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Scheme Representation for First-Logic
Scheme representation for first-order logic Spencer Breiner Carnegie Mellon University Advisor: Steve Awodey Committee: Jeremy Avigad Hans Halvorson Pieter Hofstra February 12, 2014 arXiv:1402.2600v1 [math.LO] 11 Feb 2014 Contents 1 Logical spectra 11 1.1 The spectrum M0 .......................... 11 1.2 Sheaves on M0 ............................ 20 1.3 Thegenericmodel .......................... 24 1.4 The spectral groupoid M = Spec(T)................ 27 1.5 Stability, compactness and definability . 31 1.6 Classicalfirst-orderlogic. 37 2 Pretopos Logic 43 2.1 Coherentlogicandpretoposes. 43 2.2 Factorization in Ptop ........................ 51 2.3 Semantics, slices and localization . 57 2.4 Themethodofdiagrams. .. .. .. .. .. .. .. .. .. 61 2.5 ClassicaltheoriesandBooleanpretoposes . 70 3 Logical Schemes 74 3.1 StacksandSheaves.......................... 74 3.2 Affineschemes ............................ 80 3.3 Thecategoryoflogicalschemes . 87 3.4 Opensubschemesandgluing . 93 3.5 Limitsofschemes........................... 98 1 4 Applications 110 4.1 OT asasite..............................111 4.2 Structuresheafasuniverse . 119 4.3 Isotropy ................................125 4.4 ConceptualCompleteness . 134 2 Introduction Although contemporary model theory has been called “algebraic geometry mi- nus fields” [15], the formal methods of the two fields are radically different. This dissertation aims to shrink that gap by presenting a theory of “logical schemes,” geometric entities which relate to first-order logical theories in much the same way that -
Continuous First-Order Logic
Continuous First-Order Logic Wesley Calvert Calcutta Logic Circle 4 September 2011 Wesley Calvert (SIU / IMSc) Continuous First-Order Logic 4 September 2011 1 / 45 Definition A first-order theory T is said to be stable iff there are less than the maximum possible number of types over T , up to equivalence. Theorem (Shelah's Main Gap Theorem) If T is a first-order theory and is stable and . , then the class of models looks like . Otherwise, there's no hope. Model-Theoretic Beginnings Problem Given a theory T , describe the structure of models of T . Wesley Calvert (SIU / IMSc) Continuous First-Order Logic 4 September 2011 2 / 45 Theorem (Shelah's Main Gap Theorem) If T is a first-order theory and is stable and . , then the class of models looks like . Otherwise, there's no hope. Model-Theoretic Beginnings Problem Given a theory T , describe the structure of models of T . Definition A first-order theory T is said to be stable iff there are less than the maximum possible number of types over T , up to equivalence. Wesley Calvert (SIU / IMSc) Continuous First-Order Logic 4 September 2011 2 / 45 Model-Theoretic Beginnings Problem Given a theory T , describe the structure of models of T . Definition A first-order theory T is said to be stable iff there are less than the maximum possible number of types over T , up to equivalence. Theorem (Shelah's Main Gap Theorem) If T is a first-order theory and is stable and . , then the class of models looks like . Otherwise, there's no hope. -
Proof Diagrams for Multiplicative Linear Logic
Proof Diagrams for Multiplicative Linear Logic Matteo Acclavio I2M Marseille, France Aix-Marseile Universit´e [email protected] The original idea of proof nets can be formulated by means of interaction nets syntax. Additional machinery as switching, jumps and graph connectivity is needed in order to ensure correspondence between a proof structure and a correct proof in sequent calculus. In this paper we give an interpretationof proof nets in the syntax of string diagrams. Even though we lose standard proof equivalence, our construction allows to define a framework where soundness and well-typeness of a diagram can be verified in linear time. Introduction Proof nets are a geometrical representation of linear logic proofs introduced by J-Y.Girard [5]. The build- ing blocks of proof nets are called proof structures that have been generalized by Y. Lafont [11] in the so-called interaction nets. To recognize if a proof structure is a proof net one needs to verify its sequen- tializability property, that is, whether it corresponds to a linear logic proof derivation. Following Girard’s original correction criterion, others methods have been introduced, notably by Danos-Regnier [4], that ensures graph acyclicity by a notion of switchings on ⊗ cells, and by Guerrini [7], that reformulates correction by means of graph contractability. Proof structures allow to recover the semantic equivalence of derivation under commutation and permutation of some inference rules. Unfortunately this property makes ineffective the aforementioned criteria in presence of the multiplicative unit ⊥. In order to recover a sequentialization condition for the multiplicative fragment with units, Girard has introduced the notion of jumps [6]. -
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. -
Elementary Model Theory Notes for MATH 762
George F. McNulty Elementary Model Theory Notes for MATH 762 drawings by the author University of South Carolina Fall 2011 Model Theory MATH 762 Fall 2011 TTh 12:30p.m.–1:45 p.m. in LeConte 303B Office Hours: 2:00pm to 3:30 pm Monday through Thursday Instructor: George F. McNulty Recommended Text: Introduction to Model Theory By Philipp Rothmaler What We Will Cover After a couple of weeks to introduce the fundamental concepts and set the context (material chosen from the first three chapters of the text), the course will proceed with the development of first-order model theory. In the text this is the material covered beginning in Chapter 4. Our aim is cover most of the material in the text (although not all the examples) as well as some material that extends beyond the topics covered in the text (notably a proof of Morley’s Categoricity Theorem). The Work Once the introductory phase of the course is completed, there will be a series of problem sets to entertain and challenge each student. Mastering the problem sets should give each student a detailed familiarity with the main concepts and theorems of model theory and how these concepts and theorems might be applied. So working through the problems sets is really the heart of the course. Most of the problems require some reflection and can usually not be resolved in just one sitting. Grades The grades in this course will be based on each student’s work on the problem sets. Roughly speaking, an A will be assigned to students whose problems sets eventually reveal a mastery of the central concepts and theorems of model theory; a B will be assigned to students whose work reveals a grasp of the basic concepts and a reasonable competence, short of mastery, in putting this grasp into play to solve problems. -
Hilog: a Foundation for Higher-Order Logic Programming
J. LOGIC PROGRAMMING 1993:15:187-230 187 HILOG: A FOUNDATION FOR HIGHER-ORDER LOGIC PROGRAMMING WEIDONG CHEN,* MICHAEL KIFER, AND DAVID S. WARREN D We describe a novel logic, called HiLog, and show that it provides a more suitable basis for logic programming than does traditional predicate logic. HiLog has a higher-order syntax and allows arbitrary terms to appear in places where predicates, functions, and atomic formulas occur in predicate calculus. But its semantics is first-order and admits a sound and complete proof procedure. Applications of HiLog are discussed, including DCG grammars, higher-order and modular logic programming, and deductive databases. a 1. PREFACE Manipulating predicates, functions, and even atomic formulas is commonplace in logic programming. For example, Prolog combines predicate calculus, higher-order, and meta-level programming in one working system, allowing programmers routine use of generic predicate definitions (e.g., transitive closure, sorting) where predi- cates can be passed as parameters and returned as values [7]. Another well-known useful feature is the “call” meta-predicate of Prolog. Applications of higher-order constructs in the database context have been pointed out in many works, including [24, 29, 411. Although predicate calculus provides the basis for Prolog, it does not have the wherewithal to support any of the above features, which, consequently, have an ad hoc status in logic programming. In this paper, we investigate the fundamental principles underlying higher-order logic programming and, in particular, shed new light on why and how these Prolog features appear to work in practice. We propose *Present address: Computer Science and Engineering, Southern Methodist University, Dallas, TX 75275. -
An Introduction to Critical Thinking and Symbolic Logic: Volume 1 Formal Logic
An Introduction to Critical Thinking and Symbolic Logic: Volume 1 Formal Logic Rebeka Ferreira and Anthony Ferrucci 1 1An Introduction to Critical Thinking and Symbolic Logic: Volume 1 Formal Logic is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. 1 Preface This textbook has developed over the last few years of teaching introductory symbolic logic and critical thinking courses. It has been truly a pleasure to have beneted from such great students and colleagues over the years. As we have become increasingly frustrated with the costs of traditional logic textbooks (though many of them deserve high praise for their accuracy and depth), the move to open source has become more and more attractive. We're happy to provide it free of charge for educational use. With that being said, there are always improvements to be made here and we would be most grateful for constructive feedback and criticism. We have chosen to write this text in LaTex and have adopted certain conventions with symbols. Certainly many important aspects of critical thinking and logic have been omitted here, including historical developments and key logicians, and for that we apologize. Our goal was to create a textbook that could be provided to students free of charge and still contain some of the more important elements of critical thinking and introductory logic. To that end, an additional benet of providing this textbook as a Open Education Resource (OER) is that we will be able to provide newer updated versions of this text more frequently, and without any concern about increased charges each time. -
Model Theory – Draft
Math 225A – Model Theory – Draft Speirs, Martin Autumn 2013 Contents Contents 1 0 General Information 5 1 Lecture 16 1.1 The Category of τ-Structures....................... 6 2 Lecture 2 11 2.1 Logics..................................... 13 2.2 Free and bound variables......................... 14 3 Lecture 3 16 3.1 Diagrams................................... 16 3.2 Canonical Models.............................. 19 4 Lecture 4 22 4.1 Relations defined by atomic formulae.................. 22 4.2 Infinitary languages............................ 22 4.3 Axiomatization............................... 24 The Arithmetical Hierarchy........................ 24 1 Contents 2 5 Lecture 5 25 5.1 Preservation of Formulae......................... 26 6 Lecture 6 31 6.1 Theories and Models............................ 31 6.2 Unnested formulae............................. 34 6.3 Definitional expansions.......................... 36 7 Lecture 7 38 7.1 Definitional expansions continued.................... 38 7.2 Atomisation/Morleyisation........................ 39 8 Lecture 8 42 8.1 Quantifier Elimination........................... 42 8.2 Quantifier Elimination for (N, <) ..................... 42 8.3 Skolem’s theorem.............................. 45 8.4 Skolem functions.............................. 46 9 Lecture 9 47 9.1 Skolemisation................................ 47 9.2 Back-and-Forth and Games........................ 49 9.3 The Ehrenfeucht-Fraïssé game...................... 50 10 Lecture 10 52 10.1 The Unnested Ehrenfeucht-Fraïssé Game................ 52 11 Lecture -
Weak Formal Systems
Filosofick´afakulta Universita Karlova v Praze Weak Formal Systems diplomov´apr´ace Praha, 2003 studijn´ı obor: logika-informatika vypracoval: Jan Henzl vedouc´ıpr´ace: Doc. RNDr. Jan Kraj´ıˇcek, DrSc. Prohlaˇsuji, ˇze jsem tuto pr´aci vypracoval samostatnˇeapouˇzil v´yhradnˇe citovan´ych pramen˚u. Contents 1Abstract 4 2 Introduction 5 3 Propositional proof systems 7 4 Examples of propositional proof systems 10 5 Predicate calculus as a propositional proof system 14 6 Weak first order theories 19 7 Theories extending T∞ 28 8 Theories with ”fast growing models” 34 9Furtherresearch 42 10 Symbol index 43 References 44 3 1Abstract In this work we study the calculi for first-order logic as propositional proof systems. It is easy to see (and discussed in this thesis formally) that predicate calculi can serve as propositional proof systems. The question is whether they can allow for some shorter proofs. The motivation for this comes from a problem whether there exists a polynomially bounded proof system. We will shortly review this problem (first stated by S.A.Cook and R.A.Reckhow [CR]) in the introduction to this thesis. We interpret calculi for predicate logic and some first-order theories as propositional proof system in the sense of Cook-Reckhow [CR] and we study their efficiency in terms of polynomial simulations. We prove that predicate calculus is polynomially equivalent to Frege systems while a theory saying that there are at least two different elements is polynomially equivalent to the Quantified propositional calculus. We prove analogous results also for some stronger theories. Further we define the notion of a ”weak theory” and show that weak theries can be polynomially simulated by the Quantified propositional logic too. -
Per Lindström FIRST-ORDER LOGIC
Philosophical Communications, Web Series, No 36 Dept. of Philosophy, Göteborg University, Sweden ISSN 1652-0459 Per Lindström FIRST-ORDER LOGIC May 15, 2006 PREFACE Predicate logic was created by Gottlob Frege (Frege (1879)) and first-order (predicate) logic was first singled out by Charles Sanders Peirce and Ernst Schröder in the late 1800s (cf. van Heijenoort (1967)), and, following their lead, by Leopold Löwenheim (Löwenheim (1915)) and Thoralf Skolem (Skolem (1920), (1922)). Both these contributions were of decisive importance in the development of modern logic. In the case of Frege's achievement this is obvious. However, Frege's (second-order) logic is far too complicated to lend itself to the type of (mathematical) investigation that completely dominates modern logic. It turned out, however, that the first-order fragment of predicate logic, in which you can quantify over “individuals” but not, as in Frege's logic, over sets of “individuals”, relations between “individuals”, etc., is a logic that is strong enough for (most) mathematical purposes and still simple enough to admit of general, nontrivial theorems, the Löwenheim theorem, later sharpened and extended by Skolem, being the first example. In stating his theorem, Löwenheim made use of the idea, introduced by Peirce and Schröder, of satisfiability in a domain D, i.e., an arbitrary set of “individuals” whose nature need not be specified; the cardinality of D is all that matters. This concept, a forerunner of the present-day notion of truth in a model, was quite foreign to the Frege-Peano-Russell tradition dominating logic at the time and its introduction and the first really significant theorem, the Löwenheim (-Skolem) theorem, may be said to mark the beginning of modern logic. -
Model Theory Notes
Model theory notes. Kevin Buzzard April 26, 2012 1 Introduction Ambrus Pal is (Jan-Mar 2008) giving some lectures on model theory. I don't know the basic definitions and facts though! So here are some notes containing the basic facts and possibly more. 2 Definitions. A language L is: (i) a set F of \function symbols", and a positive integer nf for each f 2 F (ii) a set R of \relation symnols", and a positive integer nR for each R 2 R, and (iii) a set C of \constant symbols". For example the \language of rings" might be the language with F = f+; −;:g with n+ = n− = n: = 2, R empty, and C = f0; 1g. Note that there are other ways to do it! Later on, when we get to theories (that is, axioms) we will see that we can either make minus (−) part of the language, as we just did above, or we can bung in an axiom stating that everything has an additive inverse, and hence we can \deduce" the minus function from the axioms. Sometimes innocuous changes like this really make a difference (for example, although I haven't explained any of what this means yet, we'll see later that something called \quantifier elimination" might be false in one theory and true in a completely equivalent theory with \more language and less axioms"). But for sanity's sake we have to choose once and for all what we are talking about, and Ambrus in his course choses the following: the language of rings will have F = f+; −; :; 0; 1g, the language of groups will have F = f1;:g (1 the identity constant, : the multiplication function with n: = 2, but no inverse function: we will assert existence of inverses as part of the axioms) and the language of orderings will just be one relation F = f<g. -
Elementary Model Theory
GEORGE F. MCNULTY Elementary Model Theory DRAWINGS BY THE AUTHOR UNIVERSITYOF SOUTH CAROLINA FALL 2016 ELEMENTARY MODEL THEORY PREFACE The lecture notes before you are from a one-semester graduate course in model theory that I have taught at the University of South Carolina at three or four year intervals since the 1970’s. Most of the students in these courses had already passed Ph.D. qualifying examinations in anal- ysis and algebra and most subsequently completed dissertations in number theory, analysis, al- gebra, or discrete mathematics. A few completed dissertations connected to mathematical logic. The course was typically paired in sequence with courses in computable functions, equational logic, or set theory. It has always seemed to me that there were two ways to select topics appropriate to a model theory course aimed at graduate students largely destined for parts of mathematics outside of mathematical logic. One could develop the basic facts of model theory with some quite explicit applications in analysis, algebra, number theory, or discrete mathematics in mind or one could layout the elements of model theory in its own right with the idea of giving the students some foundation upon which they could build an understanding of the deeper more powerful tools of model theory that they may want to apply, for example, in algebraic geometry. Selection primarily guided by the first principle might, for example, stress quantifier elimination, model complete- ness, and model theoretic forcing. Selection primarily guided by the second principle, it seems to me, must lead toward the theory of stability. Try as I might, a single semester does not allow both principles full play.