Fractal Geometry: History and Theory
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Fractals Self Similarity and Fractal Geometry presented by Pauline Jepp 601.73 Biological Computing Overview History Initial Monsters Details Fractals in Nature Brownian Motion L-systems Fractals defined by linear algebra operators Non-linear fractals History Euclid's 5 postulates: 1. To draw a straight line from any point to any other. 2. To produce a finite straight line continuously in a straight line. 3. To describe a circle with any centre and distance. 4. That all right angles are equal to each other. 5. That, if a straight line falling on two straight lines make the interior angles on the same side less than two right angles, if produced indefinitely, meet on that side on which are the angles less than the two right angles. History Euclid ~ "formless" patterns Mandlebrot's Fractals "Pathological" "gallery of monsters" In 1875: Continuous non-differentiable functions, ie no tangent La Femme Au Miroir 1920 Leger, Fernand Initial Monsters 1878 Cantor's set 1890 Peano's space filling curves Initial Monsters 1906 Koch curve 1960 Sierpinski's triangle Details Fractals : are self similar fractal dimension A square may be broken into N^2 self-similar pieces, each with magnification factor N Details Effective dimension Mandlebrot: " ... a notion that should not be defined precisely. It is an intuitive and potent throwback to the Pythagoreans' archaic Greek geometry" How long is the coast of Britain? Steinhaus 1954, Richardson 1961 Brownian Motion Robert Brown 1827 Jean Perrin 1906 Diffusion-limited aggregation L-Systems and Fractal Growth -
Infinite Perimeter of the Koch Snowflake And
The exact (up to infinitesimals) infinite perimeter of the Koch snowflake and its finite area Yaroslav D. Sergeyev∗ y Abstract The Koch snowflake is one of the first fractals that were mathematically described. It is interesting because it has an infinite perimeter in the limit but its limit area is finite. In this paper, a recently proposed computational methodology allowing one to execute numerical computations with infinities and infinitesimals is applied to study the Koch snowflake at infinity. Nu- merical computations with actual infinite and infinitesimal numbers can be executed on the Infinity Computer being a new supercomputer patented in USA and EU. It is revealed in the paper that at infinity the snowflake is not unique, i.e., different snowflakes can be distinguished for different infinite numbers of steps executed during the process of their generation. It is then shown that for any given infinite number n of steps it becomes possible to calculate the exact infinite number, Nn, of sides of the snowflake, the exact infinitesimal length, Ln, of each side and the exact infinite perimeter, Pn, of the Koch snowflake as the result of multiplication of the infinite Nn by the infinitesimal Ln. It is established that for different infinite n and k the infinite perimeters Pn and Pk are also different and the difference can be in- finite. It is shown that the finite areas An and Ak of the snowflakes can be also calculated exactly (up to infinitesimals) for different infinite n and k and the difference An − Ak results to be infinitesimal. Finally, snowflakes con- structed starting from different initial conditions are also studied and their quantitative characteristics at infinity are computed. -
A Tour Through Mirzakhani's Work on Moduli Spaces of Riemann Surfaces
BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY Volume 57, Number 3, July 2020, Pages 359–408 https://doi.org/10.1090/bull/1687 Article electronically published on February 3, 2020 A TOUR THROUGH MIRZAKHANI’S WORK ON MODULI SPACES OF RIEMANN SURFACES ALEX WRIGHT Abstract. We survey Mirzakhani’s work relating to Riemann surfaces, which spans about 20 papers. We target the discussion at a broad audience of non- experts. Contents 1. Introduction 359 2. Preliminaries on Teichm¨uller theory 361 3. The volume of M1,1 366 4. Integrating geometric functions over moduli space 367 5. Generalizing McShane’s identity 369 6. Computation of volumes using McShane identities 370 7. Computation of volumes using symplectic reduction 371 8. Witten’s conjecture 374 9. Counting simple closed geodesics 376 10. Random surfaces of large genus 379 11. Preliminaries on dynamics on moduli spaces 382 12. Earthquake flow 386 13. Horocyclic measures 389 14. Counting with respect to the Teichm¨uller metric 391 15. From orbits of curves to orbits in Teichm¨uller space 393 16. SL(2, R)-invariant measures and orbit closures 395 17. Classification of SL(2, R)-orbit closures 398 18. Effective counting of simple closed curves 400 19. Random walks on the mapping class group 401 Acknowledgments 402 About the author 402 References 403 1. Introduction This survey aims to be a tour through Maryam Mirzakhani’s remarkable work on Riemann surfaces, dynamics, and geometry. The star characters, all across Received by the editors May 12, 2019. 2010 Mathematics Subject Classification. Primary 32G15. c 2020 American Mathematical Society 359 License or copyright restrictions may apply to redistribution; see https://www.ams.org/journal-terms-of-use 360 ALEX WRIGHT 2 3117 4 5 12 14 16 18 19 9106 13 15 17 8 Figure 1.1. -
2010 Table of Contents Newsletter Sponsors
OKLAHOMA/ARKANSAS SECTION Volume 31, February 2010 Table of Contents Newsletter Sponsors................................................................................ 1 Section Governance ................................................................................ 6 Distinguished College/University Teacher of 2009! .............................. 7 Campus News and Notes ........................................................................ 8 Northeastern State University ............................................................. 8 Oklahoma State University ................................................................. 9 Southern Nazarene University ............................................................ 9 The University of Tulsa .................................................................... 10 Southwestern Oklahoma State University ........................................ 10 Cameron University .......................................................................... 10 Henderson State University .............................................................. 11 University of Arkansas at Monticello ............................................... 13 University of Central Oklahoma ....................................................... 14 Minutes for the 2009 Business Meeting ............................................... 15 Preliminary Announcement .................................................................. 18 The Oklahoma-Arkansas Section NExT ............................................... 21 The 2nd Annual -
President's Report
Newsletter Volume 43, No. 3 • mAY–JuNe 2013 PRESIDENT’S REPORT Greetings, once again, from 35,000 feet, returning home from a major AWM conference in Santa Clara, California. Many of you will recall the AWM 40th Anniversary conference held in 2011 at Brown University. The enthusiasm generat- The purpose of the Association ed by that conference gave rise to a plan to hold a series of biennial AWM Research for Women in Mathematics is Symposia around the country. The first of these, the AWM Research Symposium 2013, took place this weekend on the beautiful Santa Clara University campus. • to encourage women and girls to study and to have active careers The symposium attracted close to 150 participants. The program included 3 plenary in the mathematical sciences, and talks, 10 special sessions on a wide variety of topics, a contributed paper session, • to promote equal opportunity and poster sessions, a panel, and a banquet. The Santa Clara campus was in full bloom the equal treatment of women and and the weather was spectacular. Thankfully, the poster sessions and coffee breaks girls in the mathematical sciences. were held outside in a courtyard or those of us from more frigid climates might have been tempted to play hooky! The event opened with a plenary talk by Maryam Mirzakhani. Mirzakhani is a professor at Stanford and the recipient of multiple awards including the 2013 Ruth Lyttle Satter Prize. Her talk was entitled “On Random Hyperbolic Manifolds of Large Genus.” She began by describing how to associate a hyperbolic surface to a graph, then proceeded with a fascinating discussion of the metric properties of surfaces associated to random graphs. -
WHY the KOCH CURVE LIKE √ 2 1. Introduction This Essay Aims To
p WHY THE KOCH CURVE LIKE 2 XANDA KOLESNIKOW (SID: 480393797) 1. Introduction This essay aims to elucidate a connection between fractals and irrational numbers, two seemingly unrelated math- ematical objects. The notion of self-similarity will be introduced, leading to a discussion of similarity transfor- mations which are the main mathematical tool used to show this connection. The Koch curve and Koch island (or Koch snowflake) are thep two main fractals that will be used as examples throughout the essay to explain this connection, whilst π and 2 are the two examples of irrational numbers that will be discussed. Hopefully,p by the end of this essay you will be able to explain to your friends and family why the Koch curve is like 2! 2. Self-similarity An object is self-similar if part of it is identical to the whole. That is, if you are to zoom in on a particular part of the object, it will be indistinguishable from the entire object. Many objects in nature exhibit this property. For example, cauliflower appears self-similar. If you were to take a picture of a whole cauliflower (Figure 1a) and compare it to a zoomed in picture of one of its florets, you may have a hard time picking the whole cauliflower from the floret. You can repeat this procedure again, dividing the floret into smaller florets and comparing appropriately zoomed in photos of these. However, there will come a point where you can not divide the cauliflower any more and zoomed in photos of the smaller florets will be easily distinguishable from the whole cauliflower. -
Lasalle Academy Fractal Workshop – October 2006
LaSalle Academy Fractal Workshop – October 2006 Fractals Generated by Geometric Replacement Rules Sierpinski’s Gasket • Press ‘t’ • Choose ‘lsystem’ from the menu • Choose ‘sierpinski2’ from the menu • Make the order ‘0’, press ‘enter’ • Press ‘F4’ (This selects the video mode. This mode usually works well. Fractint will offer other options if you press the delete key. ‘Shift-F6’ gives more colors and better resolution, but doesn’t work on every computer.) You should see a triangle. • Press ‘z’, make the order ‘1’, ‘enter’ • Press ‘z’, make the order ‘2’, ‘enter’ • Repeat with some other orders. (Orders 8 and higher will take a LONG time, so don’t choose numbers that high unless you want to wait.) Things to Ponder Fractint repeats a simple rule many times to generate Sierpin- ski’s Gasket. The repetition of a rule is called an iteration. The order 5 image, for example, is created by performing 5 iterations. The Gasket is only complete after an infinite number of iterations of the rule. Can you figure out what the rule is? One of the characteristics of fractals is that they exhibit self-similarity on different scales. For example, consider one of the filled triangles inside of Sierpinski’s Gasket. If you zoomed in on this triangle it would look identical to the entire Gasket. You could then find a smaller triangle inside this triangle that would also look identical to the whole fractal. Sierpinski imagined the original triangle like a piece of paper. At each step, he cut out the middle triangle. How much of the piece of paper would be left if Sierpinski repeated this procedure an infinite number of times? Von Koch Snowflake • Press ‘t’, choose ‘lsystem’ from the menu, choose ‘koch1’ • Make the order ‘0’, press ‘enter’ • Press ‘z’, make the order ‘1’, ‘enter’ • Repeat for order 2 • Look at some other orders that are less than 8 (8 and higher orders take more time) Things to Ponder What is the rule that generates the von Koch snowflake? Is the von Koch snowflake self-similar in any way? Describe how. -
FRACTAL CURVES 1. Introduction “Hike Into a Forest and You Are Surrounded by Fractals. the In- Exhaustible Detail of the Livin
FRACTAL CURVES CHELLE RITZENTHALER Abstract. Fractal curves are employed in many different disci- plines to describe anything from the growth of a tree to measuring the length of a coastline. We define a fractal curve, and as a con- sequence a rectifiable curve. We explore two well known fractals: the Koch Snowflake and the space-filling Peano Curve. Addition- ally we describe a modified version of the Snowflake that is not a fractal itself. 1. Introduction \Hike into a forest and you are surrounded by fractals. The in- exhaustible detail of the living world (with its worlds within worlds) provides inspiration for photographers, painters, and seekers of spiri- tual solace; the rugged whorls of bark, the recurring branching of trees, the erratic path of a rabbit bursting from the underfoot into the brush, and the fractal pattern in the cacophonous call of peepers on a spring night." Figure 1. The Koch Snowflake, a fractal curve, taken to the 3rd iteration. 1 2 CHELLE RITZENTHALER In his book \Fractals," John Briggs gives a wonderful introduction to fractals as they are found in nature. Figure 1 shows the first three iterations of the Koch Snowflake. When the number of iterations ap- proaches infinity this figure becomes a fractal curve. It is named for its creator Helge von Koch (1904) and the interior is also known as the Koch Island. This is just one of thousands of fractal curves studied by mathematicians today. This project explores curves in the context of the definition of a fractal. In Section 3 we define what is meant when a curve is fractal. -
Lms Elections to Council and Nominating Committee 2017: Candidate Biographies
LMS ELECTIONS TO COUNCIL AND NOMINATING COMMITTEE 2017: CANDIDATE BIOGRAPHIES Candidate for election as President (1 vacancy) Caroline Series Candidates for election as Vice-President (2 vacancies) John Greenlees Catherine Hobbs Candidate for election as Treasurer (1 vacancy) Robert Curtis Candidate for election as General Secretary (1 vacancy) Stephen Huggett Candidate for election as Publications Secretary (1 vacancy) John Hunton Candidate for election as Programme Secretary (1 vacancy) Iain A Stewart Candidates for election as Education Secretary (1 vacancy) Tony Gardiner Kevin Houston Candidate for election as Librarian (Member-at-Large) (1 vacancy) June Barrow-Green Candidates for election as Member-at-Large of Council (6 x 2-year terms vacant) Mark AJ Chaplain Stephen J. Cowley Andrew Dancer Tony Gardiner Evgenios Kakariadis Katrin Leschke Brita Nucinkis Ronald Reid-Edwards Gwyneth Stallard Alina Vdovina Candidates for election to Nominating Committee (2 vacancies) H. Dugald Macpherson Martin Mathieu Andrew Treglown 1 CANDIDATE FOR ELECTION AS PRESIDENT (1 VACANCY) Caroline Series FRS, Professor of Mathematics (Emeritus), University of Warwick Email address: [email protected] Home page: http://www.maths.warwick.ac.uk/~cms/ PhD: Harvard University 1976 Previous appointments: Warwick University (Lecturer/Reader/Professor)1978-2014; EPSRC Senior Research Fellow 1999- 2004; Research Fellow, Newnham College, Cambridge 1977-8; Lecturer, Berkeley 1976-77. Research interests: Hyperbolic Geometry, Kleinian Groups, Dynamical Systems, Ergodic Theory. LMS service: Council 1989-91; Nominations Committee 1999- 2001, 2007-9, Chair 2009-12; LMS Student Texts Chief Editor 1990-2002; LMS representative to various other bodies. LMS Popular Lecturer 1999; Mary Cartwright Lecture 2000; Forder Lecturer 2003. -
Ergodic Theory, Fractal Tops and Colour Stealing 1
ERGODIC THEORY, FRACTAL TOPS AND COLOUR STEALING MICHAEL BARNSLEY Abstract. A new structure that may be associated with IFS and superIFS is described. In computer graphics applications this structure can be rendered using a new algorithm, called the “colour stealing”. 1. Ergodic Theory and Fractal Tops The goal of this lecture is to describe informally some recent realizations and work in progress concerning IFS theory with application to the geometric modelling and assignment of colours to IFS fractals and superfractals. The results will be described in the simplest setting of a single IFS with probabilities, but many generalizations are possible, most notably to superfractals. Let the iterated function system (IFS) be denoted (1.1) X; f1, ..., fN ; p1,...,pN . { } This consists of a finite set of contraction mappings (1.2) fn : X X,n=1, 2, ..., N → acting on the compact metric space (1.3) (X,d) with metric d so that for some (1.4) 0 l<1 ≤ we have (1.5) d(fn(x),fn(y)) l d(x, y) ≤ · for all x, y X.Thepn’s are strictly positive probabilities with ∈ (1.6) pn =1. n X The probability pn is associated with the map fn. We begin by reviewing the two standard structures (one and two)thatare associated with the IFS 1.1, namely its set attractor and its measure attractor, with emphasis on the Collage Property, described below. This property is of particular interest for geometrical modelling and computer graphics applications because it is the key to designing IFSs with attractor structures that model given inputs. -
Fractal Interpolation
University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2008 Fractal Interpolation Gayatri Ramesh University of Central Florida Part of the Mathematics Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Masters Thesis (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation Ramesh, Gayatri, "Fractal Interpolation" (2008). Electronic Theses and Dissertations, 2004-2019. 3687. https://stars.library.ucf.edu/etd/3687 FRACTAL INTERPOLATION by GAYATRI RAMESH B.S. University of Tennessee at Martin, 2006 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Mathematics in the College of Sciences at the University of Central Florida Orlando, Florida Fall Term 2008 ©2008 Gayatri Ramesh ii ABSTRACT This thesis is devoted to a study about Fractals and Fractal Polynomial Interpolation. Fractal Interpolation is a great topic with many interesting applications, some of which are used in everyday lives such as television, camera, and radio. The thesis is comprised of eight chapters. Chapter one contains a brief introduction and a historical account of fractals. Chapter two is about polynomial interpolation processes such as Newton’s, Hermite, and Lagrange. Chapter three focuses on iterated function systems. In this chapter I report results contained in Barnsley’s paper, Fractal Functions and Interpolation. I also mention results on iterated function system for fractal polynomial interpolation. -
Review of the Software Packages for Estimation of the Fractal Dimension
ICT Innovations 2015 Web Proceedings ISSN 1857-7288 Review of the Software Packages for Estimation of the Fractal Dimension Elena Hadzieva1, Dijana Capeska Bogatinoska1, Ljubinka Gjergjeska1, Marija Shumi- noska1, and Risto Petroski1 1 University of Information Science and Technology “St. Paul the Apostle” – Ohrid, R. Macedonia {elena.hadzieva, dijana.c.bogatinoska, ljubinka.gjergjeska}@uist.edu.mk {marija.shuminoska, risto.petroski}@cse.uist.edu.mk Abstract. The fractal dimension is used in variety of engineering and especially medical fields due to its capability of quantitative characterization of images. There are different types of fractal dimensions, among which the most used is the box counting dimension, whose estimation is based on different methods and can be done through a variety of software packages available on internet. In this pa- per, ten open source software packages for estimation of the box-counting (and other dimensions) are analyzed, tested, compared and their advantages and dis- advantages are highlighted. Few of them proved to be professional enough, reli- able and consistent software tools to be used for research purposes, in medical image analysis or other scientific fields. Keywords: Fractal dimension, box-counting fractal dimension, software tools, analysis, comparison. 1 Introduction The fractal dimension offers information relevant to the complex geometrical structure of an object, i.e. image. It represents a number that gauges the irregularity of an object, and thus can be used as a criterion for classification (as well as recognition) of objects. For instance, medical images have typical non-Euclidean, fractal structure. This fact stimulated the scientific community to apply the fractal analysis for classification and recognition of medical images, and to provide a mathematical tool for computerized medical diagnosing.