Nets, the Axiom of Choice, and the Tychonoff Theorem
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Completeness in Quasi-Pseudometric Spaces—A Survey
mathematics Article Completeness in Quasi-Pseudometric Spaces—A Survey ¸StefanCobzas Faculty of Mathematics and Computer Science, Babe¸s-BolyaiUniversity, 400 084 Cluj-Napoca, Romania; [email protected] Received:17 June 2020; Accepted: 24 July 2020; Published: 3 August 2020 Abstract: The aim of this paper is to discuss the relations between various notions of sequential completeness and the corresponding notions of completeness by nets or by filters in the setting of quasi-metric spaces. We propose a new definition of right K-Cauchy net in a quasi-metric space for which the corresponding completeness is equivalent to the sequential completeness. In this way we complete some results of R. A. Stoltenberg, Proc. London Math. Soc. 17 (1967), 226–240, and V. Gregori and J. Ferrer, Proc. Lond. Math. Soc., III Ser., 49 (1984), 36. A discussion on nets defined over ordered or pre-ordered directed sets is also included. Keywords: metric space; quasi-metric space; uniform space; quasi-uniform space; Cauchy sequence; Cauchy net; Cauchy filter; completeness MSC: 54E15; 54E25; 54E50; 46S99 1. Introduction It is well known that completeness is an essential tool in the study of metric spaces, particularly for fixed points results in such spaces. The study of completeness in quasi-metric spaces is considerably more involved, due to the lack of symmetry of the distance—there are several notions of completeness all agreing with the usual one in the metric case (see [1] or [2]). Again these notions are essential in proving fixed point results in quasi-metric spaces as it is shown by some papers on this topic as, for instance, [3–6] (see also the book [7]). -
"Mathematics for Computer Science" (MCS)
“mcs” — 2016/9/28 — 23:07 — page i — #1 Mathematics for Computer Science revised Wednesday 28th September, 2016, 23:07 Eric Lehman Google Inc. F Thomson Leighton Department of Mathematics and the Computer Science and AI Laboratory, Massachussetts Institute of Technology; Akamai Technologies Albert R Meyer Department of Electrical Engineering and Computer Science and the Computer Science and AI Laboratory, Massachussetts Institute of Technology 2016, Eric Lehman, F Tom Leighton, Albert R Meyer. This work is available under the terms of the Creative Commons Attribution-ShareAlike 3.0 license. “mcs” — 2016/9/28 — 23:07 — page ii — #2 “mcs” — 2016/9/28 — 23:07 — page iii — #3 Contents I Proofs Introduction 3 0.1 References4 1 What is a Proof? 5 1.1 Propositions5 1.2 Predicates8 1.3 The Axiomatic Method8 1.4 Our Axioms9 1.5 Proving an Implication 11 1.6 Proving an “If and Only If” 13 1.7 Proof by Cases 15 1.8 Proof by Contradiction 16 1.9 Good Proofs in Practice 17 1.10 References 19 2 The Well Ordering Principle 29 2.1 Well Ordering Proofs 29 2.2 Template for Well Ordering Proofs 30 2.3 Factoring into Primes 32 2.4 Well Ordered Sets 33 3 Logical Formulas 47 3.1 Propositions from Propositions 48 3.2 Propositional Logic in Computer Programs 51 3.3 Equivalence and Validity 54 3.4 The Algebra of Propositions 56 3.5 The SAT Problem 61 3.6 Predicate Formulas 62 3.7 References 67 4 Mathematical Data Types 93 4.1 Sets 93 4.2 Sequences 98 4.3 Functions 99 4.4 Binary Relations 101 4.5 Finite Cardinality 105 “mcs” — 2016/9/28 — 23:07 — page iv — #4 Contentsiv 5 Induction 125 5.1 Ordinary Induction 125 5.2 Strong Induction 134 5.3 Strong Induction vs. -
MTH 304: General Topology Semester 2, 2017-2018
MTH 304: General Topology Semester 2, 2017-2018 Dr. Prahlad Vaidyanathan Contents I. Continuous Functions3 1. First Definitions................................3 2. Open Sets...................................4 3. Continuity by Open Sets...........................6 II. Topological Spaces8 1. Definition and Examples...........................8 2. Metric Spaces................................. 11 3. Basis for a topology.............................. 16 4. The Product Topology on X × Y ...................... 18 Q 5. The Product Topology on Xα ....................... 20 6. Closed Sets.................................. 22 7. Continuous Functions............................. 27 8. The Quotient Topology............................ 30 III.Properties of Topological Spaces 36 1. The Hausdorff property............................ 36 2. Connectedness................................. 37 3. Path Connectedness............................. 41 4. Local Connectedness............................. 44 5. Compactness................................. 46 6. Compact Subsets of Rn ............................ 50 7. Continuous Functions on Compact Sets................... 52 8. Compactness in Metric Spaces........................ 56 9. Local Compactness.............................. 59 IV.Separation Axioms 62 1. Regular Spaces................................ 62 2. Normal Spaces................................ 64 3. Tietze's extension Theorem......................... 67 4. Urysohn Metrization Theorem........................ 71 5. Imbedding of Manifolds.......................... -
General Topology
General Topology Tom Leinster 2014{15 Contents A Topological spaces2 A1 Review of metric spaces.......................2 A2 The definition of topological space.................8 A3 Metrics versus topologies....................... 13 A4 Continuous maps........................... 17 A5 When are two spaces homeomorphic?................ 22 A6 Topological properties........................ 26 A7 Bases................................. 28 A8 Closure and interior......................... 31 A9 Subspaces (new spaces from old, 1)................. 35 A10 Products (new spaces from old, 2)................. 39 A11 Quotients (new spaces from old, 3)................. 43 A12 Review of ChapterA......................... 48 B Compactness 51 B1 The definition of compactness.................... 51 B2 Closed bounded intervals are compact............... 55 B3 Compactness and subspaces..................... 56 B4 Compactness and products..................... 58 B5 The compact subsets of Rn ..................... 59 B6 Compactness and quotients (and images)............. 61 B7 Compact metric spaces........................ 64 C Connectedness 68 C1 The definition of connectedness................... 68 C2 Connected subsets of the real line.................. 72 C3 Path-connectedness.......................... 76 C4 Connected-components and path-components........... 80 1 Chapter A Topological spaces A1 Review of metric spaces For the lecture of Thursday, 18 September 2014 Almost everything in this section should have been covered in Honours Analysis, with the possible exception of some of the examples. For that reason, this lecture is longer than usual. Definition A1.1 Let X be a set. A metric on X is a function d: X × X ! [0; 1) with the following three properties: • d(x; y) = 0 () x = y, for x; y 2 X; • d(x; y) + d(y; z) ≥ d(x; z) for all x; y; z 2 X (triangle inequality); • d(x; y) = d(y; x) for all x; y 2 X (symmetry). -
Continuity Properties and Sensitivity Analysis of Parameterized Fixed
Continuity properties and sensitivity analysis of parameterized fixed points and approximate fixed points Zachary Feinsteina Washington University in St. Louis August 2, 2016 Abstract In this paper we consider continuity of the set of fixed points and approximate fixed points for parameterized set-valued mappings. Continuity properties are provided for the fixed points of general multivalued mappings, with additional results shown for contraction mappings. Further analysis is provided for the continuity of the approxi- mate fixed points of set-valued functions. Additional results are provided on sensitivity of the fixed points via set-valued derivatives related to tangent cones. Key words: fixed point problems; approximate fixed point problems; set-valued continuity; data dependence; generalized differentiation MSC: 54H25; 54C60; 26E25; 47H04; 47H14 1 Introduction Fixed points are utilized in many applications. Often the parameters of such models are estimated from data. As such it is important to understand how the set of fixed points aZachary Feinstein, ESE, Washington University, St. Louis, MO 63130, USA, [email protected]. 1 changes with respect to the parameters. We motivate our general approach by consider applications from economics and finance. In particular, the solution set of a parameterized game (i.e., Nash equilibria) fall under this setting. Thus if the parameters of the individuals playing the game are not perfectly known, sensitivity analysis can be done in a general way even without unique equilibrium. For the author, the immediate motivation was from financial systemic risk models such as those in [10, 8, 4, 12] where methodology to estimate system parameters are studied in, e.g., [15]. -
Lecture 7 1 Overview 2 Sequences and Cartesian Products
COMPSCI 230: Discrete Mathematics for Computer Science February 4, 2019 Lecture 7 Lecturer: Debmalya Panigrahi Scribe: Erin Taylor 1 Overview In this lecture, we introduce sequences and Cartesian products. We also define relations and study their properties. 2 Sequences and Cartesian Products Recall that two fundamental properties of sets are the following: 1. A set does not contain multiple copies of the same element. 2. The order of elements in a set does not matter. For example, if S = f1, 4, 3g then S is also equal to f4, 1, 3g and f1, 1, 3, 4, 3g. If we remove these two properties from a set, the result is known as a sequence. Definition 1. A sequence is an ordered collection of elements where an element may repeat multiple times. An example of a sequence with three elements is (1, 4, 3). This sequence, unlike the statement above for sets, is not equal to (4, 1, 3), nor is it equal to (1, 1, 3, 4, 3). Often the following shorthand notation is used to define a sequence: 1 s = 8i 2 N i 2i Here the sequence (s1, s2, ... ) is formed by plugging i = 1, 2, ... into the expression to find s1, s2, and so on. This sequence is (1/2, 1/4, 1/8, ... ). We now define a new set operator; the result of this operator is a set whose elements are two-element sequences. Definition 2. The Cartesian product of sets A and B, denoted by A × B, is a set defined as follows: A × B = f(a, b) : a 2 A, b 2 Bg. -
Cartesian Powers
Cartesian Powers sequences subsets functions exponential growth +, -, x, … Analogies between number and set operations Numbers Sets Addition Disjoint union Subtraction Complement Multiplication Cartesian product Exponents ? Cartesian Powers of a Set Cartesian product of a set with itself is a Cartesian power A2 = A x A Cartesian square An ≝ A x A x … x A n’th Cartesian power n X |An| = | A x A x … x A | = |A| x |A| x … x |A| = |A|n Practical and theoretical applications Applications California License Plates California Till 1904 no registration 1905-1912 various registration formats one-time $2 fee 1913 ≤6 digits 106 = 1 million If all OK Sam? 1956 263 x 103 ≈ 17.6 m 1969 263 x 104 ≈ 176 m Binary Strings {0,1}n = { length-n binary strings } n-bit strings 0 1 1 n Set Strings Size {0,1} 0 {0,1}0 Λ 1 00 01 1 {0,1}1 0, 1 2 {0,1}2 2 {0,1}2 00, 01, 10, 11 4 000, 001, 011, 010, 10 11 3 {0,1}3 8 100, 110, 101, 111 001 011 … … … … 010 {0,1}3 n {0,1}n 0…0, …, 1…1 2n 000 111 101 | {0,1}n | =|{0,1}|n = 2n 100 110 Subsets The power set of S, denoted ℙ(S), is the collection of all subsets of S ℙ( {a,b} ) = { {}, {a}, {b}, {a,b} } ℙ({a,b}) and {0,1}2 ℙ({a,b}) a b {0,1}2 Subsets Binary strings {} 00 |ℙ(S)| = ? of S of length |S| ❌ ❌ {b} ❌ ✅ 01 {a} ✅ ❌ 10 |S| 1-1 correspondence between ℙ(S) and {0,1} {a,b} ✅ ✅ 11 |ℙ(S)| = | {0,1}|S| | = 2|S| The size of the power set is the power of the set size Functions A function from A to B maps every element a ∈ A to an element f(a) ∈ B Define a function f: specify f(a) for every a ∈ A f from {1,2,3} to {p, u} specify -
Course 221: Michaelmas Term 2006 Section 1: Sets, Functions and Countability
Course 221: Michaelmas Term 2006 Section 1: Sets, Functions and Countability David R. Wilkins Copyright c David R. Wilkins 2006 Contents 1 Sets, Functions and Countability 2 1.1 Sets . 2 1.2 Cartesian Products of Sets . 5 1.3 Relations . 6 1.4 Equivalence Relations . 6 1.5 Functions . 8 1.6 The Graph of a Function . 9 1.7 Functions and the Empty Set . 10 1.8 Injective, Surjective and Bijective Functions . 11 1.9 Inverse Functions . 13 1.10 Preimages . 14 1.11 Finite and Infinite Sets . 16 1.12 Countability . 17 1.13 Cartesian Products and Unions of Countable Sets . 18 1.14 Uncountable Sets . 21 1.15 Power Sets . 21 1.16 The Cantor Set . 22 1 1 Sets, Functions and Countability 1.1 Sets A set is a collection of objects; these objects are known as elements of the set. If an element x belongs to a set X then we denote this fact by writing x ∈ X. Sets with small numbers of elements can be specified by listing the elements of the set enclosed within braces. For example {a, b, c, d} is the set consisting of the elements a, b, c and d. Two sets are equal if and only if they have the same elements. The empty set ∅ is the set with no elements. Standard notations N, Z, Q, R and C are adopted for the following sets: • the set N of positive integers; • the set Z of integers; • the set Q of rational numbers; • the set R of real numbers; • the set C of complex numbers. -
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. -
Worksheet: Cardinality, Countable and Uncountable Sets
Math 347 Worksheet: Cardinality A.J. Hildebrand Worksheet: Cardinality, Countable and Uncountable Sets • Key Tool: Bijections. • Definition: Let A and B be sets. A bijection from A to B is a function f : A ! B that is both injective and surjective. • Properties of bijections: ∗ Compositions: The composition of bijections is a bijection. ∗ Inverse functions: The inverse function of a bijection is a bijection. ∗ Symmetry: The \bijection" relation is symmetric: If there is a bijection f from A to B, then there is also a bijection g from B to A, given by the inverse of f. • Key Definitions. • Cardinality: Two sets A and B are said to have the same cardinality if there exists a bijection from A to B. • Finite sets: A set is called finite if it is empty or has the same cardinality as the set f1; 2; : : : ; ng for some n 2 N; it is called infinite otherwise. • Countable sets: A set A is called countable (or countably infinite) if it has the same cardinality as N, i.e., if there exists a bijection between A and N. Equivalently, a set A is countable if it can be enumerated in a sequence, i.e., if all of its elements can be listed as an infinite sequence a1; a2;::: . NOTE: The above definition of \countable" is the one given in the text, and it is reserved for infinite sets. Thus finite sets are not countable according to this definition. • Uncountable sets: A set is called uncountable if it is infinite and not countable. • Two famous results with memorable proofs. -
Advanced Calculus 1. Definition: the Cartesian Product a × B
Advanced Calculus 1. Definition: The Cartesian product A × B of sets A and B is A × B = {(a, b)| a ∈ A, b ∈ B}. This generalizes in the obvious way to higher Cartesian products: A1 × · · · × An = {(a1, . , an)| a1 ∈ A1, . , an ∈ An}. 2. Example: The real line R, the plane R2 = R×R, the n-dimensional real vector space Rn, R × [0, T], Rn × [0, T] etc. 3. Definition: The dot product (or inner or scalar product) of vectors x = (x1, . , xn) n and y = (y1, . , yn) in R is n X x · y = xiyi. i=1 n 4. Definition: The magnitude (or 2-norm) of a vector x = (x1, . , xn) in R is 1 " n # 2 X 1 2 2 |x| = xi = (x · x) . i=1 5. Definition: We write f : A 7→ B if f is a function whose domain is a subset of A and whose range is a subset of B. Let x = (x1, . , xn) n n be a point in R . So, if f(x) = f(x1, . , xn) is a function that has its domain in R , we write f : Rn 7→ R. So, for example, if 2 2 f(x1, x2, x3, x4) = x2x4 sin (x1 + x3), then f : R4 7→ R. We say that f takes R4 to R. 6. This notion is easily generalized to functions from Rn to Rm. Let x ∈ Rn and n f1(x), . , fm(x) be functions taking R to R. Then we can define a function f : Rn 7→ Rm, by f(x) = (f1(x), . , fm(x)). 2 7. -
Axioms of Set Theory and Equivalents of Axiom of Choice Farighon Abdul Rahim Boise State University, [email protected]
Boise State University ScholarWorks Mathematics Undergraduate Theses Department of Mathematics 5-2014 Axioms of Set Theory and Equivalents of Axiom of Choice Farighon Abdul Rahim Boise State University, [email protected] Follow this and additional works at: http://scholarworks.boisestate.edu/ math_undergraduate_theses Part of the Set Theory Commons Recommended Citation Rahim, Farighon Abdul, "Axioms of Set Theory and Equivalents of Axiom of Choice" (2014). Mathematics Undergraduate Theses. Paper 1. Axioms of Set Theory and Equivalents of Axiom of Choice Farighon Abdul Rahim Advisor: Samuel Coskey Boise State University May 2014 1 Introduction Sets are all around us. A bag of potato chips, for instance, is a set containing certain number of individual chip’s that are its elements. University is another example of a set with students as its elements. By elements, we mean members. But sets should not be confused as to what they really are. A daughter of a blacksmith is an element of a set that contains her mother, father, and her siblings. Then this set is an element of a set that contains all the other families that live in the nearby town. So a set itself can be an element of a bigger set. In mathematics, axiom is defined to be a rule or a statement that is accepted to be true regardless of having to prove it. In a sense, axioms are self evident. In set theory, we deal with sets. Each time we state an axiom, we will do so by considering sets. Example of the set containing the blacksmith family might make it seem as if sets are finite.