A Complete Characterization of Maximal Symmetric Difference-Free Families on {1,…N}
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On Properties of Families of Sets Lecture 2
On properties of families of sets Lecture 2 Lajos Soukup Alfréd Rényi Institute of Mathematics Hungarian Academy of Sciences http://www.renyi.hu/∼soukup 7th Young Set Theory Workshop Recapitulation Recapitulation Definition: A family A⊂P(X) has property B iff χ(A)= 2, where the chromatic number of A is defined as follows: χ(A)=min{λ | ∃f : X → λ ∀A ∈ A |f [A]|≥ 2}. Recapitulation Definition: A family A⊂P(X) has property B iff χ(A)= 2, where the chromatic number of A is defined as follows: χ(A)=min{λ | ∃f : X → λ ∀A ∈ A |f [A]|≥ 2}. Theorem (E. W. Miller, 1937) ω There is an almost disjoint A⊂ ω with χ(A)= ω. Recapitulation Definition: A family A⊂P(X) has property B iff χ(A)= 2, where the chromatic number of A is defined as follows: χ(A)=min{λ | ∃f : X → λ ∀A ∈ A |f [A]|≥ 2}. Theorem (E. W. Miller, 1937) ω There is an almost disjoint A⊂ ω with χ(A)= ω. Theorem (Gy. Elekes, Gy Hoffman, 1973) ω For all infinite cardinal κ there is an almost disjoint A⊂ X with χ(A) ≥ κ. Recapitulation Definition: A family A⊂P(X) has property B iff χ(A)= 2, where the chromatic number of A is defined as follows: χ(A)=min{λ | ∃f : X → λ ∀A ∈ A |f [A]|≥ 2}. Theorem (E. W. Miller, 1937) ω There is an almost disjoint A⊂ ω with χ(A)= ω. Theorem (Gy. Elekes, Gy Hoffman, 1973) ω For all infinite cardinal κ there is an almost disjoint A⊂ X with χ(A) ≥ κ. -
Some Intersection Theorems for Ordered Sets and Graphs
IOURNAL OF COMBINATORIAL THEORY, Series A 43, 23-37 (1986) Some Intersection Theorems for Ordered Sets and Graphs F. R. K. CHUNG* AND R. L. GRAHAM AT&T Bell Laboratories, Murray Hill, New Jersey 07974 and *Bell Communications Research, Morristown, New Jersey P. FRANKL C.N.R.S., Paris, France AND J. B. SHEARER' Universify of California, Berkeley, California Communicated by the Managing Editors Received May 22, 1984 A classical topic in combinatorics is the study of problems of the following type: What are the maximum families F of subsets of a finite set with the property that the intersection of any two sets in the family satisfies some specified condition? Typical restrictions on the intersections F n F of any F and F’ in F are: (i) FnF’# 0, where all FEF have k elements (Erdos, Ko, and Rado (1961)). (ii) IFn F’I > j (Katona (1964)). In this paper, we consider the following general question: For a given family B of subsets of [n] = { 1, 2,..., n}, what is the largest family F of subsets of [n] satsifying F,F’EF-FnFzB for some BE B. Of particular interest are those B for which the maximum families consist of so- called “kernel systems,” i.e., the family of all supersets of some fixed set in B. For example, we show that the set of all (cyclic) translates of a block of consecutive integers in [n] is such a family. It turns out rather unexpectedly that many of the results we obtain here depend strongly on properties of the well-known entropy function (from information theory). -
A Class of Symmetric Difference-Closed Sets Related to Commuting Involutions John Campbell
A class of symmetric difference-closed sets related to commuting involutions John Campbell To cite this version: John Campbell. A class of symmetric difference-closed sets related to commuting involutions. Discrete Mathematics and Theoretical Computer Science, DMTCS, 2017, Vol 19 no. 1. hal-01345066v4 HAL Id: hal-01345066 https://hal.archives-ouvertes.fr/hal-01345066v4 Submitted on 18 Mar 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Discrete Mathematics and Theoretical Computer Science DMTCS vol. 19:1, 2017, #8 A class of symmetric difference-closed sets related to commuting involutions John M. Campbell York University, Canada received 19th July 2016, revised 15th Dec. 2016, 1st Feb. 2017, accepted 10th Feb. 2017. Recent research on the combinatorics of finite sets has explored the structure of symmetric difference-closed sets, and recent research in combinatorial group theory has concerned the enumeration of commuting involutions in Sn and An. In this article, we consider an interesting combination of these two subjects, by introducing classes of symmetric difference-closed sets of elements which correspond in a natural way to commuting involutions in Sn and An. We consider the natural combinatorial problem of enumerating symmetric difference-closed sets consisting of subsets of sets consisting of pairwise disjoint 2-subsets of [n], and the problem of enumerating symmetric difference-closed sets consisting of elements which correspond to commuting involutions in An. -
Families of Sets and Extended Operations Families of Sets
Families of Sets and Extended Operations Families of Sets When dealing with sets whose elements are themselves sets it is fairly common practice to refer to them as families of sets, however this is not a definition. In fact, technically, a family of sets need not be a set, because we allow repeated elements, so a family is a multiset. However, we do require that when repeated elements appear they are distinguishable. F = {A , A , A , A } with A = {a,b,c}, A ={a}, A = {a,d} and 1 2 3 4 1 2 3 A = {a} is a family of sets. 4 Extended Union and Intersection Let F be a family of sets. Then we define: The union over F by: ∪ A={x :∃ A∈F x∈A}= {x :∃ A A∈F∧x∈A} A∈F and the intersection over F by: ∩ A = {x :∀ A∈F x∈A}= {x :∀ A A∈F ⇒ x∈A}. A∈F For example, with F = {A , A , A , A } where A = {a,b,c}, 1 2 3 4 1 A ={a}, A = {a,d} and A = {a} we have: 2 3 4 ∪ A = {a ,b , c , d } and ∩ A = {a}. A∈F A∈F Theorem 2.8 For each set B in a family F of sets, a) ∩ A ⊆ B A∈F b) B ⊆ ∪ A. A∈F Pf: a) Suppose x ∈ ∩ A, then ∀A ∈ F, x ∈ A. Since B ∈ F, we have x ∈ B. Thus, ∩ A ⊆ B. b) Now suppose y ∈ B. Since B ∈ F, y ∈ ∪ A. Thus, B ⊆ ∪ A. Caveat Care must be taken with the empty family F, i.e., the family containing no sets. -
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. -
Families of Sets
FORMALIZED MATHEMATICS Number 1, January 1990 Universit´eCatholique de Louvain Families of Sets Beata Padlewska1 Warsaw University Bia lystok Summary. The article contains definitions of the following concepts: family of sets, family of subsets of a set, the intersection of a family of sets. Functors ∪, ∩, and \ are redefined for families of subsets of a set. Some properties of these notions are presented. The terminology and notation used in this paper are introduced in the following papers: [1], [3], and [2]. For simplicity we adopt the following convention: X, Y , Z, Z1, D will denote objects of the type set; x, y will denote objects of the type Any. Let us consider X. The functor \ X, with values of the type set, is defined by for x holds x ∈ it iff for Y holds Y ∈ X implies x ∈ Y, if X 6= ∅, it = ∅, otherwise. The following propositions are true: (1) X 6= ∅ implies for x holds x ∈ \ X iff for Y st Y ∈ X holds x ∈ Y, (2) \ ∅ = ∅, (3) \ X ⊆ [ X, (4) Z ∈ X implies \ X ⊆ Z, (5) ∅∈ X implies \ X = ∅, (6) X 6= ∅ &(for Z1 st Z1 ∈ X holds Z ⊆ Z1) implies Z ⊆ \ X, 1Supported by RPBP.III-24.C1. cf 1990 Fondation Philippe le Hodey 147 ISSN 0777-4028 148 Beata Padlewska (7) X 6= ∅ & X ⊆ Y implies \ Y ⊆ \ X, (8) X ∈ Y & X ⊆ Z implies \ Y ⊆ Z, (9) X ∈ Y & X ∩ Z = ∅ implies \ Y ∩ Z = ∅, (10) X 6= ∅ & Y 6= ∅ implies \(X ∪ Y )= \ X ∩ \ Y, (11) \{x} = x, (12) \{X,Y } = X ∩ Y. Set-Family stands for 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. -
INTERSECTION PROPERTIES of FAMILIES CONTAINING SETS of NEARLY the SAME SIZE P. Erdős, R. Silverman and A. Stein Abstract a Fami
INTERSECTION PROPERTIES OF FAMILIES CONTAINING SETS OF NEARLY THE SAME SIZE P . Erdős, R . Silverman and A . Stein Abstract A family F of sets has property B(s) if there exists a set S whose intersection with each set in F is non-empty but contains fewer than s elements . P . Erdős has asked whether there exists an absolute constant c such that every projective plane has property B(c) . In this paper, the authors, as a partial answer to this question, obtain the result that for n sufficiently large, every projective plane of order n has property B(c log n) . The result is a corollary of a theorem applicable to somewhat more general families of finite sets . A family F of sets has property B if there is a set S whose intersection with each set in the family is a proper subset of that set . Many algebraic and combinatorial problems may be restated in terms of property B . P . Erdős [1] proposed property B(s) as a stronger form of property B . A family F has property B(s) if there is a set S whose intersection with each set in the family is a proper subset of that set containing fewer than s elements . Property B(s) has been studied by, among others, Silverman, Levinson, Stein, Abbott and Erdos . Property B is an important combinatorial property, and the related literature includes, for example, a recent paper by D . Kleitman on Sperner families [4] . In this paper we consider 2 questions : 1) P . Erdős has asked whether there exists an absolute constant c such that every projective plane has property B(c) . -
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.