III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

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

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. (This topical aspect has since been moved to Computational Systems Physics below.)

2020: As 21st century system sciences due to a regnant worldwise cognizance form in our midst, largely unawares, the long separation of organic, evolving life and mind from an “inorganic” material ground are well on their way to a vital integrated reunivication. This holistic synthesis occurs as living systems gain deeper integrations with physical phases and in turn quantum and many-body statistical phenomena find their way into biological vitalities.

Azpeitia, Eugenio, et al. Cauliflower Fractal Forms Arise from Perturbations of Floral Gene Networks. Science. 373/192, 2021.

Bianconi, Ginestra, et al. Complex Systems in the Spotlight: Next Steps after the 2021 Nobel Prize in Physics. Journal of Physics: Complexity. 4/010201, 2023.

De Marzo, Giordano, et al. Quantifying the Unexpected: A Scientific Approach to Black Swans. Physical Review Research. 4/033079, 2022.

Krakauer, David, ed. Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute 1984 – 2019. Santa Fe, NM: Santa Fe Institute Press, 2019.

Newman, Stuart. Self-Organization in Embryonic Development. arXiv:2108.00532.

Nguyen, Thank, et al. Spatial Patterns of Urban Landscapes in the Indian Punjab are Predicted by Fractal Theory. Nature Scientific Reports. 12/1819, 2022.

Renken, Elena. Turing Patterns Turn Up in a Tiny Crystal. Quanta. August 10,, 2021.

Thurner, Stefan, et al. Introduction to the Theory of Complex Systems. Oxford: Oxford University Press, 2018.

Wolfram, Stephen. The Physicalization of Metamathematics and Its Implications for the Foundations of Mathematics. arXiv:2204.05123.

Zhang, Mengsen, et al. Topological Portraits of Multiscale Coordination Dynamics. Journal of Neuroscience Methods. Vol. 339, 2020.


2023:

Center for the Physics of Biological Function.. biophysics.princeton.edu. This is a joint effort between The CUNY Graduate Center and Princeton University and one of eleven Physics Frontier Centers established by the Physics Division of the National Science Foundation Directorate for Mathematical and Physical Sciences. We are a collection of scientists working at the interface of physics and biology with the goal of creating a physicist’s understanding of living systems: a physics of biological function that connects the myriad details of life, across all scales, to fundamental and universal physical principles. Our center focuses on new scientific opportunities and educational programs, integrating theory and experiment, research and education. Its director and long time mentor is Professor William Bialek (search).

, . Hernandez, Edward, et al. Power-law distributions of urban tree cover. Physica A: Statistical Mechanics. 643/129779, 2024.. Physica A: Statistical Mechanics.. 643/129779, 2024. De La Salle University, Manila, Philippines system physicists report an implicate presence of dynamic complexity in effect even across citified greenery. Into these mid-2020s how might we all be able, just in time, to recognize life’s ecosmome to geonome endowment so as to intentionally receive, avail and continue?

Many large-scale systems in nature and society are distinguished by self-organized criticality (SOC), a dynamical state that produces robust power-law statistics without fine-tuned parameters. However, many of these systems are also affected by human activities, leading to the dual action of self-organization and human intervention. In this work, we extract the geographical areas of tree-covered greeneries in an urbanized setting and show the constant emergence of stable power-law distributions which are independent of the specific city. The result shows that while anthropogenic factors influence the natural environment, these occasions still exhibit complex self-organization. (Abstract)

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.

Third Infinity 2013. www.thirdinfinity.mpg.de. A Conference on Physics of Biological and Complex Systems held in October in Gottingen, arranged by the International Max Planck Research School, a joint endeavor of the University of Gottingen, MPI Biophysical Chemistry, and MPI Dynamics and Self-Organization. It is of special interest for its reference to science’s historic infinities of cosmos, atom, and life, which was first noted by Pierre Teilhard de Chardin in his The Phenomenon of Man. Keynote speakers were the British neuroscientist Karl Friston, and Eytan Domany, Computational Systems Biology, Weizmann Institute of Science. A public panel on The Practice of Science was chaired by Ahmed El Hady, MPI Biological Chemistry.

And as we record in mid 2014, the new phase of integral science and animate nature these worldwide meetings achieve seem as a parallel universe far removed from worsening barbaric conflicts and carnage, the guns of August a century later. However, one might ask, could such common revolutionary knowledge unto discovery, a future light age over an return to a new darker age, be able to turn the world from perpetual war to natural wisdom and sustainable peace. We try to note this work and progress going on, but however can it become revelation?

The Third Infinity: The field of Physics may be divided today in three sub-categories: infinitely big (relativity and astronomy), infinitely small (quantum mechanics and particle physics) and infinitely complex (complex systems and biophysics). The conference Third Infinity focuses on the latter and most recently addressed infinities (such as) the diverse fields of non-linear dynamical systems, brain as a complex system, experimental biophysics and robotics.

Building upon the increasingly strong links between physics, chemistry and the life sciences, the program aims at advancing the quantitative and molecular understanding of life processes while at the same time exploring new frontiers of physics. Research topics include biomolecular structure and dynamics, biological membranes, motor proteins and pattern formation in systems of interacting cells, neuronal information processing, and hydrodynamics and pattern formation of complex fluids. (MPI Research School)

Turbulence in clouds, neuronal fireworks in the brain, the physics of individual cells and the flow of water and oil through porous stone – these, and other particularly complex systems, are the focus of the research carried out by scientists at the Max Planck Institute for Dynamics and Self-Organization. Here, “complex” means that many individual systems combine to form a whole, the dynamics of which cannot necessarily be identified through the behaviour of the individual systems. Scientists say that these systems “organise themselves”. This holds true for the interaction of neurons in the brain (for example during learning) as well as for the numerous swirls that combine to form a turbulent cloud. There is reason to hope that a better understanding of the latter will enable a more accurate prediction of the future influence of clouds on global climate. (MPI for Dynamics and Self-Organization)

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)

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.

Bardella, Giampiero, et al.. Lattice physics approaches for neural neworks.. arXiv:2405.12022. Sapienza University of Rome system physiologists scope out a necessary, obvious trace of our human cerebral faculty beyond neural nets all the way to fundamental sources. As this mid 2020s consilience becomes more evident, prime insights such as renormalization group theory (which is akin to complexity phenomena) can be found to have an integral, structuring affinity.

Modern neuroscience has evolved into a frontier field that draws on novel conceptual frames inspired by physics and complex systems science. In this regard, we introduce a mathematical framework to describe the spatiotemporal systems of neurons using lattice field theory, the reference paradigm for particle physics. We summarize its basic features to show how to readily connect this prime model to experimental variables using well-known renormalization procedures. This synopsis yields key concepts to describe neural networks using lattice physics and to gain generative models underpinned by physical principles. (Excerpt)

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)

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