Random Fractals

Total Page:16

File Type:pdf, Size:1020Kb

Random Fractals Random fractals Logan Axon Notre Dame March 29, 2010 Introduction What is a fractal? There is no universally agreed upon definition of \fractal". Mandelbrot took the from the Latin \fractus" meaning broken. He used it to describe sets that were too badly behaved for traditional geometry. Outline 1 Bad behavior by example 2 Fractal dimension 3 Random fractals Logan Axon (Notre Dame) Random fractals March 29, 2010 2 / 36 The Cantor middle thirds set Start with the unit interval [0; 1]. Remove the middle third to get 1 2 0; 3 [ 3 ; 1 . Continue removing middle thirds. The Cantor set C is what is left. 0 1 . C Logan Axon (Notre Dame) Random fractals March 29, 2010 3 / 36 The Cantor middle thirds set In symbols ::: E0 = [0; 1] 1 2 E1 = 0; [ ; 1 3 3 0 1 1 2 1 2 7 8 E = 0; [ ; [ ; [ ; 1 2 9 9 3 3 9 9 . 1 \ C C = Ei i=0 Exercise What is the total length of all the intervals removed in the construction of C? Logan Axon (Notre Dame) Random fractals March 29, 2010 4 / 36 Properties of the Cantor set C 1 1 It is self-similar: The part of C in 0; 3 is a scaled copy of all of C. 2 It has detail at all scales. 3 It is simple to define but hard to describe geometrically. 4 Its \local geometry" is strange: every open interval containing one point of C must contain other points of C as well as points not in C. All fractals should have these properties. Logan Axon (Notre Dame) Random fractals March 29, 2010 5 / 36 The von Koch curve 0) Begin with a unit line. 1) Replace the middle third with the top of an equilateral triangle. 2) Replace the middle third of each of the 4 line segments. The result is a continuous, nowhere differentiable curve with infinite length called the von Koch curve. Logan Axon (Notre Dame) Random fractals March 29, 2010 6 / 36 The von Koch curve Logan Axon (Notre Dame) Random fractals March 29, 2010 7 / 36 Generalizations of the von Koch curve The construction of the von Koch curve can be modified in a number of ways. The quadratic von Koch curve or Minkowski sausage: Logan Axon (Notre Dame) Random fractals March 29, 2010 8 / 36 The dragon curve Image source: Wikipedia Logan Axon (Notre Dame) Random fractals March 29, 2010 9 / 36 The Mandelbrot set Image source: http://www.math.utah.edu/~pa/math/mandelbrot/mandelbrot.html Constructed by looking at iterations of a function on C. We won't deal with this kind of fractal. Logan Axon (Notre Dame) Random fractals March 29, 2010 10 / 36 Dimension of a fractal One of the main tools in fractal geometry is fractal dimension. Warning: There are a lot of different ways to define fractal dimension (Hausdorff dimension is the most widely used). Our definition is almost Hausdorff dimension but only works for certain kinds of fractals. Idea Look at covering the fractal with smaller and smaller sets. As the sets get smaller we need more of them to cover the fractal. Measure how fast the number of sets increases as the size of the sets decreases. Logan Axon (Notre Dame) Random fractals March 29, 2010 11 / 36 3−n. Covering the Cantor set The construction of the Cantor set shows how to cover it with smaller and smaller sets. 0 1 We can cover C with: 0) 1 set of size 1; 1 1) 2 sets of size 3 ; 1 2) 4 sets of size 9 ; . n . n)2 sets of size ::: Logan Axon (Notre Dame) Random fractals March 29, 2010 12 / 36 Covering the Cantor set The construction of the Cantor set shows how to cover it with smaller and smaller sets. 0 1 We can cover C with: 0) 1 set of size 1; 1 1) 2 sets of size 3 ; 1 2) 4 sets of size 9 ; . n −n . n)2 sets of size ::: 3 . Logan Axon (Notre Dame) Random fractals March 29, 2010 12 / 36 8 −x >1 if 2 · 3 > 1 n < lim 3−nx (2n) = lim 2 · 3−x = 1 if 2 · 3−x = 1 n!1 n!1 :>0 if 2 · 3−x < 1 Fractal dimension of the Cantor set We want to measure how fast 2n grows relative to how fast 3−n shrinks. Do this by looking at lim 3−nx 2n n!1 for different values of x. Logan Axon (Notre Dame) Random fractals March 29, 2010 13 / 36 Fractal dimension of the Cantor set We want to measure how fast 2n grows relative to how fast 3−n shrinks. Do this by looking at lim 3−nx 2n n!1 for different values of x. 8 −x >1 if 2 · 3 > 1 n < lim 3−nx (2n) = lim 2 · 3−x = 1 if 2 · 3−x = 1 n!1 n!1 :>0 if 2 · 3−x < 1 Logan Axon (Notre Dame) Random fractals March 29, 2010 13 / 36 Fractal dimension of the Cantor set 8 1 0 d x y = lim 3−nx 2n n!1 The fractal dimension of the Cantor set is the value d where −nx n −x limn!1 3 (2 ) switches from 1 to 0. This happens when 2 · 3 = 1: Logan Axon (Notre Dame) Random fractals March 29, 2010 14 / 36 We wish to do this more generally. We won't always be covering with straight line segments so we need a good definition for the size of a more general set. Fractal dimension of the Cantor set 2 · 3−x = 1 () 2 = 3x () log 2 = x log 3 log 2 () x = log 3 log 2 Therefore the fractal dimension of the Cantor set is log 3 ≈ 0:6309: Logan Axon (Notre Dame) Random fractals March 29, 2010 15 / 36 Fractal dimension of the Cantor set 2 · 3−x = 1 () 2 = 3x () log 2 = x log 3 log 2 () x = log 3 log 2 Therefore the fractal dimension of the Cantor set is log 3 ≈ 0:6309: We wish to do this more generally. We won't always be covering with straight line segments so we need a good definition for the size of a more general set. Logan Axon (Notre Dame) Random fractals March 29, 2010 15 / 36 Diameter Definition The diameter of a set is the largest distance between two points in the set. To be technically correct, the diameter of a set is the supremum of the distances between two points in the set. For example: The diameter of the line segment [0; 1] is 1; The diameter of a triangle is the length of its longest side; The diameter of a rectangle is the length of its diagonal; The diameter of a disk is twice the radius. Logan Axon (Notre Dame) Random fractals March 29, 2010 16 / 36 Fractal dimension Suppose Nδ is the minimum number of sets of diameter δ needed to cover the set F . We compare how fast Nδ grows relative to the how fast δ shrinks by looking at x lim δ Nδ: δ!0+ 8 m 0 d x x y = lim δ Nδ δ!0+ Logan Axon (Notre Dame) Random fractals March 29, 2010 17 / 36 Fractal dimension x The fractal dimension of F is the value d where limδ!0+ δ Nδ switches from 1 to 0. 8 In symbols: x d = inf x : lim δ Nδ = 0 m δ!0+ 0 d The actual value limδ!0+ δ Nδd mayx be 0, 1, or anything in between. This value is called the d-dimensional measure of the set. Logan Axon (Notre Dame) Random fractals March 29, 2010 18 / 36 Why \dimension"? Why is this called fractal dimension? It agrees with our ideas of what dimension should be: The fractal dimension of a point is 0; The fractal dimension of a line is 1; . And the fractal dimension of the Cantor set is ≈ 0:6309. The Cantor set had properties \between" those of a point and a line. It makes sense that the fractal dimension of the Cantor set is between 0 and 1. Logan Axon (Notre Dame) Random fractals March 29, 2010 19 / 36 Fractal dimension of the von Koch curve Generalize the technique from the calculation for C. Again the construction tells us how to get covers of the curve. We can cover the curve with: (0) 1 full-sized copy of the curve; (1) 4 copies of the curve scaled by 1 3 ; (2) 16 copies of the curve scaled by 1 9 ; . (n)4 n copies of the curve scaled by 3−n. The diameter of the curve itself is 1. So ::: Logan Axon (Notre Dame) Random fractals March 29, 2010 20 / 36 Bestiary The dimension of a point is 0. The dimension of the Cantor middle thirds set is log 2 log 3 ≈ 0:6309: The dimension of a line is 1. log 4 The dimension of the von Koch curve is log 3 ≈ 1:262: The dimension of the Minkowski sausage is 1:5. The dimension of the dragon curve is 2. Many more on Wikipedia. Logan Axon (Notre Dame) Random fractals March 29, 2010 21 / 36 Romanesco broccoli (image source: Wikipedia) Logan Axon (Notre Dame) Random fractals March 29, 2010 22 / 36 The coast of Britain In one of his early papers on fractals Mandelbrot addressed the question, \How long is the coast of Britain?" This is a hard question in part because you get different answers depending on how much detail you include.
Recommended publications
  • Review On: Fractal Antenna Design Geometries and Its Applications
    www.ijecs.in International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume - 3 Issue -9 September, 2014 Page No. 8270-8275 Review On: Fractal Antenna Design Geometries and Its Applications Ankita Tiwari1, Dr. Munish Rattan2, Isha Gupta3 1GNDEC University, Department of Electronics and Communication Engineering, Gill Road, Ludhiana 141001, India [email protected] 2GNDEC University, Department of Electronics and Communication Engineering, Gill Road, Ludhiana 141001, India [email protected] 3GNDEC University, Department of Electronics and Communication Engineering, Gill Road, Ludhiana 141001, India [email protected] Abstract: In this review paper, we provide a comprehensive review of developments in the field of fractal antenna engineering. First we give brief introduction about fractal antennas and then proceed with its design geometries along with its applications in different fields. It will be shown how to quantify the space filling abilities of fractal geometries, and how this correlates with miniaturization of fractal antennas. Keywords – Fractals, self -similar, space filling, multiband 1. Introduction Modern telecommunication systems require antennas with irrespective of various extremely irregular curves or shapes wider bandwidths and smaller dimensions as compared to the that repeat themselves at any scale on which they are conventional antennas. This was beginning of antenna research examined. in various directions; use of fractal shaped antenna elements was one of them. Some of these geometries have been The term “Fractal” means linguistically “broken” or particularly useful in reducing the size of the antenna, while “fractured” from the Latin “fractus.” The term was coined by others exhibit multi-band characteristics. Several antenna Benoit Mandelbrot, a French mathematician about 20 years configurations based on fractal geometries have been reported ago in his book “The fractal geometry of Nature” [5].
    [Show full text]
  • Classical Math Fractals in Postscript Fractal Geometry I
    Kees van der Laan VOORJAAR 2013 49 Classical Math Fractals in PostScript Fractal Geometry I Abstract Classical mathematical fractals in BASIC are explained and converted into mean-and-lean EPSF defs, of which the .eps pictures are delivered in .pdf format and cropped to the prescribed BoundingBox when processed by Acrobat Pro, to be included easily in pdf(La)TEX, Word, … documents. The EPSF fractals are transcriptions of the Turtle Graphics BASIC codes or pro- grammed anew, recursively, based on the production rules of oriented objects. The Linden- mayer production rules are enriched by PostScript concepts. Experience gained in converting a TEX script into WYSIWYG Word is communicated. Keywords Acrobat Pro, Adobe, art, attractor, backtracking, BASIC, Cantor Dust, C curve, dragon curve, EPSF, FIFO, fractal, fractal dimension, fractal geometry, Game of Life, Hilbert curve, IDE (In- tegrated development Environment), IFS (Iterated Function System), infinity, kronkel (twist), Lauwerier, Lévy, LIFO, Lindenmayer, minimal encapsulated PostScript, minimal plain TeX, Minkowski, Monte Carlo, Photoshop, production rule, PSlib, self-similarity, Sierpiński (island, carpet), Star fractals, TACP,TEXworks, Turtle Graphics, (adaptable) user space, von Koch (island), Word Contents - Introduction - Lévy (Properties, PostScript program, Run the program, Turtle Graphics) Cantor - Lindenmayer enriched by PostScript concepts for the Lévy fractal 0 - von Koch (Properties, PostScript def, Turtle Graphics, von Koch island) Cantor1 - Lindenmayer enriched by PostScript concepts for the von Koch fractal Cantor2 - Kronkel Cantor - Minkowski 3 - Dragon figures - Stars - Game of Life - Annotated References - Conclusions (TEX mark up, Conversion into Word) - Acknowledgements (IDE) - Appendix: Fractal Dimension - Appendix: Cantor Dust Peano curves: order 1, 2, 3 - Appendix: Hilbert Curve - Appendix: Sierpiński islands Introduction My late professor Hans Lauwerier published nice, inspiring booklets about fractals with programs in BASIC.
    [Show full text]
  • Exploring the Effect of Direction on Vector-Based Fractals
    Exploring the Effect of Direction on Vector-Based Fractals Magdy Ibrahim and Robert J. Krawczyk College of Architecture Illinois Institute of Technology 3360 S. State St. Chicago, IL, 60616, USA Email: [email protected], [email protected] Abstract This paper investigates an approach to begin the study of fractals in architectural design. Vector-based fractals are studied to determine if the modification of vector direction in either the generator or the initiator will develop alternate fractal forms. The Koch Snowflake is used as the demonstrating fractal. Introduction A fractal is an object or quantity that displays self-similarity on all scales. The object need not exhibit exactly the same structure at all scales, but the same “type” of structures must appear on all scales [7]. Fractals were first discussed by Mandelbrot in the 1970s [4], but the idea was identified as early as 1925. Fractals have been investigated for their visual qualities as art, their relationship to explain natural processes, music, medicine, and in mathematics [5]. Javier Barrallo classified fractals [2] into six main groups depending on their type: 1. Fractals derived from standard geometry by using iterative transformations on an initial common figure. 2. IFS (Iterated Function Systems), this is a type of fractal introduced by Michael Barnsley. 3. Strange attractors. 4. Plasma fractals. Created with techniques like fractional Brownian motion. 5. L-Systems, also called Lindenmayer systems, were not invented to create fractals but to model cellular growth and interactions. 6. Fractals created by the iteration of complex polynomials. From the mathematical point of view, we can classify fractals into three major categories.
    [Show full text]
  • Measuring Fractal Dimension
    MEASURING FRACTALFRACTAL DIMENSION:DIMENSION: MORPHOLOGICAL ESTIMATES AND ITERATIVE OPTIMIZATIONOPTIMIZATION Petros MaragosMaragos and FangFang-Kuo -Kuo Sun Division of Applied SciencesSciences The AnalyticAnalytic SciencesSciences Corp. Harvard UniversityUniversity 55 Walkers Brook Drive Cambridge, MAMA 0213802138 Reading, MAMA 0186701867 Abstract An important characteristiccharacteristic of fractal signals isis theirtheir fractal dimension. For arbitrary fractals, an efficient approachapproach to to evaluateevaluate theirtheir fractal dimension isis thethe covering method.method. In thisthis paperpaper wewe unifyunify many of thethe current implementations ofof covering methodsmethods by usingusing morphologicalmorphological operations operations withwith varyingvarying structuring elements. Further, in the casecase of parametric fractalsfractals dependingdepending on on a a parameterparameter thatthat is in oneone-to-one -to -one correspondence correspondence with with their their fractal fractal dimension,dimension, we we develop develop an an optimizationoptimization method,method, which starts fromfrom anan initialinitial estimateestimate andand by by iteratively iteratively minimizing minimizing aa distancedistance betweenbetween thethe originaloriginal functionfunction and the classclass of all suchsuch functions,functions, spanningspanning thethe quantizedquantized parameterparameter space,space, convergesconverges to to the the truetrue fractalfractal dimension. 1 Introduction Fractals are mathematical setssets withwith aa highhigh
    [Show full text]
  • Paul S. Addison
    Page 1 Chapter 1— Introduction 1.1— Introduction The twin subjects of fractal geometry and chaotic dynamics have been behind an enormous change in the way scientists and engineers perceive, and subsequently model, the world in which we live. Chemists, biologists, physicists, physiologists, geologists, economists, and engineers (mechanical, electrical, chemical, civil, aeronautical etc) have all used methods developed in both fractal geometry and chaotic dynamics to explain a multitude of diverse physical phenomena: from trees to turbulence, cities to cracks, music to moon craters, measles epidemics, and much more. Many of the ideas within fractal geometry and chaotic dynamics have been in existence for a long time, however, it took the arrival of the computer, with its capacity to accurately and quickly carry out large repetitive calculations, to provide the tool necessary for the in-depth exploration of these subject areas. In recent years, the explosion of interest in fractals and chaos has essentially ridden on the back of advances in computer development. The objective of this book is to provide an elementary introduction to both fractal geometry and chaotic dynamics. The book is split into approximately two halves: the first—chapters 2–4—deals with fractal geometry and its applications, while the second—chapters 5–7—deals with chaotic dynamics. Many of the methods developed in the first half of the book, where we cover fractal geometry, will be used in the characterization (and comprehension) of the chaotic dynamical systems encountered in the second half of the book. In the rest of this chapter brief introductions to fractal geometry and chaotic dynamics are given, providing an insight to the topics covered in subsequent chapters of the book.
    [Show full text]
  • Ontologia De Domínio Fractal
    MÉTODOS COMPUTACIONAIS PARA A CONSTRUÇÃO DA ONTOLOGIA DE DOMÍNIO FRACTAL Ivo Wolff Gersberg Dissertação de Mestrado apresentada ao Programa de Pós-graduação em Engenharia Civil, COPPE, da Universidade Federal do Rio de Janeiro, como parte dos requisitos necessários à obtenção do título de Mestre em Engenharia Civil. Orientadores: Nelson Francisco Favilla Ebecken Luiz Bevilacqua Rio de Janeiro Agosto de 2011 MÉTODOS COMPUTACIONAIS PARA CONSTRUÇÃO DA ONTOLOGIA DE DOMÍNIO FRACTAL Ivo Wolff Gersberg DISSERTAÇÃO SUBMETIDA AO CORPO DOCENTE DO INSTITUTO ALBERTO LUIZ COIMBRA DE PÓS-GRADUAÇÃO E PESQUISA DE ENGENHARIA (COPPE) DA UNIVERSIDADE FEDERAL DO RIO DE JANEIRO COMO PARTE DOS REQUISITOS NECESSÁRIOS PARA A OBTENÇÃO DO GRAU DE MESTRE EM CIÊNCIAS EM ENGENHARIA CIVIL. Examinada por: ________________________________________________ Prof. Nelson Francisco Favilla Ebecken, D.Sc. ________________________________________________ Prof. Luiz Bevilacqua, Ph.D. ________________________________________________ Prof. Marta Lima de Queirós Mattoso, D.Sc. ________________________________________________ Prof. Fernanda Araújo Baião, D.Sc. RIO DE JANEIRO, RJ - BRASIL AGOSTO DE 2011 Gersberg, Ivo Wolff Métodos computacionais para a construção da Ontologia de Domínio Fractal/ Ivo Wolff Gersberg. – Rio de Janeiro: UFRJ/COPPE, 2011. XIII, 144 p.: il.; 29,7 cm. Orientador: Nelson Francisco Favilla Ebecken Luiz Bevilacqua Dissertação (mestrado) – UFRJ/ COPPE/ Programa de Engenharia Civil, 2011. Referências Bibliográficas: p. 130-133. 1. Ontologias. 2. Mineração de Textos. 3. Fractal. 4. Metodologia para Construção de Ontologias de Domínio. I. Ebecken, Nelson Francisco Favilla et al . II. Universidade Federal do Rio de Janeiro, COPPE, Programa de Engenharia Civil. III. Titulo. iii À minha mãe e meu pai, Basia e Jayme Gersberg. iv AGRADECIMENTOS Agradeço aos meus orientadores, professores Nelson Ebecken e Luiz Bevilacqua, pelo incentivo e paciência.
    [Show full text]
  • Exploring the Effect of Direction on Vector-Based Fractals
    BRIDGES Mathematical Connections in Art, Music, and Science Exploring the Effect of Direction on Vector-Based Fractals Magdy Ibrahim and Robert J. Krawczyk College of Architecture Dlinois Institute of Technology 3360 S. State St. Chicago, lL, 60616, USA Email: [email protected], [email protected] Abstract This paper investigates an approach to begin the study of fractals in architectural design. Vector-based fractals are studied to determine if the modification of vector direction in either the generator or the initiator will develop alternate fractal forms. The Koch Snowflake is used as the demonstrating fractal. Introduction A fractal is an object or quantity that displays self-similarity on all scales. The object need not exhibit exactly the same structure at all scales, but the same "type" of structures must appear on all scales [7]. Fractals were first discussed by Mandelbrot in the 1970s [4], but the idea was identified as early as 1925. Fractals have been investigated for their visual qualities as art, their relationship to explain natural processes, music, medicine, and in mathematics [5]. Javier Barrallo classified fractals [2] into six main groups depending on their type: 1. Fractals derived from standard geometry by using iterative transformations on an initial common figure. 2. IFS (Iterated Function Systems), this is a type of fractal introduced by Michael Barnsley. 3. Strange attractors. 4. Plasma fractals. Created with techniques like fractional Brownian motion. 5. L-Systems, also called Lindenmayer systems, were not invented to create fractals but to model cellular growth and interactions. 6. Fractals created by the iteration of complex polynomials. From the mathematical point of view, we can classify fractals into three major categories.
    [Show full text]
  • Faster Diffusion Across an Irregular Boundary
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by HAL-Polytechnique Faster Diffusion across an Irregular Boundary Anna Rozanova-Pierrat, Denis Grebenkov, Bernard Sapoval To cite this version: Anna Rozanova-Pierrat, Denis Grebenkov, Bernard Sapoval. Faster Diffusion across an Irreg- ular Boundary. Physical Review Letters, American Physical Society, 2012, 108, pp.240602. <10.1103/PhysRevLett.108.240602>. <hal-00760296> HAL Id: hal-00760296 https://hal-ecp.archives-ouvertes.fr/hal-00760296 Submitted on 5 Dec 2012 HAL is a multi-disciplinary open access L'archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destin´eeau d´ep^otet `ala diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publi´esou non, lished or not. The documents may come from ´emanant des ´etablissements d'enseignement et de teaching and research institutions in France or recherche fran¸caisou ´etrangers,des laboratoires abroad, or from public or private research centers. publics ou priv´es. Faster Diffusion across an Irregular Boundary A. Rozanova-Pierrat∗ Laboratoire de Physique de la Mati`ere Condens´ee, C.N.R.S. – Ecole Polytechnique, 91128 Palaiseau, France and Laboratoire de Mathematiques Appliquees aux Systemes, Ecole Centrale Paris, 92295 Chatenay-Malabry, France D. S. Grebenkov† and B. Sapoval‡ Laboratoire de Physique de la Mati`ere Condens´ee, C.N.R.S. – Ecole Polytechnique, 91128 Palaiseau, France (Dated: December 5, 2012) We investigate how the shape of a heat source may enhance global heat transfer at short time. An experiment is described that allows to obtain a direct visualization of heat propagation from a prefractal radiator.
    [Show full text]
  • Characterization and Analysis of Fractal
    COMPUTER-GENERATED FRACTALS WITH MEDICAL APPLICATION IN TRABECULAR BONE STRUCTURE HIZMAWATI MADZIN FACULTYUniversity OF COMPUTER SCIENCE of &Malaya INFORMATION TECHNOLOGY UNIVERSITY OF MALAYA KUALA LUMPUR 2006 COMPUTER-GENERATED FRACTALS WITH MEDICAL APPLICATION IN TRABECULAR BONE STRUCTURE HIZMAWATI MADZIN WGC030035 This project is to submitted to Faculty of Computer Science and Information Technology University of Malaya UniversityIn partial fulfillment ofof requirement Malaya for Degree of Master of Software Engineering Session 2006/2007 ABSTRACT Fractal can be described as a self-similarity, irregular shape and scale independent object. The generation of each fractal is dependent on the algorithm used. The fractal is generated using a form of computer-generated process to create complex, repetitive, mathematically based geometric shapes. There are two main aims of this research, one of which is to develop a prototype known as Fractal Generation System (FGS) whereby each type of fractal is generated by practical implementations of the theories with some adaptation in the following algorithms: IFS Iteration, Formula Iteration and Generator Iteration. FGS also caters for the calculation of the fractal dimension (FD) parameter using Box Counting Method (BCM). This parameter enables the system to characterize the irregularity and self-similarity of fractal shapes. FGS generates four types of fractals, which are Julia set, Mandelbrot set, Sierpinski Triangle and Koch Snowflake based on the three iterations. The FD values computed and fractal patterns generated by FGS agree well with theoretical values and existing fractal shapes. The second main aim is in relation to the importance of fractal application in the real world whereby it focuses on analyzing trabecular bone structure.
    [Show full text]
  • Fractals in Complexity and Geometry Xiaoyang Gu Iowa State University
    Iowa State University Capstones, Theses and Graduate Theses and Dissertations Dissertations 2009 Fractals in complexity and geometry Xiaoyang Gu Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/etd Part of the Computer Sciences Commons Recommended Citation Gu, Xiaoyang, "Fractals in complexity and geometry" (2009). Graduate Theses and Dissertations. 11026. https://lib.dr.iastate.edu/etd/11026 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 Graduate Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Fractals in complexity and geometry by Xiaoyang Gu A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Major: Computer Science Program of Study Committee: Jack H. Lutz, Major Professor Pavan Aduri Soumendra N. Lahiri Roger D. Maddux Elvira Mayordomo Giora Slutzki Iowa State University Ames, Iowa 2009 Copyright c Xiaoyang Gu, 2009. All rights reserved. ⃝ ii TABLE OF CONTENTS LIST OF FIGURES .................................. iv 1 INTRODUCTION ................................. 1 1.1 Fractals in Complexity Classes ........................... 2 1.1.1 Dimensions of Polynomial-Size Circuits .................. 2 1.1.2 Fractals and Derandomization ....................... 4 1.2 Fractals in Individual Sequences and Saturated Sets ............... 6 1.2.1 Saturated Sets with Prescribed Limit Frequencies of Digits ....... 7 1.2.2 The Copeland-Erd˝os Sequences ....................... 8 1.3 Effective Fractals in Geometry ........................... 10 1.3.1 Points on Computable Curves .......................
    [Show full text]
  • International Journal for Scientific Research & Development
    IJSRD - International Journal for Scientific Research & Development| Vol. 4, Issue 01, 2016 | ISSN (online): 2321-0613 A Review Analysis of Different Geometries on Fractal Antenna with Various Feeding Techniques Aditi Parmar Department of Master Engineering in Communication System Engineering L. J. Institute of Engineering and Technology, Gujarat Technological University, Ahmedabad, Gujarat Abstract— Fractal antennas have the unique property of self- A. What Are Fractals? similarity, generated by iterations, which means that various copies of an object can be found in the original shape object This question is a simple with a very complicated (and very at smaller scale size. A fractal is a rough or fragmented long) answer. An accurate answer, doesn't help much geometric shape that can be divided into smaller parts, each because it uses other fractal speak jargon that few people of which is (approximately) a reduced size copy of the understand, so the simple answer of a fractal is a shape that, whole. Fractal antenna is capable of performing operation when you look at a small part of it, has a similar (but with good-to-excellent performance at many different necessarily not identical) appearance to the shape of basic frequencies simultaneously at the same time. Normally initiator. Take, for example, a rocky mountain. From a standard antennas that have to be "cut" for the frequency for distance, you can see that how rocky it is; up close, the which they are to be used and thus the standard antennas surface is very similar. Little rocks have a similar surface to only work only well at that the frequency they are given.
    [Show full text]
  • Chapter 1 Fractal Geometries
    CHAPTER 1 Fractal Geometries 1.1 Introduction The end of the 1970s saw the idea of fractal geometry spread into numerous areas of physics. Indeed, the concept of fractal geometry, introduced by B. Mandelbrot, provides a solid framework for the analysis of natural phenomena in various scientific domains. As Roger Pynn wrote in Nature, “If this opinion continues to spread, we won’t have to wait long before the study of fractals becomes an obligatory part of the university curriculum.” The fractal concept brings many earlier mathematical studies within a single framework. The objects concerned were invented at the end of the 19th century by such mathematicians as Cantor, Peano, etc. The term “fractal” was introduced by B. Mandelbrot (fractal, i.e., that which has been infinitely divided, from the Latin “fractus,” derived from the verb “frangere,” to break). It is difficult to give a precise yet general definition of a fractal object; we shall define it, following Mandelbrot, as a set which shows irregularities on all scales. Fundamentally it is its geometric character which gives it such great scope; fractal geometry forms the missing complement to Euclidean geometry and crystalline symmetry.1 As Mandelbrot has remarked, clouds are not spheres, nor mountains cones, nor islands circles and their description requires a different geometrization. As we shall show, the idea of fractal geometry is closely linked to properties invariant under change of scale: a fractal structure is the same “from near or from far.” The concepts of self-similarity and scale invariance appeared independently in several fields; among these, in particular, are critical phenomena and second order phase transitions.2 We also find fractal geometries in particle trajectories, hydrodynamic lines of flux, waves, landscapes, mountains, islands and rivers, rocks, metals, and composite materials, plants, polymers, and gels, etc.
    [Show full text]