Life in a chaotic universe: an interview with Ilya Prigogine
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Abstract
Interview with Nobel Prize-winning physicist, Ilya Prigogine, which I had extraordinary difficulty publishing in the notoriously conservative and philosophically hide-bound Anglo-Saxon media, also rejected by Metascience, as clearly too controversial for then-editor, Jon Forge!
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Experimenting Arts and Sciences. Proceedings of the 2nd European Consortium of the International Society for Literature and Science
2020
We consider evolution of the Universe based on the standard Big Bang model, quantum models of creation, and recent theory of nonlinear dynamics, including deterministic chaos and fractals. We show that by looking for an order and harmony in the the complex surrounding real world these modern studies give also new insight into the most important philosophical issues exceeding the classical ontological principles, e.g., providing a deeper understanding of an old philosophical question: why does something exist instead of nothing? We postulate that the origin of Universe is based on a simple but nonlinear law. Finally, it is worth noting that in mathematical-natural sciences we ought to look for the sense of the world in the mystery of rationality; the sense of every existence is the justification of the Universe. Finally, we argue that this scientific view provides also sense and hope to a human existence.
Physica D: Nonlinear Phenomena, 1999
International Journal of Advances in Production Research, 2024
Prigogine's theory of dissipative structures provides a general account of entropy-driven self-organized transitions through hierarchies of structures separated by discontinuities. The theory encompasses a wide range of evolving systems throughout nature and culture. Possibilities for operationalizing a new collective rationality spanning physics and psychology emerge from Prigogine's emphases on two distinct senses of probability, on the concept of the sufficient statistic, and on the role and limitations of the Poisson distribution in formulating a "nonlinear master equation." Unnoted by Prigogine are correspondences of all three of these issues in the mathematical foundations of statistics and measurement established in the works of Ronald Fisher and his student, Georg Rasch. The three areas of correspondence inform models enabling specifically metrological approaches to quality-assured quantification across the sciences. Prigogine's sense of "deterministic chaos" is re-expressed in measurement terms as stochastic invariance and the need for "a supplementary parameter" augmenting the Poisson distribution is related to a rating scale model of measurement. Considering these connections, this paper proposes that what Prigogine anticipates as a "new intelligibility" and a new science of "collective rationality" could be pragmatically operationalized in a new metrological infrastructure, one made coherent by the generality of entropydriven nonequilibrium processes.
This book describes the birth of the new theory of Chaos. This is a difficult new concept that is still evolving but it popularized the term: Butterfly Effect and introduced new concepts to a popular audience, such as fractals and introduced pioneering thinkers, such as Feigenbaum and Mandelbrot; it inspired the novel and movie Jurassic Park. This concept opens up a new view of nature: where previously randomness had to be forced in to explain the unpredictable variations, now chaos is seen as spanning both order (patterns) and disorder. Now, this phenomenon helps explain the shape of clouds, smoke, water eddies, mountain ranges and coastlines. Implicitly, it shows how Newtonian mathematics has constrained physics (and science in general) to make simplifying assumptions that enable the calculus to become the universal tool-set of the scientific viewpoint. The book describes how this tough problem was cracked by five theoreticians described herein with a novelist's eye. Key to the solution was the early use of computers to repeat simple calculations, very many times. The viewpoint changed from static 'state' to dynamic process: becoming rather than being. Chaos is everywhere, it is switching the simple mathematical models of classical physics. It is the science of the global nature of systems. I show here (but not in the book or Wiki) that this is the start of the Death of Newtonian Physics and the Calculus: a TRUE REVOLUTION.
Cornell University - arXiv, 2015
Web Journal of Current Legal Issues, 2002
The version presented here may differ from the published version. If citing, you are advised to consult the published version for pagination, volume/issue and date of publication Tettenborn, 'From chaos to cosmos-or is it confusion?', [2002] 2 WEB JCLI
The British Journal for the Philosophy of Science, 2001
Explaining Chaos is an informative, original and enjoyable introduction to chaos theory and its associated philosophical problems. The book does not presuppose any previous background in chaos theory. Nevertheless, the discussion may be as interesting to experienced readers as it is to novices. In particular, several mathematical interludes deepen the discussion of technical issues and provide numerous interesting insights that could further enlighten readers already familiar with the central ideas. The reader will ®nd an accessible discussion striking a good balance between scienti®c and philosophical topics. Unfortunately, the physical and the philosophical parts are uneven in quality. While the treatment of the scienti®c issues is thorough and skilful, the philosophical discussions have signi®cant lacunas. Nevertheless, Smith's enthusiasm for exploring these issues is contagious and the book is a valuable contribution to a ®eld that has, despite its importance, received little attention from philosophers so far. Explaining Chaos consists of ten chapters that could be divided into two main categories: the mathematics and physics of chaos, and the implications of chaos for scienti®c practice and methodology. In Chapters 1 (dynamical systems), 2 (fractals), 6 (universality), 8 (experimental evidence for chaos), and 9 (randomness), Smith introduces the central topics of chaos theory and discusses important results. In Chapter 10, he addresses the question of how chaos could adequately be de®ned. On the whole, these chapters provide a very knowledgeable and skilful presentation of the basics of chaos theory. In Chapters 3 (models and simplicity), 4 (prediction), 5 (approximate truth), and 7 (explanation), Smith considers the methodological implications of chaos theory. Here, he aims at showing that chaos, though an interesting and exciting ®eld of investigation, by no means requires a revision of the basic traits of scienti®c methodology. Smith successfully resists the temptation to be carried away by fancy bold claims and, on the contrary, argues that chaos theory may be considered a respectable tool for decent scienti®c research.
Studia Philosophica Estonica, 2013
In recent years, computational sciences such as computational hydrodynamics or computational field theory have supplemented theoretical and experimental investigations in many scientific fields. Often, there is a seemingly fruitful overlap between theory, experiment, and numerics. The computational sciences are highly dynamic and seem a fairly successful endeavor---at least if success is measured in terms of publications or engineering applications. However, for theories, success in application and correctness are two very different things; and just the same may hold for "methodologies" like computer simulations. A lively debate on the epistemic status of computer simulations has thus emerged within the philosophy of science. This paper discusses possible problems when computer simulation and laboratory experiment are intertwined. In present experiments, stochastic methods in the form of Monte Carlo simulations are often involved in generating experimental data. It is ques...
British Journal for The Philosophy of Science, 2001
In his recent book, Explaining Chaos, Peter Smith presents a new problem in the foundations of chaos theory. Speci®cally, he argues that the standard ways of justifying idealizations in mathematical models fail when it comes to the in®nite intricacy found in strange attractors. I argue that Smith's analysis undermines much of the explanatory power of chaos theory. A better approach is developed by drawing analogies from the models found in continuum mechanics. Brit. J. Phil. Sci. 52 (2001), 683±700 & British Society for the Philosophy of Science 2001

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