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

2. A Consilience as Physics and Biology Grow Together: Active Matter

Skjeltorp, Arne and Geir Helgesen. Editorial. European Physical Journal Special Topics. 225/4, 2016. An introduction to an issue on Cooperative Particles with papers such as Entangled Active Matter: From Cells to Ants and Patchy Colloidosomes – An Emerging Class of Structures, see abstract below. For another case, see Emergent Behavior in Active Colloids by Andreas Zotti and Holger Stark in the Journal of Physics: Condensed Matter (28/253001, 2016).

Both cells and ants belong to the broad field of active matter, a novel class of non-equilibrium materials composed of many interacting units that individually consume energy and collectively generate motion or mechanical stresses. However cells and ants differ from fish and birds in that they can support static loads. This is because cells and ants can be entangled, so that individual units are bound by transient links. Entanglement gives cells and ants a set of remarkable properties usually not found together, such as the ability to flow like a fluid, spring back like an elastic solid, and self-heal. In this review, we present the biology, mechanics and dynamics of both entangled cells and ants. We apply concepts from soft matter physics and wetting to characterize these systems as well as to point out their differences, which arise from their differences in size.

Smerlak, Matteo. Natural Selection as Coarsening. arXiv:1707.05317. A Perimeter Institute for Theoretical Physics senior postdoctoral researcher deftly considers how life’s seemingly vicarious evolution might actually be rooted in and exemplify fundamental physical phenomena. A concern is a somewhat arcane terminology, better definitions and translations would help, as they might apply to biological systems. But in the later 2010s, evinced by entries here and throughout, a salutary synthesis, long foreseen, is at last coming together. See also Limiting Fitness Distributions to Evolutionary Dynamics by Smerlak and Ahmed Youssef at 1511.00296.

Analogies between evolutionary dynamics and statistical mechanics, such as Fisher's second-law-like "fundamental theorem of natural selection" and Wright's "fitness landscapes", have had a deep and fruitful influence on the development of evolutionary theory. Here I discuss a new conceptual link between evolution and statistical physics. I argue that natural selection can be viewed as a coarsening phenomenon, similar to the growth of domain size in quenched magnets or to Ostwald ripening in alloys and emulsions. In particular, I show that the most remarkable features of coarsening---scaling and self-similarity---have strict equivalents in evolutionary dynamics. This analogy has three main virtues: it brings a set of well-developed mathematical tools to bear on evolutionary dynamics; it suggests new problems in theoretical evolution; and it provides coarsening physics with a new exactly soluble model. (Abstract)

Takatori, S. C. and J. F. Brady. Towards a Thermodynamics of Active Matter. Physical Review E. 91/032117, 2015. Caltech chemical engineers proceed to quantify the unique behaviors of cosmic nature’s animate media by way of nonequilibrium theories.

Self-propulsion allows living systems to display self-organization and unusual phase behavior. Unlike passive systems in thermal equilibrium, active matter systems are not constrained by conventional thermodynamic laws. A question arises, however, as to what extent, if any, can concepts from classical thermodynamics be applied to nonequilibrium systems like active matter. Here we use the new swim pressure perspective to develop a simple theory for predicting phase separation in active matter. Using purely mechanical arguments we generate a phase diagram with a spinodal and critical point, and define a nonequilibrium chemical potential to interpret the “binodal.” We provide a generalization of thermodynamic concepts like the free energy and temperature for nonequilibrium active systems. (Abstract)

Tsimring, Lev, et al. Focus on Swarming in Biological and Related Systems. New Journal of Physics. Circa 2013 -, 2014. Tsimring, Biocircuits Institute, University of California, San Diego, with Hugues Chate, Service Physics Solid State, CEA Saclay, France and Igor Aronson, Argonne National Laboratory, introduce an open collection on statistical physics as applied to organism assemblies for a broad range of articles. For example, “From Organized Internal Traffic to Collective Navigation of Bacterial Swarms” by Gil Ariel, et al, “Collective Motion Dynamics of Active Solids and Active Crystals,” Eliseo Ferrante, et al, and “Swarming, Schooling, Milling: A Data-Driven Fish School Model” by Daniel Calovi, et al. Search, for example, the February 2014 issue to locate.

In the last 15 years, the collective motion of large numbers of self-propelled objects has become an increasingly active area of research. The examples of such collective motion abound: flocks of birds, schools of fish, swarms of insects, herds of animals etc. Swarming of living creatures is believed to be critical for the population survival under harsh conditions. The ability of motile microorganisms to communicate and coordinate their motion leads to the remarkably complex self-organized structures found in bacterial biofilms. Active intracellular transport of biological molecules within the cytoskeleton has a profound effect on the cell cycle, signaling and motility. Collective motion and self-propulsion leads to new and non-trivial material properties of the 'active' medium.

There has been a rapidly growing number of computational and theoretical works on the generic dynamic and statistical properties of collective behavior exhibited by self-propelled particles with simplified interactions, from point-like particles to rigid self-propelled rods. A variety of dynamic phases were predicted, from moving clusters, bands, to swarming states. However, to date, the connection between these simulations and experimentally observed dynamics of self-propelled particles remains unsatisfactory. (Excerpts)

Valani, Rahil and David Paganin. Deterministic Active Matter Generated Using Strange Attractors. arXiv:2110.03776. University of Adelaide and Monash University physicists provide a further mathematical finesse to explain a natural spontaneity which fosters and results in life-like movements across many substantial conditions.

Strange attractors are induced by governing differential or integro-differential equations associated with non-linear dynamical systems, but they can also drive such dynamics. When such equations contain stochastic forcing, they may be replaced by deterministic chaotic driving via an overall strange attractor. We outline a flexible deterministic means for chaotic strange-attractor driven dynamics, and illustrate its utility for modeling active matter. Similar phenomena may be modeled in this manner, such as run-and-tumble particles, run-reverse-flick motion, clustering, jamming and flocking. (Abstract)

Viswanathan, Gandhimohan, et al, eds. The Physics of Foraging: An Introduction to Random Searches and Biological Encounters. Cambridge: Cambridge University Press, 2009. The Federal University of Brazil editors Viswanathan, Marcos Da Luz, and Ernesto Raposo, are joined by Boston University’s Eugene Stanley, a pioneer since the 1970s of this presently extensive synthesis of statistical physics with organic phenomena, animal behaviors, human activities, in their environmental settings. Typical chapters are Random walks and Levy (Paul) flights, Wandering albatross, Human dispersal, and Superdiffusive searches. Once more, a scientific sense of an iterative mathematical domain underlying and guiding the movements of microbes and mice and peoples becomes evident. For later examples, see the work of Frederic Bartumeus (search) and colleagues, such as Experimental Evidence for Inherent Levy Search Behavior for Foraging Animals in Proceedings of the Royal Society B (Vol. 282/No. 1807, 2015).

Do the movements of animals, including humans, follow patterns that can be described quantitatively by simple laws of motion? If so, then why? These questions have attracted the attention of scientists in many disciplines, and stimulated debates ranging from ecological matters to queries such as 'how can there be free will if one follows a law of motion?' This is the first book on this rapidly evolving subject, introducing random searches and foraging in a way that can be understood by readers without a previous background on the subject. It reviews theory as well as experiment, addresses open problems and perspectives, and discusses applications ranging from the colonization of Madagascar by Austronesians to the diffusion of genetically modified crops. The book will interest physicists working in the field of anomalous diffusion and movement ecology as well as ecologists already familiar with the concepts and methods of statistical physics. (Synopsis)

Walker, Sara, et al. The Informational Architecture of the Cell. arXiv:1507.03877. With Hyunju Kim and Paul Davies, in this posting and New Scaling Relation for Information Transfer in Biological Networks, 1508.04174, Arizona State University astrobiologists continue their efforts for a better scientific explanation of living, self-replicating systems from their origins to our human inquiry. With reference to physicist Erwin Schrodinger’s 1940s statement and in line with Nigel Goldenfeld’s current project (search) a novel cross-fertilization, per the quotes, is proposed to inform a new physics by way of biological principles. In this regard, and for this section, the work is a major contribution to this imperative re-unification of cosmos and children.

While we have made significant advances in understanding biology over the last several decades, we have not made comparable advances in physics to unite our new understanding of biology with the foundations of physics. Schrodinger used physical principles to constrain unknown properties of biology associated with genetic heredity. One might argue that this could be done again, but now at the level of the epigenome, or interactome, and so on for any level of biological organization. But this kind of approach only serves to predict structures consistent with the laws of physics; it does not explain why they should exist in the first place. An alternative approach is that we might instead use insights from biology to constrain unknown physics. That is, we suggest a track working in the opposite direction from that proposed by Schrodinger; rather than using physics to inform biology, we propose to start by thinking about biology as a means to inform potentially new physics. (2, 1507.03877)

We avoid introducing new information-theoretic measure, since there already exist a plethora in the literature. Instead we choose a few known measures relevant to biological organization – including those of integrated information theory and information dynamics. Although we focus here on gene regulatory networks, we note that our analysis is not level specific. The formalism introduced in intended to be universal and may apply to any level of biological organization from the first self-organized living chemistries to technological societies. We do not focus on DNA per se, but consider distributed information processing as it operates within the cell, as we believe such analyses have great potential to explain, for example, why physical structures capable of storage and heredity, such as DNA, should exist in the first place. (3, 1507.03877)

Living systems are often described in terms of logic modules, information flows and computation. Such informational language is utilized in fields as diverse as evolutionary biology, neuroscience, pattern formation, colonial decision making in eusocial insects, and protein-protein interaction networks, to name just a few. Although informational analogies are widely applied, an important open question is whether information is intrinsic to the operation of biological systems or merely a useful conceptual metaphor. The debate over the ontological status of information in biology has far-reaching consequences, including implications for our understanding of whether biological organization is fully reducible to the known laws of physics and chemistry or new “informational laws" necessitating a foundational status for information in physical theory are necessary to account for living matter. (1, 1508.04174)

We hypothesize that the features reported herein may be common to biological networks of different function, and in particular, that scaling relations in information transfer may be a hallmark of biological organization. Our results are suggestive of previously unidentified information-based organizational principles that go beyond topological considerations such as scale-free structure, and may be critical to biological function. They thus open a new framework for addressing the debate over the status of information in biology, by demonstrating quantitatively how the informational architecture of biologically evolved networks can distinguish them from other classes of network architecture that do not exhibit the same informational properties as reported here. (13, 1508.04174)

Wang, Zhen, et al. Statistical Physics of Vaccination. arXiv:1608.09010. A global team from Japan, Canada, India, France, Italy, Slovenia, England, Switzerland and China, including Matjaz Perc, post a 150 page study with over 750 references for this nascent 2016 joining and synthesis of universe and human. As the long abstract conveys, complex network systems, as akin to many-body, condensed matter theories, can well quantify infectious disease epidemics as they spread through human populations. From our vantage, these advances imply an independent, universal mathematics which underlies, guides and constrains personal and social lives. By turns, it infers a revolutionary biological cosmos, as if graced by an anatomy, physiology, and indeed a stirring intelligence. The second quote is the closing paragraph – where do you ever find good literature in a technical paper? A further surmise would be a self-healing genesis uniVerse by virtue of an emergent worldwise knowledge which can be fed back to palliate, cure, and prevent the bodily and psychic maladies of a prior stochastic evolution.

Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination - one of the most important preventive measures of modern times - is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure.

Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. (Abstract)

Shakespeare famously ended his play “A Midsummer Night’s Dream" with an apology from the spirit Puck to the audience: “If we shadows have offended, Think but this, and all is mended — That you have but slumbered here While these visions did appear." We also wish to apologize to the readers in advance, for having inadvertently missed some excellent papers in the literature, having unintentionally misrepresented other papers that we did include, or being completely wrong about where the field should go next. However, there is no need for the reader to pretend our review was something they dreamed while slumbering. Instead, please write us if you feel our review was lacking in some respect, or better yet, publish some research that shows us the value of other perspectives on the field. If nothing else, we hope that our review has convinced the readers that coupled behavior-disease modeling is a rapidly growing area that promises exciting theoretical developments and empirical applications in the coming decade, especially if we draw on the accumulated knowledge of many decades of statistical physics. (125)

Weber, Christoph, et al. Physics of Active Emulsions. Reports on Progress in Physics. 82/6, 2019. As nature comes to life, MPI Physics of Complex Systems and Imperial College London biophysicists provide new appreciations of this broad class of colloidal, multi-droplet chemicals so to reveal their innate mobility. See also a Novel Physics Arising from Phase Transitions in Biology at arXiv:1809.11117.

In summary, we have discussed a new class of physical systems which we refer to as active emulsions. These emulsions are relevant to cell biology. They may allow to develop novel applications in the field of chemical engineering or aqueous computing and could help explain how life could have emerged from an inanimate mixture composed of set of simple chemically active molecules. However, the class of active emulsions also challenge our theoretical understanding of spatially heterogeneous systems driven far away from thermal equilibrium and can be used to refine existing theoretical concepts. In particular, active emulsions are characterised by non-equilibrium fluxes that maintain these system away from thermal equilibrium. (37)

Whitelam, Stephen and Robert Jack. The Statistical Mechanics of Dynamic Pathways to Self-Assembly. arXiv:1407.2505. In a paper to appear in the 2015 edition of the Annual Review of Physical Chemistry, LBNL and University of Bath materials scientists explain how a marriage of traditional physics and complex systems theories can well serve and inform an incipient new creation of nature’s living materiality.

We describe some of the important physical characteristics of the `pathways', i.e. dynamical processes, by which molecular, nanoscale and micron-scale self-assembly occurs. We highlight the fact that there exist features of self-assembly pathways that are common to a wide range of physical systems, even though those systems may be different in respect of their microscopic details. We summarize some existing theoretical descriptions of self-assembly pathways, and highlight areas -- notably, the description of self-assembly pathways that occur `far' from equilibrium -- that are likely to become increasingly important. (Abstract)

The term `self-assembly' describes dynamical processes in which components of a system organize themselves, without external direction, into ordered patterns or structures. The range of scales on which self-assembly happens is enormous: we might say that atoms are self-assembled from protons, neutrons and electrons, and that galaxies are self-assembled from their component stars. Here we focus on assembly undergone by components that range in size from a few angstroms (for example, atoms and molecules) to a few microns (for example, colloids). Assembly of such components is important both in the natural world and, increasingly, the laboratory. Structures assembled in the laboratory include three-dimensional crystals, two-dimensional lattices, closed polyhedral shells (10, 11), and other tailored nanoscale shapes. (3)

Wills, Peter. Reflexivity, Coding and Quantum Biology. Biosystems. Online September, 2019. The University of Auckland philosophical biologist continues his frontier studies beyond a constrained Darwinian selection to include self-organizion, epigenetics, autocatalysis, symbolic information with Harold Pattee and Paul Davies, cooperative groupings and more. An active, codified development with a computational guise and a “reflexive” spontaneity thus becomes evident. With this in place, it is mused that evolutionary theories might at last be fulfilling Erwin Schrodinger’s view of an intrinsic physical fertility. Wills is often joined by University of North Carolina biochemist Charles Carter (search both) for papers such as Interdependence, Reflexivity, Fidelity, Impedance Matching, and the Evolution of Genetic Coding in Molecular Biology and Evolution (35/2, 2018).

Biological systems are fundamentally computational in that they process information in a purposeful fashion rather than just transferring bits of it in a syntactical manner. It carries meaning defined by the molecular context of its cellular environment. Information processing in biological systems displays an inherent reflexivity, a tendency for the information-processing to be “about” the behaviour of the molecules that participate in the computational process. This is most evident in the operation of the genetic code, where the specificity of the reactions catalysed by the aminoacyl-tRNA synthetase (aaRS) enzymes is required to be self-sustaining. A cell’s suite of aaRS enzymes completes a reflexively autocatalytic set of molecular components capable of making themselves by way of reflexive information stored in an organism’s genome. The genetic code is a reflexively self-organised, evolved symbolic system of chemical self-description. (Abstract excerpt)

Wolchover, Natalie. A Common Logic to Seeing Cats and Cosmos. Quanta Magazine. Online December, 2014. The science writer reports on another convergence of disparate fields and theories, which are separate mainly because of different definitions. Boston University’s Pankaj Mehta and David Schwab of Northwestern University are joining statistical physics and renormalization theories with deep neural networks to learn how nature’s universal logic can recognize features (cats) among large data displays. An extrapolation might to be imagine the universe to human trajectory as engaged in its own “deep learning” project via our own self-recognition and discovery.

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