Choice, Extension, Conservation. from Transfinite to finite Methods in Abstract Algebra
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Chapter 1 Preliminaries
Chapter 1 Preliminaries 1.1 First-order theories In this section we recall some basic definitions and facts about first-order theories. Most proofs are postponed to the end of the chapter, as exercises for the reader. 1.1.1 Definitions Definition 1.1 (First-order theory) —A first-order theory T is defined by: A first-order language L , whose terms (notation: t, u, etc.) and formulas (notation: φ, • ψ, etc.) are constructed from a fixed set of function symbols (notation: f , g, h, etc.) and of predicate symbols (notation: P, Q, R, etc.) using the following grammar: Terms t ::= x f (t1,..., tk) | Formulas φ, ψ ::= t1 = t2 P(t1,..., tk) φ | | > | ⊥ | ¬ φ ψ φ ψ φ ψ x φ x φ | ⇒ | ∧ | ∨ | ∀ | ∃ (assuming that each use of a function symbol f or of a predicate symbol P matches its arity). As usual, we call a constant symbol any function symbol of arity 0. A set of closed formulas of the language L , written Ax(T ), whose elements are called • the axioms of the theory T . Given a closed formula φ of the language of T , we say that φ is derivable in T —or that φ is a theorem of T —and write T φ when there are finitely many axioms φ , . , φ Ax(T ) such ` 1 n ∈ that the sequent φ , . , φ φ (or the formula φ φ φ) is derivable in a deduction 1 n ` 1 ∧ · · · ∧ n ⇒ system for classical logic. The set of all theorems of T is written Th(T ). Conventions 1.2 (1) In this course, we only work with first-order theories with equality. -
Automated ZFC Theorem Proving with E
Automated ZFC Theorem Proving with E John Hester Department of Mathematics, University of Florida, Gainesville, Florida, USA https://people.clas.ufl.edu/hesterj/ [email protected] Abstract. I introduce an approach for automated reasoning in first or- der set theories that are not finitely axiomatizable, such as ZFC, and describe its implementation alongside the automated theorem proving software E. I then compare the results of proof search in the class based set theory NBG with those of ZFC. Keywords: ZFC · ATP · E. 1 Introduction Historically, automated reasoning in first order set theories has faced a fun- damental problem in the axiomatizations. Some theories such as ZFC widely considered as candidates for the foundations of mathematics are not finitely axiomatizable. Axiom schemas such as the schema of comprehension and the schema of replacement in ZFC are infinite, and so cannot be entirely incorpo- rated in to the prover at the beginning of a proof search. Indeed, there is no finite axiomatization of ZFC [1]. As a result, when reasoning about sufficiently strong set theories that could no longer be considered naive, some have taken the alternative approach of using extensions of ZFC that admit objects such as proper classes as first order objects, but this is not without its problems for the individual interested in proving set-theoretic propositions. As an alternative, I have programmed an extension to the automated the- orem prover E [2] that generates instances of parameter free replacement and comprehension from well formuled formulas of ZFC that are passed to it, when eligible, and adds them to the proof state while the prover is running. -
(Aka “Geometric”) Iff It Is Axiomatised by “Coherent Implications”
GEOMETRISATION OF FIRST-ORDER LOGIC ROY DYCKHOFF AND SARA NEGRI Abstract. That every first-order theory has a coherent conservative extension is regarded by some as obvious, even trivial, and by others as not at all obvious, but instead remarkable and valuable; the result is in any case neither sufficiently well-known nor easily found in the literature. Various approaches to the result are presented and discussed in detail, including one inspired by a problem in the proof theory of intermediate logics that led us to the proof of the present paper. It can be seen as a modification of Skolem's argument from 1920 for his \Normal Form" theorem. \Geometric" being the infinitary version of \coherent", it is further shown that every infinitary first-order theory, suitably restricted, has a geometric conservative extension, hence the title. The results are applied to simplify methods used in reasoning in and about modal and intermediate logics. We include also a new algorithm to generate special coherent implications from an axiom, designed to preserve the structure of formulae with relatively little use of normal forms. x1. Introduction. A theory is \coherent" (aka \geometric") iff it is axiomatised by \coherent implications", i.e. formulae of a certain simple syntactic form (given in Defini- tion 2.4). That every first-order theory has a coherent conservative extension is regarded by some as obvious (and trivial) and by others (including ourselves) as non- obvious, remarkable and valuable; it is neither well-enough known nor easily found in the literature. We came upon the result (and our first proof) while clarifying an argument from our paper [17]. -
1.4 Theories
1.4 Theories Before we start to work with one of the most central notions of mathematical logic – that of a theory – it will be useful to make some observations about countable sets. Lemma 1.3. 1. A set X is countable iff there is a surjection ψ : N X. 2. If X is countable and Y X then Y is countable. 3. If X and Y are countable, then X Y is countable. 4. If X and Y are countable, then X ¢ Y is countable. k 5. If X is countable and k 1 then X is countable. ä 6. If Xi is countable for each i È N, then Xi is countable. iÈN 7. If X is countable, then ä Xk is countable. k ÈN Ø Ù Proof. 1. If X is countably infinite note that every bijection is a surjection. If X x0,...,xn Õ Ô Õ is finite, let ψ Ôi xi for 0 i n and ψ j xn for j n. For the other direction, Ô Õ Ô Õ Ô Õ Ù let ψ be a surjection, then X is Øψ 0 , ψ 1 , ψ 2 ,... and removing duplicates from the Ô ÕÕ Ô N sequence ψ i i¥0 yields a bijective ϕ : X. È 2. Obvious if Y is finite. Otherwise, let ϕ : N X be a bijection and let y0 Y . Define " Õ Ô Õ È ϕÔn if ϕ n Y ψ : N Y,n y0 otherwise which is a surjection. 3. Let ϕ : N X and ψ : N Y be bijections. -
Lipics-FSCD-2021-29.Pdf (0.9
On the Logical Strength of Confluence and Normalisation for Cyclic Proofs Anupam Das ! Ï University of Birmingham, UK Abstract In this work we address the logical strength of confluence and normalisation for non-wellfounded typing derivations, in the tradition of “cyclic proof theory” . We present a circular version CT of Gödel’ s system T, with the aim of comparing the relative expressivity of the theories CT and T. We approach this problem by formalising rewriting-theoretic results such as confluence and normalisation for the underlying “coterm” rewriting system of CT within fragments of second-order arithmetic. We establish confluence of CT within the theory RCA0, a conservative extension of primitive recursive arithmetic and IΣ1. This allows us to recast type structures of hereditarily recursive operations as “coterm” models of T. We show that these also form models of CT, by formalising a totality argument for circular typing derivations within suitable fragments of second-order arithmetic. Relying on well-known proof mining results, we thus obtain an interpretation of CT into T; in fact, more precisely, we interpret level-n-CT into level-(n + 1)-T, an optimum result in terms of abstraction complexity. A direct consequence of these model-theoretic results is weak normalisation for CT. As further results, we also show strong normalisation for CT and continuity of functionals computed by its type 2 coterms. 2012 ACM Subject Classification Theory of computation → Equational logic and rewriting; Theory of computation → Proof theory; Theory of computation → Higher order logic; Theory of computation → Lambda calculus Keywords and phrases confluence, normalisation, system T, circular proofs, reverse mathematics, type structures Digital Object Identifier 10.4230/LIPIcs.FSCD.2021.29 Related Version This work is based on part of the following preprint, where related results, proofs and examples may be found. -
2/3 Conjecture
PROGRESS ON THE 1=3 − 2=3 CONJECTURE By Emily Jean Olson A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Mathematics | Doctor of Philosophy 2017 ABSTRACT PROGRESS ON THE 1=3 − 2=3 CONJECTURE By Emily Jean Olson Let (P; ≤) be a finite partially ordered set, also called a poset, and let n denote the cardinality of P . Fix a natural labeling on P so that the elements of P correspond to [n] = f1; 2; : : : ; ng. A linear extension is an order-preserving total order x1 ≺ x2 ≺ · · · ≺ xn on the elements of P , and more compactly, we can view this as the permutation x1x2 ··· xn in one-line notation. For distinct elements x; y 2 P , we define P(x ≺ y) to be the proportion 1 of linear extensions of P in which x comes before y. For 0 ≤ α ≤ 2, we say (x; y) is an α-balanced pair if α ≤ P(x ≺ y) ≤ 1 − α: The 1=3 − 2=3 Conjecture states that every finite partially ordered set that is not a chain has a 1=3-balanced pair. This dissertation focuses on showing the conjecture is true for certain types of partially ordered sets. We begin by discussing a special case, namely when a partial order is 1=2-balanced. For example, this happens when the poset has an automorphism with a cycle of length 2. We spend the remainder of the text proving the conjecture is true for some lattices, including Boolean, set partition, and subspace lattices; partial orders that arise from a Young diagram; and some partial orders of dimension 2. -
Inseparability and Conservative Extensions of Description Logic Ontologies: a Survey
Inseparability and Conservative Extensions of Description Logic Ontologies: A Survey Elena Botoeva1, Boris Konev2, Carsten Lutz3, Vladislav Ryzhikov1, Frank Wolter2, and Michael Zakharyaschev4 1 Free University of Bozen-Bolzano, Italy fbotoeva,[email protected] 2 University of Liverpool, UK fkonev,[email protected] 3 University of Bremen, Germany [email protected] 4 Birkbeck, University of London, UK [email protected] Abstract. The question whether an ontology can safely be replaced by another, possibly simpler, one is fundamental for many ontology engi- neering and maintenance tasks. It underpins, for example, ontology ver- sioning, ontology modularization, forgetting, and knowledge exchange. What `safe replacement' means depends on the intended application of the ontology. If, for example, it is used to query data, then the answers to any relevant ontology-mediated query should be the same over any relevant data set; if, in contrast, the ontology is used for conceptual reasoning, then the entailed subsumptions between concept expressions should coincide. This gives rise to different notions of ontology insep- arability such as query inseparability and concept inseparability, which generalize corresponding notions of conservative extensions. We survey results on various notions of inseparability in the context of descrip- tion logic ontologies, discussing their applications, useful model-theoretic characterizations, algorithms for determining whether two ontologies are inseparable (and, sometimes, for computing the difference between them if they are not), and the computational complexity of this problem. 1 Introduction Description logic (DL) ontologies provide a common vocabulary for a domain of interest together with a formal modeling of the semantics of the vocabulary items (concept names and role names). -
The Strength of Mac Lane Set Theory
The Strength of Mac Lane Set Theory A. R. D. MATHIAS D´epartement de Math´ematiques et Informatique Universit´e de la R´eunion To Saunders Mac Lane on his ninetieth birthday Abstract AUNDERS MAC LANE has drawn attention many times, particularly in his book Mathematics: Form and S Function, to the system ZBQC of set theory of which the axioms are Extensionality, Null Set, Pairing, Union, Infinity, Power Set, Restricted Separation, Foundation, and Choice, to which system, afforced by the principle, TCo, of Transitive Containment, we shall refer as MAC. His system is naturally related to systems derived from topos-theoretic notions concerning the category of sets, and is, as Mac Lane emphasizes, one that is adequate for much of mathematics. In this paper we show that the consistency strength of Mac Lane's system is not increased by adding the axioms of Kripke{Platek set theory and even the Axiom of Constructibility to Mac Lane's axioms; our method requires a close study of Axiom H, which was proposed by Mitchell; we digress to apply these methods to subsystems of Zermelo set theory Z, and obtain an apparently new proof that Z is not finitely axiomatisable; we study Friedman's strengthening KPP + AC of KP + MAC, and the Forster{Kaye subsystem KF of MAC, and use forcing over ill-founded models and forcing to establish independence results concerning MAC and KPP ; we show, again using ill-founded models, that KPP + V = L proves the consistency of KPP ; turning to systems that are type-theoretic in spirit or in fact, we show by arguments of Coret -
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. -
Counting Linear Extensions in Practice: MCMC Versus Exponential Monte Carlo
The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) Counting Linear Extensions in Practice: MCMC versus Exponential Monte Carlo Topi Talvitie Kustaa Kangas Teppo Niinimaki¨ Mikko Koivisto Dept. of Computer Science Dept. of Computer Science Dept. of Computer Science Dept. of Computer Science University of Helsinki Aalto University Aalto University University of Helsinki topi.talvitie@helsinki.fi juho-kustaa.kangas@aalto.fi teppo.niinimaki@aalto.fi mikko.koivisto@helsinki.fi Abstract diagram (Kangas et al. 2016), or the treewidth of the incom- parability graph (Eiben et al. 2016). Counting the linear extensions of a given partial order is a If an approximation with given probability is sufficient, #P-complete problem that arises in numerous applications. For polynomial-time approximation, several Markov chain the problem admits a polynomial-time solution for all posets Monte Carlo schemes have been proposed; however, little is using Markov chain Monte Carlo (MCMC) methods. The known of their efficiency in practice. This work presents an first fully-polynomial time approximation scheme of this empirical evaluation of the state-of-the-art schemes and in- kind for was based on algorithms for approximating the vol- vestigates a number of ideas to enhance their performance. In umes of convex bodies (Dyer, Frieze, and Kannan 1991). addition, we introduce a novel approximation scheme, adap- The later improvements were based on rapidly mixing tive relaxation Monte Carlo (ARMC), that leverages exact Markov chains in the set of linear extensions (Karzanov exponential-time counting algorithms. We show that approx- and Khachiyan 1991; Bubley and Dyer 1999) combined imate counting is feasible up to a few hundred elements on with Monte Carlo counting schemes (Brightwell and Win- various classes of partial orders, and within this range ARMC kler 1991; Banks et al. -
Counting Linear Extensions of Restricted Posets
COUNTING LINEAR EXTENSIONS OF RESTRICTED POSETS SAMUEL DITTMER? AND IGOR PAK? Abstract. The classical 1991 result by Brightwell and Winkler [BW91] states that the number of linear extensions of a poset is #P-complete. We extend this result to posets with certain restrictions. First, we prove that the number of linear extension for posets of height two is #P-complete. Furthermore, we prove that this holds for incidence posets of graphs. Finally, we prove that the number of linear extensions for posets of dimension two is #P-complete. 1. Introduction Counting linear extensions (#LE) of a finite poset is a fundamental problem in both Combinatorics and Computer Science, with connections and applications ranging from Sta- tistics to Optimization, to Social Choice Theory. It is primarily motivated by the following basic question: given a partial information of preferences between various objects, what are the chances of other comparisons? In 1991, Brightwell and Winkler showed that #LE is #P-complete [BW91], but for var- ious restricted classes of posets the problem remains unresolved. Notably, they conjectured that the following problem is #P-complete: #H2LE (Number of linear extensions of height-2 posets) Input: A partially ordered set P of height 2. Output: The number e(P ) of linear extensions. Here height two means that P has two levels, i.e. no chains of length 3. This problem has been open for 27 years, most recently reiterated in [Hub14, LS17]. Its solution is the first result in this paper. Theorem 1.1. #H2LE is #P-complete. Our second result is an extension of Theorem 1.1. -
Warren Goldfarb, Notes on Metamathematics
Notes on Metamathematics Warren Goldfarb W.B. Pearson Professor of Modern Mathematics and Mathematical Logic Department of Philosophy Harvard University DRAFT: January 1, 2018 In Memory of Burton Dreben (1927{1999), whose spirited teaching on G¨odeliantopics provided the original inspiration for these Notes. Contents 1 Axiomatics 1 1.1 Formal languages . 1 1.2 Axioms and rules of inference . 5 1.3 Natural numbers: the successor function . 9 1.4 General notions . 13 1.5 Peano Arithmetic. 15 1.6 Basic laws of arithmetic . 18 2 G¨odel'sProof 23 2.1 G¨odelnumbering . 23 2.2 Primitive recursive functions and relations . 25 2.3 Arithmetization of syntax . 30 2.4 Numeralwise representability . 35 2.5 Proof of incompleteness . 37 2.6 `I am not derivable' . 40 3 Formalized Metamathematics 43 3.1 The Fixed Point Lemma . 43 3.2 G¨odel'sSecond Incompleteness Theorem . 47 3.3 The First Incompleteness Theorem Sharpened . 52 3.4 L¨ob'sTheorem . 55 4 Formalizing Primitive Recursion 59 4.1 ∆0,Σ1, and Π1 formulas . 59 4.2 Σ1-completeness and Σ1-soundness . 61 4.3 Proof of Representability . 63 3 5 Formalized Semantics 69 5.1 Tarski's Theorem . 69 5.2 Defining truth for LPA .......................... 72 5.3 Uses of the truth-definition . 74 5.4 Second-order Arithmetic . 76 5.5 Partial truth predicates . 79 5.6 Truth for other languages . 81 6 Computability 85 6.1 Computability . 85 6.2 Recursive and partial recursive functions . 87 6.3 The Normal Form Theorem and the Halting Problem . 91 6.4 Turing Machines .