EQUIVALENT SETS and CARDINAL NUMBERS THESIS Presented To
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Set Theory, by Thomas Jech, Academic Press, New York, 1978, Xii + 621 Pp., '$53.00
BOOK REVIEWS 775 BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY Volume 3, Number 1, July 1980 © 1980 American Mathematical Society 0002-9904/80/0000-0 319/$01.75 Set theory, by Thomas Jech, Academic Press, New York, 1978, xii + 621 pp., '$53.00. "General set theory is pretty trivial stuff really" (Halmos; see [H, p. vi]). At least, with the hindsight afforded by Cantor, Zermelo, and others, it is pretty trivial to do the following. First, write down a list of axioms about sets and membership, enunciating some "obviously true" set-theoretic principles; the most popular Hst today is called ZFC (the Zermelo-Fraenkel axioms with the axiom of Choice). Next, explain how, from ZFC, one may derive all of conventional mathematics, including the general theory of transfinite cardi nals and ordinals. This "trivial" part of set theory is well covered in standard texts, such as [E] or [H]. Jech's book is an introduction to the "nontrivial" part. Now, nontrivial set theory may be roughly divided into two general areas. The first area, classical set theory, is a direct outgrowth of Cantor's work. Cantor set down the basic properties of cardinal numbers. In particular, he showed that if K is a cardinal number, then 2", or exp(/c), is a cardinal strictly larger than K (if A is a set of size K, 2* is the cardinality of the family of all subsets of A). Now starting with a cardinal K, we may form larger cardinals exp(ic), exp2(ic) = exp(exp(fc)), exp3(ic) = exp(exp2(ic)), and in fact this may be continued through the transfinite to form expa(»c) for every ordinal number a. -
Mathematics 144 Set Theory Fall 2012 Version
MATHEMATICS 144 SET THEORY FALL 2012 VERSION Table of Contents I. General considerations.……………………………………………………………………………………………………….1 1. Overview of the course…………………………………………………………………………………………………1 2. Historical background and motivation………………………………………………………….………………4 3. Selected problems………………………………………………………………………………………………………13 I I. Basic concepts. ………………………………………………………………………………………………………………….15 1. Topics from logic…………………………………………………………………………………………………………16 2. Notation and first steps………………………………………………………………………………………………26 3. Simple examples…………………………………………………………………………………………………………30 I I I. Constructions in set theory.………………………………………………………………………………..……….34 1. Boolean algebra operations.……………………………………………………………………………………….34 2. Ordered pairs and Cartesian products……………………………………………………………………… ….40 3. Larger constructions………………………………………………………………………………………………..….42 4. A convenient assumption………………………………………………………………………………………… ….45 I V. Relations and functions ……………………………………………………………………………………………….49 1.Binary relations………………………………………………………………………………………………………… ….49 2. Partial and linear orderings……………………………..………………………………………………… ………… 56 3. Functions…………………………………………………………………………………………………………… ….…….. 61 4. Composite and inverse function.…………………………………………………………………………… …….. 70 5. Constructions involving functions ………………………………………………………………………… ……… 77 6. Order types……………………………………………………………………………………………………… …………… 80 i V. Number systems and set theory …………………………………………………………………………………. 84 1. The Natural Numbers and Integers…………………………………………………………………………….83 2. Finite induction -
641 1. P. Erdös and A. H. Stone, Some Remarks on Almost Periodic
1946] DENSITY CHARACTERS 641 BIBLIOGRAPHY 1. P. Erdös and A. H. Stone, Some remarks on almost periodic transformations, Bull. Amer. Math. Soc. vol. 51 (1945) pp. 126-130. 2. W. H. Gottschalk, Powers of homeomorphisms with almost periodic propertiesf Bull. Amer. Math. Soc. vol. 50 (1944) pp. 222-227. UNIVERSITY OF PENNSYLVANIA AND UNIVERSITY OF VIRGINIA A REMARK ON DENSITY CHARACTERS EDWIN HEWITT1 Let X be an arbitrary topological space satisfying the TVseparation axiom [l, Chap. 1, §4, p. 58].2 We recall the following definition [3, p. 329]. DEFINITION 1. The least cardinal number of a dense subset of the space X is said to be the density character of X. It is denoted by the symbol %{X). We denote the cardinal number of a set A by | A |. Pospisil has pointed out [4] that if X is a Hausdorff space, then (1) |X| g 22SW. This inequality is easily established. Let D be a dense subset of the Hausdorff space X such that \D\ =S(-X'). For an arbitrary point pÇ^X and an arbitrary complete neighborhood system Vp at p, let Vp be the family of all sets UC\D, where U^VP. Thus to every point of X, a certain family of subsets of D is assigned. Since X is a Haus dorff space, VpT^Vq whenever p j*£q, and the correspondence assigning each point p to the family <DP is one-to-one. Since X is in one-to-one correspondence with a sub-hierarchy of the hierarchy of all families of subsets of D, the inequality (1) follows. -
Fast and Private Computation of Cardinality of Set Intersection and Union
Fast and Private Computation of Cardinality of Set Intersection and Union Emiliano De Cristofaroy, Paolo Gastiz, and Gene Tsudikz yPARC zUC Irvine Abstract. With massive amounts of electronic information stored, trans- ferred, and shared every day, legitimate needs for sensitive information must be reconciled with natural privacy concerns. This motivates var- ious cryptographic techniques for privacy-preserving information shar- ing, such as Private Set Intersection (PSI) and Private Set Union (PSU). Such techniques involve two parties { client and server { each with a private input set. At the end, client learns the intersection (or union) of the two respective sets, while server learns nothing. However, if desired functionality is private computation of cardinality rather than contents, of set intersection, PSI and PSU protocols are not appropriate, as they yield too much information. In this paper, we design an efficient crypto- graphic protocol for Private Set Intersection Cardinality (PSI-CA) that yields only the size of set intersection, with security in the presence of both semi-honest and malicious adversaries. To the best of our knowl- edge, it is the first protocol that achieves complexities linear in the size of input sets. We then show how the same protocol can be used to pri- vately compute set union cardinality. We also design an extension that supports authorization of client input. 1 Introduction Proliferation of, and growing reliance on, electronic information trigger the increase in the amount of sensitive data stored and processed in cyberspace. Consequently, there is a strong need for efficient cryptographic techniques that allow sharing information with privacy. Among these, Private Set Intersection (PSI) [11, 24, 14, 21, 15, 22, 9, 8, 18], and Private Set Union (PSU) [24, 15, 17, 12, 32] have attracted a lot of attention from the research community. -
1 Measurable Sets
Math 4351, Fall 2018 Chapter 11 in Goldberg 1 Measurable Sets Our goal is to define what is meant by a measurable set E ⊆ [a; b] ⊂ R and a measurable function f :[a; b] ! R. We defined the length of an open set and a closed set, denoted as jGj and jF j, e.g., j[a; b]j = b − a: We will use another notation for complement and the notation in the Goldberg text. Let Ec = [a; b] n E = [a; b] − E. Also, E1 n E2 = E1 − E2: Definitions: Let E ⊆ [a; b]. Outer measure of a set E: m(E) = inffjGj : for all G open and E ⊆ Gg. Inner measure of a set E: m(E) = supfjF j : for all F closed and F ⊆ Eg: 0 ≤ m(E) ≤ m(E). A set E is a measurable set if m(E) = m(E) and the measure of E is denoted as m(E). The symmetric difference of two sets E1 and E2 is defined as E1∆E2 = (E1 − E2) [ (E2 − E1): A set is called an Fσ set (F-sigma set) if it is a union of a countable number of closed sets. A set is called a Gδ set (G-delta set) if it is a countable intersection of open sets. Properties of Measurable Sets on [a; b]: 1. If E1 and E2 are subsets of [a; b] and E1 ⊆ E2, then m(E1) ≤ m(E2) and m(E1) ≤ m(E2). In addition, if E1 and E2 are measurable subsets of [a; b] and E1 ⊆ E2, then m(E1) ≤ m(E2). -
Julia's Efficient Algorithm for Subtyping Unions and Covariant
Julia’s Efficient Algorithm for Subtyping Unions and Covariant Tuples Benjamin Chung Northeastern University, Boston, MA, USA [email protected] Francesco Zappa Nardelli Inria of Paris, Paris, France [email protected] Jan Vitek Northeastern University, Boston, MA, USA Czech Technical University in Prague, Czech Republic [email protected] Abstract The Julia programming language supports multiple dispatch and provides a rich type annotation language to specify method applicability. When multiple methods are applicable for a given call, Julia relies on subtyping between method signatures to pick the correct method to invoke. Julia’s subtyping algorithm is surprisingly complex, and determining whether it is correct remains an open question. In this paper, we focus on one piece of this problem: the interaction between union types and covariant tuples. Previous work normalized unions inside tuples to disjunctive normal form. However, this strategy has two drawbacks: complex type signatures induce space explosion, and interference between normalization and other features of Julia’s type system. In this paper, we describe the algorithm that Julia uses to compute subtyping between tuples and unions – an algorithm that is immune to space explosion and plays well with other features of the language. We prove this algorithm correct and complete against a semantic-subtyping denotational model in Coq. 2012 ACM Subject Classification Theory of computation → Type theory Keywords and phrases Type systems, Subtyping, Union types Digital Object Identifier 10.4230/LIPIcs.ECOOP.2019.24 Category Pearl Supplement Material ECOOP 2019 Artifact Evaluation approved artifact available at https://dx.doi.org/10.4230/DARTS.5.2.8 Acknowledgements The authors thank Jiahao Chen for starting us down the path of understanding Julia, and Jeff Bezanson for coming up with Julia’s subtyping algorithm. -
Cardinal Invariants Concerning Functions Whose Sum Is Almost Continuous Krzysztof Ciesielski West Virginia University, [email protected]
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by The Research Repository @ WVU (West Virginia University) Faculty Scholarship 1995 Cardinal Invariants Concerning Functions Whose Sum Is Almost Continuous Krzysztof Ciesielski West Virginia University, [email protected] Follow this and additional works at: https://researchrepository.wvu.edu/faculty_publications Part of the Mathematics Commons Digital Commons Citation Ciesielski, Krzysztof, "Cardinal Invariants Concerning Functions Whose Sum Is Almost Continuous" (1995). Faculty Scholarship. 822. https://researchrepository.wvu.edu/faculty_publications/822 This Article is brought to you for free and open access by The Research Repository @ WVU. It has been accepted for inclusion in Faculty Scholarship by an authorized administrator of The Research Repository @ WVU. For more information, please contact [email protected]. Cardinal invariants concerning functions whose sum is almost continuous. Krzysztof Ciesielski1, Department of Mathematics, West Virginia University, Mor- gantown, WV 26506-6310 ([email protected]) Arnold W. Miller1, York University, Department of Mathematics, North York, Ontario M3J 1P3, Canada, Permanent address: University of Wisconsin-Madison, Department of Mathematics, Van Vleck Hall, 480 Lincoln Drive, Madison, Wis- consin 53706-1388, USA ([email protected]) Abstract Let A stand for the class of all almost continuous functions from R to R and let A(A) be the smallest cardinality of a family F ⊆ RR for which there is no g: R → R with the property that f + g ∈ A for all f ∈ F . We define cardinal number A(D) for the class D of all real functions with the Darboux property similarly. -
Elements of Set Theory
Elements of set theory April 1, 2014 ii Contents 1 Zermelo{Fraenkel axiomatization 1 1.1 Historical context . 1 1.2 The language of the theory . 3 1.3 The most basic axioms . 4 1.4 Axiom of Infinity . 4 1.5 Axiom schema of Comprehension . 5 1.6 Functions . 6 1.7 Axiom of Choice . 7 1.8 Axiom schema of Replacement . 9 1.9 Axiom of Regularity . 9 2 Basic notions 11 2.1 Transitive sets . 11 2.2 Von Neumann's natural numbers . 11 2.3 Finite and infinite sets . 15 2.4 Cardinality . 17 2.5 Countable and uncountable sets . 19 3 Ordinals 21 3.1 Basic definitions . 21 3.2 Transfinite induction and recursion . 25 3.3 Applications with choice . 26 3.4 Applications without choice . 29 3.5 Cardinal numbers . 31 4 Descriptive set theory 35 4.1 Rational and real numbers . 35 4.2 Topological spaces . 37 4.3 Polish spaces . 39 4.4 Borel sets . 43 4.5 Analytic sets . 46 4.6 Lebesgue's mistake . 48 iii iv CONTENTS 5 Formal logic 51 5.1 Propositional logic . 51 5.1.1 Propositional logic: syntax . 51 5.1.2 Propositional logic: semantics . 52 5.1.3 Propositional logic: completeness . 53 5.2 First order logic . 56 5.2.1 First order logic: syntax . 56 5.2.2 First order logic: semantics . 59 5.2.3 Completeness theorem . 60 6 Model theory 67 6.1 Basic notions . 67 6.2 Ultraproducts and nonstandard analysis . 68 6.3 Quantifier elimination and the real closed fields . -
21 Cardinal and Ordinal Numbers. by W. Sierpióski. Monografie Mate
BOOK REVIEWS 21 Cardinal and ordinal numbers. By W. Sierpióski. Monografie Mate- matyczne, vol. 34. Warszawa, Panstwowe Wydawnictwo Naukowe, 1958. 487 pp. Not since the publication in 1928 of his Leçons sur les nombres transfinis has Sierpióski written a book on transfinite numbers. The present book, embodying the fruits of a lifetime of research and ex perience in teaching the subject, is therefore most welcome. Although generally similar in outline to the earlier work, it is an entirely new book, and more than twice as long. The exposition is leisurely and thickly interspersed with illuminating discussion and examples. The result is a book which is highly instructive and eminently readable. Whether one takes the chapters in order or dips in at random he is almost sure to find something interesting. Many examples and ap plications are included in the form of exercises, nearly all accom panied by solutions. The exposition is from the standpoint of naive set theory. No axioms, other than the axiom of choice, are ever stated explicitly, although Zermelo's system is occasionally referred to. But the role of the axiom of choice is a central theme throughout the book. For a student who wishes to learn just when and how this axiom is needed this is the best book yet written. There is an excellent chapter de voted to theorems equivalent to the axiom of choice. These include not only well-ordering, trichotomy, and Zorn's principle, but also several less familiar propositions: Lindenbaum's theorem that of any two nonempty sets one is equivalent to a partition of the other; Vaught's theorem that every family of nonempty sets contains a maximal disjoint family; Tarski's theorem that every cardinal has a successor, and other propositions of cardinal arithmetic; Kurepa's theorem that the proposition that every partially ordered set con tains a maximal family of incomparable elements is an equivalent when joined with the ordering principle, i.e., the proposition that every set can be ordered. -
Naïve Set Theory Basic Definitions Naïve Set Theory Is the Non-Axiomatic Treatment of Set Theory
Naïve Set Theory Basic Definitions Naïve set theory is the non-axiomatic treatment of set theory. In the axiomatic treatment, which we will only allude to at times, a set is an undefined term. For us however, a set will be thought of as a collection of some (possibly none) objects. These objects are called the members (or elements) of the set. We use the symbol "∈" to indicate membership in a set. Thus, if A is a set and x is one of its members, we write x ∈ A and say "x is an element of A" or "x is in A" or "x is a member of A". Note that "∈" is not the same as the Greek letter "ε" epsilon. Basic Definitions Sets can be described notationally in many ways, but always using the set brackets "{" and "}". If possible, one can just list the elements of the set: A = {1,3, oranges, lions, an old wad of gum} or give an indication of the elements: ℕ = {1,2,3, ... } ℤ = {..., -2,-1,0,1,2, ...} or (most frequently in mathematics) using set-builder notation: S = {x ∈ ℝ | 1 < x ≤ 7 } or {x ∈ ℝ : 1 < x ≤ 7 } which is read as "S is the set of real numbers x, such that x is greater than 1 and less than or equal to 7". In some areas of mathematics sets may be denoted by special notations. For instance, in analysis S would be written (1,7]. Basic Definitions Note that sets do not contain repeated elements. An element is either in or not in a set, never "in the set 5 times" for instance. -
Fast and Private Computation of Cardinality of Set Intersection and Union*
Fast and Private Computation of Cardinality of Set Intersection and Union* Emiliano De Cristofaroy, Paolo Gastiz, Gene Tsudikz yPARC zUC Irvine Abstract In many everyday scenarios, sensitive information must be shared between parties without com- plete mutual trust. Private set operations are particularly useful to enable sharing information with privacy, as they allow two or more parties to jointly compute operations on their sets (e.g., intersec- tion, union, etc.), such that only the minimum required amount of information is disclosed. In the last few years, the research community has proposed a number of secure and efficient techniques for Private Set Intersection (PSI), however, somewhat less explored is the problem of computing the magnitude, rather than the contents, of the intersection – we denote this problem as Private Set In- tersection Cardinality (PSI-CA). This paper explores a few PSI-CA variations and constructs several protocols that are more efficient than the state-of-the-art. 1 Introduction Proliferation of, and growing reliance on, electronic information generate an increasing amount of sensitive data stored and processed in the cyberspace. Consequently, there is a compelling need for efficient cryptographic techniques that allow sharing information while protecting privacy. Among these, Private Set Intersection (PSI) [15, 29, 18, 26, 19, 27, 12, 11, 22], and Private Set Union (PSU) [29, 19, 21, 16, 36] have recently attracted a lot of attention from the research community. In particular, PSI allows one party (client) to compute the intersection of its set with that of another party (server), such that: (i) server does not learn client input, and (ii) client learns no information about server input, beyond the intersection. -
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.