Relations and Partial Orders
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A Theory of Well-Connected Relations 99
INFORMA TION SCIENCES 19, 97- 134 (1979) 97 A Theory of Well-conwcted Relations SUDHIR K. ARORA and K. C. SMITH Lkpartment of Conputer Science, Uniwrsity of Toronto, Toronto, Cuna& MSS IA7 Communicated by John M. Richardson ABSTRACT The simple concept of a well-connected relation (WCR) is defined and then developed into a theory for studying the structure of binary relations. Several interesting partitions of a binary relation are identified. It is shown that binary relations can be separated into families which form a hierarchy. Finally, concepts of universal algebra are extended to the family of “prime” relations. One application for the theory is in the logical design of data bases. INTRODUCTION Data in an information system have been studied from several points of view [2, 4, 9, 10, Ill. With the growing interest in data base systems, the possibility for structuring the data in various ways has been explored by several authors. For example, Delobel [9] defines “elementary functional relations” and proposes a theory based on this building block; Zaniolo [lo] defines “atomic relations” as a basic building block for data; Furtado and Kerschberg [ 1 l] have “quotient relations.” Further, many authors have noted and studied specific data structures, such as “functional dependencies” [4], “multivalued dependencies” [5], “contextual dependencies” [6], “mutual de- pendencies” [12] (which happen to be same as contextual dependencies), and “hierarchical dependencies” [ 131. In this paper we define a new building block, “well-connected relations,” and propose a theory to study binary relations. Elsewhere [6] we have applied this theory to the study of dependency structures of data. -
Filtering Germs: Groupoids Associated to Inverse Semigroups
FILTERING GERMS: GROUPOIDS ASSOCIATED TO INVERSE SEMIGROUPS BECKY ARMSTRONG, LISA ORLOFF CLARK, ASTRID AN HUEF, MALCOLM JONES, AND YING-FEN LIN Abstract. We investigate various groupoids associated to an arbitrary inverse semigroup with zero. We show that the groupoid of filters with respect to the natural partial order is isomorphic to the groupoid of germs arising from the standard action of the inverse semigroup on the space of idempotent filters. We also investigate the restriction of this isomorphism to the groupoid of tight filters and to the groupoid of ultrafilters. 1. Introduction An inverse semigroup is a set S endowed with an associative binary operation such that for each a 2 S, there is a unique a∗ 2 S, called the inverse of a, satisfying aa∗a = a and a∗aa∗ = a∗: The study of ´etalegroupoids associated to inverse semigroups was initiated by Renault [Ren80, Remark III.2.4]. We consider two well known groupoid constructions: the filter approach and the germ approach, and we show that the two approaches yield isomorphic groupoids. Every inverse semigroup has a natural partial order, and a filter is a nonempty down-directed up-set with respect to this order. The filter approach to groupoid construction first appeared in [Len08], and was later simplified in [LMS13]. Work in this area is ongoing; see for instance, [Bic21, BC20, Cas20]. Every inverse semigroup acts on the filters of its subsemigroup of idempotents. The groupoid of germs associated to an inverse semigroup encodes this action. Paterson pioneered the germ approach in [Pat99] with the introduction of the universal groupoid of an inverse semigroup. -
Relations on Semigroups
International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-04, Issue-09, Dec 2018 Relations on Semigroups 1D.D.Padma Priya, 2G.Shobhalatha, 3U.Nagireddy, 4R.Bhuvana Vijaya 1 Sr.Assistant Professor, Department of Mathematics, New Horizon College Of Engineering, Bangalore, India, Research scholar, Department of Mathematics, JNTUA- Anantapuram [email protected] 2Professor, Department of Mathematics, SKU-Anantapuram, India, [email protected] 3Assistant Professor, Rayalaseema University, Kurnool, India, [email protected] 4Associate Professor, Department of Mathematics, JNTUA- Anantapuram, India, [email protected] Abstract: Equivalence relations play a vital role in the study of quotient structures of different algebraic structures. Semigroups being one of the algebraic structures are sets with associative binary operation defined on them. Semigroup theory is one of such subject to determine and analyze equivalence relations in the sense that it could be easily understood. This paper contains the quotient structures of semigroups by extending equivalence relations as congruences. We define different types of relations on the semigroups and prove they are equivalence, partial order, congruence or weakly separative congruence relations. Keywords: Semigroup, binary relation, Equivalence and congruence relations. I. INTRODUCTION [1,2,3 and 4] Algebraic structures play a prominent role in mathematics with wide range of applications in science and engineering. A semigroup -
Scott Spaces and the Dcpo Category
SCOTT SPACES AND THE DCPO CATEGORY JORDAN BROWN Abstract. Directed-complete partial orders (dcpo’s) arise often in the study of λ-calculus. Here we investigate certain properties of dcpo’s and the Scott spaces they induce. We introduce a new construction which allows for the canonical extension of a partial order to a dcpo and give a proof that the dcpo introduced by Zhao, Xi, and Chen is well-filtered. Contents 1. Introduction 1 2. General Definitions and the Finite Case 2 3. Connectedness of Scott Spaces 5 4. The Categorical Structure of DCPO 6 5. Suprema and the Waybelow Relation 7 6. Hofmann-Mislove Theorem 9 7. Ordinal-Based DCPOs 11 8. Acknowledgments 13 References 13 1. Introduction Directed-complete partially ordered sets (dcpo’s) often arise in the study of λ-calculus. Namely, they are often used to construct models for λ theories. There are several versions of the λ-calculus, all of which attempt to describe the ‘computable’ functions. The first robust descriptions of λ-calculus appeared around the same time as the definition of Turing machines, and Turing’s paper introducing computing machines includes a proof that his computable functions are precisely the λ-definable ones [5] [8]. Though we do not address the λ-calculus directly here, an exposition of certain λ theories and the construction of Scott space models for them can be found in [1]. In these models, computable functions correspond to continuous functions with respect to the Scott topology. It is thus with an eye to the application of topological tools in the study of computability that we investigate the Scott topology. -
Section 8.6 What Is a Partial Order?
Announcements ICS 6B } Regrades for Quiz #3 and Homeworks #4 & Boolean Algebra & Logic 5 are due Today Lecture Notes for Summer Quarter, 2008 Michele Rousseau Set 8 – Ch. 8.6, 11.6 Lecture Set 8 - Chpts 8.6, 11.1 2 Today’s Lecture } Chapter 8 8.6, Chapter 11 11.1 ● Partial Orderings 8.6 Chapter 8: Section 8.6 ● Boolean Functions 11.1 Partial Orderings (Continued) Lecture Set 8 - Chpts 8.6, 11.1 3 What is a Partial Order? Some more defintions Let R be a relation on A. The R is a partial order iff R is: } If A,R is a poset and a,b are A, reflexive, antisymmetric, & transitive we say that: } A,R is called a partially ordered set or “poset” ● “a and b are comparable” if ab or ba } Notation: ◘ i.e. if a,bR and b,aR ● If A, R is a poset and a and b are 2 elements of A ● “a and b are incomparable” if neither ab nor ba such that a,bR, we write a b instead of aRb ◘ i.e if a,bR and b,aR } If two objects are always related in a poset it is called a total order, linear order or simple order. NOTE: it is not required that two things be related under a partial order. ● In this case A,R is called a chain. ● i.e if any two elements of A are comparable ● That’s the “partial” of it. ● So for all a,b A, it is true that a,bR or b,aR 5 Lecture Set 8 - Chpts 8.6, 11.1 6 1 Now onto more examples… More Examples Let Aa,b,c,d and let R be the relation Let A0,1,2,3 and on A represented by the diagraph Let R0,01,1, 2,0,2,2,2,33,3 The R is reflexive, but We draw the associated digraph: a b not antisymmetric a,c &c,a It is easy to check that R is 0 and not 1 c d transitive d,cc,a, but not d,a Refl. -
[Math.NT] 1 Nov 2006
ADJOINING IDENTITIES AND ZEROS TO SEMIGROUPS MELVYN B. NATHANSON Abstract. This note shows how iteration of the standard process of adjoining identities and zeros to semigroups gives rise naturally to the lexicographical ordering on the additive semigroups of n-tuples of nonnegative integers and n-tuples of integers. 1. Semigroups with identities and zeros A binary operation ∗ on a set S is associative if (a ∗ b) ∗ c = a ∗ (b ∗ c) for all a,b,c ∈ S. A semigroup is a nonempty set with an associative binary operation ∗. The semigroup is abelian if a ∗ b = b ∗ a for all a,b ∈ S. The trivial semigroup S0 consists of a single element s0 such that s0 ∗ s0 = s0. Theorems about abstract semigroups are, in a sense, theorems about the pure process of multiplication. An element u in a semigroup S is an identity if u ∗ a = a ∗ u = a for all a ∈ S. If u and u′ are identities in a semigroup, then u = u ∗ u′ = u′ and so a semigroup contains at most one identity. A semigroup with an identity is called a monoid. If S is a semigroup that is not a monoid, that is, if S does not contain an identity element, there is a simple process to adjoin an identity to S. Let u be an element not in S and let I(S,u)= S ∪{u}. We extend the binary operation ∗ from S to I(S,u) by defining u ∗ a = a ∗ u = a for all a ∈ S, and u ∗ u = u. Then I(S,u) is a monoid with identity u. -
Sets, Relations, Pos and Lattices
Contents 1 Discrete structures F TECHN O OL E O T G U Y IT K T H S A N R I A N G A P I U D R N I 19 51 yog, km s kOflm^ Chittaranjan Mandal (IIT Kharagpur) SCLD January 21, 2020 1 / 23 Discrete structures Section outline Lattices (contd.) Boolean lattice 1 Discrete structures Boolean lattice structure Sets Boolean algebra Relations Additional Boolean algebra Lattices properties F TECHN O OL E O T G U Y IT K T H S A N R I A N G A P I U D R N I 19 51 yog, km s kOflm^ Chittaranjan Mandal (IIT Kharagpur) SCLD January 21, 2020 2 / 23 S = fXjX 62 Xg S 2 S? [Russell’s paradox] Set union: A [ B A B Set intersection: A \ B A B U Complement: S A Set difference: A − B = A \ B A B + Natural numbers: N = f0; 1; 2; 3;:::g or f1; 2; 3;:::g = Z Integers: Z = f:::; −3; −2; −1; 0; 1; 2; 3;:::g Universal set: U Empty set: ? = fg Discrete structures Sets Sets A set A of elements: A = fa; b; cg F TECHN O OL E O T G U Y IT K T H S A N R I A N G A P I U D R N I 19 51 yog, km s kOflm^ Chittaranjan Mandal (IIT Kharagpur) SCLD January 21, 2020 3 / 23 S = fXjX 62 Xg S 2 S? [Russell’s paradox] Set union: A [ B A B Set intersection: A \ B A B U Complement: S A Set difference: A − B = A \ B A B Integers: Z = f:::; −3; −2; −1; 0; 1; 2; 3;:::g Universal set: U Empty set: ? = fg Discrete structures Sets Sets A set A of elements: A = fa; b; cg + Natural numbers: N = f0; 1; 2; 3;:::g or f1; 2; 3;:::g = Z F TECHN O OL E O T G U Y IT K T H S A N R I A N G A P I U D R N I 19 51 yog, km s kOflm^ Chittaranjan Mandal (IIT Kharagpur) SCLD January 21, 2020 3 / 23 S = fXjX -
Binary Relations and Functions
Harvard University, Math 101, Spring 2015 Binary relations and Functions 1 Binary Relations Intuitively, a binary relation is a rule to pair elements of a sets A to element of a set B. When two elements a 2 A is in a relation to an element b 2 B we write a R b . Since the order is relevant, we can completely characterize a relation R by the set of ordered pairs (a; b) such that a R b. This motivates the following formal definition: Definition A binary relation between two sets A and B is a subset of the Cartesian product A×B. In other words, a binary relation is an element of P(A × B). A binary relation on A is a subset of P(A2). It is useful to introduce the notions of domain and range of a binary relation R from a set A to a set B: • Dom(R) = fx 2 A : 9 y 2 B xRyg Ran(R) = fy 2 B : 9 x 2 A : xRyg. 2 Properties of a relation on a set Given a binary relation R on a set A, we have the following definitions: • R is transitive iff 8x; y; z 2 A :(xRy and yRz) =) xRz: • R is reflexive iff 8x 2 A : x Rx • R is irreflexive iff 8x 2 A : :(xRx) • R is symmetric iff 8x; y 2 A : xRy =) yRx • R is asymmetric iff 8x; y 2 A : xRy =):(yRx): 1 • R is antisymmetric iff 8x; y 2 A :(xRy and yRx) =) x = y: In a given set A, we can always define one special relation called the identity relation. -
Relations 21
2. CLOSURE OF RELATIONS 21 2. Closure of Relations 2.1. Definition of the Closure of Relations. Definition 2.1.1. Given a relation R on a set A and a property P of relations, the closure of R with respect to property P , denoted ClP (R), is smallest relation on A that contains R and has property P . That is, ClP (R) is the relation obtained by adding the minimum number of ordered pairs to R necessary to obtain property P . Discussion To say that ClP (R) is the “smallest” relation on A containing R and having property P means that • R ⊆ ClP (R), • ClP (R) has property P , and • if S is another relation with property P and R ⊆ S, then ClP (R) ⊆ S. The following theorem gives an equivalent way to define the closure of a relation. \ Theorem 2.1.1. If R is a relation on a set A, then ClP (R) = S, where S∈P P = {S|R ⊆ S and S has property P }. Exercise 2.1.1. Prove Theorem 2.1.1. [Recall that one way to show two sets, A and B, are equal is to show A ⊆ B and B ⊆ A.] 2.2. Reflexive Closure. Definition 2.2.1. Let A be a set and let ∆ = {(x, x)|x ∈ A}. ∆ is called the diagonal relation on A. Theorem 2.2.1. Let R be a relation on A. The reflexive closure of R, denoted r(R), is the relation R ∪ ∆. Proof. Clearly, R ∪ ∆ is reflexive, since (a, a) ∈ ∆ ⊆ R ∪ ∆ for every a ∈ A. -
Scalability of Reflexive-Transitive Closure Tables As Hierarchical Data Solutions
Scalability of Reflexive- Transitive Closure Tables as Hierarchical Data Solutions Analysis via SQL Server 2008 R2 Brandon Berry, Engineer 12/8/2011 Reflexive-Transitive Closure (RTC) tables, when used to persist hierarchical data, present many advantages over alternative persistence strategies such as path enumeration. Such advantages include, but are not limited to, referential integrity and a simple structure for data queries. However, RTC tables grow exponentially and present a concern with scaling both operational performance of the RTC table and volume of the RTC data. Discovering these practical performance boundaries involves understanding the growth patterns of reflexive and transitive binary relations and observing sample data for large hierarchical models. Table of Contents 1 Introduction ......................................................................................................................................... 2 2 Reflexive-Transitive Closure Properties ................................................................................................. 3 2.1 Reflexivity ...................................................................................................................................... 3 2.2 Transitivity ..................................................................................................................................... 3 2.3 Closure .......................................................................................................................................... 4 3 Scalability -
Generic Filters in Partially Ordered Sets Esfandiar Eslami Iowa State University
Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 1982 Generic filters in partially ordered sets Esfandiar Eslami Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Mathematics Commons Recommended Citation Eslami, Esfandiar, "Generic filters in partially ordered sets " (1982). Retrospective Theses and Dissertations. 7038. https://lib.dr.iastate.edu/rtd/7038 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. INFORMATION TO USERS This was produced from a copy of a document sent to us for microfilming. While most advanced technological means to photograph and reproduce this docum. have been used, the quality is heavily dependent upon the quality of the mate submitted. The following explanation of techniques is provided to help you underst markings or notations which may appear on this reproduction. 1.The sign or "target" for pages apparently lacking from the documen photographed is "Missing Page(s)". If it was possible to obtain the missin; page(s) or section, they are spliced into the film along with adjacent pages This may have necessitated cutting through an image and duplicatin; adjacent pages to assure you of complete continuity. 2. When an image on the film is obliterated with a round black mark it is ai indication that the film inspector noticed either blurred copy because o movement during exposure, or duplicate copy. -
Data Monoids∗
Data Monoids∗ Mikolaj Bojańczyk1 1 University of Warsaw Abstract We develop an algebraic theory for languages of data words. We prove that, under certain conditions, a language of data words is definable in first-order logic if and only if its syntactic monoid is aperiodic. 1998 ACM Subject Classification F.4.3 Formal Languages Keywords and phrases Monoid, Data Words, Nominal Set, First-Order Logic Digital Object Identifier 10.4230/LIPIcs.STACS.2011.105 1 Introduction This paper is an attempt to combine two fields. The first field is the algebraic theory of regular languages. In this theory, a regular lan- guage is represented by its syntactic monoid, which is a finite monoid. It turns out that many important properties of the language are reflected in the structure of its syntactic monoid. One particularly beautiful result is the Schützenberger-McNaughton-Papert theorem, which describes the expressive power of first-order logic. Let L ⊆ A∗ be a regular language. Then L is definable in first-order logic if and only if its syntactic monoid ML is aperiodic. For instance, the language “words where there exists a position with label a” is defined by the first-order logic formula (this example does not even use the order on positions <, which is also allowed in general) ∃x. a(x). The syntactic monoid of this language is isomorphic to {0, 1} with multiplication, where 0 corresponds to the words that satisfy the formula, and 1 to the words that do not. Clearly, this monoid does not contain any non-trivial group. There are many results similar to theorem above, each one providing a connection between seemingly unrelated concepts of logic and algebra, see e.g.