Provata, Astero, et al. DNA Viewed as an Out-of-Equilibrium Structure. Physical Review E. 89/052105, 2014. Reviewed more in Genome Complex Systems as a good example of an integral synthesis of life and law.

Pruessner, Gunnar. Complex Systems, Non-Equilibrium Dynamics and Self-Organization. Entropy. Online January, 2017. The Imperial College London mathematician invites papers for a Special mid 2017 Issue on this subject phenomena. We record because its description note Active Matter as an exemplary instance.

Over the last two decades or so, the notion of complex systems has found its way into many different areas of science and humanities, allowing for a quantitative understanding of phenomena that were traditionally studied in a more qualitative fashion. A particularly attractive aspect of complex systems is the emergence of co-operative phenomena, or self-organisation, often driven by non-equilibrium dynamics that relies on an external (energy) source. Such systems seem to be all around us, and govern and represent all that we do and are. Particular interest in self-organisation and non-equilibrium systems in the form of "active matter" has been generated within the biological sciences with the continued emphasis of more quantitative methods. Pattern or tissue formation may be a particularly good example of a phenomenon suitable for the present issue. Other good examples may be entropy production in sociological and financial systems or recent developments in self-organised criticality.

Ramaswamy, Sriram. The Mechanics and Statistics of Active Matter. Annual Review of Condensed Matter Physics. 1/323, 2010. The Centre for Condensed Matter Theory, Indian Institute of Science, Bangalore, biophysicist introduces the concept of “active matter” to represent novel appreciations, as the quotes say, of a natural materiality suffused by its own internal agency and dynamic motion. The phrase has gained currency in such 2013 writings by Cristina Marchetti, et al and Mark Buchanan (search each).

Active particles contain internal degrees of freedom with the ability to take in and dissipate energy and, in the process, execute systematic movement. Examples include all living organisms and their motile constituents such as molecular motors. This article reviews recent progress in applying the principles of nonequilibrium statistical mechanics and hydrodynamics to form a systematic theory of the behaviour of collections of active particles -- active matter -- with only minimal regard to microscopic details. A unified view of the many kinds of active matter is presented, encompassing not only living systems but inanimate analogues. (Abstract)

The viewpoint of this review is that living matter can fruitfully be regarded as a kind of material and studied using the tools of condensed matter physics and statistical mechanics; that there is a practical way to encode into such a description those features of the living state that are relevant to materials science; and that the results of such an endeavour will help us better understand, control and perhaps mimic active cellular matter. (325).

A comprehensive theory of this ubiquitous type of condensed matter is a natural imperative for the physicist, and should yield a catalogue of the generic behaviours, such as nonequilibrium phases and phase transitions, the nature of correlations and response, and characteristic instabilities. Second, therefore, the generic tendencies emerging from the theory of active matter, unless suppressed by specific mechanisms, must arise in vivo, which is why biologists should care about it. (325-326) The reader should keep in mind that theories of active matter were formulated not in response to a specific puzzle posed by experiments but rather to incorporate living, metabolizing, spontaneously moving matter into the condensed-matter fold. (326)

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