A Fascination with Fractals Richard Taylor Richard
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Writing the History of Dynamical Systems and Chaos
Historia Mathematica 29 (2002), 273–339 doi:10.1006/hmat.2002.2351 Writing the History of Dynamical Systems and Chaos: View metadata, citation and similar papersLongue at core.ac.uk Dur´ee and Revolution, Disciplines and Cultures1 brought to you by CORE provided by Elsevier - Publisher Connector David Aubin Max-Planck Institut fur¨ Wissenschaftsgeschichte, Berlin, Germany E-mail: [email protected] and Amy Dahan Dalmedico Centre national de la recherche scientifique and Centre Alexandre-Koyre,´ Paris, France E-mail: [email protected] Between the late 1960s and the beginning of the 1980s, the wide recognition that simple dynamical laws could give rise to complex behaviors was sometimes hailed as a true scientific revolution impacting several disciplines, for which a striking label was coined—“chaos.” Mathematicians quickly pointed out that the purported revolution was relying on the abstract theory of dynamical systems founded in the late 19th century by Henri Poincar´e who had already reached a similar conclusion. In this paper, we flesh out the historiographical tensions arising from these confrontations: longue-duree´ history and revolution; abstract mathematics and the use of mathematical techniques in various other domains. After reviewing the historiography of dynamical systems theory from Poincar´e to the 1960s, we highlight the pioneering work of a few individuals (Steve Smale, Edward Lorenz, David Ruelle). We then go on to discuss the nature of the chaos phenomenon, which, we argue, was a conceptual reconfiguration as -
Lewis Fry Richardson: Scientist, Visionary and Pacifist
Lett Mat Int DOI 10.1007/s40329-014-0063-z Lewis Fry Richardson: scientist, visionary and pacifist Angelo Vulpiani Ó Centro P.RI.ST.EM, Universita` Commerciale Luigi Bocconi 2014 Abstract The aim of this paper is to present the main The last of seven children in a thriving English Quaker aspects of the life of Lewis Fry Richardson and his most family, in 1898 Richardson enrolled in Durham College of important scientific contributions. Of particular importance Science, and two years later was awarded a grant to study are the seminal concepts of turbulent diffusion, turbulent at King’s College in Cambridge, where he received a cascade and self-similar processes, which led to a profound diverse education: he read physics, mathematics, chemis- transformation of the way weather forecasts, turbulent try, meteorology, botany, and psychology. At the beginning flows and, more generally, complex systems are viewed. of his career he was quite uncertain about which road to follow, but he later resolved to work in several areas, just Keywords Lewis Fry Richardson Á Weather forecasting Á like the great German scientist Helmholtz, who was a Turbulent diffusion Á Turbulent cascade Á Numerical physician and then a physicist, but following a different methods Á Fractals Á Self-similarity order. In his words, he decided ‘‘to spend the first half of my life under the strict discipline of physics, and after- Lewis Fry Richardson (1881–1953), while undeservedly wards to apply that training to researches on living things’’. little known, had a fundamental (often posthumous) role in In addition to contributing important results to meteo- twentieth-century science. -
Decomposing the Dynamics of the Lorenz 1963 Model Using Unstable
Decomposing the Dynamics of the Lorenz 1963 model using Unstable Periodic Orbits: Averages, Transitions, and Quasi-Invariant Sets Chiara Cecilia Maiocchi∗ and Valerio Lucarini† Centre for the Mathematics of Planet Earth, University of Reading and Department of Mathematics and Statistics, University of Reading Unstable periodic orbits (UPOs) are a valuable tool for studying chaotic dynamical systems. They allow one to extract information from a system and to distill its dynamical structure. We consider here the Lorenz 1963 model with the classic parameters’ value and decompose its dynamics in terms of UPOs. We investigate how a chaotic orbit can be approximated in terms of UPOs. At each instant, we rank the UPOs according to their proximity to the position of the orbit in the phase space. We study this process from two different perspectives. First, we find that, somewhat unexpectedly, longer period UPOs overwhelmingly provide the best local approximation to the trajectory, even if our UPO-detecting algorithm severely undersamples them. Second, we construct a finite-state Markov chain by studying the scattering of the forward trajectory between the neighbourhood of the various UPOs. Each UPO and its neighbourhood are taken as a possible state of the system. We then study the transitions between the different states. Through the analysis of the subdominant eigenvectors of the corresponding stochastic matrix we provide a different interpretation of the mixing processes occurring in the system by taking advantage of the concept of quasi-invariant sets. I. INTRODUCTION would suffice in obtaining an accurate approximation of ergodic averages [70–72]. These results are proven to be Unstable periodic orbits (UPOs) play an important valid for dynamical systems exhibiting strong chaoticity role in the analysis of dynamical systems that exhibit [73, 74], such as hyperbolic and Axiom A systems chaotic behaviour and in some cases they provide a [75, 76]. -
EGU 2018 EGU – Abstracts
CEN @ EGU 2018 EGU – abstracts Summary of Presentations, Sessions, Orals, PICOs and Posters by CEN/ CliSAP Scientists www.clisap.de www.cen.uni-hamburg.de https://twitter.com/CENunihh Presentations @ EGU 2018 CliSAP/CEN/UHH Member/Presenter; CliSAP/CEN/UHH Member Monday, 9th of April Sessions TS10.2 Hypervelocity impact cratering: Mechanics and environmental consequences Convener: Ulrich Riller | Co-Convener: Michael Poelchau Orals / Mon, 09 Apr, 10:30–12:00 / Room 1.61 Posters / Attendance Mon, 09 Apr, 17:30–19:00 / Hall X2 Orals BG1.1, Application of stable isotopes in Biogeosciences (co-organized by the European Association of Geochemistry (EAG) , Orals, 08:30–10:00, Room 2.20 09:00– EGU2018-19620 Nitrate sources in the catchment basin of the Rhône River by 09:15 Alexander Bratek, Kirstin Daehnke, Tina Sanders, and Jürgen Möbius OS2.4, Oceanography at coastal scales. Modelling, coupling, observations and benefits from coastal Research Infrastructures , Orals, 10:30–12:00, Room 1.85 EGU2018-7112 Synergy between satellite observations and model simulations 11:15– during extreme events by Anne Wiese, Joanna Staneva, Arno Behrens, Johannes 11:30 Schulz-Stellenfleth, and Luciana Fenoglio-Marc Sessions / Orals / Posters TS10.2, Hypervelocity impact cratering: Mechanics and environmental consequences , Orals, 10:30–12:00, Room 1.61 11:30– EGU2018-4309 Dynamics of the thermal aureole of the Sudbury impact melt 11:45 sheet, Canada by Paul Göllner and Ulrich Riller GD8.3/GMPV9.4/TS9.10, The geology of the Azores: a comprehensive approach to understanding a unique geological, geochemical and geodynamic setting (co-organized) , PICO, 15:30–17:00, PICO spot 3 15:30– EGU2018-8375 The submarine geology of the Azores Plateau – insights from 15:32 marine reflection seismic and multi-beam imaging by Christian Huebscher PICO3.1 15:56– EGU2018-9441 Extensional forces in intraplate magmatism: constraints from 15:58 Faial Island, Azores by René H.W. -
The Mathematical Heritage of Henri Poincaré
http://dx.doi.org/10.1090/pspum/039.1 THE MATHEMATICAL HERITAGE of HENRI POINCARE PROCEEDINGS OF SYMPOSIA IN PURE MATHEMATICS Volume 39, Part 1 THE MATHEMATICAL HERITAGE Of HENRI POINCARE AMERICAN MATHEMATICAL SOCIETY PROVIDENCE, RHODE ISLAND PROCEEDINGS OF SYMPOSIA IN PURE MATHEMATICS OF THE AMERICAN MATHEMATICAL SOCIETY VOLUME 39 PROCEEDINGS OF THE SYMPOSIUM ON THE MATHEMATICAL HERITAGE OF HENRI POINCARfe HELD AT INDIANA UNIVERSITY BLOOMINGTON, INDIANA APRIL 7-10, 1980 EDITED BY FELIX E. BROWDER Prepared by the American Mathematical Society with partial support from National Science Foundation grant MCS 79-22916 1980 Mathematics Subject Classification. Primary 01-XX, 14-XX, 22-XX, 30-XX, 32-XX, 34-XX, 35-XX, 47-XX, 53-XX, 55-XX, 57-XX, 58-XX, 70-XX, 76-XX, 83-XX. Library of Congress Cataloging in Publication Data Main entry under title: The Mathematical Heritage of Henri Poincare\ (Proceedings of symposia in pure mathematics; v. 39, pt. 1— ) Bibliography: p. 1. Mathematics—Congresses. 2. Poincare', Henri, 1854—1912— Congresses. I. Browder, Felix E. II. Series: Proceedings of symposia in pure mathematics; v. 39, pt. 1, etc. QA1.M4266 1983 510 83-2774 ISBN 0-8218-1442-7 (set) ISBN 0-8218-1449-4 (part 2) ISBN 0-8218-1448-6 (part 1) ISSN 0082-0717 COPYING AND REPRINTING. Individual readers of this publication, and nonprofit librar• ies acting for them are permitted to make fair use of the material, such as to copy an article for use in teaching or research. Permission is granted to quote brief passages from this publication in re• views provided the customary acknowledgement of the source is given. -
Τα Cellular Automata Στο Σχεδιασμό
τα cellular automata στο σχεδιασμό μια προσέγγιση στις αναδρομικές σχεδιαστικές διαδικασίες Ηρώ Δημητρίου επιβλέπων Σωκράτης Γιαννούδης 2 Πολυτεχνείο Κρήτης Τμήμα Αρχιτεκτόνων Μηχανικών ερευνητική εργασία Ηρώ Δημητρίου επιβλέπων καθηγητής Σωκράτης Γιαννούδης Τα Cellular Automata στο σχεδιασμό μια προσέγγιση στις αναδρομικές σχεδιαστικές διαδικασίες Χανιά, Μάιος 2013 Chaos and Order - Carlo Allarde περιεχόμενα 0001. εισαγωγή 7 0010. χάος και πολυπλοκότητα 13 a. μια ιστορική αναδρομή στο χάος: Henri Poincare - Edward Lorenz 17 b. το χάος 22 c. η πολυπλοκότητα 23 d. αυτοοργάνωση και emergence 29 0011. cellular automata 31 0100. τα cellular automata στο σχεδιασμό 39 a. τα CA στην στην αρχιτεκτονική: Paul Coates 45 b. η φιλοσοφική προσέγγιση της διεπιστημονικότητας του σχεδιασμού 57 c. προσομοίωση της αστικής ανάπτυξης μέσω CA 61 d. η περίπτωση της Changsha 63 0101. συμπεράσματα 71 βιβλιογραφία 77 1. Metamorphosis II - M.C.Escher 6 0001. εισαγωγή Η επιστήμη εξακολουθεί να είναι η εξ αποκαλύψεως προφητική περιγραφή του κόσμου, όπως αυτός φαίνεται από ένα θεϊκό ή δαιμονικό σημείο αναφοράς. Ilya Prigogine 7 0001. 8 0001. Στοιχεία της τρέχουσας αρχιτεκτονικής θεωρίας και μεθοδολογίας προτείνουν μια εναλλακτική λύση στις πάγιες αρχιτεκτονικές μεθοδολογίες και σε ορισμένες περιπτώσεις υιοθετούν πτυχές του νέου τρόπου της κατανόησής μας για την επιστήμη. Αυτά τα στοιχεία εμπίπτουν σε τρεις κατηγορίες. Πρώτον, μεθοδολογίες που προτείνουν μια εναλλακτική λύση για τη γραμμικότητα και την αιτιοκρατία της παραδοσιακής αρχιτεκτονικής σχεδιαστικής διαδικασίας και θίγουν τον κεντρικό έλεγχο του αρχιτέκτονα, δεύτερον, η πρόταση μιας μεθοδολογίας με βάση την προσομοίωση της αυτο-οργάνωσης στην ανάπτυξη και εξέλιξη των φυσικών συστημάτων και τρίτον, σε ορισμένες περιπτώσεις, συναρτήσει των δύο προηγούμενων, είναι μεθοδολογίες οι οποίες πειραματίζονται με την αναδυόμενη μορφή σε εικονικά περιβάλλοντα. -
Montana Throne Molly Gupta Laura Brannan Fractals: a Visual Display of Mathematics Linear Algebra
Montana Throne Molly Gupta Laura Brannan Fractals: A Visual Display of Mathematics Linear Algebra - Math 2270 Introduction: Fractals are infinite patterns that look similar at all levels of magnification and exist between the normal dimensions. With the advent of the computer, we can generate these complex structures to model natural structures around us such as blood vessels, heartbeat rhythms, trees, forests, and mountains, to name a few. I will begin by explaining how different linear transformations have been used to create fractals. Then I will explain how I have created fractals using linear transformations and include the computer-generated results. A Brief History: Fractals seem to be a relatively new concept in mathematics, but that may be because the term was coined only 43 years ago. It is in the century before Benoit Mandelbrot coined the term that the study of concepts now considered fractals really started to gain traction. The invention of the computer provided the computing power needed to generate fractals visually and further their study and interest. Expand on the ideas by century: 17th century ideas • Leibniz 19th century ideas • Karl Weierstrass • George Cantor • Felix Klein • Henri Poincare 20th century ideas • Helge von Koch • Waclaw Sierpinski • Gaston Julia • Pierre Fatou • Felix Hausdorff • Paul Levy • Benoit Mandelbrot • Lewis Fry Richardson • Loren Carpenter How They Work: Infinitely complex objects, revealed upon enlarging. Basics: translations, uniform scaling and non-uniform scaling then translations. Utilize translation vectors. Concepts used in fractals-- Affine Transformation (operate on individual points in the set), Rotation Matrix, Similitude Transformation Affine-- translations, scalings, reflections, rotations Insert Equations here. -
Strange Attractors in a Multisector Business Cycle Model
Journal of Economic Behavior and Organization 8 (1987) 397411. North-Holland STRANGE ATTRACTORS IN A MULTISECTOR BUSINESS CYCLE MODEL Hans-Walter LORENZ* Uniuersity of Giittingen, 34 Giittingen, FRG Received October 1985. final version received December 1986 Three coupled oscillating sectors in a multisector Kaldor-type business cycle model can give rise to the occurrence of chaotic motion. If the sectors are linked by investment demand interdependencies, this coupling can be interpreted as a perturbation of a motion on a three- dimensional torus. A theorem by Newhouse, Ruelle and Takens implies that such a perturbation may possess a strange attractor with the consequence that the flow of the perturbed system may become irregular or chaotic. A numerical investigation reveals that parameter values can be found which indeed lead to chaotic trajectories in this cycle model. 1. Introduction Recent work on chaos and strange attractors in non-linear dynamical systems has raised the question whether a ‘route to turbulence’ can be traced in a continuous-time dynamical system by means of a steady increase of a control parameter and successive bifurcations with a change of the topo- logical nature of the trajectories. A famous example for such a route to turbulence was provided by Ruelle and Takens (1971)‘: Starting with an asymptotically stable fixed point for low values of the parameter, the system undergoes a Hopf bifurcation if the control parameter is sufficiently in- creased. While a second Hopf bifurcation implies a bifurcation of the generated limit cycle to a two-dimensional torus, a third Hopf bifurcation can lead to the occurrence of a strange attractor and hence of chaos. -
Fractal Attraction Chaos: Chaotic Art Orderly Science
Fractal attraction Chaos: Chaotic Art Orderly Science “…. My wisdom is ignored as much as chaos. What’s my nothingness compared with the wonder awaiting you?” (Arthur Rimbaud). If we look up the meaning of Chaos in the dictionary, we find: "…the primordial indistinct state of all elements, the shapeless matter before creation and order in the world”. Anyway, the word Chaos has acquired a new meaning for the modern Chaos Theory (it was Jim Yorke, a mathematician of the University of Maryland, who first, in 1975, used this expression to describe those systems made of complex order structures, that gave extremely difficult predictability problems and that, spontaneously and simultaneously, produced chaos and order together). As a matter of fact, if before it was synonymous of disorder and confusion, later became, in the field of science, the definition of a system that is not only accidental, but also provided with a deeper complex structure. Just these systems are slightly influenced by every little initial variation that, as time goes by, nourishes consequences on a large scale. This phenomenon, summarized by that ironical example, known as “butterfly effect” - the air moved today in Peking by a butterfly’s wings will soon cause a tempest in New York – was discovered by Edward Lorenz at the beginning of the 60’s. By developing a simple mathematic pattern to represent the weather conditions, he discovered that the solutions of those equations were particularly influenced by the variations made at the beginning. Completely different courses took shape from almost identical starting points, and any long-term forecast was useless. -
Geometry of Chaos
Part I Geometry of chaos e start out with a recapitulation of the basic notions of dynamics. Our aim is narrow; we keep the exposition focused on prerequisites to the applications to W be developed in this text. We assume that the reader is familiar with dynamics on the level of the introductory texts mentioned in remark 1.1, and concentrate here on developing intuition about what a dynamical system can do. It will be a broad stroke description, since describing all possible behaviors of dynamical systems is beyond human ken. While for a novice there is no shortcut through this lengthy detour, a sophisticated traveler might bravely skip this well-trodden territory and embark upon the journey at chapter 18. The fate has handed you a law of nature. What are you to do with it? 1. Define your dynamical system (M; f ): the space M of its possible states, and the law f t of their evolution in time. 2. Pin it down locally–is there anything about it that is stationary? Try to determine its equilibria / fixed points (chapter2). 3. Cut across it, represent as a return map from a section to a section (chapter3). 4. Explore the neighborhood by linearizing the flow; check the linear stability of its equilibria / fixed points, their stability eigen-directions (chapters4 and5). 5. Does your system have a symmetry? If so, you must use it (chapters 10 to 12). Slice & dice it (chapter 13). 6. Go global: train by partitioning the state space of 1-dimensional maps. Label the regions by symbolic dynamics (chapter 14). -
Fractals Dalton Allan and Brian Dalke College of Science, Engineering & Technology Nominated by Amy Hlavacek, Associate Professor of Mathematics
Fractals Dalton Allan and Brian Dalke College of Science, Engineering & Technology Nominated by Amy Hlavacek, Associate Professor of Mathematics Dalton is a dual-enrolled student at Saginaw Arts and Sciences Academy and Saginaw Valley State University. He has taken mathematics classes at SVSU for the past four years and physics classes for the past year. Dalton has also worked in the Math and Physics Resource Center since September 2010. Dalton plans to continue his study of mathematics at the Massachusetts Institute of Technology. Brian is a part-time mathematics and English student. He has a B.S. degree with majors in physics and chemistry from the University of Wisconsin--Eau Claire and was a scientific researcher for The Dow Chemical Company for more than 20 years. In 2005, he was certified to teach physics, chemistry, mathematics and English and subsequently taught mostly high school mathematics for five years. Currently, he enjoys helping SVSU students as a Professional Tutor in the Math and Physics Resource Center. In his spare time, Brian finds joy playing softball, growing roses, reading, camping, and spending time with his wife, Lorelle. Introduction For much of the past two-and-one-half millennia, humans have viewed our geometrical world through the lens of a Euclidian paradigm. Despite knowing that our planet is spherically shaped, math- ematicians have developed the mathematics of non-Euclidian geometry only within the past 200 years. Similarly, only in the past century have mathematicians developed an understanding of such common phenomena as snowflakes, clouds, coastlines, lightning bolts, rivers, patterns in vegetation, and the tra- jectory of molecules in Brownian motion (Peitgen 75). -
Lewis Fry Richardson's Forecast Factory for Real
Lewis Fry Richardson’s forecast factory – for real Andrew Charlton-Perez horizontal momentum, pressure, humidity 1. Forecasts are made by solving math- and stratospheric temperature over central ematical equations which represent and Helen Dacre Europe, using initial conditions from an the physical laws governing the University of Reading analysis by Bjerknes for 20 May 1910. This atmosphere. forecast was manually computed by 2. Forecasts are often made on a grid of The idea that supercomputers are an impor- Richardson between 1916 and 1918, when, points which represent different geo- tant part of making forecasts of the weather as a Quaker (and therefore a pacifist), he graphical locations. and climate is well known amongst the gen- served as an ambulance driver in Cham- eral population. However, the details of their pagne, France. Famously, his forecast pro- use are somewhat mysterious. A concept duced very large tendencies in most of its A scaled-down forecast factory Weather – February 2011, Vol. 66, No. 2 66, No. Vol. 2011, – February Weather used to illustrate many undergraduate components – much larger than those In order to make the problem tractable for numerical weather prediction courses is the observed in the real atmosphere (Lynch, secondary-school-age children and to make idea of a giant ‘forecast factory’, conceived 2006, p.133, discusses the reasons for this). it possible to complete the activity in a rea- by Lewis Fry Richardson in 1922. In this Nonetheless, the principles of Richardson’s sonably short time (~30 minutes) it was article, a way of using the same idea to forecast, particularly the application of math- necessary to design a forecast factory which communicate key ideas in numerical ematical techniques to solving the primi - solved a much simpler problem than that weather prediction to the general public is tive equations on a grid representing the used by Richardson.