(logo) Natural Genesis (logo text)
A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
Table of Contents
Introduction
Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
Glossary
Recent Additions
Search
Submit

III. An Organic Habitable Zone UniVerse

1. A Consilience of Biology and Physics: Active Matter

This section was added in 2013 to cover a growing flow of research papers across these sciences that are finding an integral affinity between them. By our worldwise compass, quantum, condensed matter, many-body, statistical mechanics, and other fields are becoming perceived to have quite lively inferences. At the same while, organic evolutionary systems via anatomic forms, physiologic metabolism, neural architecture and cognizance, dynamic ecosystems and human societies are found to exhibit physical principles. In origin of life studies and elsewhere, as an organic nature spreads ever deeper roots, so does material substance gain an endemic conducive fertility. For example, systems biophysicist Nigel Goldenfeld (search) has advised that biology will become physics in the 21st century and biology is the new condensed matter physics.

An aspect within this overdue reunion is known by an Active Matter phrase. It was first used by the Indian physicist Sriram Ramaswamy in 2010 to designate a novel form of self-propelled material motion. As the quote notes, the endeavor has since engaged many self-assembled and mobile phases. A “Soft Matter” version studies all manner structural properties of pliable biomolecular and cellular forms. A common implication seems to be an innate mathematical source that serves to structure and guide the gravid spontaneity of a procreative evolution and history.

Active matter is composed of large numbers of active "agents", each of which consumes energy in order to move or to exert forces. Such systems are intrinsically out of thermal equilibrium. Active matter systems break time reversal symmetry because energy is being continually dissipated by the individual constituents. Most examples of active matter are biological in origin and span the scales from bacteria and self-organising bio-polymers to schools of fish and flocks of birds. (Wikipedia)

2020:

Azaele, Sandro, et al. Statistical Mechanics of Ecological Systems. arXiv:1506.01721.

Bialek, William. Perspectives on Theory at the Interface of Physics and Biology. arXiv:1512.08954.

Cartwright, Julyan, et al. DNA as Information: At the Crossroads between Biology, Mathematics, Physics and Chemistry. Philosophical Transactions of the Royal Society A. Vol.374/Iss.2063, 2016.

Cavagna, Andrea and Irene Giardina. Bird Flocks as Condensed Matter Systems. Annual Review of Condensed Matter Physics. Volume 5, 2014.

Crosato, Emanuele, at al. Thermodynamics of Emergent Structure in Active Matter. arXiv:1812.08527.

Fodor, Etienne and Cristina Marchetti. The Statistical Physics of Active Matter. arXiv:1708.08652.

Goldenfeld, Nigel and Carl Woese. Life is Physics: Evolution as a Collective Phenomenon Far from Equilibrium. Annual Review of Condensed Matter Physics. Volume 2, 2011.

Gompper, Gerhard, et al. The 2019 Motile Active Matter Roadmap. Journal of Physics: Condensed Matter. 32/29, 2020.

Katsnelson, Mikhail, et al. Towards Physical Principles of Biological Evolution. Physica Scripta. 93/4, 2018.

Lee, Chiu Fan and Jean David Wurtz. Novel Physics Arising From Phase Transitions in Biology. Journal of Physics D. 52/2, 2019.

McFadden, Johnjoe and Jim Al-Khalili. The Origins of Quantum Biology. Proceedings of the Royal Society A. Vol.474/Iss.2220, 2018.

Ramaswamy, Sriram. The Mechanics and Statistics of Active Matter. Annual Review of Condensed Matter Physics. 1/323, 2010.

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.

International Centre for Theoretical Physics: Quantitative Life Sciences. www.ictp.it/research/qls.aspx. A 2017 website for this research area at the global institute in Trieste founded by the Nobel laureate physicist Abdus Salam which has become a vital home for many third-world students. On the ICTP main site, other programs such as Statistical Physics, Earth System Physics, and Sustainable Energy can be viewed.

Quantitative Life Sciences: In the last decade, the progressive integration of a wide range of different disciplines - including physics, statistics, information theory, biochemistry, genetics and medicine, population genetics and game theory - and increased availability of quantitative data has led to major advances in most diverse domains of life sciences, from molecular and cell biology to terrestrial and oceanic ecology, economics and quantitative finance. The integration process between disciplines has led to the consolidation of a new research domain, which we describe as ‘quantitative life sciences’ to provide a sense of its breadth.

Agliari, Elena, et al. Collective Behaviours: From Biochemical Kinetics to Electronic Circuits. Nature Scientific Reports. 3/3458, 2013. University of Parma, and Sapienza University of Rome, physicists join the increasing witness of a wholly repetitive reality across every stratified realm. As the second quote notes, a good part of the work going forward is to translate terminologies from the various approaches and schools into an agreed, accessible description upon the same elephantine creation. For example, it is interesting to see a “cooperativity” being attributed even to chemical domains. And “cybernetics” is just another take on this naturally active materiality. See also posted herein on this same December 10th “Simple Mathematical Law Benchmarks Human Confrontations” whence it would be great to learn the programs that drive day and night, so we might behave better.

In this work we aim to highlight a close analogy between cooperative behaviors in chemical kinetics and cybernetics; this is realized by using a common language for their description, that is mean-field statistical mechanics. First, we perform a one-to-one mapping between paradigmatic behaviors in chemical kinetics (i.e., non-cooperative, cooperative, ultra-sensitive, anti-cooperative) and in mean-field statistical mechanics (i.e., paramagnetic, high and low temperature ferromagnetic, anti-ferromagnetic). Interestingly, the statistical mechanics approach allows a unified, broad theory for all scenarios. (Abstract)

In this work, we describe collective behaviors in chemical kinetics through mean-field statistical mechanics. Stimulated by the successes of the latter in formalizing classical cybernetic subjects, as neural networks in artificial intelligence or NP-completeness problems in logic, we successfully tested the statistical mechanics framework as a common language to read from a cybernetic perspective chemical kinetic reactions, whose complex features are at the very basis of several biological devices. (9)

Agrawal, Adyant and Sujin Babu. Self-organization in a Bimotility Mixture of Model Microswimmers. Physical Review E. 97/020401, 2018. Within the new APS Physics Subject Headings directory (Google), the Research Areas are collective behavior and self-organized systems, Physical Systems are Active Matter and Multi-Organism Systems, and Techniques is Theories of collective dynamics & active matter, an example of how physical science has lately come to life. Specifically Indian Institute of Technology, New Delhi physicists find such nonlinear, cooperative phenomena to innately manifest itself within mobile microbial populations.

Agrawal, Ankit, et al. Chromatin as Active Matter. Journal of Statistical Mechanics. 014001, 2017. Indian biophysicists pursue a better understanding of genetic phenomena by way of perceiving it as a phase of natural self-activity.

Alexandrov, Dmitri and Andrey Zubarev. Patterns in Soft and Biological Matters. Philosophical Transactions of the Royal Society A. April, 2020. Ural Federal University, Russia bioresearchers introduce a special edition with this title. Papers such as Stochastic Phenomena in Pattern Formation for Distributed Nonlinear Systems, On the Theory of Magnetic Hyperthermia, and Constructive Role of Noise and Diffusion in an Excitable Slow-Fast Population System describe many ways that material substance can come alive, and while showing how living systems arise from physical principles. In each case the manifest presence of an immaterial mathematical realm is evident.

This issue is devoted to theoretical, computer and experimental studies of internal heterogeneous patterns, their morphology and evolution in various soft physical, organic and inorganic materials. Their importance is due to the significant role of internal structures on the macroscopic properties and behaviour of natural and manufactured tissues and materials. Modern methods of computer modelling, statistical physics, heat and mass transfer, statistical hydrodynamics, nonlinear dynamics and experimental methods are presented. Special attention is paid to biological systems such as drug transport, hydrodynamic patterns in blood, protein, insulin crystals and more. (Abstract excerpt)

Asano, Masanari, et al. Towards Modeling of Epigenetic Evolution with the Aid of Theory of Open Quantum Systems. AIP Conference Proceedings. 1508, December, 2013. A paper from a Quantum Theory: Reconsiderations of Foundations 6 meeting held in Vaxjo, Sweden, 2012. In a Quantum-Like Decision Making: From Biology to Behavioral Economics session, six information, mathematical, and biological specialists from Tokyo University of Science and Linnaeus University, Vaxjo, offer another example of the nascent confluence of foundational physics with life’s innate genetic, organismic development and vitality.

We apply theory of open quantum systems to modeling of epigenetic evolution. This is an attempt to unify Darwinian and Lamarckian viewpoints on evolution on the basis of a quantum-like model. The state of uncertainty of cell's epigenome is resolved to a stable and inherited epigenetic configuration. This process of evolution and stabilization is described by the quantum master equation (the Gorini-Kossakowski-Sudarshan-Lindblad equation). The initial state of epigenome starting interaction with a new environment is represented as a pure quantum state. It evolves to a steady state solution of the quantum master equation given by a diagonal density matrix. The latter represents the state resulting from a series of epimutations induced by the environment. (Abstract)

Recently Lamarckism was strongly supported by studies of epigenetic mutations and their inheritance. Instead of the (neo-)Darwinian natural selection model by which mutations in genome occur randomly and then the environment selects the “best organisms” (or cells populations), by the (neo)-Lamarckian model changes in the structure of the epigenome are directly “driven” by the environment and this environmental design is enherited already by the next generation. One of the main distinguishing features of (neo)Lamarckian evolution is that changes are generated and inherited very quickly. Instead of a long series of generations with random mutations in genes and the corresponding natural selection, experimenters observe direct “translation” of the environmental pressure to the structure of cells’ epigenomes: epimutations are “selected” very quickly. (75)

Attanasi, Alessandro, et al. Information Transfer and Behavioral Inertia in Starling Flocks. Nature Physics. Online August, 2014. A team of University of Rome, Sapienza, and Universidad Nacional de La Plata, Argentina, researchers including Andrea Cavagna and Irene Giardina, achieve a most sophisticated analysis of these startling formations. A prime factor is the relative rate of information transfer – the faster it is, the more coherent the group. Its significance was noted in a July 27 Science news item How Bird Flocks are Like Liquid Helium by Marcus Woo because the paper goes on to compare the phenomena with liquid helium dynamics.

The new model also predicts that information travels faster if the flock is well aligned—something else the team observed, Cavagna says. Other models don’t predict or explain that relationship. "This could be the evolutionary drive to have an ordered flock," he says, because the birds would be able to maneuver more rapidly and elude potential predators, among other things. Interestingly, Cavagna adds, the new model is mathematically identical to the equations that describe superfluid helium. When helium is cooled close to absolute zero, it becomes a liquid with no viscosity at all, as dictated by the laws of quantum physics. Every atom in the superfluid is in the same quantum state, exhibiting a cohesion that's mathematically similar to a starling flock. The similarities are an example of how deep principles in physics and math apply to many physical systems, Cavagna says.(Woo, Science)

Attanasi, Alessandro, et al. Superfluid Transport of Information in Turning Flocks of Starlings. arXiv:1303.7097. As the Abstract describes, an eleven member team from Italy and Argentina, including Andrea Cavagna and Irene Giardina, by way of sophisticated video instrumentation and mathematical analysis, are able to quantify such a consistent formation of dynamic group patterns. The great leap is then to realize it is akin to phenomena found in superfluid flows of super cold (4 degrees Kelvin) liquid helium. Once again, to observe, across widely disparate realms a genomic nature draws upon and repeats the same patterns and processes. As physics and biology interweave and become one (as Nigel Goldenfeld predicts), as this knowledge passes to our humanity, what wondrous discovery might await?

Collective decision-making in biological systems requires all individuals in the group to go through a behavioural change of state. During this transition, the efficiency of information transport is a key factor to prevent cohesion loss and preserve robustness. We propose a novel theory whose cornerstone is the existence of a conserved spin current generated by the gauge symmetry of the system. The theory turns out to be mathematically identical to that of superfluid transport in liquid helium and it explains the dissipationless propagating mode observed in turning flocks. Superfluidity also provides a quantitative expression for the speed of propagation of the information, according to which transport must be swifter the stronger the group's orientational order. We argue that the link between strong order and efficient decision-making required by superfluidity may be the adaptive drive for the high degree of behavioural polarization observed in many living groups. The mathematical equivalence between superfluid liquids and turning flocks is a compelling demonstration of the far-reaching consequences of symmetry and conservation laws across different natural systems. (Abstract)

Azaele, Sandro, et al. Statistical Mechanics of Ecological Systems. arXiv:1506.01721. Akin to Ehud Meron’s Nonlinear Physics of Ecosystems, (2015), six mathematicians with postings in the UK, USA, and Italy, including Jayanth Banavar and Amos Maritan, contribute to this growing scientific integration across living nature’s widest expanse. See Reviews of Modern Physics (88/035003, 2016) for its journal publication.

Just as statistical mechanics provides a framework to relate the microscopic properties of individual atoms and molecules to the macroscopic or bulk properties of materials, ecology needs a theory to relate key biological properties at the individual scale, with macro-ecological properties at the community scale. Nevertheless, this step is more than a mere generalization of the standard statistical mechanics approach. Indeed, in contrast to inanimate matter, for which particles have a given identity with known interactions that are always at play, in ecosystems we deal with entities that evolve, mutate and change, and that can turn on or off as well as tune their interactions with partners. Thus the problem at the core of the statistical physics of ecological systems is to identify the key elements one needs to incorporate in models in order to reproduce the known emergent patterns and eventually discover new ones. (1)

Baluska, Frantisek and Guenther Witzany. At the Dawn of a New Revolution in Life Sciences. World Journal of Biological Chemistry. 4/2, 2013. In this online posting, a botanist and a philosopher comment on Nobel laureate biologist Sydney Brenner’s article “The Revolution in the Life Sciences” in Science (338/1427, 2012) which calls an expanded biology based on advances in systems genetics, that is “essentially physics with computation.” Here is the epochal shift and correction in our midst via a reunion of biology and an organic cosmos (maybe “physicology” from physiology). At once quantum and classical phases come together, while barren mechanism becomes conducive to life and children. See also Brenner’s note Life’s Code Script in Nature (482/461, 2012).

Sydney Brenner describes the radical revolution in life sciences during his lifetime: the occupation of biology by quantum mechanics, concerning the fundamental questions of matter and energy followed by the rise of genetics that showed that chromosomes were the carriers of genes. Biology is, in this respect, physics with computation, i.e, the bottom-top approach in biology is sufficient to solve all our goals in life science. In contrast to this we demonstrate, that biology and life is not only physics and digital information encoded in DNA sequences. In order to understand life in its whole complexity, the top-bottom processes such as occurs in epigenetics and non-coding RNA regulations leads to a new revolution in life sciences.

Barra, Adriano, et al. An Analysis of a Large Dataset on Immigrant Integration in Spain: The Statistical Mechanics Perspective on Social Action. Nature Scientific Reports. 4/4174, 2014. Italian and Spanish theorists contribute to growing realizations that a formative presence of physical principles can be seen, far removed, to be in manifest evidence for human societal movements. Again a common mathematical agency and force seems to be in structural effect, here for disparate migrations. Other papers in Planetary Personsphere find similar manifestations even for the worst wars.

How does immigrant integration in a country change with immigration density? Guided by a statistical mechanics perspective we propose a novel approach to this problem. The analysis focuses on classical integration quantifiers such as the percentage of jobs (temporary and permanent) given to immigrants, mixed marriages, and newborns with parents of mixed origin. We find that the average values of different quantifiers may exhibit either linear or non-linear growth on immigrant density and we suggest that social action, a concept identified by Max Weber, causes the observed non-linearity. Using the statistical mechanics notion of interaction to quantitatively emulate social action, a unified mathematical model for integration is proposed and it is shown to explain both growth behaviors observed. The linear theory instead, ignoring the possibility of interaction effects would underestimate the quantifiers up to 30% when immigrant densities are low, and overestimate them as much when densities are high. The capacity to quantitatively isolate different types of integration mechanisms makes our framework a suitable tool in the quest for more efficient integration policies. (Abstract)

To summarize our work we have analyzed a specific dataset of integration quantifiers in Spain and identified the empirical laws at growing immigration densities. Focusing on their average values on the national scale we found two types of growth and we have provided a simple theoretical framework for their interpretation. Our results could improve our ability to target integration policies since they provide an operative method to distinguish whether a macro phenomenon such as immigrant integration is the product of social action, as in the case of intermarriages and newborns with mixed parents, or the product of the common action of many people, as in the labor market case. Our study shows the potential gain in introducing new families of mathematical models based on a statistical mechanics extension of discrete choice theory, since the latter offers a set of formal tools to systematically analyze and quantify socioeconomic situations. (6)

Becker, Nikolaj and Paolo Sibani. Evolution and Non-Equilibrium Physics: A Study of the Tangled Nature Model. Europhysics Letters EPL. 105/18005, 2014. University of Southern Denmark scientists proceed to connect life’s long development as due to complex interactive systems with deep statistical, dynamic physical principles. Tangled Nature is drawn from a 2002 paper “Tangled Nature: A Model of Evolutionary Ecology” by Imperial College mathematicians Kim Christensen, et al (Journal of Theoretical Biology 216/73), see Abstract below.

We argue that the stochastic dynamics of interacting agents which replicate, mutate and die constitutes a non-equilibrium physical process akin to aging in complex materials. Specifically, our study uses extensive computer simulations of the Tangled Nature Model (TNM) of biological evolution to show that punctuated equilibria successively generated by the model's dynamics have increasing entropy and are separated by increasing entropic barriers. We further show that these states are organized in a hierarchy and that limiting the values of possible interactions to a finite interval leads to stationary fluctuations within a component of the latter. A coarse-grained description based on the temporal statistics of quakes, the events leading from one component of the hierarchy to the next, accounts for the logarithmic growth of the population and the decaying rate of change of macroscopic variables. Finally, we question the role of fitness in large-scale evolution models and speculate on the possible evolutionary role of rejuvenation and memory effects. (Abstract)

We discuss a simple model of co-evolution. In order to emphasize the effect of interaction between individuals, the entire population is subjected to the same physical environment. Species are emergent structures and extinction, origination and diversity are entirely a consequence of co-evolutionary interaction between individuals. For comparison, we consider both asexual and sexually reproducing populations. In either case, the system evolves through periods of hectic reorganization separated by periods of coherent stable coexistence. (Christensen)

1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10  Next