1 Convergence in Topological Spaces
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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]). -
Directed Sets and Topological Spaces Definable in O-Minimal Structures
Directed sets and topological spaces definable in o-minimal structures. Pablo And´ujarGuerrero∗ Margaret E. M. Thomas ∗ Erik Walsbergy 2010 Mathematics Subject Classification. 03C64 (Primary), 54A20, 54A05, 54D30 (Secondary). Key words. o-minimality, directed sets, definable topological spaces. Abstract We study directed sets definable in o-minimal structures, show- ing that in expansions of ordered fields these admit cofinal definable curves, as well as a suitable analogue in expansions of ordered groups, and furthermore that no analogue holds in full generality. We use the theory of tame pairs to extend the results in the field case to definable families of sets with the finite intersection property. We then apply our results to the study of definable topologies. We prove that all de- finable topological spaces display properties akin to first countability, and give several characterizations of a notion of definable compactness due to Peterzil and Steinhorn [PS99] generalized to this setting. 1 Introduction The study of objects definable in o-minimal structures is motivated by the notion that o-minimality provides a rich but \tame" setting for the theories of said objects. In this paper we study directed sets definable in o-minimal structures, focusing on expansions of groups and fields. By \directed set" we mean a preordered set in which every finite subset has a lower (if downward ∗Department of Mathematics, Purdue University, 150 N. University Street, West Lafayette, IN 47907-2067, U.S.A. E-mail addresses: [email protected] (And´ujarGuer- rero), [email protected] (Thomas) yDepartment of Mathematics, Statistics, and Computer Science, Department of Math- ematics, University of California, Irvine, 340 Rowland Hall (Bldg.# 400), Irvine, CA 92697-3875, U.S.A. -
Algebra I Chapter 1. Basic Facts from Set Theory 1.1 Glossary of Abbreviations
Notes: c F.P. Greenleaf, 2000-2014 v43-s14sets.tex (version 1/1/2014) Algebra I Chapter 1. Basic Facts from Set Theory 1.1 Glossary of abbreviations. Below we list some standard math symbols that will be used as shorthand abbreviations throughout this course. means “for all; for every” • ∀ means “there exists (at least one)” • ∃ ! means “there exists exactly one” • ∃ s.t. means “such that” • = means “implies” • ⇒ means “if and only if” • ⇐⇒ x A means “the point x belongs to a set A;” x / A means “x is not in A” • ∈ ∈ N denotes the set of natural numbers (counting numbers) 1, 2, 3, • · · · Z denotes the set of all integers (positive, negative or zero) • Q denotes the set of rational numbers • R denotes the set of real numbers • C denotes the set of complex numbers • x A : P (x) If A is a set, this denotes the subset of elements x in A such that •statement { ∈ P (x)} is true. As examples of the last notation for specifying subsets: x R : x2 +1 2 = ( , 1] [1, ) { ∈ ≥ } −∞ − ∪ ∞ x R : x2 +1=0 = { ∈ } ∅ z C : z2 +1=0 = +i, i where i = √ 1 { ∈ } { − } − 1.2 Basic facts from set theory. Next we review the basic definitions and notations of set theory, which will be used throughout our discussions of algebra. denotes the empty set, the set with nothing in it • ∅ x A means that the point x belongs to a set A, or that x is an element of A. • ∈ A B means A is a subset of B – i.e. -
Basic Properties of Filter Convergence Spaces
Basic Properties of Filter Convergence Spaces Barbel¨ M. R. Stadlery, Peter F. Stadlery;z;∗ yInstitut fur¨ Theoretische Chemie, Universit¨at Wien, W¨ahringerstraße 17, A-1090 Wien, Austria zThe Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA ∗Address for corresponce Abstract. This technical report summarized facts from the basic theory of filter convergence spaces and gives detailed proofs for them. Many of the results collected here are well known for various types of spaces. We have made no attempt to find the original proofs. 1. Introduction Mathematical notions such as convergence, continuity, and separation are, at textbook level, usually associated with topological spaces. It is possible, however, to introduce them in a much more abstract way, based on axioms for convergence instead of neighborhood. This approach was explored in seminal work by Choquet [4], Hausdorff [12], Katˇetov [14], Kent [16], and others. Here we give a brief introduction to this line of reasoning. While the material is well known to specialists it does not seem to be easily accessible to non-topologists. In some cases we include proofs of elementary facts for two reasons: (i) The most basic facts are quoted without proofs in research papers, and (ii) the proofs may serve as examples to see the rather abstract formalism at work. 2. Sets and Filters Let X be a set, P(X) its power set, and H ⊆ P(X). The we define H∗ = fA ⊆ Xj(X n A) 2= Hg (1) H# = fA ⊆ Xj8Q 2 H : A \ Q =6 ;g The set systems H∗ and H# are called the conjugate and the grill of H, respectively. -
Topology and Data
BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY Volume 46, Number 2, April 2009, Pages 255–308 S 0273-0979(09)01249-X Article electronically published on January 29, 2009 TOPOLOGY AND DATA GUNNAR CARLSSON 1. Introduction An important feature of modern science and engineering is that data of various kinds is being produced at an unprecedented rate. This is so in part because of new experimental methods, and in part because of the increase in the availability of high powered computing technology. It is also clear that the nature of the data we are obtaining is significantly different. For example, it is now often the case that we are given data in the form of very long vectors, where all but a few of the coordinates turn out to be irrelevant to the questions of interest, and further that we don’t necessarily know which coordinates are the interesting ones. A related fact is that the data is often very high-dimensional, which severely restricts our ability to visualize it. The data obtained is also often much noisier than in the past and has more missing information (missing data). This is particularly so in the case of biological data, particularly high throughput data from microarray or other sources. Our ability to analyze this data, both in terms of quantity and the nature of the data, is clearly not keeping pace with the data being produced. In this paper, we will discuss how geometry and topology can be applied to make useful contributions to the analysis of various kinds of data. -
Topological Spaces and Neighborhood Filters
Topological spaces and neighborhood filters Jordan Bell [email protected] Department of Mathematics, University of Toronto April 3, 2014 If X is a set, a filter on X is a set F of subsets of X such that ; 62 F; if A; B 2 F then A \ B 2 F; if A ⊆ X and there is some B 2 F such that B ⊆ A, then A 2 F. For example, if x 2 X then the set of all subsets of X that include x is a filter on X.1 A basis for the filter F is a subset B ⊆ F such that if A 2 F then there is some B 2 B such that B ⊆ A. If X is a set, a topology on X is a set O of subsets of X such that: ;;X 2 O; S if Uα 2 O for all α 2 I, then Uα 2 O; if I is finite and Uα 2 O for all α 2 I, T α2I then α2I Uα 2 O. If N ⊆ X and x 2 X, we say that N is a neighborhood of x if there is some U 2 O such that x 2 U ⊆ N. In particular, an open set is a neighborhood of every element of itself. A basis for a topology O is a subset B of O such that if x 2 X then there is some B 2 B such that x 2 B, and such that if B1;B2 2 B and x 2 B1 \ B2, then there is some B3 2 B such that 2 x 2 B3 ⊆ B1 \ B2. -
"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. -
Ergodicity and Metric Transitivity
Chapter 25 Ergodicity and Metric Transitivity Section 25.1 explains the ideas of ergodicity (roughly, there is only one invariant set of positive measure) and metric transivity (roughly, the system has a positive probability of going from any- where to anywhere), and why they are (almost) the same. Section 25.2 gives some examples of ergodic systems. Section 25.3 deduces some consequences of ergodicity, most im- portantly that time averages have deterministic limits ( 25.3.1), and an asymptotic approach to independence between even§ts at widely separated times ( 25.3.2), admittedly in a very weak sense. § 25.1 Metric Transitivity Definition 341 (Ergodic Systems, Processes, Measures and Transfor- mations) A dynamical system Ξ, , µ, T is ergodic, or an ergodic system or an ergodic process when µ(C) = 0 orXµ(C) = 1 for every T -invariant set C. µ is called a T -ergodic measure, and T is called a µ-ergodic transformation, or just an ergodic measure and ergodic transformation, respectively. Remark: Most authorities require a µ-ergodic transformation to also be measure-preserving for µ. But (Corollary 54) measure-preserving transforma- tions are necessarily stationary, and we want to minimize our stationarity as- sumptions. So what most books call “ergodic”, we have to qualify as “stationary and ergodic”. (Conversely, when other people talk about processes being “sta- tionary and ergodic”, they mean “stationary with only one ergodic component”; but of that, more later. Definition 342 (Metric Transitivity) A dynamical system is metrically tran- sitive, metrically indecomposable, or irreducible when, for any two sets A, B n ∈ , if µ(A), µ(B) > 0, there exists an n such that µ(T − A B) > 0. -
Cofinal Stable Logics
Guram Bezhanishvili Cofinal Stable Logics Nick Bezhanishvili Julia Ilin Abstract. We generalize the (∧, ∨)-canonical formulas to (∧, ∨)-canonical rules, and prove that each intuitionistic multi-conclusion consequence relation is axiomatizable by (∧, ∨)-canonical rules. This yields a convenient characterization of stable superintuition- istic logics. The (∧, ∨)-canonical formulas are analogues of the (∧, →)-canonical formulas, which are the algebraic counterpart of Zakharyaschev’s canonical formulas for superintu- itionistic logics (si-logics for short). Consequently, stable si-logics are analogues of subframe si-logics. We introduce cofinal stable intuitionistic multi-conclusion consequence relations and cofinal stable si-logics, thus answering the question of what the analogues of cofinal subframe logics should be. This is done by utilizing the (∧, ∨, ¬)-reduct of Heyting alge- bras. We prove that every cofinal stable si-logic has the finite model property, and that there are continuum many cofinal stable si-logics that are not stable. We conclude with several examples showing the similarities and differences between the classes of stable, cofinal stable, subframe, and cofinal subframe si-logics. Keywords: Intuitionistic logic, Intuitionistic multi-conclusion consequence relation, Axiomatization, Heyting algebra, Variety, Universal class. Mathematics Subject Classification: 03B55 · 06D20. 1. Introduction Superintuitionistic logics (si-logics for short) are propositional logics extend- ing the intuitionistic propositional calculus IPC. Consistent si-logics are also known as intermediate logics as they are exactly the logics situated between IPC and the classical propositional calculus CPC.BytheG¨odel translation, si-logics are closely related to modal logics extending S4.Ade- tailed account of si-logics and how they relate to modal logics can be found in [8]. -
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.......................... -
POINT-COFINITE COVERS in the LAVER MODEL 1. Background Let
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 138, Number 9, September 2010, Pages 3313–3321 S 0002-9939(10)10407-9 Article electronically published on April 30, 2010 POINT-COFINITE COVERS IN THE LAVER MODEL ARNOLD W. MILLER AND BOAZ TSABAN (Communicated by Julia Knight) Abstract. Let S1(Γ, Γ) be the statement: For each sequence of point-cofinite open covers, one can pick one element from each cover and obtain a point- cofinite cover. b is the minimal cardinality of a set of reals not satisfying S1(Γ, Γ). We prove the following assertions: (1) If there is an unbounded tower, then there are sets of reals of cardinality b satisfying S1(Γ, Γ). (2) It is consistent that all sets of reals satisfying S1(Γ, Γ) have cardinality smaller than b. These results can also be formulated as dealing with Arhangel’ski˘ı’s property α2 for spaces of continuous real-valued functions. The main technical result is that in Laver’s model, each set of reals of cardinality b has an unbounded Borel image in the Baire space ωω. 1. Background Let P be a nontrivial property of sets of reals. The critical cardinality of P , denoted non(P ), is the minimal cardinality of a set of reals not satisfying P .A natural question is whether there is a set of reals of cardinality at least non(P ), which satisfies P , i.e., a nontrivial example. We consider the following property. Let X be a set of reals. U is a point-cofinite cover of X if U is infinite, and for each x ∈ X, {U ∈U: x ∈ U} is a cofinite subset of U.1 Having X fixed in the background, let Γ be the family of all point- cofinite open covers of X. -
COFINAL TYPES of ULTRAFILTERS 1. Introduction We Say That a Poset
COFINAL TYPES OF ULTRAFILTERS DILIP RAGHAVAN AND STEVO TODORCEVIC Abstract. We study Tukey types of ultrafilters on !, focusing on the question of when Tukey reducibility is equivalent to Rudin-Keisler reducibility. We give several conditions under which this equivalence holds. We show that there are only c many ultrafilters that are Tukey below any basically generated ultrafil- ter. The class of basically generated ultrafilters includes all known ultrafilters <! that are not Tukey above [!1] . We give a complete characterization of all ultrafilters that are Tukey below a selective. A counterexample showing that Tukey reducibility and RK reducibility can diverge within the class of P-points is also given. 1. Introduction We say that a poset hD; ≤i is directed if any two members of D have an upper bound in D. A set X ⊂ D is unbounded in D if it doesn't have an upper bound in D. A set X ⊂ D is said to be cofinal in D if 8y 2 D9x 2 X [y ≤ x]. Given directed sets D and E, a map f : D ! E is called a Tukey map if the image (under f) of every unbounded subset of D is unbounded in E. A map g : E ! D is called a convergent map if the image (under g) of every cofinal subset of E is cofinal in D. It is easy to see that there is a Tukey map f : D ! E iff there exists a convergent g : E ! D. When this situation obtains, we say that D is Tukey reducible to E, and we write D ≤T E.