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The inevitable “layering” of models to extend the reach of our understanding

Sat, 02/25/2023 - 15:36

Bruce Edmonds


There is a modelling norm that one should be able to completely understand one’s own model. Whilst acknowledging there is a trade-off between a model’s representational adequacy and its simplicity of formulation, this tradition assumes there will be a “sweet spot” where the model is just tractable but also good enough to be usefully informative about the target of modelling – in the words attributed to Einstein, “Everything should be made as simple as possible, but no simpler1. But what do we do about all the phenomena where to get an adequate model2 one has to settle for a complex one (where by “complex” I mean a model that we do not completely understand)? Despite the tradition in Physics to the contrary, it would be an incredibly strong assumption that there are no such phenomena, i.e. that an adequate simple model is always possible (Edmonds 2013).      

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Conflicting Models for the Origin of Life

Fri, 02/24/2023 - 15:16

Editor(s):Stoyan K. Smoukov, Joseph Seckbach, Richard Gordon

Conflicting Models for the Origin of Life provides a forum to compare and contrast the many hypotheses that have been put forward to explain the origin of life.

There is a revolution brewing in the field of Origin of Life: in the process of trying to figure out how Life started, many researchers believe there is an impending second creation of life, not necessarily biological. Up-to-date understanding is needed to prepare us for the technological, and societal changes it would bring. Schrodinger’s 1944 “What is life?” included the insight of an information carrier, which inspired the discovery of the structure of DNA. In “Conflicting Models of the Origin of Life” a selection of the world’s experts are brought together to cover different aspects of the research: from progress towards synthetic life – artificial cells and sub-cellular components, to new definitions of life and the unexpected places life could (have) emerge(d). Chapters also cover fundamental questions of how memory could emerge from memoryless processes, and how we can tell if a molecule may have emerged from life. Similarly, cutting-edge research discusses plausible reactions for the emergence of life both on Earth and on exoplanets. Additional perspectives from geologists, philosophers and even roboticists thinking about the origin of life round out this volume. The text is a state-of-the-art snapshot of the latest developments on the emergence of life, to be used both in graduate classes and by citizen scientists.

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Salt Polygons and Porous Media Convection

Fri, 02/24/2023 - 11:38

Jana Lasser, Joanna M. Nield, Marcel Ernst, Volker Karius, Giles F. S. Wiggs, Matthew R. Threadgold, Cédric Beaume, and Lucas Goehring
Phys. Rev. X 13, 011025

From fairy circles to patterned ground and columnar joints, natural patterns spontaneously appear in many complex geophysical settings. Here, we investigate the origins of polygonally patterned crusts of salt playa and salt pans. These beautifully regular features, approximately a meter in diameter, are found worldwide and are fundamentally important to the transport of salt and dust in arid regions. We show that they are consistent with the surface expression of buoyancy-driven convection in the porous soil beneath a salt crust. By combining quantitative results from direct field observations, analog experiments, and numerical simulations, we further determine the conditions under which salt polygons should form, as well as how their characteristic size emerges.

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Fri, 02/24/2023 - 10:38


Advances in Complex SystemsVol. 25, No. 07, 2250009

Long-range connections play an essential role in dynamical processes on networks, on the processing of information in biological networks, on the structure of social and economical networks and in the propagation of opinions and epidemics. Here, we review the evidence for long-range connections in real-world networks and discuss the nature of the nonlocal diffusion arising from different distance-dependent laws. Particular attention is devoted to the characterization of diffusion in finite networks for moderate large times and to the comparison of distance laws of exponential and power type.

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Networks of climate change: connecting causes and consequences

Thu, 02/23/2023 - 19:29

Petter Holme & Juan C. Rocha 

Applied Network Science volume 8, Article number: 10 (2023)

Understanding the causes and consequences of, and devising countermeasures to, global warming is a profoundly complex problem. Network representations are sometimes the only way forward, and sometimes able to reduce the complexity of the original problem. Networks are both necessary and natural elements of climate science. Furthermore, networks form a mathematical foundation for a multitude of computational and analytical techniques. We are only beginning to see the benefits of this connection between the sciences of climate change and network science. In this review, we cover the wide spectrum of network applications in the climate-change literature—what they represent, how they are analyzed, and what insights they bring. We also discuss network data, tools, and problems yet to be explored.

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Thu, 02/23/2023 - 17:37


Advances in Complex SystemsVol. 25, No. 07, 2250010

Among diverse topics in complex network analysis, the idea of extracting a small set of nodes which can maximally influence other nodes in the network has a variety of applications, especially for e-marketing and social networking. While there is an abundance of heuristics to identify such influential nodes, the method of quantifying the influence itself, has not been investigated in the research community. Most of the classical and state-of-the-art works use Diffusion tests for influence benchmark of a particular set of nodes in the network. The underlying study challenges this method and conducts thorough experiments to show that for real-world applications, the diffusion test alone is not only insufficient, but in some cases is also an inaccurate method of benchmarking. Using eight widely adopted heuristics, 25 networks were tested using Diffusion tests and compared with resilience test, we found out that no single algorithm performs consistently on both types of tests. Thus, we conclude that a more accurate way of benchmarking a set of influential nodes is to run diffusion tests alongside resilience test, in order to label a certain technique as best performer.

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Scaling up the self-optimization model by means of on-the-fly computation of weights

Thu, 02/23/2023 - 15:28

Natalya Weber; Werner Koch; Tom Froese

The Self-Optimization (SO) model is a useful computational model for investigating self-organization in “soft” Artificial life (ALife) as it has been shown to be general enough to model various complex adaptive systems. So far, existing work has been done on relatively small network sizes, precluding the investigation of novel phenomena that might emerge from the complexity arising from large numbers of nodes interacting in interconnected networks. This work introduces a novel implementation of the SO model that scales as O(N2) with respect to the number of nodes N, and demonstrates the applicability of the SO model to networks with system sizes several orders of magnitude higher than previously was investigated. Removing the prohibitive computational cost of the naive O(N3) algorithm, our on-the-fly computation paves the way for investigating substantially larger system sizes, allowing for more variety and complexity in future studies.

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How fingerprints get their one-of-a-kind swirls

Wed, 02/22/2023 - 17:43

The intricate patterns are created during fetal development when fine ridges on the skin form and crash into each other.

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Complexity Explorables | The Prisoner’s Kaleidoscope

Wed, 02/22/2023 - 15:42

This explorable illustrates beautiful dynamical patterns that can be generated by a simple game theoretic model on a lattice. The core of the model is the Prisoner’s Dilemma, a legendary game analyzed in game theory. In the game, two players can choose to cooperate or defect. Depending on their choice, they receive a pre-specified payoffs. The payoffs are chosen such that it seems difficult to make the right strategy choice.

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Wed, 02/22/2023 - 15:33

Complexity72h is an interdisciplinary workshop for young researchers in complex systems. Participants form teams and carry out projects in a three days’ time, i.e. 72 hours. The goal of each team is to upload on the arXiv (or similar repositories) a report of their work by the end of the event. The editions of 2018 and 2019 were a success: 11 out of 11 projects became arXiv preprints and new collaborations were born. Complexity72h is back for a 2023 edition, which will take place in Palma (Mallorca, Spain) on June 26-30.

More info & application: 
Deadline for applications: March 1st 2023

Effective Connectivity and Bias Entropy Improve Prediction of Dynamical Regime in Automata Networks

Tue, 02/21/2023 - 10:29

Felipe Xavier Costa, Jordan C. Rozum, Austin M. Marcus, and Luis M. Rocha

Entropy 2023, 25(2), 374

Biomolecular network dynamics are thought to operate near the critical boundary between ordered and disordered regimes, where large perturbations to a small set of elements neither die out nor spread on average. A biomolecular automaton (e.g., gene, protein) typically has high regulatory redundancy, where small subsets of regulators determine activation via collective canalization. Previous work has shown that effective connectivity, a measure of collective canalization, leads to improved dynamical regime prediction for homogeneous automata networks. We expand this by (i) studying random Boolean networks (RBNs) with heterogeneous in-degree distributions, (ii) considering additional experimentally validated automata network models of biomolecular processes, and (iii) considering new measures of heterogeneity in automata network logic. We found that effective connectivity improves dynamical regime prediction in the models considered; in RBNs, combining effective connectivity with bias entropy further improves the prediction. Our work yields a new understanding of criticality in biomolecular networks that accounts for collective canalization, redundancy, and heterogeneity in the connectivity and logic of their automata models. The strong link we demonstrate between criticality and regulatory redundancy provides a means to modulate the dynamical regime of biochemical networks.

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Tracking stolen bikes in Amsterdam

Thu, 02/16/2023 - 14:51

Venverloo T, Duarte F, Benson T, Leoni P, Hoogendoorn S, Ratti C (2023) Tracking stolen bikes in Amsterdam. PLoS ONE 18(2): e0279906.

Crime has major influences in urban life, from migration and mobility patterns, to housing prices and neighborhood liveability. However, urban crime studies still largely rely on static data reported by the various institutions and organizations dedicated to urban safety. In this paper, we demonstrate how the use of digital technologies enables the fine-grained analysis of specific crimes over time and space. This paper leverages the rise of ubiquitous sensing to investigate the issue of bike theft in Amsterdam—a city with a dominant cycling culture, where reportedly more than 80,000 bikes are stolen every year. We use active location tracking to unveil where stolen bikes travel to and what their temporal patterns are. This is the first study using tracking technologies to focus on two critical aspects of contemporary cities: active mobility and urban crime.

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Biology as involving laws and inconceivable without them

Tue, 02/14/2023 - 15:50

Richard Creath 

Theory in Biosciences volume 142, pages61–66 (2023)

There is an old attempt to divide the sciences into sciences of laws and the historical sciences. More recently, John Beatty has drawn the distinction so that biology is a historical science and urged that there are no genuinely biological laws. This paper shows that there are indeed biological laws, specifically statistical ones, notably in evolutionary theory. Moreover, all or almost all other areas of biology involve laws as well. Even history involves laws. Finally, the paper shows that this pervasiveness of laws is compatible with the most basic commitments of those who, like Beatty, would claim that biology is only historical.

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Mediterranean School of Complex Networks 2023

Mon, 02/13/2023 - 12:03

Catania, Sicily 25 – 30 June 2023

In the last decade, network theory has been revealed to be a perfect instrument to model the structure of complex systems and the dynamical process they are involved into. The wide variety of applications to social sciences, technological networks, biology, transportation and economic, to cite just only some of them, showed that network theory is suitable to provide new insights into many problems.
Given the success of the Seventh Edition in 2022 of the Mediterranean School of Complex Networks, we call for applications to the Eighth Edition in 2023.

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Journal launched: Frontiers in Complex Systems

Mon, 02/13/2023 - 11:59

Frontiers in Complex Systems publishes rigorously peer-reviewed quantitative research on Complex Systems, either theoretical, experimental, mathematical, computational or data description. Field Chief Editor Maxi San Miguel at the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) in Spain is supported by an outstanding Editorial Board of international experts. This open-access journal is to become the reference and natural publication outlet for the Complex Systems community at large, and to be at the forefront of disseminating and communicating scientific knowledge and technological innovation in the field to researchers, academics, entrepreneurs, companies, policy makers and the public worldwide.

Frontiers in Complex Systems covers fundamental questions, theories and general methodologies on complex systems as well as the cross-disciplinary application of these concepts and methods, often giving rise to new disciplines. It provides a forum for cross-disciplinary communication and welcomes quantitative research from different fields including Physics, Mathematics, Computer Sciences, Artificial Intelligence, Engineering, Climate change, Economics and Finance, Social Sciences, Linguistics, Ecology, Neuroscience, Health Sciences, Epidemics, Mobility and Transport, City Science, etc. Submissions to Frontiers in Complex Systems are made to appropriate specialty sections, each of which devoted to a specific sub-field and having their own expert editorial board. Aligned with the cross-disciplinary scope of the journal, some of these sections are shared with other Frontiers journals, providing an enhanced visibility of the research in different scientific communities.

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Complexity and Evolution

Sun, 02/12/2023 - 10:43

Tomas Veloz, Francis Heylighen, and Olaf Witkowski

Entropy 2023, 25(2), 286

Understanding the underlying structure of evolutionary processes is one the most important issues of scientific enquiry of this century. In the twentieth century, scientific thinking witnessed the overwhelming power of the evolutionary paradigm. It not only solidified the foundations of diverse areas, such as cell-biology, ecology, and economics, but also fostered the development of novel mathematical and computational tools to model and simulate how evolutionary processes take place.
In addition to the application of the evolutionary paradigm and the discovery of the evolutionary features for processes of diverse nature, there is another interesting aspect which touches upon the emergence of novel evolutionary processes. Namely, the emergence of an evolutionary process requires a complex transition between a prior form where no evolutionary process is undergoing and a posterior form where the evolutionary process has been triggered.
Theoretical methods to describe the emergence of evolutionary processes require the consideration of complex systemic notions, such as self-organization, resilience, contextuality, among others. Therefore, complexity and evolution became intertwined notions: evolution not only leads to but also depends on the development of increasingly complex forms and functions.
In this Special Issue, we put together eight articles, mostly of interdisciplinary nature, that explore from recent advances in the modeling of complex systems, as well as of the increasing modeling power and growth of databases associated to evolutionary processes.

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Entanglement, Symmetry Breaking and Collapse: Correspondences Between Quantum and Self-Organizing Dynamics

Sat, 02/11/2023 - 15:33

Francis Heylighen 

Foundations of Science volume 28, pages 85–107 (2023)

Quantum phenomena are notoriously difficult to grasp. The present paper first reviews the most important quantum concepts in a non-technical manner: superposition, uncertainty, collapse of the wave function, entanglement and non-locality. It then tries to clarify these concepts by examining their analogues in complex, self-organizing systems. These include bifurcations, attractors, emergent constraints, order parameters and non-local correlations. They are illustrated with concrete examples that include Rayleigh–Bénard convection, social self-organization and Gestalt perception of ambiguous figures. In both cases, quantum and self-organizing, the core process appears to be a symmetry breaking that irreversibly and unpredictably “collapses” an ambiguous state into one of a number of initially equivalent “eigenstates” or “attractors”. Some speculations are proposed about the non-linear amplification of quantum fluctuations of the vacuum being ultimately responsible for such symmetry breaking.

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From autopoiesis to self-optimization: Toward an enactive model of biological regulation

Thu, 02/09/2023 - 17:12

Tom Froese, Natalya Weber, Ivan Shpurov, Takashi Ikegami

The theory of autopoiesis has been influential in many areas of theoretical biology, especially in the fields of artificial life and origins of life. However, it has not managed to productively connect with mainstream biology, partly for theoretical reasons, but arguably mainly because deriving specific working hypotheses has been challenging. The theory has recently undergone significant conceptual development in the enactive approach to life and mind. Hidden complexity in the original conception of autopoiesis has been explicated in the service of other operationalizable concepts related to self-individuation: precariousness, adaptivity, and agency. Here we advance these developments by highlighting the interplay of these concepts with considerations from thermodynamics: reversibility, irreversibility, and path-dependence. We interpret this interplay in terms of the self-optimization model, and present modeling results that illustrate how these minimal conditions enable a system to re-organize itself such that it tends toward coordinated constraint satisfaction at the system level. Although the model is still very abstract, these results point in a direction where the enactive approach could productively connect with cell biology.

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Experiments with Social Network Interventions – Nicholas A. Christakis

Thu, 02/09/2023 - 14:18


Network Science Society Colloquium – January 25, 2023

Nicholas A. Christakis
Experiments with Social Network Interventions

Human beings choose their friends, and often their neighbors and co-workers, and we inherit our relatives; and each of the people to whom we are connected also does the same, such that, in the end, we assemble ourselves into face-to-face social networks that obey particular mathematical and sociological rules. Why do we do this? And how might a deep understanding of human social network structure and function be used to intervene in the world to make it better? Here, I will review recent research from our lab describing three classes of interventions involving both offline and online networks: (1) interventions that rewire the connections between people; (2) interventions that manipulate social contagion, modifying the flow of desirable or undesirable properties; and (3) interventions that manipulate the positions of people within network structures. I will illustrate what can be done using a variety of experiments in settings as diverse as fostering cooperation or the diffusion of innovation in networked groups online, to fostering health behavior change in developing world villages and towns. I will also discuss recent experiments with “hybrid systems” comprised of both humans and artificial intelligence (AI) agents interacting in small groups. Overall, by taking account of people’s structural embeddedness in social networks, and by understanding social influence, it is possible to intervene in social systems to enhance desirable population-level properties as diverse as health, wealth, cooperation, coordination, and learning.

About the Speaker
Nicholas A. Christakis, MD, PhD, MPH, is a social scientist and physician at Yale University who conducts research in the fields of network science, biosocial science, and behavior genetics. His current work focuses on how human biology and health affect, and are affected by, social interactions and social networks. He directs the Human Nature Lab and is the Co-Director of the Yale Institute for Network Science. He is the Sterling Professor of Social and Natural Science at Yale University, appointed in the Departments of Sociology; Medicine; Ecology and Evolutionary Biology; Biomedical Engineering; and the School of Management.

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Urban scaling laws arise from within-city inequalities

Tue, 02/07/2023 - 17:12

Martin Arvidsson, Niclas Lovsjö & Marc Keuschnigg 
Nature Human Behaviour (2023)

Theories of urban scaling have demonstrated remarkable predictive accuracy at aggregate levels. However, they have overlooked the stark inequalities that exist within cities. Human networking and productivity exhibit heavy-tailed distributions, with some individuals contributing disproportionately to city totals. Here we use micro-level data from Europe and the United States on interconnectivity, productivity and innovation in cities. We find that the tails of within-city distributions and their growth by city size account for 36–80% of previously reported scaling effects, and 56–87% of the variance in scaling between indicators of varying economic complexity. Providing explanatory depth to these findings, we identify a mechanism—city size-dependent cumulative advantage—that constitutes an important channel through which differences in the size of tails emerge. Our findings demonstrate that urban scaling is in large part a story about inequality in cities, implying that the causal processes underlying the heavier tails in larger cities must be considered in explanations of urban scaling. This result also shows that agglomeration effects benefit urban elites the most, with the majority of city dwellers partially excluded from the socio-economic benefits of growing cities.

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