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Arxiv:0704.2561V2 [Math.QA] 27 Apr 2007 Nttto O Xeln Okn Odtos H Eoda Second the Conditions
DUAL FEYNMAN TRANSFORM FOR MODULAR OPERADS J. CHUANG AND A. LAZAREV Abstract. We introduce and study the notion of a dual Feynman transform of a modular operad. This generalizes and gives a conceptual explanation of Kontsevich’s dual construction producing graph cohomology classes from a contractible differential graded Frobenius alge- bra. The dual Feynman transform of a modular operad is indeed linear dual to the Feynman transform introduced by Getzler and Kapranov when evaluated on vacuum graphs. In marked contrast to the Feynman transform, the dual notion admits an extremely simple presentation via generators and relations; this leads to an explicit and easy description of its algebras. We discuss a further generalization of the dual Feynman transform whose algebras are not neces- sarily contractible. This naturally gives rise to a two-colored graph complex analogous to the Boardman-Vogt topological tree complex. Contents Introduction 1 Notation and conventions 2 1. Main construction 4 2. Twisted modular operads and their algebras 8 3. Algebras over the dual Feynman transform 12 4. Stable graph complexes 13 4.1. Commutative case 14 4.2. Associative case 15 5. Examples 17 6. Moduli spaces of metric graphs 19 6.1. Commutative case 19 6.2. Associative case 21 7. BV-resolution of a modular operad 22 7.1. Basic construction and description of algebras 22 7.2. Stable BV-graph complexes 23 References 26 Introduction arXiv:0704.2561v2 [math.QA] 27 Apr 2007 The relationship between operadic algebras and various moduli spaces goes back to Kontse- vich’s seminal papers [19] and [20] where graph homology was also introduced. -
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. -
Operations Per Se, to See If the Proposed Chi Is Indeed Fruitful
DOCUMENT RESUME ED 204 124 SE 035 176 AUTHOR Weaver, J. F. TTTLE "Addition," "Subtraction" and Mathematical Operations. 7NSTITOTION. Wisconsin Univ., Madison. Research and Development Center for Individualized Schooling. SPONS AGENCY Neional Inst. 1pf Education (ED), Washington. D.C. REPORT NO WIOCIS-PP-79-7 PUB DATE Nov 79 GRANT OS-NIE-G-91-0009 NOTE 98p.: Report from the Mathematics Work Group. Paper prepared for the'Seminar on the Initial Learning of Addition and' Subtraction. Skills (Racine, WI, November 26-29, 1979). Contains occasional light and broken type. Not available in hard copy due to copyright restrictions.. EDPS PRICE MF01 Plum Postage. PC Not Available from EDRS. DEseR.TPT00S *Addition: Behavioral Obiectives: Cognitive Oblectives: Cognitive Processes: *Elementary School Mathematics: Elementary Secondary Education: Learning Theories: Mathematical Concepts: Mathematics Curriculum: *Mathematics Education: *Mathematics Instruction: Number Concepts: *Subtraction: Teaching Methods IDENTIFIERS *Mathematics Education ResearCh: *Number 4 Operations ABSTRACT This-report opens by asking how operations in general, and addition and subtraction in particular, ante characterized for 'elementary school students, and examines the "standard" Instruction of these topics through secondary. schooling. Some common errors and/or "sloppiness" in the typical textbook presentations are noted, and suggestions are made that these probleks could lend to pupil difficulties in understanding mathematics. The ambiguity of interpretation .of number sentences of the VW's "a+b=c". and "a-b=c" leads into a comparison of the familiar use of binary operations with a unary-operator interpretation of such sentences. The second half of this document focuses on points of vier that promote .varying approaches to the development of mathematical skills and abilities within young children. -
Hyperoperations and Nopt Structures
Hyperoperations and Nopt Structures Alister Wilson Abstract (Beta version) The concept of formal power towers by analogy to formal power series is introduced. Bracketing patterns for combining hyperoperations are pictured. Nopt structures are introduced by reference to Nept structures. Briefly speaking, Nept structures are a notation that help picturing the seed(m)-Ackermann number sequence by reference to exponential function and multitudinous nestings thereof. A systematic structure is observed and described. Keywords: Large numbers, formal power towers, Nopt structures. 1 Contents i Acknowledgements 3 ii List of Figures and Tables 3 I Introduction 4 II Philosophical Considerations 5 III Bracketing patterns and hyperoperations 8 3.1 Some Examples 8 3.2 Top-down versus bottom-up 9 3.3 Bracketing patterns and binary operations 10 3.4 Bracketing patterns with exponentiation and tetration 12 3.5 Bracketing and 4 consecutive hyperoperations 15 3.6 A quick look at the start of the Grzegorczyk hierarchy 17 3.7 Reconsidering top-down and bottom-up 18 IV Nopt Structures 20 4.1 Introduction to Nept and Nopt structures 20 4.2 Defining Nopts from Nepts 21 4.3 Seed Values: “n” and “theta ) n” 24 4.4 A method for generating Nopt structures 25 4.5 Magnitude inequalities inside Nopt structures 32 V Applying Nopt Structures 33 5.1 The gi-sequence and g-subscript towers 33 5.2 Nopt structures and Conway chained arrows 35 VI Glossary 39 VII Further Reading and Weblinks 42 2 i Acknowledgements I’d like to express my gratitude to Wikipedia for supplying an enormous range of high quality mathematics articles. -
'Doing and Undoing' Applied to the Action of Exchange Reveals
mathematics Article How the Theme of ‘Doing and Undoing’ Applied to the Action of Exchange Reveals Overlooked Core Ideas in School Mathematics John Mason 1,2 1 Department of Mathematics and Statistics, Open University, Milton Keynes MK7 6AA, UK; [email protected] 2 Department of Education, University of Oxford, 15 Norham Gardens, Oxford OX2 6PY, UK Abstract: The theme of ‘undoing a doing’ is applied to the ubiquitous action of exchange, showing how exchange pervades a school’s mathematics curriculum. It is possible that many obstacles encountered in school mathematics arise from an impoverished sense of exchange, for learners and possibly for teachers. The approach is phenomenological, in that the reader is urged to undertake the tasks themselves, so that the pedagogical and mathematical comments, and elaborations, may connect directly to immediate experience. Keywords: doing and undoing; exchange; substitution 1. Introduction Arithmetic is seen here as the study of actions (usually by numbers) on numbers, whereas calculation is an epiphenomenon: useful as a skill, but only to facilitate recognition Citation: Mason, J. How the Theme of relationships between numbers. Particular relationships may, upon articulation and of ‘Doing and Undoing’ Applied to analysis (generalisation), turn out to be properties that hold more generally. This way of the Action of Exchange Reveals thinking sets the scene for the pervasive mathematical theme of inverse, also known as Overlooked Core Ideas in School doing and undoing (Gardiner [1,2]; Mason [3]; SMP [4]). Exploiting this theme brings to Mathematics. Mathematics 2021, 9, the surface core ideas, such as exchange, which, although appearing sporadically in most 1530. -
Bitwise Operators
Logical operations ANDORNOTXORAND,OR,NOT,XOR •Loggpical operations are the o perations that have its result as a true or false. • The logical operations can be: • Unary operations that has only one operand (NOT) • ex. NOT operand • Binary operations that has two operands (AND,OR,XOR) • ex. operand 1 AND operand 2 operand 1 OR operand 2 operand 1 XOR operand 2 1 Dr.AbuArqoub Logical operations ANDORNOTXORAND,OR,NOT,XOR • Operands of logical operations can be: - operands that have values true or false - operands that have binary digits 0 or 1. (in this case the operations called bitwise operations). • In computer programming ,a bitwise operation operates on one or two bit patterns or binary numerals at the level of their individual bits. 2 Dr.AbuArqoub Truth tables • The following tables (truth tables ) that shows the result of logical operations that operates on values true, false. x y Z=x AND y x y Z=x OR y F F F F F F F T F F T T T F F T F T T T T T T T x y Z=x XOR y x NOT X F F F F T F T T T F T F T T T F 3 Dr.AbuArqoub Bitwise Operations • In computer programming ,a bitwise operation operates on one or two bit patterns or binary numerals at the level of their individual bits. • Bitwise operators • NOT • The bitwise NOT, or complement, is an unary operation that performs logical negation on each bit, forming the ones' complement of the given binary value. -
Some Aspects of Semirings
Appendix A Some Aspects of Semirings Semirings considered as a common generalization of associative rings and dis- tributive lattices provide important tools in different branches of computer science. Hence structural results on semirings are interesting and are a basic concept. Semi- rings appear in different mathematical areas, such as ideals of a ring, as positive cones of partially ordered rings and fields, vector bundles, in the context of topolog- ical considerations and in the foundation of arithmetic etc. In this appendix some algebraic concepts are introduced in order to generalize the corresponding concepts of semirings N of non-negative integers and their algebraic theory is discussed. A.1 Introductory Concepts H.S. Vandiver gave the first formal definition of a semiring and developed the the- ory of a special class of semirings in 1934. A semiring S is defined as an algebra (S, +, ·) such that (S, +) and (S, ·) are semigroups connected by a(b+c) = ab+ac and (b+c)a = ba+ca for all a,b,c ∈ S.ThesetN of all non-negative integers with usual addition and multiplication of integers is an example of a semiring, called the semiring of non-negative integers. A semiring S may have an additive zero ◦ defined by ◦+a = a +◦=a for all a ∈ S or a multiplicative zero 0 defined by 0a = a0 = 0 for all a ∈ S. S may contain both ◦ and 0 but they may not coincide. Consider the semiring (N, +, ·), where N is the set of all non-negative integers; a + b ={lcm of a and b, when a = 0,b= 0}; = 0, otherwise; and a · b = usual product of a and b. -
Introduction to Groups, Rings and Fields
Introduction to Groups, Rings and Fields HT and TT 2011 H. A. Priestley 0. Familiar algebraic systems: review and a look ahead. GRF is an ALGEBRA course, and specifically a course about algebraic structures. This introduc- tory section revisits ideas met in the early part of Analysis I and in Linear Algebra I, to set the scene and provide motivation. 0.1 Familiar number systems Consider the traditional number systems N = 0, 1, 2,... the natural numbers { } Z = m n m, n N the integers { − | ∈ } Q = m/n m, n Z, n = 0 the rational numbers { | ∈ } R the real numbers C the complex numbers for which we have N Z Q R C. ⊂ ⊂ ⊂ ⊂ These come equipped with the familiar arithmetic operations of sum and product. The real numbers: Analysis I built on the real numbers. Right at the start of that course you were given a set of assumptions about R, falling under three headings: (1) Algebraic properties (laws of arithmetic), (2) order properties, (3) Completeness Axiom; summarised as saying the real numbers form a complete ordered field. (1) The algebraic properties of R You were told in Analysis I: Addition: for each pair of real numbers a and b there exists a unique real number a + b such that + is a commutative and associative operation; • there exists in R a zero, 0, for addition: a +0=0+ a = a for all a R; • ∈ for each a R there exists an additive inverse a R such that a+( a)=( a)+a = 0. • ∈ − ∈ − − Multiplication: for each pair of real numbers a and b there exists a unique real number a b such that · is a commutative and associative operation; • · there exists in R an identity, 1, for multiplication: a 1 = 1 a = a for all a R; • · · ∈ for each a R with a = 0 there exists an additive inverse a−1 R such that a a−1 = • a−1 a = 1.∈ ∈ · · Addition and multiplication together: forall a,b,c R, we have the distributive law a (b + c)= a b + a c. -
Vector Spaces
Chapter 2 Vector Spaces 2.1 INTRODUCTION In various practical and theoretical problems, we come across a set V whose elements may be vectors in two or three dimensions or real-valued functions, which can be added and multi- plied by a constant (number) in a natural way, the result being again an element of V. Such concrete situations suggest the concept of a vector space. Vector spaces play an important role in many branches of mathematics and physics. In analysis infinite dimensional vector spaces (in fact, normed vector spaces) are more important than finite dimensional vector spaces while in linear algebra finite dimensional vector spaces are used, because they are simple and linear transformations on them can be represented by matrices. This chapter mainly deals with finite dimensional vector spaces. 2.2 DEFINITION AND EXAMPLES VECTOR SPACE. An algebraic structure (V, F, ⊕, ) consisting of a non-void set V , a field F, a binary operation ⊕ on V and an external mapping : F ×V → V associating each a ∈ F,v ∈ V to a unique element a v ∈ V is said to be a vector space over field F, if the following axioms are satisfied: V -1 (V, ⊕) is an abelian group. V -2 For all u, v ∈ V and a, b ∈ F, we have (i) a (u ⊕ v)=a u ⊕ a v, (ii) (a + b) u = a u ⊕ b u, (iii) (ab) u = a (b u), (iv) 1 u = u. The elements of V are called vectors and those of F are called scalars. The mapping is called scalar multiplication and the binary operation ⊕ is termed vector addition. -
28. Com. Rings: Units and Zero-Divisors
M7210 Lecture 28 Friday October 26, 2012 Commutative Rings III We assume all rings are commutative and have multiplicative identity (different from 0). Units and zero-divisors Definition. Let A be a commutative ring and let a ∈ A. i) a is called a unit if a 6=0A and there is b ∈ A such that ab =1A. ii) a is called a zero-divisor if a 6= 0A and there is non-zero b ∈ A such that ab = 0A. A (commutative) ring with no zero-divisors is called an integral domain. Remark. In the zero ring Z = {0}, 0Z = 1Z. This is an annoying detail that our definition must take into account, and this is why the stipulation “a 6= 0A” appears in i). The zero ring plays a very minor role in commutative algebra, but it is important nonetheless because it is a valid model of the equational theory of rings-with-identity and it is the final object in the category of rings. We exclude this ring in the discussion below (and occasionally include a reminder that we are doing so). Fact. In any (non-zero commutative) ring R the set of zero-divisors and the set of units are disjoint. Proof . Let u ∈ R \{0}. If there is z ∈ R such that uz = 0, then for any t ∈ R, (tu)z = 0. Thus, there is no t ∈ R such that tu = 1. Fact. Let R be a ring. The set U(R) of units of R forms a group. Examples. The units in Z are 1 and −1. -
Notes on Algebraic Structures
Notes on Algebraic Structures Peter J. Cameron ii Preface These are the notes of the second-year course Algebraic Structures I at Queen Mary, University of London, as I taught it in the second semester 2005–2006. After a short introductory chapter consisting mainly of reminders about such topics as functions, equivalence relations, matrices, polynomials and permuta- tions, the notes fall into two chapters, dealing with rings and groups respec- tively. I have chosen this order because everybody is familiar with the ring of integers and can appreciate what we are trying to do when we generalise its prop- erties; there is no well-known group to play the same role. Fairly large parts of the two chapters (subrings/subgroups, homomorphisms, ideals/normal subgroups, Isomorphism Theorems) run parallel to each other, so the results on groups serve as revision for the results on rings. Towards the end, the two topics diverge. In ring theory, we study factorisation in integral domains, and apply it to the con- struction of fields; in group theory we prove Cayley’s Theorem and look at some small groups. The set text for the course is my own book Introduction to Algebra, Ox- ford University Press. I have refrained from reading the book while teaching the course, preferring to have another go at writing out this material. According to the learning outcomes for the course, a studing passing the course is expected to be able to do the following: • Give the following. Definitions of binary operations, associative, commuta- tive, identity element, inverses, cancellation. Proofs of uniqueness of iden- tity element, and of inverse. -
Episode 7.03 – Coding Bitwise Operations
Episode 7.03 – Coding Bitwise Operations Welcome to the Geek Author series on Computer Organization and Design Fundamentals. I’m David Tarnoff, and in this series, we are working our way through the topics of Computer Organization, Computer Architecture, Digital Design, and Embedded System Design. If you’re interested in the inner workings of a computer, then you’re in the right place. The only background you’ll need for this series is an understanding of integer math, and if possible, a little experience with a programming language such as Java. And one more thing. This episode has direct consequences for our code. You can find coding examples on the episode worksheet, a link to which can be found on the transcript page at intermation.com. Way back in Episode 2.2 – Unsigned Binary Conversion, we introduced three operators that allow us to manipulate integers at the bit level: the logical shift left (represented with two adjacent less-than operators, <<), the arithmetic shift right (represented with two adjacent greater-than operators, >>), and the logical shift right (represented with three adjacent greater-than operators, >>>). These special operators allow us to take all of the bits in a binary integer and move them left or right by a specified number of bit positions. The syntax of all three of these operators is to place the integer we wish to shift on the left side of the operator and the number of bits we wish to shift it by on the right side of the operator. In that episode, we introduced these operators to show how bit shifts could take the place of multiplication or division by powers of two.