Examples of Groups in Abstract Algebra Course Books
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LINEAR ALGEBRA METHODS in COMBINATORICS László Babai
LINEAR ALGEBRA METHODS IN COMBINATORICS L´aszl´oBabai and P´eterFrankl Version 2.1∗ March 2020 ||||| ∗ Slight update of Version 2, 1992. ||||||||||||||||||||||| 1 c L´aszl´oBabai and P´eterFrankl. 1988, 1992, 2020. Preface Due perhaps to a recognition of the wide applicability of their elementary concepts and techniques, both combinatorics and linear algebra have gained increased representation in college mathematics curricula in recent decades. The combinatorial nature of the determinant expansion (and the related difficulty in teaching it) may hint at the plausibility of some link between the two areas. A more profound connection, the use of determinants in combinatorial enumeration goes back at least to the work of Kirchhoff in the middle of the 19th century on counting spanning trees in an electrical network. It is much less known, however, that quite apart from the theory of determinants, the elements of the theory of linear spaces has found striking applications to the theory of families of finite sets. With a mere knowledge of the concept of linear independence, unexpected connections can be made between algebra and combinatorics, thus greatly enhancing the impact of each subject on the student's perception of beauty and sense of coherence in mathematics. If these adjectives seem inflated, the reader is kindly invited to open the first chapter of the book, read the first page to the point where the first result is stated (\No more than 32 clubs can be formed in Oddtown"), and try to prove it before reading on. (The effect would, of course, be magnified if the title of this volume did not give away where to look for clues.) What we have said so far may suggest that the best place to present this material is a mathematics enhancement program for motivated high school students. -
Problems in Abstract Algebra
STUDENT MATHEMATICAL LIBRARY Volume 82 Problems in Abstract Algebra A. R. Wadsworth 10.1090/stml/082 STUDENT MATHEMATICAL LIBRARY Volume 82 Problems in Abstract Algebra A. R. Wadsworth American Mathematical Society Providence, Rhode Island Editorial Board Satyan L. Devadoss John Stillwell (Chair) Erica Flapan Serge Tabachnikov 2010 Mathematics Subject Classification. Primary 00A07, 12-01, 13-01, 15-01, 20-01. For additional information and updates on this book, visit www.ams.org/bookpages/stml-82 Library of Congress Cataloging-in-Publication Data Names: Wadsworth, Adrian R., 1947– Title: Problems in abstract algebra / A. R. Wadsworth. Description: Providence, Rhode Island: American Mathematical Society, [2017] | Series: Student mathematical library; volume 82 | Includes bibliographical references and index. Identifiers: LCCN 2016057500 | ISBN 9781470435837 (alk. paper) Subjects: LCSH: Algebra, Abstract – Textbooks. | AMS: General – General and miscellaneous specific topics – Problem books. msc | Field theory and polyno- mials – Instructional exposition (textbooks, tutorial papers, etc.). msc | Com- mutative algebra – Instructional exposition (textbooks, tutorial papers, etc.). msc | Linear and multilinear algebra; matrix theory – Instructional exposition (textbooks, tutorial papers, etc.). msc | Group theory and generalizations – Instructional exposition (textbooks, tutorial papers, etc.). msc Classification: LCC QA162 .W33 2017 | DDC 512/.02–dc23 LC record available at https://lccn.loc.gov/2016057500 Copying and reprinting. Individual readers of this publication, and nonprofit libraries acting for them, are permitted to make fair use of the material, such as to copy select pages for use in teaching or research. Permission is granted to quote brief passages from this publication in reviews, provided the customary acknowledgment of the source is given. Republication, systematic copying, or multiple reproduction of any material in this publication is permitted only under license from the American Mathematical Society. -
Abstract Algebra
Abstract Algebra Martin Isaacs, University of Wisconsin-Madison (Chair) Patrick Bahls, University of North Carolina, Asheville Thomas Judson, Stephen F. Austin State University Harriet Pollatsek, Mount Holyoke College Diana White, University of Colorado Denver 1 Introduction What follows is a report summarizing the proposals of a group charged with developing recommendations for undergraduate curricula in abstract algebra.1 We begin by articulating the principles that shaped the discussions that led to these recommendations. We then indicate several learning goals; some of these address specific content areas and others address students' general development. Next, we include three sample syllabi, each tailored to meet the needs of specific types of institutions and students. Finally, we present a brief list of references including sample texts. 2 Guiding Principles We lay out here several principles that underlie our recommendations for undergraduate Abstract Algebra courses. Although these principles are very general, we indicate some of their specific implications in the discussions of learning goals and curricula below. Diversity of students We believe that a course in Abstract Algebra is valuable for a wide variety of students, including mathematics majors, mathematics education majors, mathematics minors, and majors in STEM disciplines such as physics, chemistry, and computer science. Such a course is essential preparation for secondary teaching and for many doctoral programs in mathematics. Moreover, algebra can capture the imagination of students whose attraction to mathematics is primarily to structure and abstraction (for example, 1As with any document that is produced by a committee, there were some disagreements and compromises. The committee members had many lively and spirited communications on what undergraduate Abstract Algebra should look like for the next ten years. -
Abstract Algebra
Abstract Algebra Paul Melvin Bryn Mawr College Fall 2011 lecture notes loosely based on Dummit and Foote's text Abstract Algebra (3rd ed) Prerequisite: Linear Algebra (203) 1 Introduction Pure Mathematics Algebra Analysis Foundations (set theory/logic) G eometry & Topology What is Algebra? • Number systems N = f1; 2; 3;::: g \natural numbers" Z = f:::; −1; 0; 1; 2;::: g \integers" Q = ffractionsg \rational numbers" R = fdecimalsg = pts on the line \real numbers" p C = fa + bi j a; b 2 R; i = −1g = pts in the plane \complex nos" k polar form re iθ, where a = r cos θ; b = r sin θ a + bi b r θ a p Note N ⊂ Z ⊂ Q ⊂ R ⊂ C (all proper inclusions, e.g. 2 62 Q; exercise) There are many other important number systems inside C. 2 • Structure \binary operations" + and · associative, commutative, and distributive properties \identity elements" 0 and 1 for + and · resp. 2 solve equations, e.g. 1 ax + bx + c = 0 has two (complex) solutions i p −b ± b2 − 4ac x = 2a 2 2 2 2 x + y = z has infinitely many solutions, even in N (thei \Pythagorian triples": (3,4,5), (5,12,13), . ). n n n 3 x + y = z has no solutions x; y; z 2 N for any fixed n ≥ 3 (Fermat'si Last Theorem, proved in 1995 by Andrew Wiles; we'll give a proof for n = 3 at end of semester). • Abstract systems groups, rings, fields, vector spaces, modules, . A group is a set G with an associative binary operation ∗ which has an identity element e (x ∗ e = x = e ∗ x for all x 2 G) and inverses for each of its elements (8 x 2 G; 9 y 2 G such that x ∗ y = y ∗ x = e). -
SUMMARY of PART II: GROUPS 1. Motivation and Overview 1.1. Why
SUMMARY OF PART II: GROUPS 1. Motivation and overview 1.1. Why study groups? The group concept is truly fundamental not only for algebra, but for mathematics in general, as groups appear in mathematical theories as diverse as number theory (e.g. the solutions of Diophantine equations often form a group), Galois theory (the solutions(=roots) of a polynomial equation may satisfy hidden symmetries which can be put together into a group), geometry (e.g. the isometries of a given geometric space or object form a group) or topology (e.g. an important tool is the fundamental group of a topological space), but also in physics (e.g. the Lorentz group which in concerned with the symmetries of space-time in relativity theory, or the “gauge” symmetry group of the famous standard model). Our task for the course is to understand whole classes of groups—mostly we will concentrate on finite groups which are already very difficult to classify. Our main examples for these shall be the cyclic groups Cn, symmetric groups Sn (on n letters), the alternating groups An and the dihedral groups Dn. The most “fundamental” of these are the symmetric groups, as every finite group can be embedded into a certain finite symmetric group (Cayley’s Theorem). We will be able to classify all groups of order 2p and p2, where p is a prime. We will also find structure results on subgroups which exist for a given such group (Cauchy’s Theorem, Sylow Theorems). Finally, abelian groups can be controlled far easier than general (i.e., possibly non-abelian) groups, and we will give a full classification for all such abelian groups, at least when they can be generated by finitely many elements. -
1 Algebra Vs. Abstract Algebra 2 Abstract Number Systems in Linear
MATH 2135, LINEAR ALGEBRA, Winter 2017 and multiplication is also called the “logical and” operation. For example, we Handout 1: Lecture Notes on Fields can calculate like this: Peter Selinger 1 · ((1 + 0) + 1) + 1 = 1 · (1 + 1) + 1 = 1 · 0 + 1 = 0+1 1 Algebra vs. abstract algebra = 1. Operations such as addition and multiplication can be considered at several dif- 2 Abstract number systems in linear algebra ferent levels: • Arithmetic deals with specific calculation rules, such as 8 + 3 = 11. It is As you already know, Linear Algebra deals with subjects such as matrix multi- usually taught in elementary school. plication, linear combinations, solutions of systems of linear equations, and so on. It makes heavy use of addition, subtraction, multiplication, and division of • Algebra deals with the idea that operations satisfy laws, such as a(b+c)= scalars (think, for example, of the rule for multiplying matrices). ab + ac. Such laws can be used, among other things, to solve equations It turns out that most of what we do in linear algebra does not rely on the spe- such as 3x + 5 = 14. cific laws of arithmetic. Linear algebra works equally well over “alternative” • Abstract algebra is the idea that we can use the laws of algebra, such as arithmetics. a(b + c) = ab + ac, while abandoning the rules of arithmetic, such as Example 2.1. Consider multiplying two matrices, using arithmetic modulo 2 8 + 3 = 11. Thus, in abstract algebra, we are able to speak of entirely instead of the usual arithmetic. different “number” systems, for example, systems in which 1+1=0. -
Algebraic Topology - Wikipedia, the Free Encyclopedia Page 1 of 5
Algebraic topology - Wikipedia, the free encyclopedia Page 1 of 5 Algebraic topology From Wikipedia, the free encyclopedia Algebraic topology is a branch of mathematics which uses tools from abstract algebra to study topological spaces. The basic goal is to find algebraic invariants that classify topological spaces up to homeomorphism, though usually most classify up to homotopy equivalence. Although algebraic topology primarily uses algebra to study topological problems, using topology to solve algebraic problems is sometimes also possible. Algebraic topology, for example, allows for a convenient proof that any subgroup of a free group is again a free group. Contents 1 The method of algebraic invariants 2 Setting in category theory 3 Results on homology 4 Applications of algebraic topology 5 Notable algebraic topologists 6 Important theorems in algebraic topology 7 See also 8 Notes 9 References 10 Further reading The method of algebraic invariants An older name for the subject was combinatorial topology , implying an emphasis on how a space X was constructed from simpler ones (the modern standard tool for such construction is the CW-complex ). The basic method now applied in algebraic topology is to investigate spaces via algebraic invariants by mapping them, for example, to groups which have a great deal of manageable structure in a way that respects the relation of homeomorphism (or more general homotopy) of spaces. This allows one to recast statements about topological spaces into statements about groups, which are often easier to prove. Two major ways in which this can be done are through fundamental groups, or more generally homotopy theory, and through homology and cohomology groups. -
Introduction to Abstract Algebra (Math 113)
Introduction to Abstract Algebra (Math 113) Alexander Paulin, with edits by David Corwin FOR FALL 2019 MATH 113 002 ONLY Contents 1 Introduction 4 1.1 What is Algebra? . 4 1.2 Sets . 6 1.3 Functions . 9 1.4 Equivalence Relations . 12 2 The Structure of + and × on Z 15 2.1 Basic Observations . 15 2.2 Factorization and the Fundamental Theorem of Arithmetic . 17 2.3 Congruences . 20 3 Groups 23 1 3.1 Basic Definitions . 23 3.1.1 Cayley Tables for Binary Operations and Groups . 28 3.2 Subgroups, Cosets and Lagrange's Theorem . 30 3.3 Generating Sets for Groups . 35 3.4 Permutation Groups and Finite Symmetric Groups . 40 3.4.1 Active vs. Passive Notation for Permutations . 40 3.4.2 The Symmetric Group Sym3 . 43 3.4.3 Symmetric Groups in General . 44 3.5 Group Actions . 52 3.5.1 The Orbit-Stabiliser Theorem . 55 3.5.2 Centralizers and Conjugacy Classes . 59 3.5.3 Sylow's Theorem . 66 3.6 Symmetry of Sets with Extra Structure . 68 3.7 Normal Subgroups and Isomorphism Theorems . 73 3.8 Direct Products and Direct Sums . 83 3.9 Finitely Generated Abelian Groups . 85 3.10 Finite Abelian Groups . 90 3.11 The Classification of Finite Groups (Proofs Omitted) . 95 4 Rings, Ideals, and Homomorphisms 100 2 4.1 Basic Definitions . 100 4.2 Ideals, Quotient Rings and the First Isomorphism Theorem for Rings . 105 4.3 Properties of Elements of Rings . 109 4.4 Polynomial Rings . 112 4.5 Ring Extensions . 115 4.6 Field of Fractions . -
The Classical Matrix Groups 1 Groups
The Classical Matrix Groups CDs 270, Spring 2010/2011 The notes provide a brief review of matrix groups. The primary goal is to motivate the lan- guage and symbols used to represent rotations (SO(2) and SO(3)) and spatial displacements (SE(2) and SE(3)). 1 Groups A group, G, is a mathematical structure with the following characteristics and properties: i. the group consists of a set of elements {gj} which can be indexed. The indices j may form a finite, countably infinite, or continous (uncountably infinite) set. ii. An associative binary group operation, denoted by 0 ∗0 , termed the group product. The product of two group elements is also a group element: ∀ gi, gj ∈ G gi ∗ gj = gk, where gk ∈ G. iii. A unique group identify element, e, with the property that: e ∗ gj = gj for all gj ∈ G. −1 iv. For every gj ∈ G, there must exist an inverse element, gj , such that −1 gj ∗ gj = e. Simple examples of groups include the integers, Z, with addition as the group operation, and the real numbers mod zero, R − {0}, with multiplication as the group operation. 1.1 The General Linear Group, GL(N) The set of all N × N invertible matrices with the group operation of matrix multiplication forms the General Linear Group of dimension N. This group is denoted by the symbol GL(N), or GL(N, K) where K is a field, such as R, C, etc. Generally, we will only consider the cases where K = R or K = C, which are respectively denoted by GL(N, R) and GL(N, C). -
Group Theory
Group theory March 7, 2016 Nearly all of the central symmetries of modern physics are group symmetries, for simple a reason. If we imagine a transformation of our fields or coordinates, we can look at linear versions of those transformations. Such linear transformations may be represented by matrices, and therefore (as we shall see) even finite transformations may be given a matrix representation. But matrix multiplication has an important property: associativity. We get a group if we couple this property with three further simple observations: (1) we expect two transformations to combine in such a way as to give another allowed transformation, (2) the identity may always be regarded as a null transformation, and (3) any transformation that we can do we can also undo. These four properties (associativity, closure, identity, and inverses) are the defining properties of a group. 1 Finite groups Define: A group is a pair G = fS; ◦} where S is a set and ◦ is an operation mapping pairs of elements in S to elements in S (i.e., ◦ : S × S ! S: This implies closure) and satisfying the following conditions: 1. Existence of an identity: 9 e 2 S such that e ◦ a = a ◦ e = a; 8a 2 S: 2. Existence of inverses: 8 a 2 S; 9 a−1 2 S such that a ◦ a−1 = a−1 ◦ a = e: 3. Associativity: 8 a; b; c 2 S; a ◦ (b ◦ c) = (a ◦ b) ◦ c = a ◦ b ◦ c We consider several examples of groups. 1. The simplest group is the familiar boolean one with two elements S = f0; 1g where the operation ◦ is addition modulo two. -
Abstract Linear Algebra Math 350
Abstract Linear Algebra Math 350 April 29, 2015 Contents 1 An introduction to vector spaces 2 1.1 Basic definitions & preliminaries . .4 1.2 Basic algebraic properties of vector spaces . .6 1.3 Subspaces . .7 2 Dimension 10 2.1 Linear combination . 10 2.2 Bases . 13 2.3 Dimension . 14 2.4 Zorn's lemma & the basis extension theorem . 16 3 Linear transformations 18 3.1 Definition & examples . 18 3.2 Rank-nullity theorem . 21 3.3 Vector space isomorphisims . 26 3.4 The matrix of a linear transformation . 28 4 Complex operators 34 4.1 Operators & polynomials . 34 4.2 Eigenvectors & eigenvalues . 36 4.3 Direct sums . 45 4.4 Generalized eigenvectors . 49 4.5 The characteristic polynomial . 54 4.6 Jordan basis theorem . 56 1 Chapter 1 An introduction to vector spaces Abstract linear algebra is one of the pillars of modern mathematics. Its theory is used in every branch of mathematics and its applications can be found all around our everyday life. Without linear algebra, modern conveniences such as the Google search algorithm, iPhones, and microprocessors would not exist. But what is abstract linear algebra? It is the study of vectors and functions on vectors from an abstract perspective. To explain what we mean by an abstract perspective, let us jump in and review our familiar notion of vectors. Recall that a vector of length n is a n × 1 array 2 3 a1 6 a2 7 6 7 ; 6 . 7 4 . 5 an where ai are real numbers, i.e., ai 2 R. It is also customary to define 82 3 9 a1 > > <>6 a2 7 => n = 6 7 j a 2 ; R 6 . -
Math 171 Abstract Algebra I: Groups & Rings Shahriar Shahriari
Course Description Math 171 Abstract Algebra I: Groups & Rings Shahriar Shahriari What is Abstract Algebra? Is there a formula|similar to the quadratic formula|for solving fifth degree algebraic equations? How do you go about finding all the integer solutions to an equation like y3 = x2 + 4? Abstract Algebra has its roots in attempts to answer these classical problems, but its methods and techniques permeate all of modern mathematics. Modern abstract algebra is organized around the axiomatic study of algebraic structures. Vector spaces|that you studied in linear algebra|are an example of an algebraic structure, but there are many more. All algebraic structures have common features, but each has its own distinct personality and its own areas of application. This first semester of abstract algebra will be devoted to the study of groups and rings. Groups are mathematicians way of capturing and analyzing symmetry while rings allow for a thorough study of arithmetical operations. The course develops groups and rings axiomatically and from first principles. While, we will prove everything along the way, we will also spend time developing mathematical intuition for these algebraic structures. From very meager beginnings, we will develop a powerful theory. My hope is that, by the end of the semester, you will have an appreciation for the depth, beauty, and power of this area of mathematics. Text. We will cover a good bit of Chapters 1{12 and 15{18 of the following text: Shahriar Shahriari, Algebra in Action, A course in groups, rings, and fields, Amer- ican Mathematical Society, 2017. Sample Questions. Here are three problems that you will be to do by the end of the course.