Notation Systems and Recursive Ordered Fields 1 By
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Mathematics I Basic Mathematics
Mathematics I Basic Mathematics Prepared by Prof. Jairus. Khalagai African Virtual university Université Virtuelle Africaine Universidade Virtual Africana African Virtual University NOTICE This document is published under the conditions of the Creative Commons http://en.wikipedia.org/wiki/Creative_Commons Attribution http://creativecommons.org/licenses/by/2.5/ License (abbreviated “cc-by”), Version 2.5. African Virtual University Table of ConTenTs I. Mathematics 1, Basic Mathematics _____________________________ 3 II. Prerequisite Course or Knowledge _____________________________ 3 III. Time ____________________________________________________ 3 IV. Materials _________________________________________________ 3 V. Module Rationale __________________________________________ 4 VI. Content __________________________________________________ 5 6.1 Overview ____________________________________________ 5 6.2 Outline _____________________________________________ 6 VII. General Objective(s) ________________________________________ 8 VIII. Specific Learning Objectives __________________________________ 8 IX. Teaching and Learning Activities ______________________________ 10 X. Key Concepts (Glossary) ____________________________________ 16 XI. Compulsory Readings ______________________________________ 18 XII. Compulsory Resources _____________________________________ 19 XIII. Useful Links _____________________________________________ 20 XIV. Learning Activities _________________________________________ 23 XV. Synthesis Of The Module ___________________________________ -
Axioms and Algebraic Systems*
Axioms and algebraic systems* Leong Yu Kiang Department of Mathematics National University of Singapore In this talk, we introduce the important concept of a group, mention some equivalent sets of axioms for groups, and point out the relationship between the individual axioms. We also mention briefly the definitions of a ring and a field. Definition 1. A binary operation on a non-empty set S is a rule which associates to each ordered pair (a, b) of elements of S a unique element, denoted by a* b, in S. The binary relation itself is often denoted by *· It may also be considered as a mapping from S x S to S, i.e., * : S X S ~ S, where (a, b) ~a* b, a, bE S. Example 1. Ordinary addition and multiplication of real numbers are binary operations on the set IR of real numbers. We write a+ b, a· b respectively. Ordinary division -;- is a binary relation on the set IR* of non-zero real numbers. We write a -;- b. Definition 2. A binary relation * on S is associative if for every a, b, c in s, (a* b) * c =a* (b *c). Example 2. The binary operations + and · on IR (Example 1) are as sociative. The binary relation -;- on IR* (Example 1) is not associative smce 1 3 1 ~ 2) ~ 3 _J_ - 1 ~ (2 ~ 3). ( • • = -6 I 2 = • • * Talk given at the Workshop on Algebraic Structures organized by the Singapore Mathemat- ical Society for school teachers on 5 September 1988. 11 Definition 3. A semi-group is a non-€mpty set S together with an asso ciative binary operation *, and is denoted by (S, *). -
A List of Arithmetical Structures Complete with Respect to the First
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Theoretical Computer Science 257 (2001) 115–151 www.elsevier.com/locate/tcs A list of arithmetical structures complete with respect to the ÿrst-order deÿnability Ivan Korec∗;X Slovak Academy of Sciences, Mathematical Institute, Stefanikovaà 49, 814 73 Bratislava, Slovak Republic Abstract A structure with base set N is complete with respect to the ÿrst-order deÿnability in the class of arithmetical structures if and only if the operations +; × are deÿnable in it. A list of such structures is presented. Although structures with Pascal’s triangles modulo n are preferred a little, an e,ort was made to collect as many simply formulated results as possible. c 2001 Elsevier Science B.V. All rights reserved. MSC: primary 03B10; 03C07; secondary 11B65; 11U07 Keywords: Elementary deÿnability; Pascal’s triangle modulo n; Arithmetical structures; Undecid- able theories 1. Introduction A list of (arithmetical) structures complete with respect of the ÿrst-order deÿnability power (shortly: def-complete structures) will be presented. (The term “def-strongest” was used in the previous versions.) Most of them have the base set N but also structures with some other universes are considered. (Formal deÿnitions are given below.) The class of arithmetical structures can be quasi-ordered by ÿrst-order deÿnability power. After the usual factorization we obtain a partially ordered set, and def-complete struc- tures will form its greatest element. Of course, there are stronger structures (with respect to the ÿrst-order deÿnability) outside of the class of arithmetical structures. -
Basic Concepts of Set Theory, Functions and Relations 1. Basic
Ling 310, adapted from UMass Ling 409, Partee lecture notes March 1, 2006 p. 1 Basic Concepts of Set Theory, Functions and Relations 1. Basic Concepts of Set Theory........................................................................................................................1 1.1. Sets and elements ...................................................................................................................................1 1.2. Specification of sets ...............................................................................................................................2 1.3. Identity and cardinality ..........................................................................................................................3 1.4. Subsets ...................................................................................................................................................4 1.5. Power sets .............................................................................................................................................4 1.6. Operations on sets: union, intersection...................................................................................................4 1.7 More operations on sets: difference, complement...................................................................................5 1.8. Set-theoretic equalities ...........................................................................................................................5 Chapter 2. Relations and Functions ..................................................................................................................6 -
Enumeration of Finite Automata 1 Z(A) = 1
INFOI~MATION AND CONTROL 10, 499-508 (1967) Enumeration of Finite Automata 1 FRANK HARARY AND ED PALMER Department of Mathematics, University of Michigan, Ann Arbor, Michigan Harary ( 1960, 1964), in a survey of 27 unsolved problems in graphical enumeration, asked for the number of different finite automata. Re- cently, Harrison (1965) solved this problem, but without considering automata with initial and final states. With the aid of the Power Group Enumeration Theorem (Harary and Palmer, 1965, 1966) the entire problem can be handled routinely. The method involves a confrontation of several different operations on permutation groups. To set the stage, we enumerate ordered pairs of functions with respect to the product of two power groups. Finite automata are then concisely defined as certain ordered pah's of functions. We review the enumeration of automata in the natural setting of the power group, and then extend this result to enumerate automata with initial and terminal states. I. ENUMERATION THEOREM For completeness we require a number of definitions, which are now given. Let A be a permutation group of order m = ]A I and degree d acting on the set X = Ix1, x~, -.. , xa}. The cycle index of A, denoted Z(A), is defined as follows. Let jk(a) be the number of cycles of length k in the disjoint cycle decomposition of any permutation a in A. Let al, a2, ... , aa be variables. Then the cycle index, which is a poly- nomial in the variables a~, is given by d Z(A) = 1_ ~ H ~,~(°~ . (1) ~$ a EA k=l We sometimes write Z(A; al, as, .. -
Binary Operations
4-22-2007 Binary Operations Definition. A binary operation on a set X is a function f : X × X → X. In other words, a binary operation takes a pair of elements of X and produces an element of X. It’s customary to use infix notation for binary operations. Thus, rather than write f(a, b) for the binary operation acting on elements a, b ∈ X, you write afb. Since all those letters can get confusing, it’s also customary to use certain symbols — +, ·, ∗ — for binary operations. Thus, f(a, b) becomes (say) a + b or a · b or a ∗ b. Example. Addition is a binary operation on the set Z of integers: For every pair of integers m, n, there corresponds an integer m + n. Multiplication is also a binary operation on the set Z of integers: For every pair of integers m, n, there corresponds an integer m · n. However, division is not a binary operation on the set Z of integers. For example, if I take the pair 3 (3, 0), I can’t perform the operation . A binary operation on a set must be defined for all pairs of elements 0 from the set. Likewise, a ∗ b = (a random number bigger than a or b) does not define a binary operation on Z. In this case, I don’t have a function Z × Z → Z, since the output is ambiguously defined. (Is 3 ∗ 5 equal to 6? Or is it 117?) When a binary operation occurs in mathematics, it usually has properties that make it useful in con- structing abstract structures. -
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 ; ◦). -
Formal Construction of a Set Theory in Coq
Saarland University Faculty of Natural Sciences and Technology I Department of Computer Science Masters Thesis Formal Construction of a Set Theory in Coq submitted by Jonas Kaiser on November 23, 2012 Supervisor Prof. Dr. Gert Smolka Advisor Dr. Chad E. Brown Reviewers Prof. Dr. Gert Smolka Dr. Chad E. Brown Eidesstattliche Erklarung¨ Ich erklare¨ hiermit an Eides Statt, dass ich die vorliegende Arbeit selbststandig¨ verfasst und keine anderen als die angegebenen Quellen und Hilfsmittel verwendet habe. Statement in Lieu of an Oath I hereby confirm that I have written this thesis on my own and that I have not used any other media or materials than the ones referred to in this thesis. Einverstandniserkl¨ arung¨ Ich bin damit einverstanden, dass meine (bestandene) Arbeit in beiden Versionen in die Bibliothek der Informatik aufgenommen und damit vero¨ffentlicht wird. Declaration of Consent I agree to make both versions of my thesis (with a passing grade) accessible to the public by having them added to the library of the Computer Science Department. Saarbrucken,¨ (Datum/Date) (Unterschrift/Signature) iii Acknowledgements First of all I would like to express my sincerest gratitude towards my advisor, Chad Brown, who supported me throughout this work. His extensive knowledge and insights opened my eyes to the beauty of axiomatic set theory and foundational mathematics. We spent many hours discussing the minute details of the various constructions and he taught me the importance of mathematical rigour. Equally important was the support of my supervisor, Prof. Smolka, who first introduced me to the topic and was there whenever a question arose. -
Do We Need Recursion?
Do We Need Recursion? V´ıtˇezslav Svejdarˇ Charles University in Prague Appeared in Igor Sedl´arand Martin Blicha eds., The Logica Yearbook 2019, pp. 193{204, College Publications, London, 2020. Abstract The operation of primitive recursion, and recursion in a more general sense, is undoubtedly a useful tool. However, we will explain that in two situa- tion where we work with it, namely in the definition of partial recursive functions and in logic when defining the basic syntactic notions, its use can be avoided. We will also explain why one would want to do so. 1 What is recursion, where do we meet it? Recursion in a narrow sense is an operation with multivariable functions whose arguments are natural numbers. Let z denote the k-tuple z1; : : ; zk (where the number k of variables does not have to be indicated), and let fb(x; z) denote the code hf(0; z); : : ; f(x − 1; z)i of the sequence f(0; z); : : ; f(x − 1; z) under some suitable coding of finite sequences. If (1), (2) or (3) holds for any choice of arguments: f(0) = a; f(x + 1) = h(f(x); x); (1) f(0; z) = g(z); f(x + 1; z) = h(f(x; z); x; z); (2) f(x; z) = h(fb(x; z); z); (3) then in the cases (1) and (2) we say that f is derived from a number a and a function h or from two functions g and h by primitive recursion, while in the case (3) we say that f is derived from h by course-of-values recursion. -
Ernesto Calleros: an Introduction to Group Theory
FINAL REPORT: INTRODUCTION TO GROUPS ERNESTO D. CALLEROS PROFESSOR DAVID LARSON MATH 482 25 APRIL 2013 TEXAS A&M UNIVERSITY A group in an algebra setting is a type of set that, together with some operation, obeys a predefined set of rules called axioms. In order to understand these rules and to be able to define them precisely, it helps to understand binary operations first. Definition 1. A binary operation ∗ on a set S is a function mapping S × S into S. For each (a; b) 2 S × S, we will denote the element ∗(a; b) of S by a ∗ b. To emphasize certain conditions for a binary operation on a set, we give the following remarks: Remark 2. By definition, a binary operation ∗ on a set S is well-defined; that is, ∗ assigns exactly one element to each possible ordered pair of elements in S. Remark 3. For a binary operation ∗ on a set S, S is closed under ∗; that is, for all a; b 2 S, we also have a ∗ b 2 S. We proceed with some examples. Example 4. Determine if usual addition is a binary operation on the sets Z, Q, f1,2,3g. Solution. Given a; b 2 Z, a + b is a well-defined element of Z. Also, Z is closed under addition, so addition is a binary operation on Z. Similarly, addition is a binary operation on Q. However, 2 + 2 = 4 2= f1; 2; 3g, so addition is not closed on f1; 2; 3g, and thus is not a binary operation on this set. -
Equivalents to the Axiom of Choice and Their Uses A
EQUIVALENTS TO THE AXIOM OF CHOICE AND THEIR USES A Thesis Presented to The Faculty of the Department of Mathematics California State University, Los Angeles In Partial Fulfillment of the Requirements for the Degree Master of Science in Mathematics By James Szufu Yang c 2015 James Szufu Yang ALL RIGHTS RESERVED ii The thesis of James Szufu Yang is approved. Mike Krebs, Ph.D. Kristin Webster, Ph.D. Michael Hoffman, Ph.D., Committee Chair Grant Fraser, Ph.D., Department Chair California State University, Los Angeles June 2015 iii ABSTRACT Equivalents to the Axiom of Choice and Their Uses By James Szufu Yang In set theory, the Axiom of Choice (AC) was formulated in 1904 by Ernst Zermelo. It is an addition to the older Zermelo-Fraenkel (ZF) set theory. We call it Zermelo-Fraenkel set theory with the Axiom of Choice and abbreviate it as ZFC. This paper starts with an introduction to the foundations of ZFC set the- ory, which includes the Zermelo-Fraenkel axioms, partially ordered sets (posets), the Cartesian product, the Axiom of Choice, and their related proofs. It then intro- duces several equivalent forms of the Axiom of Choice and proves that they are all equivalent. In the end, equivalents to the Axiom of Choice are used to prove a few fundamental theorems in set theory, linear analysis, and abstract algebra. This paper is concluded by a brief review of the work in it, followed by a few points of interest for further study in mathematics and/or set theory. iv ACKNOWLEDGMENTS Between the two department requirements to complete a master's degree in mathematics − the comprehensive exams and a thesis, I really wanted to experience doing a research and writing a serious academic paper. -
Axioms for High-School Algebra This Is a Version of Sections 4.1 and 4.2
Axioms for high-school algebra This is a version of Sections 4.1 and 4.2. Key definitions • Let X be a non-empty set. A binary operation ∗ on X associates with every ordered pair (x; y) of elements of X a single element x ∗ y of X. • The binary operation ∗ is said to be commutative if x∗y = y ∗x for all x; y 2 X. • The binary operation ∗ is said to be associative if (x ∗ y) ∗ z = x ∗ (y ∗ z) for all x; y; z 2 X. • An identity for ∗ is an element e such that e ∗ x = x = x ∗ e for all x 2 X. • Let e be an identity for ∗. Then the element x is said to be invertible if there is an element y such that x ∗ y = e = y ∗ x. Algebraic properties of R We will only describe the properties of addition and multiplication. Subtraction and division are not viewed as binary operations in their own right. Instead, we define a − b = a + (−b): Thus to subtract b means the same thing as adding −b. Likewise, we define anb = a ÷ b = a × b−1 if b 6= 0: Thus to divide by b is to multiply by b−1. Axioms for addition in R (F1): Addition is associative. Let x, y and z be any numbers. Then (x + y) + z = x + (y + z). (F2): There is an additive identity. The number 0 (zero) is the additive identity. This means that x + 0 = x = 0 + x for any number x. (F3): Each number has a unique additive inverse.