This Is the Online Version of Elementary Set Theory with a Universal Set, by M. Randall Holmes, Made Available Online by Permission of the Publishers
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Biequivalence Vector Spaces in the Alternative Set Theory
Comment.Math.Univ.Carolin. 32,3 (1991)517–544 517 Biequivalence vector spaces in the alternative set theory Miroslav Smˇ ´ıd, Pavol Zlatoˇs Abstract. As a counterpart to classical topological vector spaces in the alternative set the- ory, biequivalence vector spaces (over the field Q of all rational numbers) are introduced and their basic properties are listed. A methodological consequence opening a new view to- wards the relationship between the algebraic and topological dual is quoted. The existence of various types of valuations on a biequivalence vector space inducing its biequivalence is proved. Normability is characterized in terms of total convexity of the monad and/or of the galaxy of 0. Finally, the existence of a rather strong type of basis for a fairly extensive area of biequivalence vector spaces, containing all the most important particular cases, is established. Keywords: alternative set theory, biequivalence, vector space, monad, galaxy, symmetric Sd-closure, dual, valuation, norm, convex, basis Classification: Primary 46Q05, 46A06, 46A35; Secondary 03E70, 03H05, 46A09 Contents: 0. Introduction 1. Notation and preliminaries 2. Symmetric Sd-closures 3. Vector spaces over Q 4. Biequivalence vector spaces 5. Duals 6. Valuations on vector spaces 7. The envelope operation 8. Bases in biequivalence vector spaces 0. Introduction. The aim of this paper is to lay a foundation to the investigation of topological (or perhaps also bornological) vector spaces within the framework of the alternative set theory (AST), which could enable a rather elementary exposition of some topics of functional analysis reducing them to the study of formally finite dimensional vector spaces equipped with some additional “nonsharp” or “hazy” first order structure representing the topology. -
A Formalization of Logic in Diagonal-Free Cylindric Algebras Andrew John Ylvisaker Iowa State University
Iowa State University Capstones, Theses and Graduate Theses and Dissertations Dissertations 2012 A formalization of logic in diagonal-free cylindric algebras Andrew John Ylvisaker Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/etd Part of the Mathematics Commons Recommended Citation Ylvisaker, Andrew John, "A formalization of logic in diagonal-free cylindric algebras" (2012). Graduate Theses and Dissertations. 12536. https://lib.dr.iastate.edu/etd/12536 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 Graduate Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. A formalization of logic in diagonal-free cylindric algebras by Andrew John Ylvisaker A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Major: Mathematics Program of Study Committee: Roger D. Maddux, Major Professor Maria Axenovich Cliff Bergman Bill Robinson Paul Sacks Iowa State University Ames, Iowa 2012 Copyright c Andrew John Ylvisaker, 2012. All rights reserved. ii TABLE OF CONTENTS LIST OF TABLES . iii LIST OF FIGURES . iv CHAPTER 1. BACKGROUND MATERIAL . 1 1.1 Introduction . .1 1.2 First-order logic . .4 1.3 General algebra and Boolean algebras with operators . .6 1.4 Relation algebras . 11 1.5 Cylindric algebras . 17 CHAPTER 2. RELATION ALGEBRAIC REDUCTS . 21 2.1 Definitions . 21 2.2 Preliminary lemmas . 27 + 2.3 Q RA reducts in Df3 ..................................... -
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 -
Redalyc.Sets and Pluralities
Red de Revistas Científicas de América Latina, el Caribe, España y Portugal Sistema de Información Científica Gustavo Fernández Díez Sets and Pluralities Revista Colombiana de Filosofía de la Ciencia, vol. IX, núm. 19, 2009, pp. 5-22, Universidad El Bosque Colombia Available in: http://www.redalyc.org/articulo.oa?id=41418349001 Revista Colombiana de Filosofía de la Ciencia, ISSN (Printed Version): 0124-4620 [email protected] Universidad El Bosque Colombia How to cite Complete issue More information about this article Journal's homepage www.redalyc.org Non-Profit Academic Project, developed under the Open Acces Initiative Sets and Pluralities1 Gustavo Fernández Díez2 Resumen En este artículo estudio el trasfondo filosófico del sistema de lógica conocido como “lógica plural”, o “lógica de cuantificadores plurales”, de aparición relativamente reciente (y en alza notable en los últimos años). En particular, comparo la noción de “conjunto” emanada de la teoría axiomática de conjuntos, con la noción de “plura- lidad” que se encuentra detrás de este nuevo sistema. Mi conclusión es que los dos son completamente diferentes en su alcance y sus límites, y que la diferencia proviene de las diferentes motivaciones que han dado lugar a cada uno. Mientras que la teoría de conjuntos es una teoría genuinamente matemática, que tiene el interés matemático como ingrediente principal, la lógica plural ha aparecido como respuesta a considera- ciones lingüísticas, relacionadas con la estructura lógica de los enunciados plurales del inglés y el resto de los lenguajes naturales. Palabras clave: conjunto, teoría de conjuntos, pluralidad, cuantificación plural, lógica plural. Abstract In this paper I study the philosophical background of the relatively recent (and in the last few years increasingly flourishing) system of logic called “plural logic”, or “logic of plural quantifiers”. -
COMPSCI 501: Formal Language Theory Insights on Computability Turing Machines Are a Model of Computation Two (No Longer) Surpris
Insights on Computability Turing machines are a model of computation COMPSCI 501: Formal Language Theory Lecture 11: Turing Machines Two (no longer) surprising facts: Marius Minea Although simple, can describe everything [email protected] a (real) computer can do. University of Massachusetts Amherst Although computers are powerful, not everything is computable! Plus: “play” / program with Turing machines! 13 February 2019 Why should we formally define computation? Must indeed an algorithm exist? Back to 1900: David Hilbert’s 23 open problems Increasingly a realization that sometimes this may not be the case. Tenth problem: “Occasionally it happens that we seek the solution under insufficient Given a Diophantine equation with any number of un- hypotheses or in an incorrect sense, and for this reason do not succeed. known quantities and with rational integral numerical The problem then arises: to show the impossibility of the solution under coefficients: To devise a process according to which the given hypotheses or in the sense contemplated.” it can be determined in a finite number of operations Hilbert, 1900 whether the equation is solvable in rational integers. This asks, in effect, for an algorithm. Hilbert’s Entscheidungsproblem (1928): Is there an algorithm that And “to devise” suggests there should be one. decides whether a statement in first-order logic is valid? Church and Turing A Turing machine, informally Church and Turing both showed in 1936 that a solution to the Entscheidungsproblem is impossible for the theory of arithmetic. control To make and prove such a statement, one needs to define computability. In a recent paper Alonzo Church has introduced an idea of “effective calculability”, read/write head which is equivalent to my “computability”, but is very differently defined. -
An Axiomatic Approach to Physical Systems
' An Axiomatic Approach $ to Physical Systems & % Januari 2004 ❦ ' Summary $ Mereology is generally considered as a formal theory of the part-whole relation- ship concerning material bodies, such as planets, pickles and protons. We argue that mereology can be considered more generally as axiomatising the concept of a physical system, such as a planet in a gravitation-potential, a pickle in heart- burn and a proton in an electro-magnetic field. We design a theory of sets and physical systems by extending standard set-theory (ZFC) with mereological axioms. The resulting theory deductively extends both `Mereology' of Tarski & L`esniewski as well as the well-known `calculus of individuals' of Leonard & Goodman. We prove a number of theorems and demonstrate that our theory extends ZFC con- servatively and hence equiconsistently. We also erect a model of our theory in ZFC. The lesson to be learned from this paper reads that not only is a marriage between standard set-theory and mereology logically respectable, leading to a rigorous vin- dication of how physicists talk about physical systems, but in addition that sets and physical systems interact at the formal level both quite smoothly and non- trivially. & % Contents 0 Pre-Mereological Investigations 1 0.0 Overview . 1 0.1 Motivation . 1 0.2 Heuristics . 2 0.3 Requirements . 5 0.4 Extant Mereological Theories . 6 1 Mereological Investigations 8 1.0 The Language of Physical Systems . 8 1.1 The Domain of Mereological Discourse . 9 1.2 Mereological Axioms . 13 1.2.0 Plenitude vs. Parsimony . 13 1.2.1 Subsystem Axioms . 15 1.2.2 Composite Physical Systems . -
Self-Organizing Tuple Reconstruction in Column-Stores
Self-organizing Tuple Reconstruction in Column-stores Stratos Idreos Martin L. Kersten Stefan Manegold CWI Amsterdam CWI Amsterdam CWI Amsterdam The Netherlands The Netherlands The Netherlands [email protected] [email protected] [email protected] ABSTRACT 1. INTRODUCTION Column-stores gained popularity as a promising physical de- A prime feature of column-stores is to provide improved sign alternative. Each attribute of a relation is physically performance over row-stores in the case that workloads re- stored as a separate column allowing queries to load only quire only a few attributes of wide tables at a time. Each the required attributes. The overhead incurred is on-the-fly relation R is physically stored as a set of columns; one col- tuple reconstruction for multi-attribute queries. Each tu- umn for each attribute of R. This way, a query needs to load ple reconstruction is a join of two columns based on tuple only the required attributes from each relevant relation. IDs, making it a significant cost component. The ultimate This happens at the expense of requiring explicit (partial) physical design is to have multiple presorted copies of each tuple reconstruction in case multiple attributes are required. base table such that tuples are already appropriately orga- Each tuple reconstruction is a join between two columns nized in multiple different orders across the various columns. based on tuple IDs/positions and becomes a significant cost This requires the ability to predict the workload, idle time component in column-stores especially for multi-attribute to prepare, and infrequent updates. queries [2, 6, 10]. -
On the Boundary Between Mereology and Topology
On the Boundary Between Mereology and Topology Achille C. Varzi Istituto per la Ricerca Scientifica e Tecnologica, I-38100 Trento, Italy [email protected] (Final version published in Roberto Casati, Barry Smith, and Graham White (eds.), Philosophy and the Cognitive Sciences. Proceedings of the 16th International Wittgenstein Symposium, Vienna, Hölder-Pichler-Tempsky, 1994, pp. 423–442.) 1. Introduction Much recent work aimed at providing a formal ontology for the common-sense world has emphasized the need for a mereological account to be supplemented with topological concepts and principles. There are at least two reasons under- lying this view. The first is truly metaphysical and relates to the task of charac- terizing individual integrity or organic unity: since the notion of connectedness runs afoul of plain mereology, a theory of parts and wholes really needs to in- corporate a topological machinery of some sort. The second reason has been stressed mainly in connection with applications to certain areas of artificial in- telligence, most notably naive physics and qualitative reasoning about space and time: here mereology proves useful to account for certain basic relation- ships among things or events; but one needs topology to account for the fact that, say, two events can be continuous with each other, or that something can be inside, outside, abutting, or surrounding something else. These motivations (at times combined with others, e.g., semantic transpar- ency or computational efficiency) have led to the development of theories in which both mereological and topological notions play a pivotal role. How ex- actly these notions are related, however, and how the underlying principles should interact with one another, is still a rather unexplored issue. -
Weak Representation Theory in the Calculus of Relations Jeremy F
Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 2006 Weak representation theory in the calculus of relations Jeremy F. Alm Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Mathematics Commons Recommended Citation Alm, Jeremy F., "Weak representation theory in the calculus of relations " (2006). Retrospective Theses and Dissertations. 1795. https://lib.dr.iastate.edu/rtd/1795 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]. Weak representation theory in the calculus of relations by Jeremy F. Aim A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Major: Mathematics Program of Study Committee: Roger Maddux, Major Professor Maria Axenovich Paul Sacks Jonathan Smith William Robinson Iowa State University Ames, Iowa 2006 Copyright © Jeremy F. Aim, 2006. All rights reserved. UMI Number: 3217250 INFORMATION TO USERS The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleed-through, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. -
Sets, Functions
Sets 1 Sets Informally: A set is a collection of (mathematical) objects, with the collection treated as a single mathematical object. Examples: • real numbers, • complex numbers, C • integers, • All students in our class Defining Sets Sets can be defined directly: e.g. {1,2,4,8,16,32,…}, {CSC1130,CSC2110,…} Order, number of occurence are not important. e.g. {A,B,C} = {C,B,A} = {A,A,B,C,B} A set can be an element of another set. {1,{2},{3,{4}}} Defining Sets by Predicates The set of elements, x, in A such that P(x) is true. {}x APx| ( ) The set of prime numbers: Commonly Used Sets • N = {0, 1, 2, 3, …}, the set of natural numbers • Z = {…, -2, -1, 0, 1, 2, …}, the set of integers • Z+ = {1, 2, 3, …}, the set of positive integers • Q = {p/q | p Z, q Z, and q ≠ 0}, the set of rational numbers • R, the set of real numbers Special Sets • Empty Set (null set): a set that has no elements, denoted by ф or {}. • Example: The set of all positive integers that are greater than their squares is an empty set. • Singleton set: a set with one element • Compare: ф and {ф} – Ф: an empty set. Think of this as an empty folder – {ф}: a set with one element. The element is an empty set. Think of this as an folder with an empty folder in it. Venn Diagrams • Represent sets graphically • The universal set U, which contains all the objects under consideration, is represented by a rectangle. -
A Translation Approach to Portable Ontology Specifications
Knowledge Systems Laboratory September 1992 Technical Report KSL 92-71 Revised April 1993 A Translation Approach to Portable Ontology Specifications by Thomas R. Gruber Appeared in Knowledge Acquisition, 5(2):199-220, 1993. KNOWLEDGE SYSTEMS LABORATORY Computer Science Department Stanford University Stanford, California 94305 A Translation Approach to Portable Ontology Specifications Thomas R. Gruber Knowledge System Laboratory Stanford University 701 Welch Road, Building C Palo Alto, CA 94304 [email protected] Abstract To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse — definitions of classes, relations, functions, and other objects — is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations. We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how -
The Universal Finite Set 3
THE UNIVERSAL FINITE SET JOEL DAVID HAMKINS AND W. HUGH WOODIN Abstract. We define a certain finite set in set theory { x | ϕ(x) } and prove that it exhibits a universal extension property: it can be any desired particular finite set in the right set-theoretic universe and it can become successively any desired larger finite set in top-extensions of that universe. Specifically, ZFC proves the set is finite; the definition ϕ has complexity Σ2, so that any affirmative instance of it ϕ(x) is verified in any sufficiently large rank-initial segment of the universe Vθ ; the set is empty in any transitive model and others; and if ϕ defines the set y in some countable model M of ZFC and y ⊆ z for some finite set z in M, then there is a top-extension of M to a model N in which ϕ defines the new set z. Thus, the set shows that no model of set theory can realize a maximal Σ2 theory with its natural number parameters, although this is possible without parameters. Using the universal finite set, we prove that the validities of top-extensional set-theoretic potentialism, the modal principles valid in the Kripke model of all countable models of set theory, each accessing its top-extensions, are precisely the assertions of S4. Furthermore, if ZFC is consistent, then there are models of ZFC realizing the top-extensional maximality principle. 1. Introduction The second author [Woo11] established the universal algorithm phenomenon, showing that there is a Turing machine program with a certain universal top- extension property in models of arithmetic.