Arithmetic Algorithms for Hereditarily Binary Natural Numbers
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Homeomorphisms Group of Normed Vector Space: Conjugacy Problems
HOMEOMORPHISMS GROUP OF NORMED VECTOR SPACE: CONJUGACY PROBLEMS AND THE KOOPMAN OPERATOR MICKAEL¨ D. CHEKROUN AND JEAN ROUX Abstract. This article is concerned with conjugacy problems arising in the homeomorphisms group, Hom(F ), of unbounded subsets F of normed vector spaces E. Given two homeomor- phisms f and g in Hom(F ), it is shown how the existence of a conjugacy may be related to the existence of a common generalized eigenfunction of the associated Koopman operators. This common eigenfunction serves to build a topology on Hom(F ), where the conjugacy is obtained as limit of a sequence generated by the conjugacy operator, when this limit exists. The main conjugacy theorem is presented in a class of generalized Lipeomorphisms. 1. Introduction In this article we consider the conjugacy problem in the homeomorphisms group of a finite dimensional normed vector space E. It is out of the scope of the present work to review the problem of conjugacy in general, and the reader may consult for instance [13, 16, 29, 33, 26, 42, 45, 51, 52] and references therein, to get a partial survey of the question from a dynamical point of view. The present work raises the problem of conjugacy in the group Hom(F ) consisting of homeomorphisms of an unbounded subset F of E and is intended to demonstrate how the conjugacy problem, in such a case, may be related to spectral properties of the associated Koopman operators. In this sense, this paper provides new insights on the relations between the spectral theory of dynamical systems [5, 17, 23, 36] and the topological conjugacy problem [51, 52]1. -
Iterated Function Systems, Ruelle Operators, and Invariant Projective Measures
MATHEMATICS OF COMPUTATION Volume 75, Number 256, October 2006, Pages 1931–1970 S 0025-5718(06)01861-8 Article electronically published on May 31, 2006 ITERATED FUNCTION SYSTEMS, RUELLE OPERATORS, AND INVARIANT PROJECTIVE MEASURES DORIN ERVIN DUTKAY AND PALLE E. T. JORGENSEN Abstract. We introduce a Fourier-based harmonic analysis for a class of dis- crete dynamical systems which arise from Iterated Function Systems. Our starting point is the following pair of special features of these systems. (1) We assume that a measurable space X comes with a finite-to-one endomorphism r : X → X which is onto but not one-to-one. (2) In the case of affine Iterated Function Systems (IFSs) in Rd, this harmonic analysis arises naturally as a spectral duality defined from a given pair of finite subsets B,L in Rd of the same cardinality which generate complex Hadamard matrices. Our harmonic analysis for these iterated function systems (IFS) (X, µ)is based on a Markov process on certain paths. The probabilities are determined by a weight function W on X. From W we define a transition operator RW acting on functions on X, and a corresponding class H of continuous RW - harmonic functions. The properties of the functions in H are analyzed, and they determine the spectral theory of L2(µ).ForaffineIFSsweestablish orthogonal bases in L2(µ). These bases are generated by paths with infinite repetition of finite words. We use this in the last section to analyze tiles in Rd. 1. Introduction One of the reasons wavelets have found so many uses and applications is that they are especially attractive from the computational point of view. -
Recursion, Writing, Iteration. a Proposal for a Graphics Foundation of Computational Reason Luca M
Recursion, Writing, Iteration. A Proposal for a Graphics Foundation of Computational Reason Luca M. Possati To cite this version: Luca M. Possati. Recursion, Writing, Iteration. A Proposal for a Graphics Foundation of Computa- tional Reason. 2015. hal-01321076 HAL Id: hal-01321076 https://hal.archives-ouvertes.fr/hal-01321076 Preprint submitted on 24 May 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 1/16 Recursion, Writing, Iteration A Proposal for a Graphics Foundation of Computational Reason Luca M. Possati In this paper we present a set of philosophical analyses to defend the thesis that computational reason is founded in writing; only what can be written is computable. We will focus on the relations among three main concepts: recursion, writing and iteration. The most important questions we will address are: • What does it mean to compute something? • What is a recursive structure? • Can we clarify the nature of recursion by investigating writing? • What kind of identity is presupposed by a recursive structure and by computation? Our theoretical path will lead us to a radical revision of the philosophical notion of identity. The act of iterating is rooted in an abstract space – we will try to outline a topological description of iteration. -
CM55: Special Prime-Field Elliptic Curves Almost Optimizing Den Boer's
CM55: special prime-field elliptic curves almost optimizing den Boer's reduction between Diffie–Hellman and discrete logs Daniel R. L. Brown∗ February 24, 2015 Abstract Using the Pohlig{Hellman algorithm, den Boer reduced the discrete logarithm prob- lem to the Diffie–Hellman problem in groups of an order whose prime factors were each one plus a smooth number. This report reviews some related general conjectural lower bounds on the Diffie–Hellman problem in elliptic curve groups that relax the smoothness condition into a more commonly true condition. This report focuses on some elliptic curve parameters defined over a prime field size of size 9 + 55 × 2288, whose special form may provide some efficiency advantages over random fields of similar sizes. The curve has a point of Proth prime order 1 + 55 × 2286, which helps to nearly optimize the den Boer reduction. This curve is constructed using the CM method. It has cofactor 4, trace 6, and fundamental discriminant −55. This report also tries to consolidate the variety of ways of deciding between elliptic curves (or other algorithms) given the efficiency and security of each. Contents 1 Introduction3 2 Previous Work and Motivation4 2.1 den Boer's Reduction between DHP and DLP . .4 2.2 Complex Multiplication Method of Generating Elliptic Curves . .4 2.3 Earlier Publication of the CM55 Parameters . .4 3 Provable Security: Reducing DLP to DHP5 3.1 A Special Case of den Boer's Algorithm . .5 3.2 More Costly Reductions with Fewer Oracle Calls . .7 3.3 Relaxing the Smoothness Requirements . 11 4 Resisting Other Attacks on CM55 (if Trusted) 13 4.1 Resistance to the MOV Attack . -
Bézier Curves Are Attractors of Iterated Function Systems
New York Journal of Mathematics New York J. Math. 13 (2007) 107–115. All B´ezier curves are attractors of iterated function systems Chand T. John Abstract. The fields of computer aided geometric design and fractal geom- etry have evolved independently of each other over the past several decades. However, the existence of so-called smooth fractals, i.e., smooth curves or sur- faces that have a self-similar nature, is now well-known. Here we describe the self-affine nature of quadratic B´ezier curves in detail and discuss how these self-affine properties can be extended to other types of polynomial and ra- tional curves. We also show how these properties can be used to control shape changes in complex fractal shapes by performing simple perturbations to smooth curves. Contents 1. Introduction 107 2. Quadratic B´ezier curves 108 3. Iterated function systems 109 4. An IFS with a QBC attractor 110 5. All QBCs are attractors of IFSs 111 6. Controlling fractals with B´ezier curves 112 7. Conclusion and future work 114 References 114 1. Introduction In the late 1950s, advancements in hardware technology made it possible to effi- ciently manufacture curved 3D shapes out of blocks of wood or steel. It soon became apparent that the bottleneck in mass production of curved 3D shapes was the lack of adequate software for designing these shapes. B´ezier curves were first introduced in the 1960s independently by two engineers in separate French automotive compa- nies: first by Paul de Casteljau at Citro¨en, and then by Pierre B´ezier at R´enault. -
Goldbach's Conjecture
U.U.D.M. Project Report 2020:37 Goldbach’s Conjecture Johan Härdig Examensarbete i matematik, 15 hp Handledare: Veronica Crispin Quinonez Examinator: Martin Herschend Augusti 2020 Department of Mathematics Uppsala University Goldbach's Conjecture Johan H¨ardig Contents 1 Introduction 3 1.1 Definition of the Conjectures . 3 2 Prime Numbers and their Distribution 4 2.1 Early Results . 4 2.2 Prime Number Theorem . 6 3 Heuristic and Probabilistic Justification 8 3.1 Method Presented by Gaze & Gaze . 8 3.1.1 Sieve Method by Gaze & Gaze . 9 3.1.2 Example . 10 3.2 Prime Number Theorem for Arithmetic Progressions . 11 3.3 Distribution of Primes Across Prime Residue Classes . 14 3.4 Heuristic Justification by Gaze & Gaze . 15 3.4.1 Conclusion . 16 3.5 Goldbach's Comet . 17 4 The Ternary Goldbach's Conjecture 18 4.1 Historical Overview . 18 4.2 Approach . 19 4.3 Theorems and Methods in the Proof . 20 4.3.1 Hardy-Littlewood Circle Method . 20 4.3.2 Vinogradov's Theorem . 22 4.3.3 The Large Sieve . 24 4.3.4 L-functions . 24 4.3.5 Computational Methods . 26 4.4 The Proof . 29 1 CONTENTS 2 Abstract The following text will provide a historical perspective as well as investigate different approaches to the unsolved mathematical problem Goldbach's conjecture stated by Christian Goldbach in the year 1742. First off, there will be an overview of the early history of prime num- bers, and then a brief description of the Prime Number Theorem. Subsequently, an example of a heuristic and probabilistic method of justifying the binary Goldbach's conjecture, proposed by Gaze and Gaze, will be discussed. -
Primegrid's Mega Prime Search
PrimeGrid’s Mega Prime Search On 23 October 2012, PrimeGrid’s Proth Prime Search project found the Mega Prime: 9*23497442 +1 The prime is 1,052,836 digits long and will enter Chris Caldwell's “The Largest Known Primes Database” (http://primes.utm.edu/primes) ranked 51st overall. This prime is also a Generalized Fermat prime and ranks as the 12th largest found. The discovery was made by Heinz Ming of Switzerland using an Intel Core(TM) i7 CPU 860 @ 2.80GHz with 8GB RAM, running Windows 7 Professional. This computer took just over 5 hours 59 minutes to complete the primality test using LLR. Heinz is a member of the Aggie The Pew team. The prime was verified by Tim McArdle, a member of the Don't Panic Labs team, using an AMD Athlon(tm) II P340 Dual-Core Processor with 6 GB RAM, running Windows 7 Professional. Credits for the discovery are as follows: 1. Heinz Ming (Swtzerland), discoverer 2. PrimeGrid, et al. 3. Srsieve, sieving program developed by Geoff Reynolds 4. PSieve, sieving program developed by Ken Brazier and Geoff Reynolds 5. LLR, primality program developed by Jean Penné 6. OpenPFGW, a primality program developed by Chris Nash & Jim Fougeron with maintenance and improvements by Mark Rodenkirch OpenPFGW, a primality program developed by Chris Nash & Jim Fougeron, was used to check for Fermat Number divisibility (including generalized and extended). For more information about Fermat and generalized Fermat Number divisors, please see Wilfrid Keller's sites: http://www.prothsearch.net/fermat.html http://www1.uni-hamburg.de/RRZ/W.Keller/GFNfacs.html Generalized and extended generalized Fermat number divisors discovered are as follows: 9*2^3497442+1 is a Factor of GF(3497441,7) 9*2^3497442+1 is a Factor of xGF(3497438,9,8) 9*2^3497442+1 is a Factor of GF(3497441,10) 9*2^3497442+1 is a Factor of xGF(3497439,11,3) 9*2^3497442+1 is a Factor of xGF(3497441,12,5) Using a single PC would have taken years to find this prime. -
Summary of Unit 1: Iterated Functions 1
Summary of Unit 1: Iterated Functions 1 Summary of Unit 1: Iterated Functions David P. Feldman http://www.complexityexplorer.org/ Summary of Unit 1: Iterated Functions 2 Functions • A function is a rule that takes a number as input and outputs another number. • A function is an action. • Functions are deterministic. The output is determined only by the input. x f(x) f David P. Feldman http://www.complexityexplorer.org/ Summary of Unit 1: Iterated Functions 3 Iteration and Dynamical Systems • We iterate a function by turning it into a feedback loop. • The output of one step is used as the input for the next. • An iterated function is a dynamical system, a system that evolves in time according to a well-defined, unchanging rule. x f(x) f David P. Feldman http://www.complexityexplorer.org/ Summary of Unit 1: Iterated Functions 4 Itineraries and Seeds • We iterate a function by applying it again and again to a number. • The number we start with is called the seed or initial condition and is usually denoted x0. • The resulting sequence of numbers is called the itinerary or orbit. • It is also sometimes called a time series or a trajectory. • The iterates are denoted xt. Ex: x5 is the fifth iterate. David P. Feldman http://www.complexityexplorer.org/ Summary of Unit 1: Iterated Functions 5 Time Series Plots • A useful way to visualize an itinerary is with a time series plot. 0.8 0.7 0.6 0.5 t 0.4 x 0.3 0.2 0.1 0.0 0 1 2 3 4 5 6 7 8 9 10 time t • The time series plotted above is: 0.123, 0.189, 0.268, 0.343, 0.395, 0.418, 0.428, 0.426, 0.428, 0.429, 0.429. -
Solving Iterated Functions Using Genetic Programming Michael D
Solving Iterated Functions Using Genetic Programming Michael D. Schmidt Hod Lipson Computational Synthesis Lab Computational Synthesis Lab Cornell University Cornell University Ithaca, NY 14853 Ithaca, NY 14853 [email protected] [email protected] ABSTRACT various communities. Renowned physicist Michael Fisher is An iterated function f(x) is a function that when composed with rumored to have solved the puzzle within five minutes [2]; itself, produces a given expression f(f(x))=g(x). Iterated functions however, few have matched this feat. are essential constructs in fractal theory and dynamical systems, The problem is enticing because of its apparent simplicity. Similar but few analysis techniques exist for solving them analytically. problems such as f(f(x)) = x2, or f(f(x)) = x4 + b are straightforward Here we propose using genetic programming to find analytical (see Table 1). The fact that the slight modification from these solutions to iterated functions of arbitrary form. We demonstrate easier functions makes the problem much more challenging this technique on the notoriously hard iterated function problem of highlights the difficulty in solving iterated function problems. finding f(x) such that f(f(x))=x2–2. While some analytical techniques have been developed to find a specific solution to Table 1. A few example iterated functions problems. problems of this form, we show that it can be readily solved using genetic programming without recourse to deep mathematical Iterated Function Solution insight. We find a previously unknown solution to this problem, suggesting that genetic programming may be an essential tool for f(f(x)) = x f(x) = x finding solutions to arbitrary iterated functions. -
A Prime Experience CP.Pdf
p 2 −1 M 44 Mersenne n 2 2 −1 Fermat n 2 2( − )1 − 2 n 3 3 k × 2 +1 m − n , m = n +1 m − n n 2 + 1 3 A Prime Experience. Version 1.00 – May 2008. Written by Anthony Harradine and Alastair Lupton Copyright © Harradine and Lupton 2008. Copyright Information. The materials within, in their present form, can be used free of charge for the purpose of facilitating the learning of children in such a way that no monetary profit is made. The materials cannot be used or reproduced in any other publications or for use in any other way without the express permission of the authors. © A Harradine & A Lupton Draft, May, 2008 WIP 2 Index Section Page 1. What do you know about Primes? 5 2. Arithmetic Sequences of Prime Numbers. 6 3. Generating Prime Numbers. 7 4. Going Further. 9 5. eTech Support. 10 6. Appendix. 14 7. Answers. 16 © A Harradine & A Lupton Draft, May, 2008 WIP 3 Using this resource. This resource is not a text book. It contains material that is hoped will be covered as a dialogue between students and teacher and/or students and students. You, as a teacher, must plan carefully ‘your performance’. The inclusion of all the ‘stuff’ is to support: • you (the teacher) in how to plan your performance – what questions to ask, when and so on, • the student that may be absent, • parents or tutors who may be unfamiliar with the way in which this approach unfolds. Professional development sessions in how to deliver this approach are available. -
Iterated Function System
IARJSET ISSN (Online) 2393-8021 ISSN (Print) 2394-1588 International Advanced Research Journal in Science, Engineering and Technology ISO 3297:2007 Certified Vol. 3, Issue 8, August 2016 Iterated Function System S. C. Shrivastava Department of Applied Mathematics, Rungta College of Engineering and Technology, Bhilai C.G., India Abstract: Fractal image compression through IFS is very important for the efficient transmission and storage of digital data. Fractal is made up of the union of several copies of itself and IFS is defined by a finite number of affine transformation which characterized by Translation, scaling, shearing and rotat ion. In this paper we describe the necessary conditions to form an Iterated Function System and how fractals are generated through affine transformations. Keywords: Iterated Function System; Contraction Mapping. 1. INTRODUCTION The exploration of fractal geometry is usually traced back Metric Spaces definition: A space X with a real-valued to the publication of the book “The Fractal Geometry of function d: X × X → ℜ is called a metric space (X, d) if d Nature” [1] by the IBM mathematician Benoit B. possess the following properties: Mandelbrot. Iterated Function System is a method of constructing fractals, which consists of a set of maps that 1. d(x, y) ≥ 0 for ∀ x, y ∈ X explicitly list the similarities of the shape. Though the 2. d(x, y) = d(y, x) ∀ x, y ∈ X formal name Iterated Function Systems or IFS was coined 3. d x, y ≤ d x, z + d z, y ∀ x, y, z ∈ X . (triangle by Barnsley and Demko [2] in 1985, the basic concept is inequality). -
Aspects of Functional Iteration Milton Eugene Winger Iowa State University
Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 1972 Aspects of functional iteration Milton Eugene Winger Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Statistics and Probability Commons Recommended Citation Winger, Milton Eugene, "Aspects of functional iteration " (1972). Retrospective Theses and Dissertations. 5876. https://lib.dr.iastate.edu/rtd/5876 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 dissertation was produced from a microfilm copy of the original document. While the most advanced technological means to photograph and reproduce this document have been used, the quality is heavily dependent upon the quality of the original submitted. The following explanation of techniques is provided to help you understand markings or patterns which may appear on this reproduction. 1. The sign or "target" for pages apparently lacking from the document photographed is "Missing Page(s)". If it was possible to obtain the missing page(s) or section, they are spliced into the film along with adjacent pages. This may have necessitated cutting thru an image and duplicating adjacent pages to insure you complete continuity. 2. When an image on the film is obliterated with a large round black mark, it is an indication that the photographer suspected that the copy may have moved during exposure and thus cause a blurred image.