Math 402: Group Theory S. Paul Smith
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Octonion Multiplication and Heawood's
CONFLUENTES MATHEMATICI Bruno SÉVENNEC Octonion multiplication and Heawood’s map Tome 5, no 2 (2013), p. 71-76. <http://cml.cedram.org/item?id=CML_2013__5_2_71_0> © Les auteurs et Confluentes Mathematici, 2013. Tous droits réservés. L’accès aux articles de la revue « Confluentes Mathematici » (http://cml.cedram.org/), implique l’accord avec les condi- tions générales d’utilisation (http://cml.cedram.org/legal/). Toute reproduction en tout ou partie de cet article sous quelque forme que ce soit pour tout usage autre que l’utilisation á fin strictement personnelle du copiste est constitutive d’une infrac- tion pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright. cedram Article mis en ligne dans le cadre du Centre de diffusion des revues académiques de mathématiques http://www.cedram.org/ Confluentes Math. 5, 2 (2013) 71-76 OCTONION MULTIPLICATION AND HEAWOOD’S MAP BRUNO SÉVENNEC Abstract. In this note, the octonion multiplication table is recovered from a regular tesse- lation of the equilateral two timensional torus by seven hexagons, also known as Heawood’s map. Almost any article or book dealing with Cayley-Graves algebra O of octonions (to be recalled shortly) has a picture like the following Figure 0.1 representing the so-called ‘Fano plane’, which will be denoted by Π, together with some cyclic ordering on each of its ‘lines’. The Fano plane is a set of seven points, in which seven three-point subsets called ‘lines’ are specified, such that any two points are contained in a unique line, and any two lines intersect in a unique point, giving a so-called (combinatorial) projective plane [8,7]. -
An Introduction to Pythagorean Arithmetic
AN INTRODUCTION TO PYTHAGOREAN ARITHMETIC by JASON SCOTT NICHOLSON B.Sc. (Pure Mathematics), University of Calgary, 1993 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES Department of Mathematics We accept this thesis as conforming tc^ the required standard THE UNIVERSITY OF BRITISH COLUMBIA March 1996 © Jason S. Nicholson, 1996 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my i department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of The University of British Columbia Vancouver, Canada Dale //W 39, If96. DE-6 (2/88) Abstract This thesis provides a look at some aspects of Pythagorean Arithmetic. The topic is intro• duced by looking at the historical context in which the Pythagoreans nourished, that is at the arithmetic known to the ancient Egyptians and Babylonians. The view of mathematics that the Pythagoreans held is introduced via a look at the extraordinary life of Pythagoras and a description of the mystical mathematical doctrine that he taught. His disciples, the Pythagore• ans, and their school and history are briefly mentioned. Also, the lives and works of some of the authors of the main sources for Pythagorean arithmetic and thought, namely Euclid and the Neo-Pythagoreans Nicomachus of Gerasa, Theon of Smyrna, and Proclus of Lycia, are looked i at in more detail. -
Multiplication Fact Strategies Assessment Directions and Analysis
Multiplication Fact Strategies Wichita Public Schools Curriculum and Instructional Design Mathematics Revised 2014 KCCRS version Table of Contents Introduction Page Research Connections (Strategies) 3 Making Meaning for Operations 7 Assessment 9 Tools 13 Doubles 23 Fives 31 Zeroes and Ones 35 Strategy Focus Review 41 Tens 45 Nines 48 Squared Numbers 54 Strategy Focus Review 59 Double and Double Again 64 Double and One More Set 69 Half and Then Double 74 Strategy Focus Review 80 Related Equations (fact families) 82 Practice and Review 92 Wichita Public Schools 2014 2 Research Connections Where Do Fact Strategies Fit In? Adapted from Randall Charles Fact strategies are considered a crucial second phase in a three-phase program for teaching students basic math facts. The first phase is concept learning. Here, the goal is for students to understand the meanings of multiplication and division. In this phase, students focus on actions (i.e. “groups of”, “equal parts”, “building arrays”) that relate to multiplication and division concepts. An important instructional bridge that is often neglected between concept learning and memorization is the second phase, fact strategies. There are two goals in this phase. First, students need to recognize there are clusters of multiplication and division facts that relate in certain ways. Second, students need to understand those relationships. These lessons are designed to assist with the second phase of this process. If you have students that are not ready, you will need to address the first phase of concept learning. The third phase is memorization of the basic facts. Here the goal is for students to master products and quotients so they can recall them efficiently and accurately, and retain them over time. -
Some Mathematics
Copyright Cambridge University Press 2003. On-screen viewing permitted. Printing not permitted. http://www.cambridge.org/0521642981 You can buy this book for 30 pounds or $50. See http://www.inference.phy.cam.ac.uk/mackay/itila/ for links. C Some Mathematics C.1 Finite field theory Most linear codes are expressed in the language of Galois theory Why are Galois fields an appropriate language for linear codes? First, a defi- nition and some examples. AfieldF is a set F = {0,F} such that 1. F forms an Abelian group under an addition operation ‘+’, with + 01 · 01 0 being the identity; [Abelian means all elements commute, i.e., 0 01 0 00 satisfy a + b = b + a.] 1 10 1 01 2. F forms an Abelian group under a multiplication operation ‘·’; multiplication of any element by 0 yields 0; Table C.1. Addition and 3. these operations satisfy the distributive rule (a + b) · c = a · c + b · c. multiplication tables for GF (2). For example, the real numbers form a field, with ‘+’ and ‘·’denoting ordinary addition and multiplication. + 01AB 0 01AB AGaloisfieldGF q q ( ) is a field with a finite number of elements . 1 10BA A unique Galois field exists for any q = pm,wherep is a prime number A AB 01 and m is a positive integer; there are no other finite fields. B BA10 · 01AB GF (2). The addition and multiplication tables for GF (2) are shown in ta- 0 00 0 0 ble C.1. These are the rules of addition and multiplication modulo 2. 1 01AB A AB GF (p). -
Math 311 - Introduction to Proof and Abstract Mathematics Group Assignment # 15 Name: Due: at the End of Class on Tuesday, March 26Th
Math 311 - Introduction to Proof and Abstract Mathematics Group Assignment # 15 Name: Due: At the end of class on Tuesday, March 26th More on Functions: Definition 5.1.7: Let A, B, C, and D be sets. Let f : A B and g : C D be functions. Then f = g if: → → A = C and B = D • For all x A, f(x)= g(x). • ∈ Intuitively speaking, this definition tells us that a function is determined by its underlying correspondence, not its specific formula or rule. Another way to think of this is that a function is determined by the set of points that occur on its graph. 1. Give a specific example of two functions that are defined by different rules (or formulas) but that are equal as functions. 2. Consider the functions f(x)= x and g(x)= √x2. Find: (a) A domain for which these functions are equal. (b) A domain for which these functions are not equal. Definition 5.1.9 Let X be a set. The identity function on X is the function IX : X X defined by, for all x X, → ∈ IX (x)= x. 3. Let f(x)= x cos(2πx). Prove that f(x) is the identity function when X = Z but not when X = R. Definition 5.1.10 Let n Z with n 0, and let a0,a1, ,an R such that an = 0. The function p : R R is a ∈ ≥ ··· ∈ 6 n n−1 → polynomial of degree n with real coefficients a0,a1, ,an if for all x R, p(x)= anx +an−1x + +a1x+a0. -
1 Monoids and Groups
1 Monoids and groups 1.1 Definition. A monoid is a set M together with a map M × M ! M; (x; y) 7! x · y such that (i) (x · y) · z = x · (y · z) 8x; y; z 2 M (associativity); (ii) 9e 2 M such that x · e = e · x = x for all x 2 M (e = the identity element of M). 1.2 Examples. 1) Z with addition of integers (e = 0) 2) Z with multiplication of integers (e = 1) 3) Mn(R) = fthe set of all n × n matrices with coefficients in Rg with ma- trix multiplication (e = I = the identity matrix) 4) U = any set P (U) := fthe set of all subsets of Ug P (U) is a monoid with A · B := A [ B and e = ?. 5) Let U = any set F (U) := fthe set of all functions f : U ! Ug F (U) is a monoid with multiplication given by composition of functions (e = idU = the identity function). 1.3 Definition. A monoid is commutative if x · y = y · x for all x; y 2 M. 1.4 Example. Monoids 1), 2), 4) in 1.2 are commutative; 3), 5) are not. 1 1.5 Note. Associativity implies that for x1; : : : ; xk 2 M the expression x1 · x2 ····· xk has the same value regardless how we place parentheses within it; e.g.: (x1 · x2) · (x3 · x4) = ((x1 · x2) · x3) · x4 = x1 · ((x2 · x3) · x4) etc. 1.6 Note. A monoid has only one identity element: if e; e0 2 M are identity elements then e = e · e0 = e0 1.7 Definition. -
Lecture 3 Partially Ordered Sets
Lecture 3 Partially ordered sets Now for something totally different. In life, useful sets are rarely “just” sets. They often come with additional structure. For example, R isn’t useful just because it’s some set. It’s useful because we can add its elements, multiply its elements, and even compare its elements. If A is, for example, the set of all bananas and apples on earth, it’s not as natural to do any of these things with elements of A. Today, we’ll talk about a structure called a partial order. 3.1 Preliminaries First, let me remind you of something called the Cartesian product, or direct product of sets. Definition 3.1.1. Let A and B be sets. Then the Cartesian product of A and B is defined to be the set consisting of all pairs (a, b) where a A and œ b B. We denote the Cartesian product by œ A B. ◊ Example 3.1.2. R2 is the Cartesian product R R. ◊ Example 3.1.3. Let T be the set of all t-shirts in Hiro’s closet, and S the set of all shorts in Hiro’s closet. Then S T represents the collection of all ◊ possible outfits Hiro is willing to consider in August. (I.e., Hiro is willing to consider putting on any of his shorts together with any of his t-shirts.) 23 24 LECTURE 3. PARTIALLY ORDERED SETS Note that we can “repeat” the Cartesian product operation, or apply it many times at once. Example 3.1.4. -
Lecture 19: Alternating Group
MATH 433 Applied Algebra Lecture 19: Alternating group. Abstract groups. Sign of a permutation Theorem 1 For any n ≥ 2 there exists a unique function sgn : S(n) → {−1, 1} such that • sgn(πσ)= sgn(π) sgn(σ) for all π, σ ∈ S(n), • sgn(τ)= −1 for any transposition τ in S(n). A permutation π is called even if it is a product of an even number of transpositions, and odd if it is a product of an odd number of transpositions. It turns out that π is even if sgn(π)=1 and odd if sgn(π)= −1. Theorem 2 (i) sgn(πσ)= sgn(π) sgn(σ) for any π, σ ∈ S(n). (ii) sgn(π−1)= sgn(π) for any π ∈ S(n). (iii) sgn(id) = 1. (iv) sgn(τ)= −1 for any transposition τ. (v) sgn(σ)=(−1)r−1 for any cycle σ of length r. Alternating group Given an integer n ≥ 2, the alternating group on n symbols, denoted An or A(n), is the set of all even permutations in the symmetric group S(n). Theorem (i) For any two permutations π, σ ∈ A(n), the product πσ is also in A(n). (ii) The identity function id is in A(n). (iii) For any permutation π ∈ A(n), the inverse π−1 is in A(n). In other words, the product of even permutations is even, the identity function is an even permutation, and the inverse of an even permutation is even. Theorem The alternating group A(n) has n!/2 elements. -
Theoretical Probability and Statistics
Theoretical Probability and Statistics Charles J. Geyer Copyright 1998, 1999, 2000, 2001, 2008 by Charles J. Geyer September 5, 2008 Contents 1 Finite Probability Models 1 1.1 Probability Mass Functions . 1 1.2 Events and Measures . 5 1.3 Random Variables and Expectation . 6 A Greek Letters 9 B Sets and Functions 11 B.1 Sets . 11 B.2 Intervals . 12 B.3 Functions . 12 C Summary of Brand-Name Distributions 14 C.1 The Discrete Uniform Distribution . 14 C.2 The Bernoulli Distribution . 14 i Chapter 1 Finite Probability Models The fundamental idea in probability theory is a probability model, also called a probability distribution. Probability models can be specified in several differ- ent ways • probability mass function (PMF), • probability density function (PDF), • distribution function (DF), • probability measure, and • function mapping from one probability model to another. We will meet probability mass functions and probability measures in this chap- ter, and will meet others later. The terms “probability model” and “probability distribution” don’t indicate how the model is specified, just that it is specified somehow. 1.1 Probability Mass Functions A probability mass function (PMF) is a function pr Ω −−−−→ R which satisfies the following conditions: its values are nonnegative pr(ω) ≥ 0, ω ∈ Ω (1.1a) and sum to one X pr(ω) = 1. (1.1b) ω∈Ω The domain Ω of the PMF is called the sample space of the probability model. The sample space is required to be nonempty in order that (1.1b) make sense. 1 CHAPTER 1. FINITE PROBABILITY MODELS 2 In this chapter we require all sample spaces to be finite sets. -
Inverse Monoids Associated with the Complexity Class NP
Inverse monoids associated with the complexity class NP J.C. Birget 6 March 2017 Abstract We study the P versus NP problem through properties of functions and monoids, continuing the work of [3]. Here we consider inverse monoids whose properties and relationships determine whether P is different from NP, or whether injective one-way functions (with respect to worst-case complexity) exist. 1 Introduction We give a few definitions before motivating the monoid approach to the P versus NP problem. Some of these notions appeared already in [3]. By function we mean a partial function A∗ → A∗, where A is a finite alphabet (usually, A = {0, 1}), and A∗ denotes the set of all finite strings over A. Let Dom(f) (⊆ A∗) denote the domain of f, i.e., {x ∈ A∗ : f(x) is defined}; and let Im(f) (⊆ A∗) denote the image (or range) of f, i.e., {f(x) : x ∈ ∗ ∗ Dom(f)}. The length of x ∈ A is denoted by |x|. The restriction of f to X ⊆ A is denoted by f|X , and the identity function on X is denoted by idX or id|X . Definition 1.1 (inverse, co-inverse, mutual inverse) A function f ′ is an inverse of a function f iff f ◦ f ′ ◦ f = f. In that case we also say that f is a co-inverse of f ′. If f ′ is both an inverse and a co-inverse of f, we say that f ′ is a mutual inverse of f, or that f ′ and f are mutual inverses (of each other).1 It is easy to see that f ′ is an inverse of f iff for every y ∈ Im(f): f ′(y) is defined and f ′(y) ∈ f −1(y). -
Math 131: Introduction to Topology 1
Math 131: Introduction to Topology 1 Professor Denis Auroux Fall, 2019 Contents 9/4/2019 - Introduction, Metric Spaces, Basic Notions3 9/9/2019 - Topological Spaces, Bases9 9/11/2019 - Subspaces, Products, Continuity 15 9/16/2019 - Continuity, Homeomorphisms, Limit Points 21 9/18/2019 - Sequences, Limits, Products 26 9/23/2019 - More Product Topologies, Connectedness 32 9/25/2019 - Connectedness, Path Connectedness 37 9/30/2019 - Compactness 42 10/2/2019 - Compactness, Uncountability, Metric Spaces 45 10/7/2019 - Compactness, Limit Points, Sequences 49 10/9/2019 - Compactifications and Local Compactness 53 10/16/2019 - Countability, Separability, and Normal Spaces 57 10/21/2019 - Urysohn's Lemma and the Metrization Theorem 61 1 Please email Beckham Myers at [email protected] with any corrections, questions, or comments. Any mistakes or errors are mine. 10/23/2019 - Category Theory, Paths, Homotopy 64 10/28/2019 - The Fundamental Group(oid) 70 10/30/2019 - Covering Spaces, Path Lifting 75 11/4/2019 - Fundamental Group of the Circle, Quotients and Gluing 80 11/6/2019 - The Brouwer Fixed Point Theorem 85 11/11/2019 - Antipodes and the Borsuk-Ulam Theorem 88 11/13/2019 - Deformation Retracts and Homotopy Equivalence 91 11/18/2019 - Computing the Fundamental Group 95 11/20/2019 - Equivalence of Covering Spaces and the Universal Cover 99 11/25/2019 - Universal Covering Spaces, Free Groups 104 12/2/2019 - Seifert-Van Kampen Theorem, Final Examples 109 2 9/4/2019 - Introduction, Metric Spaces, Basic Notions The instructor for this course is Professor Denis Auroux. His email is [email protected] and his office is SC539. -
19. Automorphism Group of S Definition-Lemma 19.1. Let G Be A
19. Automorphism group of Sn Definition-Lemma 19.1. Let G be a group. The automorphism group of G, denoted Aut(G), is the subgroup of A(Sn) of all automorphisms of G. Proof. We check that Aut(G) is closed under products and inverses. Suppose that φ and 2 Aut(G). Let ξ = φ ◦ . If g and h 2 G then ξ(gh) = (φ ◦ )(gh) = φ( (gh)) = φ( (g) (h)) = φ( (g))φ( (h)) = (φ ◦ )(g)(φ ◦ )(h) = ξ(g)ξ(h): Thus ξ = φ◦ is a group homomorphism. Thus Aut(G) is closed under products. Now let ξ = φ−1. If g and h 2 G then we can find g0 and h0 such that g = φ(g0) and h = φ(h0). It follows that ξ(gh) = ξ(φ(g0)φ(h0)) = ξ(φ(g0h0)) = g0h0 = ξ(g)ξ(h): Thus ξ = φ−1 is a group homomorphism. Thus Aut(G) is closed under inverses. Lemma 19.2. Let G be a group and let a 2 G. φa is the automorphism of G given by conjugation by a, φ(g) = aga−1. If a and b 2 G then φab = φaφb: Proof. Both sides are functions from G to G. We just need to check that they have the same effect on any element g of G: (φa ◦ φb)(g) = φa(φb(g)) −1 = φa(bgb ) = a(bgb−1)a−1 = (ab)g(ab)−1 = φab(g): 1 Definition-Lemma 19.3. We say that an automorphism φ of G is inner if φ = φa for some a.