The new physics needed to probe the origins of life
A World Beyond Physics: The Emergence and Evolution of Life Stuart A. Kauffman Oxford University Press (2019)
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His key insight is motivated by what he calls “the nonergodic world” — that of objects more complex than atoms. Most atoms are simple, so all their possible states can exist over a reasonable period of time. Once they start interacting to form molecules, the number of possible states becomes mind-bogglingly massive. Only a tiny number of proteins that are modestly complex — say, 200 amino acids long — have emerged over the entire history of the Universe. Generating all 20020 of the possibilities would take aeons. Given such limitations, how does what does exist ever come into being?
Nature 569, 36-38 (2019)
Source: www.nature.com
Singularity cities
We propose an upgraded gravitational model which provides population counts beyond the binary (urban/non-urban) city simulations. Numerically studying the model output, we find that the radial population density gradients follow power-laws where the exponent is related to the preset gravity exponent γ. Similarly, the urban fraction decays exponentially, again determined by γ. The population density gradient can be related to radial fractality and it turns out that the typical exponents imply that cities are basically zero-dimensional. Increasing the gravity exponent leads to extreme compactness and the loss of radial symmetry. We study the shape of the major central cluster by means of another three fractal dimensions and find that overall its fractality is dominated by the size and the influence of γ is minor. The fundamental allometry, between population and area of the major central cluster, is related to the gravity exponent but restricted to the case of higher densities in large cities. We argue that cities are shaped by power-law proximity. We complement the numerical analysis by economics arguments employing travel costs as well as housing rent determined by supply and demand. Our work contributes to the understanding of gravitational effects, radial gradients, and urban morphology. The model allows to generate and investigate city structures under laboratory conditions.
Singularity cities
Yunfei Li, Diego Rybski, Jürgen P. Kropp
Environment and Planning B: Urban Analytics and City Science
Source: journals.sagepub.com
Complex Systems in Aesthetics and Arts
The arts are one of the most complex of human endeavours, and so it is fitting that a special issue on Complex Systems in Aesthetics and Arts is being published. As the editors of this special issue, we would like to thank the reviewers of the submitted papers for their hard work in making this issue possible, as well as the authors who submitted their work and were very responsive to the comments of the reviewers and editors.
The word complexity has a specific meaning in the context of “complex systems” research, as the study of systems made of many components—not in themselves necessarily complex—that through loosely coupled, local interactions generate complex, emergent behaviours. Such systems have the potential to act as the basis for the production of artworks, whether entirely computer generated or as a result of a cocreative system between humans and computers. Such art might make its impact through the intrinsic interest of the complex behaviour in the system, by representing, exploring, or connoting some worldly aspect of complexity, or by using complex systems as a way of exploring a space of possible works. Furthermore, complex systems research has the potential to simulate emergent processes in the artworld, such as the interaction between artists, audiences, and critics, or the development of aesthetic ideas or artistic fashions over time.
Complex Systems in Aesthetics and Arts
Juan Romero, Colin Johnson, and Jon McCormack
Complexity
Volume 2019, Article ID 9836102, 2 pages
Source: www.hindawi.com
Particle velocity controls phase transitions in contagion dynamics
Interactions often require the proximity between particles. The movement of particles, thus, drives the change of the neighbors which are located in their proximity, leading to a sequence of interactions. In pathogenic contagion, infections occur through proximal interactions, but at the same time, the movement facilitates the co-location of different strains. We analyze how the particle velocity impacts on the phase transitions on the contagion process of both a single infection and two cooperative infections. First, we identify an optimal velocity (close to half of the interaction range normalized by the recovery time) associated with the largest epidemic threshold, such that decreasing the velocity below the optimal value leads to larger outbreaks. Second, in the cooperative case, the system displays a continuous transition for low velocities, which becomes discontinuous for velocities of the order of three times the optimal velocity. Finally, we describe these characteristic regimes and explain the mechanisms driving the dynamics.
Particle velocity controls phase transitions in contagion dynamics
Jorge P. Rodríguez, Fakhteh Ghanbarnejad & Víctor M. Eguíluz
Scientific Reports volume 9, Article number: 6463 (2019)
Source: www.nature.com
SOLSTICE 2019 – Summer Solstice Conference on Discrete Models of Complex Systems 2019
15-17 July 2019
Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
Source: solstice2019.loria.fr
Summer School in Computational and Theoretical Models in Neuroscience – Venice 09-14 September 2019
Approaches and techniques from Physics, Mathematics and Computational Science are increasingly becoming critical for understanding and modelling the brain, and also for designing and interpreting experiments. Modeling is an essential tool to cut through the vast complexity of neurobiological systems and their many interacting elements.
ConTaMiNEURO 2019 wants to convey central ideas, methods, and practices of modern computational neuroscience through a combination of lectures, tutorials, and seminars. During the course’s mornings, distinguished international faculty deliver lectures and seminars on selected topics in computational neuroscience (see below). For the remainder of the time, students work on research projects in teams of 3-4 people under close supervision of expert tutors and faculty. Research projects will include data analyses and the development of theories to explain experimental observations.
Thanks to the support of our sponsor, the early bird registration fee for Ph.Ds students and Post Docs is 200 Euro, the deadline is 30 June 2019. MAX 40 participants.
An amazing line uo of Invited Speakers:
Ken Miller, Columbia University, USA. Yiota Poirazi, IMBB-FORTH, Creta. Nicolas Brunel*, Duke University, USA. Andrea Brovelli, University of Marsille. Jordi Soriano, University of Barcellona Mazzuccato Luca, University of Oregon Stefano Panzeri, IIT Rovereto Jesus Cortes, IKERBASQUE: The Basque Foundation for Science Lucilla De Arcangelis, University of Campania Raffaella Burioni, University of Parma Gustavo Deco, Pompeu Fabra University, Barcelona Jonathan Touboul, Brandeis University (USA) Susanne Ditlevsen, University of Copenaghen Alessandro Treves, Trieste SISSA Misha Tsodyks, Weizmann Institute of Science Eleni Vasilaki, University of Shieffield Marcello Pelillo, European Center of Living Techonology & University of Venice Tommaso Fellin, IIT Genova Maria Victoria Sánchez Vives , ICREA-IDIBAPS (Barcelona) Marco dal Maschio, University of Padova Serena del Santo, University of Granada Lorenzo Fontolan, Janelia Research Campus
Source: neuroschool19.liphlab.com
