DOCSLIB.ORG

Mathematical Artwork in Python Collin J

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Mathematical Artwork in Python Collin J Mathematical Artwork in Python Collin J. Delker Mathematical Artwork in Python © 2020 Collin J. Delker, All Rights Reserved. Except as permitted under the United States Copyright Act of 1976, no part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written permission of the publisher, with the exception that the program listings may be entered, stored, and executed in a computer system, but they may not be reproduced for publication. Editing and Code Testing: David G. Delker https://codeismycanvas.art Albuquerque, New Mexico, USA Cover Image: Newton Polynomial fractal with orbit traps of a thin strip along the real axis and a small circle. CONTENTS: 1 Introduction 1 1.1 History ........................................... 2 1.2 Use of Python ....................................... 3 1.3 Saving your Images ................................... 5 1.4 Organization ....................................... 6 2 Math and Python Background 7 2.1 Numerical Computations ................................ 7 2.2 Trigonometric functions ................................ 9 2.3 Polar and Rectangular Coordinates .......................... 10 2.4 Coordinate Formulas .................................. 10 2.5 Complex Numbers .................................... 11 2.6 Histograms ........................................ 12 3 Computer Graphics 15 3.1 Raster Graphics ..................................... 15 3.2 Vector Graphics ...................................... 17 3.3 Representing Color ................................... 19 4 Parametric Methods 23 4.1 Pendulums ......................................... 24 4.2 Harmonographs ..................................... 27 4.3 Spirograph ........................................ 31 4.4 Non-physical Curves ................................... 33 4.5 Fancier coloring ..................................... 35 4.6 Using Many Shapes ................................... 37 4.7 Parametric Drawings .................................. 40 4.8 Examples Gallery ..................................... 47 4.9 Experiments ........................................ 51 5 Randomness 53 5.1 Random number generation .............................. 54 5.2 Making Randomized Curves .............................. 56 5.3 Physics with Randomness ............................... 62 5.4 Textured Lines ...................................... 67 5.5 Textured Shapes and Backgrounds .......................... 71 5.6 Gallery ........................................... 75 5.7 Experiments ........................................ 79 6 Orbits and Escape Fractals 81 6.1 Iterative systems ..................................... 81 i 6.2 Escape Time ........................................ 86 6.3 Variations ......................................... 92 6.4 Refining .......................................... 95 6.5 Exploring ......................................... 100 6.6 Gallery ........................................... 100 6.7 Experiments ........................................ 102 7 Orbit Traps 103 7.1 Trap shapes ........................................ 109 7.2 Trap coloring methods ................................. 113 7.3 Multiple Traps ...................................... 118 7.4 Recurrence functions .................................. 119 7.5 Tips ............................................. 120 7.6 Examples ......................................... 121 7.7 Experiments ........................................ 123 8 Orbit Density Fractals 125 8.1 Attractors ......................................... 125 8.2 Coloring techniques ................................... 131 8.3 Orbits that Escape .................................... 137 8.4 Examples Gallery ..................................... 142 8.5 Experiments ........................................ 143 9 The Buddhabrot 145 9.1 Optimizations ....................................... 150 9.2 Iteration Depth ...................................... 151 9.3 Noise ............................................ 153 9.4 Coloring .......................................... 155 9.5 Zooming .......................................... 157 9.6 Minimum Iterations ................................... 157 9.7 Gallery ........................................... 163 9.8 Experiments ........................................ 166 10 Color Theory 167 10.1 Hue, Saturation, Lightness ............................... 167 10.2 Color Wheels ....................................... 168 10.3 Palettes and Schemes .................................. 171 10.4 Gradients ......................................... 174 10.5 Experiments ........................................ 177 11 Composition 179 11.1 Simplicity ......................................... 179 11.2 Rule of Thirds ....................................... 180 11.3 Leading Lines and Curves ............................... 181 11.4 Balance ........................................... 182 11.5 Framing .......................................... 183 11.6 Avoid Mergers ...................................... 184 12 Polishing the Image 185 12.1 Antialiasing ........................................ 185 12.2 Color Limitations ..................................... 187 12.3 File Formats ........................................ 188 12.4 Preparing for print .................................... 189 12.5 Workflow .......................................... 193 ii 13 APPENDIX: Code 195 13.1 Python Setup ....................................... 195 13.2 Color Conversions .................................... 196 13.3 Interactive Jupyter Fractals .............................. 199 14 APPENDIX: About this Book 201 14.1 Writing a book in Jupyter ................................ 201 14.2 About the Author ..................................... 203 Bibliography 205 iii iv CHAPTER ONE INTRODUCTION When I was in college, I decided I should learn some Python programming. Most engineering students at the time used MATLAB for programming and data analysis work, but because of licensing issues, MATLAB was only available in the university’s compter labs, and I was too cheap to buy the student version. One cold weekend, I really wasn’t keen on trekking off through a foot of snow to the computer lab just to finish some data analysis I was working on, but I kept hearing good things about the Python language. Rather than venturing out in the cold, I stayed in my cozy bedroom office and decided to see what Python could do. Since most of my research work involved visualizing measurement data with different kinds of plots, I decided the best way to learn how to use Python for data and plotting was to figure out how to use it to make fractals. After installing Python and a few libraries on my laptop, it just took an hour or two to learn enough code to make my first Mandelbrot set, one of the original fractal images first discovered, show up on the screen. Amazed at how easyitwas to do things in Python, I quickly picked it up and used it for all my research data processing needs. Like almost every student, I found plenty of excuses to procrastinate on school work and do other things that weren’t about getting closer to graduating. Before long I was experimenting with other fractal variations and eventually set up my first website, on the university server, with some of the images I created. While a lot of computer programmers experiment with making fractals and like to use fractal computations to run benchmark tests of their code and hardware, the artistic side of fractal design is often neglected. Search the internet for fractals and, while there are many beautiful ones out there, you’ll find even more that look like plots from a journal paper - maybe mathe- matically correct but having no regard for composition, color, or aesthetics. This book aims to bridge the gaps between the math, the programming, and the design of algorithmically- based art. The artist needs aspects of all three to make the best images. We won’t go deeply into any one of these three aspects, but hopefully I will provide enough background on each of them to make some interesting images that can be considered pieces of art. The other goal of this book is to show how this style of art can be made from its roots as mathematical equations. There are many canned software programs, both stand-alone ap- plications and programming libraries, that make it easy to create fractals, but they become magic black-box machines where the user punches in a few random numbers and out comes an image. When I have used these, I was left unsatisfied with having no understanding of what really was going on behind the scenes. What’s the fun in making art based on math when we don’t actually understand the math? This book avoids any pre-compiled libraries and gets down to the basics of the equations themselves. By implementing the code from the ground up, we will know exactly what is going on and how to adjust it to do what we want. Prerequisites for this book include a basic understanding of math, including algebra and a lit- tle trigonometry. Some of the art is based on simple physics, such as the relationship between 1 Mathematical Artwork in Python distance, velocity, and acceleration, but both the math and physics should be understandable at a high-school level. Familiarity with the Python programming language is also assumed, although enough background and examples are given that this book could also be a good com- panion for advancing the reader’s Python skills, just as the first
Load more

Recommended publications
  • Mathematics Is a Gentleman's Art: Analysis and Synthesis in American College Geometry Teaching, 1790-1840 Amy K
    Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 2000 Mathematics is a gentleman's art: Analysis and synthesis in American college geometry teaching, 1790-1840 Amy K. Ackerberg-Hastings Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Higher Education and Teaching Commons, History of Science, Technology, and Medicine Commons, and the Science and Mathematics Education Commons Recommended Citation Ackerberg-Hastings, Amy K., "Mathematics is a gentleman's art: Analysis and synthesis in American college geometry teaching, 1790-1840 " (2000). Retrospective Theses and Dissertations. 12669. https://lib.dr.iastate.edu/rtd/12669 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margwis, and improper alignment can adversely affect reproduction. in the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted.
    [Show full text]
  • Recurrence Plots for the Analysis of Complex Systems Norbert Marwan∗, M
    Physics Reports 438 (2007) 237–329 www.elsevier.com/locate/physrep Recurrence plots for the analysis of complex systems Norbert Marwan∗, M. Carmen Romano, Marco Thiel, Jürgen Kurths Nonlinear Dynamics Group, Institute of Physics, University of Potsdam, Potsdam 14415, Germany Accepted 3 November 2006 Available online 12 January 2007 editor: I. Procaccia Abstract Recurrence is a fundamental property of dynamical systems, which can be exploited to characterise the system’s behaviour in phase space. A powerful tool for their visualisation and analysis called recurrence plot was introduced in the late 1980’s. This report is a comprehensive overview covering recurrence based methods and their applications with an emphasis on recent developments. After a brief outline of the theory of recurrences, the basic idea of the recurrence plot with its variations is presented. This includes the quantification of recurrence plots, like the recurrence quantification analysis, which is highly effective to detect, e. g., transitions in the dynamics of systems from time series. A main point is how to link recurrences to dynamical invariants and unstable periodic orbits. This and further evidence suggest that recurrences contain all relevant information about a system’s behaviour. As the respective phase spaces of two systems change due to coupling, recurrence plots allow studying and quantifying their interaction. This fact also provides us with a sensitive tool for the study of synchronisation of complex systems. In the last part of the report several applications of recurrence plots in economy, physiology, neuroscience, earth sciences, astrophysics and engineering are shown. The aim of this work is to provide the readers with the know how for the application of recurrence plot based methods in their own field of research.
    [Show full text]
  • Feasibility Study for Teaching Geometry and Other Topics Using Three-Dimensional Printers
    Feasibility Study For Teaching Geometry and Other Topics Using Three-Dimensional Printers Elizabeth Ann Slavkovsky A Thesis in the Field of Mathematics for Teaching for the Degree of Master of Liberal Arts in Extension Studies Harvard University October 2012 Abstract Since 2003, 3D printer technology has shown explosive growth, and has become significantly less expensive and more available. 3D printers at a hobbyist level are available for as little as $550, putting them in reach of individuals and schools. In addition, there are many “pay by the part” 3D printing services available to anyone who can design in three dimensions. 3D graphics programs are also widely available; where 10 years ago few could afford the technology to design in three dimensions, now anyone with a computer can download Google SketchUp or Blender for free. Many jobs now require more 3D skills, including medical, mining, video game design, and countless other fields. Because of this, the 3D printer has found its way into the classroom, particularly for STEM (science, technology, engineering, and math) programs in all grade levels. However, most of these programs focus mainly on the design and engineering possibilities for students. This thesis project was to explore the difficulty and benefits of the technology in the mathematics classroom. For this thesis project we researched the technology available and purchased a hobby-level 3D printer to see how well it might work for someone without extensive technology background. We sent designed parts away. In addition, we tried out Google SketchUp, Blender, Mathematica, and other programs for designing parts. We came up with several lessons and demos around the printer design.
    [Show full text]
  • The Swinging Spring: Regular and Chaotic Motion
    References The Swinging Spring: Regular and Chaotic Motion Leah Ganis May 30th, 2013 Leah Ganis The Swinging Spring: Regular and Chaotic Motion References Outline of Talk I Introduction to Problem I The Basics: Hamiltonian, Equations of Motion, Fixed Points, Stability I Linear Modes I The Progressing Ellipse and Other Regular Motions I Chaotic Motion I References Leah Ganis The Swinging Spring: Regular and Chaotic Motion References Introduction The swinging spring, or elastic pendulum, is a simple mechanical system in which many different types of motion can occur. The system is comprised of a heavy mass, attached to an essentially massless spring which does not deform. The system moves under the force of gravity and in accordance with Hooke's Law. z y r φ x k m Leah Ganis The Swinging Spring: Regular and Chaotic Motion References The Basics We can write down the equations of motion by finding the Lagrangian of the system and using the Euler-Lagrange equations. The Lagrangian, L is given by L = T − V where T is the kinetic energy of the system and V is the potential energy. Leah Ganis The Swinging Spring: Regular and Chaotic Motion References The Basics In Cartesian coordinates, the kinetic energy is given by the following: 1 T = m(_x2 +y _ 2 +z _2) 2 and the potential is given by the sum of gravitational potential and the spring potential: 1 V = mgz + k(r − l )2 2 0 where m is the mass, g is the gravitational constant, k the spring constant, r the stretched length of the spring (px2 + y 2 + z2), and l0 the unstretched length of the spring.
    [Show full text]
  • Fractal Growth on the Surface of a Planet and in Orbit Around It
    Wilfrid Laurier University Scholars Commons @ Laurier Physics and Computer Science Faculty Publications Physics and Computer Science 10-2014 Fractal Growth on the Surface of a Planet and in Orbit around It Ioannis Haranas Wilfrid Laurier University, [email protected] Ioannis Gkigkitzis East Carolina University, [email protected] Athanasios Alexiou Ionian University Follow this and additional works at: https://scholars.wlu.ca/phys_faculty Part of the Mathematics Commons, and the Physics Commons Recommended Citation Haranas, I., Gkigkitzis, I., Alexiou, A. Fractal Growth on the Surface of a Planet and in Orbit around it. Microgravity Sci. Technol. (2014) 26:313–325. DOI: 10.1007/s12217-014-9397-6 This Article is brought to you for free and open access by the Physics and Computer Science at Scholars Commons @ Laurier. It has been accepted for inclusion in Physics and Computer Science Faculty Publications by an authorized administrator of Scholars Commons @ Laurier. For more information, please contact [email protected]. 1 Fractal Growth on the Surface of a Planet and in Orbit around it 1Ioannis Haranas, 2Ioannis Gkigkitzis, 3Athanasios Alexiou 1Dept. of Physics and Astronomy, York University, 4700 Keele Street, Toronto, Ontario, M3J 1P3, Canada 2Departments of Mathematics and Biomedical Physics, East Carolina University, 124 Austin Building, East Fifth Street, Greenville, NC 27858-4353, USA 3Department of Informatics, Ionian University, Plateia Tsirigoti 7, Corfu, 49100, Greece Abstract: Fractals are defined as geometric shapes that exhibit symmetry of scale. This simply implies that fractal is a shape that it would still look the same even if somebody could zoom in on one of its parts an infinite number of times.
    [Show full text]
  • Möbius Bridges
    { Final version for JMA - Nov 2, 2017 } Möbius Bridges Carlo H. Séquin CS Division, University of California, Berkeley E-mail: [email protected] Abstract Key concepts and geometrical constraints are discussed that allow the construction of a usable bridge that is topological equivalent to a Möbius band. A multi-year search in publications and on the internet for real-world bridges that meet these requirements has not identified a single clean construction that warrants the designation “Möbius bridge,” but a few promising designs can be found. Several simple but practical designs are presented here. 1. Introduction July 2017 marks the twentieth installment of the annual Bridges conference [1], which elucidates the connections between mathematics and art, music, architecture, and many other cultural venues. This year the conference has been held in Waterloo, Canada. In its twenty-year history it has visited many places around the globe, including Seoul in South Korea, Coimbra in Portugal, Pécz in Hungary, and Leeuwarden in the Netherlands, the hometown of M.C. Escher. This conference series got started by Reza Sarhangi [2] at Southwestern College in Winfield, Kansas. After a few occurrences at this initial location, Reza Sarhangi and other core members of this conference started discussing the possibility of establishing some kind of a commemorative entity of the conference on the Winfield campus. Since Escher, Möbius, and Klein are among the heroes of this Math-Art community, suggestions included an Escher Garden, a Möbius Bridge, or a Klein Bottle House. This prompted me to study the feasibility of such entities; and over the following year, I developed some practical designs for bridges and buildings that follow the geometry of a Möbius band [3].
    [Show full text]
  • Correlated Brownian Motion and Diffusion of Defects in Spatially Extended Chaotic Systems
    Correlated Brownian motion and diffusion of defects in spatially extended chaotic systems Cite as: Chaos 29, 071104 (2019); https://doi.org/10.1063/1.5113783 Submitted: 07 June 2019 . Accepted: 29 June 2019 . Published Online: 16 July 2019 S. T. da Silva, T. L. Prado, S. R. Lopes , and R. L. Viana ARTICLES YOU MAY BE INTERESTED IN Intricate features in the lifetime and deposition of atmospheric aerosol particles Chaos: An Interdisciplinary Journal of Nonlinear Science 29, 071103 (2019); https:// doi.org/10.1063/1.5110385 Non-adiabatic membrane voltage fluctuations driven by two ligand-gated ion channels Chaos: An Interdisciplinary Journal of Nonlinear Science 29, 073108 (2019); https:// doi.org/10.1063/1.5096303 Symmetry induced group consensus Chaos: An Interdisciplinary Journal of Nonlinear Science 29, 073101 (2019); https:// doi.org/10.1063/1.5098335 Chaos 29, 071104 (2019); https://doi.org/10.1063/1.5113783 29, 071104 © 2019 Author(s). Chaos ARTICLE scitation.org/journal/cha Correlated Brownian motion and diffusion of defects in spatially extended chaotic systems Cite as: Chaos 29, 071104 (2019); doi: 10.1063/1.5113783 Submitted: 7 June 2019 · Accepted: 29 June 2019 · Published Online: 16 July 2019 View Online Export Citation CrossMark S. T. da Silva, T. L. Prado, S. R. Lopes, and R. L. Vianaa) AFFILIATIONS Departament of Physics, Federal University of Paraná, 81531-990 Curitiba, Paraná, Brazil a)Author to whom correspondence should be addressed: viana@fisica.ufpr.br ABSTRACT One of the spatiotemporal patterns exhibited by coupled map lattices with nearest-neighbor coupling is the appearance of chaotic defects, which are spatially localized regions of chaotic dynamics with a particlelike behavior.
    [Show full text]
  • Dynamics of the Elastic Pendulum Qisong Xiao; Shenghao Xia ; Corey Zammit; Nirantha Balagopal; Zijun Li Agenda
    Dynamics of the Elastic Pendulum Qisong Xiao; Shenghao Xia ; Corey Zammit; Nirantha Balagopal; Zijun Li Agenda • Introduction to the elastic pendulum problem • Derivations of the equations of motion • Real-life examples of an elastic pendulum • Trivial cases & equilibrium states • MATLAB models The Elastic Problem (Simple Harmonic Motion) 푑2푥 푑2푥 푘 • 퐹 = 푚 = −푘푥 = − 푥 푛푒푡 푑푡2 푑푡2 푚 • Solve this differential equation to find 푥 푡 = 푐1 cos 휔푡 + 푐2 sin 휔푡 = 퐴푐표푠(휔푡 − 휑) • With velocity and acceleration 푣 푡 = −퐴휔 sin 휔푡 + 휑 푎 푡 = −퐴휔2cos(휔푡 + 휑) • Total energy of the system 퐸 = 퐾 푡 + 푈 푡 1 1 1 = 푚푣푡2 + 푘푥2 = 푘퐴2 2 2 2 The Pendulum Problem (with some assumptions) • With position vector of point mass 푥 = 푙 푠푖푛휃푖 − 푐표푠휃푗 , define 푟 such that 푥 = 푙푟 and 휃 = 푐표푠휃푖 + 푠푖푛휃푗 • Find the first and second derivatives of the position vector: 푑푥 푑휃 = 푙 휃 푑푡 푑푡 2 푑2푥 푑2휃 푑휃 = 푙 휃 − 푙 푟 푑푡2 푑푡2 푑푡 • From Newton’s Law, (neglecting frictional force) 푑2푥 푚 = 퐹 + 퐹 푑푡2 푔 푡 The Pendulum Problem (with some assumptions) Defining force of gravity as 퐹푔 = −푚푔푗 = 푚푔푐표푠휃푟 − 푚푔푠푖푛휃휃 and tension of the string as 퐹푡 = −푇푟 : 2 푑휃 −푚푙 = 푚푔푐표푠휃 − 푇 푑푡 푑2휃 푚푙 = −푚푔푠푖푛휃 푑푡2 Define 휔0 = 푔/푙 to find the solution: 푑2휃 푔 = − 푠푖푛휃 = −휔2푠푖푛휃 푑푡2 푙 0 Derivation of Equations of Motion • m = pendulum mass • mspring = spring mass • l = unstreatched spring length • k = spring constant • g = acceleration due to gravity • Ft = pre-tension of spring 푚푔−퐹 • r = static spring stretch, 푟 = 푡 s 푠 푘 • rd = dynamic spring stretch • r = total spring stretch 푟푠 + 푟푑 Derivation of Equations of Motion
    [Show full text]
  • An Image Cryptography Using Henon Map and Arnold Cat Map
    International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 04 | Apr-2018 www.irjet.net p-ISSN: 2395-0072 An Image Cryptography using Henon Map and Arnold Cat Map. Pranjali Sankhe1, Shruti Pimple2, Surabhi Singh3, Anita Lahane4 1,2,3 UG Student VIII SEM, B.E., Computer Engg., RGIT, Mumbai, India 4Assistant Professor, Department of Computer Engg., RGIT, Mumbai, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - In this digital world i.e. the transmission of non- 2. METHODOLOGY physical data that has been encoded digitally for the purpose of storage Security is a continuous process via which data can 2.1 HENON MAP be secured from several active and passive attacks. Encryption technique protects the confidentiality of a message or 1. The Henon map is a discrete time dynamic system information which is in the form of multimedia (text, image, introduces by michel henon. and video).In this paper, a new symmetric image encryption 2. The map depends on two parameters, a and b, which algorithm is proposed based on Henon’s chaotic system with for the classical Henon map have values of a = 1.4 and byte sequences applied with a novel approach of pixel shuffling b = 0.3. For the classical values the Henon map is of an image which results in an effective and efficient chaotic. For other values of a and b the map may be encryption of images. The Arnold Cat Map is a discrete system chaotic, intermittent, or converge to a periodic orbit. that stretches and folds its trajectories in phase space. Cryptography is the process of encryption and decryption of 3.
    [Show full text]
  • Bridges: a World Community for Mathematical Art
    Accepted manuscript for The Mathematical Intelligencer, ISSN: 0343-6993 (print version) ISSN: 1866-7414 (electronic version) The final publication is available at Springer via http://link.springer.com/article/10.1007/s00283-016-9630-9 DOI 10.1007/s00283-016-9630-9 Bridges: A World Community for Mathematical Art Kristóf Fenyvesi Mathematical Art Reborn: Academic Gathering or Festival of the Arts? This is not the first time the Mathematical Communities column has featured the Bridges Organization: the 2005 conference1, in the breathtaking Canadian Rocky Mountains at Banff, was described in these pages by Doris Schattschneider [Schattschneider, 2006], a regular Bridges participant and Escher-specialist. The 2005 conference saw the debut of Delicious Rivers, Ellen Maddow’s play on the life of Robert Ammann, a postal worker who discovered a number of aperiodic tilings.2 Marjorie Senechal, The Mathematical Intelligencer’s current editor-in-chief, served as Maddow's consultant.3 A theatre premiér at a conference on mathematics? A production performed by mathematicians, moonlighting as actors? But this is Bridges. A quick look at the 2005 conference relays the “essence” of this scientific and artistic “happening” resembling a first-rate festival of the arts. True to its title, Renaissance Banff, the 2005 Bridges gave all members of its community, whether based in the sciences or the arts, the feeling that they had helped bring about a genuine rebirth. I use “community” in its most complete sense—including adults, children, artists, university professors, art lovers and local people—for the wealth of conference activities could only be accomplished through the participation of each and every individual present.
    [Show full text]
  • WHAT IS a CHAOTIC ATTRACTOR? 1. Introduction J. Yorke Coined the Word 'Chaos' As Applied to Deterministic Systems. R. Devane
    WHAT IS A CHAOTIC ATTRACTOR? CLARK ROBINSON Abstract. Devaney gave a mathematical definition of the term chaos, which had earlier been introduced by Yorke. We discuss issues involved in choosing the properties that characterize chaos. We also discuss how this term can be combined with the definition of an attractor. 1. Introduction J. Yorke coined the word `chaos' as applied to deterministic systems. R. Devaney gave the first mathematical definition for a map to be chaotic on the whole space where a map is defined. Since that time, there have been several different definitions of chaos which emphasize different aspects of the map. Some of these are more computable and others are more mathematical. See [9] a comparison of many of these definitions. There is probably no one best or correct definition of chaos. In this paper, we discuss what we feel is one of better mathematical definition. (It may not be as computable as some of the other definitions, e.g., the one by Alligood, Sauer, and Yorke.) Our definition is very similar to the one given by Martelli in [8] and [9]. We also combine the concepts of chaos and attractors and discuss chaotic attractors. 2. Basic definitions We start by giving the basic definitions needed to define a chaotic attractor. We give the definitions for a diffeomorphism (or map), but those for a system of differential equations are similar. The orbit of a point x∗ by F is the set O(x∗; F) = f Fi(x∗) : i 2 Z g. An invariant set for a diffeomorphism F is an set A in the domain such that F(A) = A.
    [Show full text]
  • Introduction to Ultra Fractal
    Introduction to Ultra Fractal Text and images © 2001 Kerry Mitchell Table of Contents Introduction ..................................................................................................................................... 2 Assumptions ........................................................................................................................ 2 Conventions ........................................................................................................................ 2 What Are Fractals? ......................................................................................................................... 3 Shapes with Infinite Detail .................................................................................................. 3 Defined By Iteration ........................................................................................................... 4 Approximating Infinity ....................................................................................................... 4 Using Ultra Fractal .......................................................................................................................... 6 Starting Ultra Fractal ........................................................................................................... 6 Formula ............................................................................................................................... 6 Size .....................................................................................................................................
    [Show full text]