F1.3YE2 Revision Notes on Group Theory 1 Introduction 2 Binary
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Algebra I (Math 200)
Algebra I (Math 200) UCSC, Fall 2009 Robert Boltje Contents 1 Semigroups and Monoids 1 2 Groups 4 3 Normal Subgroups and Factor Groups 11 4 Normal and Subnormal Series 17 5 Group Actions 22 6 Symmetric and Alternating Groups 29 7 Direct and Semidirect Products 33 8 Free Groups and Presentations 35 9 Rings, Basic Definitions and Properties 40 10 Homomorphisms, Ideals and Factor Rings 45 11 Divisibility in Integral Domains 55 12 Unique Factorization Domains (UFD), Principal Ideal Do- mains (PID) and Euclidean Domains 60 13 Localization 65 14 Polynomial Rings 69 Chapter I: Groups 1 Semigroups and Monoids 1.1 Definition Let S be a set. (a) A binary operation on S is a map b : S × S ! S. Usually, b(x; y) is abbreviated by xy, x · y, x ∗ y, x • y, x ◦ y, x + y, etc. (b) Let (x; y) 7! x ∗ y be a binary operation on S. (i) ∗ is called associative, if (x ∗ y) ∗ z = x ∗ (y ∗ z) for all x; y; z 2 S. (ii) ∗ is called commutative, if x ∗ y = y ∗ x for all x; y 2 S. (iii) An element e 2 S is called a left (resp. right) identity, if e ∗ x = x (resp. x ∗ e = x) for all x 2 S. It is called an identity element if it is a left and right identity. (c) S together with a binary operation ∗ is called a semigroup, if ∗ is as- sociative. A semigroup (S; ∗) is called a monoid if it has an identity element. 1.2 Examples (a) Addition (resp. -
Boolean and Abstract Algebra Winter 2019
Queen's University School of Computing CISC 203: Discrete Mathematics for Computing II Lecture 7: Boolean and Abstract Algebra Winter 2019 1 Boolean Algebras Recall from your study of set theory in CISC 102 that a set is a collection of items that are related in some way by a common property or rule. There are a number of operations that can be applied to sets, like [, \, and C. Combining these operations in a certain way allows us to develop a number of identities or laws relating to sets, and this is known as the algebra of sets. In a classical logic course, the first thing you typically learn about is propositional calculus, which is the branch of logic that studies propositions and connectives between propositions. For instance, \all men are mortal" and \Socrates is a man" are propositions, and using propositional calculus, we may conclude that \Socrates is mortal". In a sense, propositional calculus is very closely related to set theory, in that propo- sitional calculus is the study of the set of propositions together with connective operations on propositions. Moreover, we can use combinations of connective operations to develop the laws of propositional calculus as well as a collection of rules of inference, which gives us even more power to manipulate propositions. Before we continue, it is worth noting that the operations mentioned previously|and indeed, most of the operations we have been using throughout these notes|have a special name. Operations like [ and \ apply to pairs of sets in the same way that + and × apply to pairs of numbers. -
7.2 Binary Operators Closure
last edited April 19, 2016 7.2 Binary Operators A precise discussion of symmetry benefits from the development of what math- ematicians call a group, which is a special kind of set we have not yet explicitly considered. However, before we define a group and explore its properties, we reconsider several familiar sets and some of their most basic features. Over the last several sections, we have considered many di↵erent kinds of sets. We have considered sets of integers (natural numbers, even numbers, odd numbers), sets of rational numbers, sets of vertices, edges, colors, polyhedra and many others. In many of these examples – though certainly not in all of them – we are familiar with rules that tell us how to combine two elements to form another element. For example, if we are dealing with the natural numbers, we might considered the rules of addition, or the rules of multiplication, both of which tell us how to take two elements of N and combine them to give us a (possibly distinct) third element. This motivates the following definition. Definition 26. Given a set S,abinary operator ? is a rule that takes two elements a, b S and manipulates them to give us a third, not necessarily distinct, element2 a?b. Although the term binary operator might be new to us, we are already familiar with many examples. As hinted to earlier, the rule for adding two numbers to give us a third number is a binary operator on the set of integers, or on the set of rational numbers, or on the set of real numbers. -
An Elementary Approach to Boolean Algebra
Eastern Illinois University The Keep Plan B Papers Student Theses & Publications 6-1-1961 An Elementary Approach to Boolean Algebra Ruth Queary Follow this and additional works at: https://thekeep.eiu.edu/plan_b Recommended Citation Queary, Ruth, "An Elementary Approach to Boolean Algebra" (1961). Plan B Papers. 142. https://thekeep.eiu.edu/plan_b/142 This Dissertation/Thesis is brought to you for free and open access by the Student Theses & Publications at The Keep. It has been accepted for inclusion in Plan B Papers by an authorized administrator of The Keep. For more information, please contact [email protected]. r AN ELEr.:ENTARY APPRCACH TC BCCLF.AN ALGEBRA RUTH QUEAHY L _J AN ELE1~1ENTARY APPRCACH TC BC CLEAN ALGEBRA Submitted to the I<:athematics Department of EASTERN ILLINCIS UNIVERSITY as partial fulfillment for the degree of !•:ASTER CF SCIENCE IN EJUCATION. Date :---"'f~~-----/_,_ffo--..i.-/ _ RUTH QUEARY JUNE 1961 PURPOSE AND PLAN The purpose of this paper is to provide an elementary approach to Boolean algebra. It is designed to give an idea of what is meant by a Boclean algebra and to supply the necessary background material. The only prerequisite for this unit is one year of high school algebra and an open mind so that new concepts will be considered reason able even though they nay conflict with preconceived ideas. A mathematical science when put in final form consists of a set of undefined terms and unproved propositions called postulates, in terrrs of which all other concepts are defined, and from which all other propositions are proved. -
Irreducible Representations of Finite Monoids
U.U.D.M. Project Report 2019:11 Irreducible representations of finite monoids Christoffer Hindlycke Examensarbete i matematik, 30 hp Handledare: Volodymyr Mazorchuk Examinator: Denis Gaidashev Mars 2019 Department of Mathematics Uppsala University Irreducible representations of finite monoids Christoffer Hindlycke Contents Introduction 2 Theory 3 Finite monoids and their structure . .3 Introductory notions . .3 Cyclic semigroups . .6 Green’s relations . .7 von Neumann regularity . 10 The theory of an idempotent . 11 The five functors Inde, Coinde, Rese,Te and Ne ..................... 11 Idempotents and simple modules . 14 Irreducible representations of a finite monoid . 17 Monoid algebras . 17 Clifford-Munn-Ponizovski˘ıtheory . 20 Application 24 The symmetric inverse monoid . 24 Calculating the irreducible representations of I3 ........................ 25 Appendix: Prerequisite theory 37 Basic definitions . 37 Finite dimensional algebras . 41 Semisimple modules and algebras . 41 Indecomposable modules . 42 An introduction to idempotents . 42 1 Irreducible representations of finite monoids Christoffer Hindlycke Introduction This paper is a literature study of the 2016 book Representation Theory of Finite Monoids by Benjamin Steinberg [3]. As this book contains too much interesting material for a simple master thesis, we have narrowed our attention to chapters 1, 4 and 5. This thesis is divided into three main parts: Theory, Application and Appendix. Within the Theory chapter, we (as the name might suggest) develop the necessary theory to assist with finding irreducible representations of finite monoids. Finite monoids and their structure gives elementary definitions as regards to finite monoids, and expands on the basic theory of their structure. This part corresponds to chapter 1 in [3]. The theory of an idempotent develops just enough theory regarding idempotents to enable us to state a key result, from which the principal result later follows almost immediately. -
[Math.NA] 10 Jan 2001 Plctoso H Dmoetmti Ler Odsrt O Discrete to Algebra [9]– Matrix Theory
Idempotent Interval Analysis and Optimization Problems ∗ G. L. Litvinov ([email protected]) International Sophus Lie Centre A. N. Sobolevski˘ı([email protected]) M. V. Lomonosov Moscow State University Abstract. Many problems in optimization theory are strongly nonlinear in the traditional sense but possess a hidden linear structure over suitable idempotent semirings. After an overview of ‘Idempotent Mathematics’ with an emphasis on matrix theory, interval analysis over idempotent semirings is developed. The theory is applied to construction of exact interval solutions to the interval discrete sta- tionary Bellman equation. Solution of an interval system is typically NP -hard in the traditional interval linear algebra; in the idempotent case it is polynomial. A generalization to the case of positive semirings is outlined. Keywords: Idempotent Mathematics, Interval Analysis, idempotent semiring, dis- crete optimization, interval discrete Bellman equation MSC codes: 65G10, 16Y60, 06F05, 08A70, 65K10 Introduction Many problems in the optimization theory and other fields of mathe- matics are nonlinear in the traditional sense but appear to be linear over semirings with idempotent addition.1 This approach is developed systematically as Idempotent Analysis or Idempotent Mathematics (see, e.g., [1]–[8]). In this paper we present an idempotent version of Interval Analysis (its classical version is presented, e.g., in [9]–[12]) and discuss applications of the idempotent matrix algebra to discrete optimization theory. The idempotent interval analysis appears to be best suited for treat- ing problems with order-preserving transformations of input data. It gives exact interval solutions to optimization problems with interval un- arXiv:math/0101080v1 [math.NA] 10 Jan 2001 certainties without any conditions of smallness on uncertainty intervals. -
Semigroups and Monoids
S Luis Alonso-Ovalle // Contents Subgroups Semigroups and monoids Subgroups Groups. A group G is an algebra consisting of a set G and a single binary operation ◦ satisfying the following axioms: . ◦ is completely defined and G is closed under ◦. ◦ is associative. G contains an identity element. Each element in G has an inverse element. Subgroups. We define a subgroup G0 as a subalgebra of G which is itself a group. Examples: . The group of even integers with addition is a proper subgroup of the group of all integers with addition. The group of all rotations of the square h{I, R, R0, R00}, ◦i, where ◦ is the composition of the operations is a subgroup of the group of all symmetries of the square. Some non-subgroups: SEMIGROUPS AND MONOIDS . The system h{I, R, R0}, ◦i is not a subgroup (and not even a subalgebra) of the original group. Why? (Hint: ◦ closure). The set of all non-negative integers with addition is a subalgebra of the group of all integers with addition, because the non-negative integers are closed under addition. But it is not a subgroup because it is not itself a group: it is associative and has a zero, but . does any member (except for ) have an inverse? Order. The order of any group G is the number of members in the set G. The order of any subgroup exactly divides the order of the parental group. E.g.: only subgroups of order , , and are possible for a -member group. (The theorem does not guarantee that every subset having the proper number of members will give rise to a subgroup. -
Binary Operations
Binary operations 1 Binary operations The essence of algebra is to combine two things and get a third. We make this into a definition: Definition 1.1. Let X be a set. A binary operation on X is a function F : X × X ! X. However, we don't write the value of the function on a pair (a; b) as F (a; b), but rather use some intermediate symbol to denote this value, such as a + b or a · b, often simply abbreviated as ab, or a ◦ b. For the moment, we will often use a ∗ b to denote an arbitrary binary operation. Definition 1.2. A binary structure (X; ∗) is a pair consisting of a set X and a binary operation on X. Example 1.3. The examples are almost too numerous to mention. For example, using +, we have (N; +), (Z; +), (Q; +), (R; +), (C; +), as well as n vector space and matrix examples such as (R ; +) or (Mn;m(R); +). Using n subtraction, we have (Z; −), (Q; −), (R; −), (C; −), (R ; −), (Mn;m(R); −), but not (N; −). For multiplication, we have (N; ·), (Z; ·), (Q; ·), (R; ·), (C; ·). If we define ∗ ∗ ∗ Q = fa 2 Q : a 6= 0g, R = fa 2 R : a 6= 0g, C = fa 2 C : a 6= 0g, ∗ ∗ ∗ then (Q ; ·), (R ; ·), (C ; ·) are also binary structures. But, for example, ∗ (Q ; +) is not a binary structure. Likewise, (U(1); ·) and (µn; ·) are binary structures. In addition there are matrix examples: (Mn(R); ·), (GLn(R); ·), (SLn(R); ·), (On; ·), (SOn; ·). Next, there are function composition examples: for a set X,(XX ; ◦) and (SX ; ◦). -
Ring (Mathematics) 1 Ring (Mathematics)
Ring (mathematics) 1 Ring (mathematics) In mathematics, a ring is an algebraic structure consisting of a set together with two binary operations usually called addition and multiplication, where the set is an abelian group under addition (called the additive group of the ring) and a monoid under multiplication such that multiplication distributes over addition.a[›] In other words the ring axioms require that addition is commutative, addition and multiplication are associative, multiplication distributes over addition, each element in the set has an additive inverse, and there exists an additive identity. One of the most common examples of a ring is the set of integers endowed with its natural operations of addition and multiplication. Certain variations of the definition of a ring are sometimes employed, and these are outlined later in the article. Polynomials, represented here by curves, form a ring under addition The branch of mathematics that studies rings is known and multiplication. as ring theory. Ring theorists study properties common to both familiar mathematical structures such as integers and polynomials, and to the many less well-known mathematical structures that also satisfy the axioms of ring theory. The ubiquity of rings makes them a central organizing principle of contemporary mathematics.[1] Ring theory may be used to understand fundamental physical laws, such as those underlying special relativity and symmetry phenomena in molecular chemistry. The concept of a ring first arose from attempts to prove Fermat's last theorem, starting with Richard Dedekind in the 1880s. After contributions from other fields, mainly number theory, the ring notion was generalized and firmly established during the 1920s by Emmy Noether and Wolfgang Krull.[2] Modern ring theory—a very active mathematical discipline—studies rings in their own right. -
TEACHING NOTES a NOTE on IDENTITY ELEMENTS Ho Soo Thong Temasek Junior College Tay Yong Chiang*
TEACHING NOTES A NOTE ON IDENTITY ELEMENTS Ho Soo Thong Temasek Junior College Tay Yong Chiang* In niost books on elementary group theory, the axiom on the existence of an identity element e in a non-empty set G with a binary operation* is simply mentioned as: for all a E G, e * a = a = a * e ••...•••.•••.(I) without further elaboration. As a result, students vecy ofter fail to gain an insight into the meaning of (I). The two common mistakes they make are: Firstly. they fail to see that the condition must hold for all a E G. Secondly, they tend to prove either e * a = a or a * e = a only. We hope that this note will help students have a better understanding of the identity axiom. Also, we show how, given a set with a binary operation defined on it, one may find the identity element. Further, we hope that students will be able to define new opera tions using our techniques. Let * be a binary operation on m, the set of real numbers, defined by a * b = a + (b - 1)(b - 2). We note that for all a~: m , and a * 1 =a a * 2 = a. The numbers 1 and 2 are known as right identity elements with respect to the operation* . On the other hand, there exists no element r (say) such that r * b = b for all b~: Rl. This can be proved by contradiction as follows. If possible, r * b = b for all bE Rl. Hence r + (b - 1)(b - 2) =b which is an identity and such an identity is impossible. -
Order (Group Theory) 1 Order (Group Theory)
Order (group theory) 1 Order (group theory) In group theory, a branch of mathematics, the term order is used in two closely-related senses: • The order of a group is its cardinality, i.e., the number of its elements. • The order, sometimes period, of an element a of a group is the smallest positive integer m such that am = e (where e denotes the identity element of the group, and am denotes the product of m copies of a). If no such m exists, a is said to have infinite order. All elements of finite groups have finite order. The order of a group G is denoted by ord(G) or |G| and the order of an element a by ord(a) or |a|. Example Example. The symmetric group S has the following multiplication table. 3 • e s t u v w e e s t u v w s s e v w t u t t u e s w v u u t w v e s v v w s e u t w w v u t s e This group has six elements, so ord(S ) = 6. By definition, the order of the identity, e, is 1. Each of s, t, and w 3 squares to e, so these group elements have order 2. Completing the enumeration, both u and v have order 3, for u2 = v and u3 = vu = e, and v2 = u and v3 = uv = e. Order and structure The order of a group and that of an element tend to speak about the structure of the group. -
Algebraic Division by Zero Implemented As Quasigeometric Multiplication by Infinity in Real and Complex Multispatial Hyperspaces
Available online at www.worldscientificnews.com WSN 92(2) (2018) 171-197 EISSN 2392-2192 Algebraic division by zero implemented as quasigeometric multiplication by infinity in real and complex multispatial hyperspaces Jakub Czajko Science/Mathematics Education Department, Southern University and A&M College, Baton Rouge, LA 70813, USA E-mail address: [email protected] ABSTRACT An unrestricted division by zero implemented as an algebraic multiplication by infinity is feasible within a multispatial hyperspace comprising several quasigeometric spaces. Keywords: Division by zero, infinity, multispatiality, multispatial uncertainty principle 1. INTRODUCTION Numbers used to be identified with their values. Yet complex numbers have two distinct single-number values: modulus/length and angle/phase, which can vary independently of each other. Since values are attributes of the algebraic entities called numbers, we need yet another way to define these entities and establish a basis that specifies their attributes. In an operational sense a number can be defined as the outcome of an algebraic operation. We must know the space where the numbers reside and the basis in which they are represented. Since division is inverse of multiplication, then reciprocal/contragradient basis can be used to represent inverse numbers for division [1]. Note that dual space, as conjugate space [2] is a space of functionals defined on elements of the primary space [3-5]. Although dual geometries are identical as sets, their geometrical structures are different [6] for duality can ( Received 18 December 2017; Accepted 03 January 2018; Date of Publication 04 January 2018 ) World Scientific News 92(2) (2018) 171-197 form anti-isomorphism or inverse isomorphism [7].