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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. -
Right Ideals of a Ring and Sublanguages of Science
RIGHT IDEALS OF A RING AND SUBLANGUAGES OF SCIENCE Javier Arias Navarro Ph.D. In General Linguistics and Spanish Language http://www.javierarias.info/ Abstract Among Zellig Harris’s numerous contributions to linguistics his theory of the sublanguages of science probably ranks among the most underrated. However, not only has this theory led to some exhaustive and meaningful applications in the study of the grammar of immunology language and its changes over time, but it also illustrates the nature of mathematical relations between chunks or subsets of a grammar and the language as a whole. This becomes most clear when dealing with the connection between metalanguage and language, as well as when reflecting on operators. This paper tries to justify the claim that the sublanguages of science stand in a particular algebraic relation to the rest of the language they are embedded in, namely, that of right ideals in a ring. Keywords: Zellig Sabbetai Harris, Information Structure of Language, Sublanguages of Science, Ideal Numbers, Ernst Kummer, Ideals, Richard Dedekind, Ring Theory, Right Ideals, Emmy Noether, Order Theory, Marshall Harvey Stone. §1. Preliminary Word In recent work (Arias 2015)1 a line of research has been outlined in which the basic tenets underpinning the algebraic treatment of language are explored. The claim was there made that the concept of ideal in a ring could account for the structure of so- called sublanguages of science in a very precise way. The present text is based on that work, by exploring in some detail the consequences of such statement. §2. Introduction Zellig Harris (1909-1992) contributions to the field of linguistics were manifold and in many respects of utmost significance. -
Notes on Mathematical Logic David W. Kueker
Notes on Mathematical Logic David W. Kueker University of Maryland, College Park E-mail address: [email protected] URL: http://www-users.math.umd.edu/~dwk/ Contents Chapter 0. Introduction: What Is Logic? 1 Part 1. Elementary Logic 5 Chapter 1. Sentential Logic 7 0. Introduction 7 1. Sentences of Sentential Logic 8 2. Truth Assignments 11 3. Logical Consequence 13 4. Compactness 17 5. Formal Deductions 19 6. Exercises 20 20 Chapter 2. First-Order Logic 23 0. Introduction 23 1. Formulas of First Order Logic 24 2. Structures for First Order Logic 28 3. Logical Consequence and Validity 33 4. Formal Deductions 37 5. Theories and Their Models 42 6. Exercises 46 46 Chapter 3. The Completeness Theorem 49 0. Introduction 49 1. Henkin Sets and Their Models 49 2. Constructing Henkin Sets 52 3. Consequences of the Completeness Theorem 54 4. Completeness Categoricity, Quantifier Elimination 57 5. Exercises 58 58 Part 2. Model Theory 59 Chapter 4. Some Methods in Model Theory 61 0. Introduction 61 1. Realizing and Omitting Types 61 2. Elementary Extensions and Chains 66 3. The Back-and-Forth Method 69 i ii CONTENTS 4. Exercises 71 71 Chapter 5. Countable Models of Complete Theories 73 0. Introduction 73 1. Prime Models 73 2. Universal and Saturated Models 75 3. Theories with Just Finitely Many Countable Models 77 4. Exercises 79 79 Chapter 6. Further Topics in Model Theory 81 0. Introduction 81 1. Interpolation and Definability 81 2. Saturated Models 84 3. Skolem Functions and Indescernables 87 4. Some Applications 91 5. -
Contents 3 Homomorphisms, Ideals, and Quotients
Ring Theory (part 3): Homomorphisms, Ideals, and Quotients (by Evan Dummit, 2018, v. 1.01) Contents 3 Homomorphisms, Ideals, and Quotients 1 3.1 Ring Isomorphisms and Homomorphisms . 1 3.1.1 Ring Isomorphisms . 1 3.1.2 Ring Homomorphisms . 4 3.2 Ideals and Quotient Rings . 7 3.2.1 Ideals . 8 3.2.2 Quotient Rings . 9 3.2.3 Homomorphisms and Quotient Rings . 11 3.3 Properties of Ideals . 13 3.3.1 The Isomorphism Theorems . 13 3.3.2 Generation of Ideals . 14 3.3.3 Maximal and Prime Ideals . 17 3.3.4 The Chinese Remainder Theorem . 20 3.4 Rings of Fractions . 21 3 Homomorphisms, Ideals, and Quotients In this chapter, we will examine some more intricate properties of general rings. We begin with a discussion of isomorphisms, which provide a way of identifying two rings whose structures are identical, and then examine the broader class of ring homomorphisms, which are the structure-preserving functions from one ring to another. Next, we study ideals and quotient rings, which provide the most general version of modular arithmetic in a ring, and which are fundamentally connected with ring homomorphisms. We close with a detailed study of the structure of ideals and quotients in commutative rings with 1. 3.1 Ring Isomorphisms and Homomorphisms • We begin our study with a discussion of structure-preserving maps between rings. 3.1.1 Ring Isomorphisms • We have encountered several examples of rings with very similar structures. • For example, consider the two rings R = Z=6Z and S = (Z=2Z) × (Z=3Z). -
A Remark About Algebraicity in Complete Partial Orders
A remark ab out algebraicity in complete partial orders Draft Leonid Libkin Department of Computer and Information Science University of Pennsylvania Philadelphia PA USA Email libkinsaulcisupennedu Abstract I prove a characterization theorem for algebraic b ounded complete cp os similar to that for algebraic lattices It is wellknown that a lattice is algebraic i it isomorphic to a lattice of subalgebras of an algebra Algebraicity plays the central role in denotational semantics for programming languages but the structures used there are not exactly algebraic lattices they are complete algebraic partial orders In this note I shall characterize such p osets as p osets of certain subalgebras of partial algebras Let me recall the denitions A p oset is called complete and is usually abbreviated as a cpo if it contains least upp er b ounds or suprema of directed subsets I shall use t for supremum An element x of D is called compact if x tX where X D is directed implies x x for some x X A cp o is called algebraic if for any x D the set of compact elements b elow x is directed and its supremum equals x A cp o D is bounded complete if supremum of X D denoted by tX as well exists whenever X is b ounded ab ove in D ie there is a D such that a x for all x X I shall use a more convenient notation a a instead of tfa a g An element x of a b ounded complete cp o D is compact 1 n 1 n if whenever tX exists and x tX x tX where X X is nite In a b ounded complete cp o the set of compact elements b elow any element is always -
An Outline of Algebraic Set Theory
An Outline of Algebraic Set Theory Steve Awodey Dedicated to Saunders Mac Lane, 1909–2005 Abstract This survey article is intended to introduce the reader to the field of Algebraic Set Theory, in which models of set theory of a new and fascinating kind are determined algebraically. The method is quite robust, admitting adjustment in several respects to model different theories including classical, intuitionistic, bounded, and predicative ones. Under this scheme some familiar set theoretic properties are related to algebraic ones, like freeness, while others result from logical constraints, like definability. The overall theory is complete in two important respects: conventional elementary set theory axiomatizes the class of algebraic models, and the axioms provided for the abstract algebraic framework itself are also complete with respect to a range of natural models consisting of “ideals” of sets, suitably defined. Some previous results involving realizability, forcing, and sheaf models are subsumed, and the prospects for further such unification seem bright. 1 Contents 1 Introduction 3 2 The category of classes 10 2.1 Smallmaps ............................ 12 2.2 Powerclasses............................ 14 2.3 UniversesandInfinity . 15 2.4 Classcategories .......................... 16 2.5 Thetoposofsets ......................... 17 3 Algebraic models of set theory 18 3.1 ThesettheoryBIST ....................... 18 3.2 Algebraic soundness of BIST . 20 3.3 Algebraic completeness of BIST . 21 4 Classes as ideals of sets 23 4.1 Smallmapsandideals . .. .. 24 4.2 Powerclasses and universes . 26 4.3 Conservativity........................... 29 5 Ideal models 29 5.1 Freealgebras ........................... 29 5.2 Collection ............................. 30 5.3 Idealcompleteness . .. .. 32 6 Variations 33 References 36 2 1 Introduction Algebraic set theory (AST) is a new approach to the construction of models of set theory, invented by Andr´eJoyal and Ieke Moerdijk and first presented in [16]. -
An Introduction to Ramsey Theory Fast Functions, Infinity, and Metamathematics
STUDENT MATHEMATICAL LIBRARY Volume 87 An Introduction to Ramsey Theory Fast Functions, Infinity, and Metamathematics Matthew Katz Jan Reimann Mathematics Advanced Study Semesters 10.1090/stml/087 An Introduction to Ramsey Theory STUDENT MATHEMATICAL LIBRARY Volume 87 An Introduction to Ramsey Theory Fast Functions, Infinity, and Metamathematics Matthew Katz Jan Reimann Mathematics Advanced Study Semesters Editorial Board Satyan L. Devadoss John Stillwell (Chair) Rosa Orellana Serge Tabachnikov 2010 Mathematics Subject Classification. Primary 05D10, 03-01, 03E10, 03B10, 03B25, 03D20, 03H15. Jan Reimann was partially supported by NSF Grant DMS-1201263. For additional information and updates on this book, visit www.ams.org/bookpages/stml-87 Library of Congress Cataloging-in-Publication Data Names: Katz, Matthew, 1986– author. | Reimann, Jan, 1971– author. | Pennsylvania State University. Mathematics Advanced Study Semesters. Title: An introduction to Ramsey theory: Fast functions, infinity, and metamathemat- ics / Matthew Katz, Jan Reimann. Description: Providence, Rhode Island: American Mathematical Society, [2018] | Series: Student mathematical library; 87 | “Mathematics Advanced Study Semesters.” | Includes bibliographical references and index. Identifiers: LCCN 2018024651 | ISBN 9781470442903 (alk. paper) Subjects: LCSH: Ramsey theory. | Combinatorial analysis. | AMS: Combinatorics – Extremal combinatorics – Ramsey theory. msc | Mathematical logic and foundations – Instructional exposition (textbooks, tutorial papers, etc.). msc | Mathematical -
A New Proof of the Completeness of the Lukasiewicz Axioms^)
A NEW PROOF OF THE COMPLETENESS OF THE LUKASIEWICZ AXIOMS^) BY C. C. CHANG The purpose of this note is to provide a new proof for the completeness of the Lukasiewicz axioms for infinite valued propositional logic. For the existing proof of completeness and a history of the problem in general we refer the readers to [l; 2; 3; 4]. The proof as was given in [4] was essentially metamathematical in nature; the proof we offer here is essentially algebraic in nature, which, to some extent, justifies the program initiated by the author in [2]. In what follows we assume thorough familiarity with the contents of [2] and adopt the notation and terminology of [2]. The crux of this proof is con- tained in the following two observations: Instead of using locally finite MV- algebras as the basic building blocks in the structure theory of MV-algebras, we shall use linearly ordered ones. The one-to-one correspondence between linearly ordered MV-algebras and segments of ordered abelian groups enables us to make use of some known results in the first-order theory of ordered abelian groups(2). We say that P is a prime ideal of an MV-algebra A if, and only if, (i) P is an ideal of A, and (ii) for each x, yEA, either xyEP or xyEP- Lemma 1. If P is a prime ideal of A, then A/P is a linearly ordered MV- algebra. Proof. By 3.11 of [2], we have to prove that given x/P and y/P, either x/P^y/P or y/P^x/P. -
Model Completeness and Relative Decidability
Model Completeness and Relative Decidability Jennifer Chubb, Russell Miller,∗ & Reed Solomon March 5, 2019 Abstract We study the implications of model completeness of a theory for the effectiveness of presentations of models of that theory. It is im- mediate that for a computable model A of a computably enumerable, model complete theory, the entire elementary diagram E(A) must be decidable. We prove that indeed a c.e. theory T is model complete if and only if there is a uniform procedure that succeeds in deciding E(A) from the atomic diagram ∆(A) for all countable models A of T . Moreover, if every presentation of a single isomorphism type A has this property of relative decidability, then there must be a procedure with succeeds uniformly for all presentations of an expansion (A,~a) by finitely many new constants. We end with a conjecture about the situation when all models of a theory are relatively decidable. 1 Introduction The broad goal of computable model theory is to investigate the effective arXiv:1903.00734v1 [math.LO] 2 Mar 2019 aspects of model theory. Here we will carry out exactly this process with the model-theoretic concept of model completeness. This notion is well-known and has been widely studied in model theory, but to our knowledge there has never been any thorough examination of its implications for computability in structures with the domain ω. We now rectify this omission, and find natural and satisfactory equivalents for the basic notion of model completeness of a first-order theory. Our two principal results are each readily stated: that a ∗The second author was supported by NSF grant # DMS-1362206, Simons Foundation grant # 581896, and several PSC-CUNY research awards. -
More Model Theory Notes Miscellaneous Information, Loosely Organized
More Model Theory Notes Miscellaneous information, loosely organized. 1. Kinds of Models A countable homogeneous model M is one such that, for any partial elementary map f : A ! M with A ⊆ M finite, and any a 2 M, f extends to a partial elementary map A [ fag ! M. As a consequence, any partial elementary map to M is extendible to an automorphism of M. Atomic models (see below) are homogeneous. A prime model of T is one that elementarily embeds into every other model of T of the same cardinality. Any theory with fewer than continuum-many types has a prime model, and if a theory has a prime model, it is unique up to isomorphism. Prime models are homogeneous. On the other end, a model is universal if every other model of its size elementarily embeds into it. Recall a type is a set of formulas with the same tuple of free variables; generally to be called a type we require consistency. The type of an element or tuple from a model is all the formulas it satisfies. One might think of the type of an element as a sort of identity card for automorphisms: automorphisms of a model preserve types. A complete type is the analogue of a complete theory, one where every formula of the appropriate free variables or its negation appears. Types of elements and tuples are always complete. A type is principal if there is one formula in the type that implies all the rest; principal complete types are often called isolated. A trivial example of an isolated type is that generated by the formula x = c where c is any constant in the language, or x = t(¯c) where t is any composition of appropriate-arity functions andc ¯ is a tuple of constants. -
Lattice Theory Lecture 2 Distributive Lattices
Lattice Theory Lecture 2 Distributive lattices John Harding New Mexico State University www.math.nmsu.edu/∼JohnHarding.html [email protected] Toulouse, July 2017 Distributive lattices Distributive law for all x; y; z x ∨ (y ∧ z) = (x ∨ y) ∧ (x ∨ z) Modular law if x ≤ z then x ∨ (y ∧ z) = (x ∨ y) ∧ (x ∨ z) Definition The lattices M5 and N5 are as follows: z x y z y x M5 N5 Note M5 is Modular, not distributive, and N5 is Non-modular. Both have 5 elements. 2 / 44 Recognizing distributive lattices Theorem Let L be a lattice. 1. L is modular iff N5 is not a sublattice of L 2. L is distributive iff neither M5; N5 is a sublattice of L Proof The \⇒" direction of each is obvious. For 1 \⇐" if L is not modular, there are x < z with x ∨ (y ∧ z) < (x ∨ y) ∧ (x ∨ z) (why?) Then the following is a sublattice of L. x ∨ y x y z y ( ∨ ) ∧ x ∨ (y ∧ z) y ∧ z 3 / 44 Exercise Give the details that the figure on the previous page is a sublattice. Do the 2 \⇐" direction. The lattice N5 is \projective" in lattices, meaning that if L is a lattice and f ∶ L → N5 is an onto lattice homomorphism, then there is a one-one lattice homomorphism g ∶ N5 → L with f ○ g = id. 4 / 44 Complements Definition Elements x; y of a bounded lattice L are complements if x ∧ y = 0 and x ∨ y = 1. In general, an element might have no complements, or many. 5 / 44 Complements Theorem In a bounded distributive lattice, an element has at most one complement. -
LOGIC I 1. the Completeness Theorem 1.1. on Consequences
LOGIC I VICTORIA GITMAN 1. The Completeness Theorem The Completeness Theorem was proved by Kurt G¨odelin 1929. To state the theorem we must formally define the notion of proof. This is not because it is good to give formal proofs, but rather so that we can prove mathematical theorems about the concept of proof. {Arnold Miller 1.1. On consequences and proofs. Suppose that T is some first-order theory. What are the consequences of T ? The obvious answer is that they are statements provable from T (supposing for a second that we know what that means). But there is another possibility. The consequences of T could mean statements that hold true in every model of T . Do the proof theoretic and the model theoretic notions of consequence coincide? Once, we formally define proofs, it will be obvious, by the definition of truth, that a statement that is provable from T must hold in every model of T . Does the converse hold? The question was posed in the 1920's by David Hilbert (of the 23 problems fame). The answer is that remarkably, yes, it does! This result, known as the Completeness Theorem for first-order logic, was proved by Kurt G¨odel in 1929. According to the Completeness Theorem provability and semantic truth are indeed two very different aspects of the same phenomena. In order to prove the Completeness Theorem, we first need a formal notion of proof. As mathematicians, we all know that a proof is a series of deductions, where each statement proceeds by logical reasoning from the previous ones.