Foundations of Mathematics Chapter 1: Foundations of Geometry
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A Hierarchy of Computably Enumerable Degrees, Ii: Some Recent Developments and New Directions
A HIERARCHY OF COMPUTABLY ENUMERABLE DEGREES, II: SOME RECENT DEVELOPMENTS AND NEW DIRECTIONS ROD DOWNEY, NOAM GREENBERG, AND ELLEN HAMMATT Abstract. A transfinite hierarchy of Turing degrees of c.e. sets has been used to calibrate the dynamics of families of constructions in computability theory, and yields natural definability results. We review the main results of the area, and discuss splittings of c.e. degrees, and finding maximal degrees in upper cones. 1. Vaughan Jones This paper is part of for the Vaughan Jones memorial issue of the New Zealand Journal of Mathematics. Vaughan had a massive influence on World and New Zealand mathematics, both through his work and his personal commitment. Downey first met Vaughan in the early 1990's, around the time he won the Fields Medal. Vaughan had the vision of improving mathematics in New Zealand, and hoped his Fields Medal could be leveraged to this effect. It is fair to say that at the time, maths in New Zealand was not as well-connected internationally as it might have been. It was fortunate that not only was there a lot of press coverage, at the same time another visionary was operating in New Zealand: Sir Ian Axford. Ian pioneered the Marsden Fund, and a group of mathematicians gathered by Vaughan, Marston Conder, David Gauld, Gaven Martin, and Rod Downey, put forth a proposal for summer meetings to the Marsden Fund. The huge influence of Vaughan saw to it that this was approved, and this group set about bringing in external experts to enrich the NZ scene. -
Computability and Incompleteness Fact Sheets
Computability and Incompleteness Fact Sheets Computability Definition. A Turing machine is given by: A finite set of symbols, s1; : : : ; sm (including a \blank" symbol) • A finite set of states, q1; : : : ; qn (including a special \start" state) • A finite set of instructions, each of the form • If in state qi scanning symbol sj, perform act A and go to state qk where A is either \move right," \move left," or \write symbol sl." The notion of a \computation" of a Turing machine can be described in terms of the data above. From now on, when I write \let f be a function from strings to strings," I mean that there is a finite set of symbols Σ such that f is a function from strings of symbols in Σ to strings of symbols in Σ. I will also adopt the analogous convention for sets. Definition. Let f be a function from strings to strings. Then f is computable (or recursive) if there is a Turing machine M that works as follows: when M is started with its input head at the beginning of the string x (on an otherwise blank tape), it eventually halts with its head at the beginning of the string f(x). Definition. Let S be a set of strings. Then S is computable (or decidable, or recursive) if there is a Turing machine M that works as follows: when M is started with its input head at the beginning of the string x, then if x is in S, then M eventually halts, with its head on a special \yes" • symbol; and if x is not in S, then M eventually halts, with its head on a special • \no" symbol. -
Weakly Precomplete Computably Enumerable Equivalence Relations
Math. Log. Quart. 62, No. 1–2, 111–127 (2016) / DOI 10.1002/malq.201500057 Weakly precomplete computably enumerable equivalence relations Serikzhan Badaev1 ∗ and Andrea Sorbi2∗∗ 1 Department of Mechanics and Mathematics, Al-Farabi Kazakh National University, Almaty, 050038, Kazakhstan 2 Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Universita` Degli Studi di Siena, 53100, Siena, Italy Received 28 July 2015, accepted 4 November 2015 Published online 17 February 2016 Using computable reducibility ≤ on equivalence relations, we investigate weakly precomplete ceers (a “ceer” is a computably enumerable equivalence relation on the natural numbers), and we compare their class with the more restricted class of precomplete ceers. We show that there are infinitely many isomorphism types of universal (in fact uniformly finitely precomplete) weakly precomplete ceers , that are not precomplete; and there are infinitely many isomorphism types of non-universal weakly precomplete ceers. Whereas the Visser space of a precomplete ceer always contains an infinite effectively discrete subset, there exist weakly precomplete ceers whose Visser spaces do not contain infinite effectively discrete subsets. As a consequence, contrary to precomplete ceers which always yield partitions into effectively inseparable sets, we show that although weakly precomplete ceers always yield partitions into computably inseparable sets, nevertheless there are weakly precomplete ceers for which no equivalence class is creative. Finally, we show that the index set of the precomplete ceers is 3-complete, whereas the index set of the weakly precomplete ceers is 3-complete. As a consequence of these results, we also show that the index sets of the uniformly precomplete ceers and of the e-complete ceers are 3-complete. -
Propositional Logic, Modal Logic, Propo- Sitional Dynamic Logic and first-Order Logic
A I L Madhavan Mukund Chennai Mathematical Institute E-mail: [email protected] Abstract ese are lecture notes for an introductory course on logic aimed at graduate students in Com- puter Science. e notes cover techniques and results from propositional logic, modal logic, propo- sitional dynamic logic and first-order logic. e notes are based on a course taught to first year PhD students at SPIC Mathematical Institute, Madras, during August–December, . Contents Propositional Logic . Syntax . . Semantics . . Axiomatisations . . Maximal Consistent Sets and Completeness . . Compactness and Strong Completeness . Modal Logic . Syntax . . Semantics . . Correspondence eory . . Axiomatising valid formulas . . Bisimulations and expressiveness . . Decidability: Filtrations and the finite model property . . Labelled transition systems and multi-modal logic . Dynamic Logic . Syntax . . Semantics . . Axiomatising valid formulas . First-Order Logic . Syntax . . Semantics . . Formalisations in first-order logic . . Satisfiability: Henkin’s reduction to propositional logic . . Compactness and the L¨owenheim-Skolem eorem . . A Complete Axiomatisation . . Variants of the L¨owenheim-Skolem eorem . . Elementary Classes . . Elementarily Equivalent Structures . . An Algebraic Characterisation of Elementary Equivalence . . Decidability . Propositional Logic . Syntax P = f g We begin with a countably infinite set of atomic propositions p0, p1,... and two logical con- nectives : (read as not) and _ (read as or). e set Φ of formulas of propositional logic is the smallest set satisfying the following conditions: • Every atomic proposition p is a member of Φ. • If α is a member of Φ, so is (:α). • If α and β are members of Φ, so is (α _ β). We shall normally omit parentheses unless we need to explicitly clarify the structure of a formula. -
Calcium: Computing in Exact Real and Complex Fields Fredrik Johansson
Calcium: computing in exact real and complex fields Fredrik Johansson To cite this version: Fredrik Johansson. Calcium: computing in exact real and complex fields. ISSAC ’21, Jul 2021, Virtual Event, Russia. 10.1145/3452143.3465513. hal-02986375v2 HAL Id: hal-02986375 https://hal.inria.fr/hal-02986375v2 Submitted on 15 May 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Calcium: computing in exact real and complex fields Fredrik Johansson [email protected] Inria Bordeaux and Institut Math. Bordeaux 33400 Talence, France ABSTRACT This paper presents Calcium,1 a C library for exact computa- Calcium is a C library for real and complex numbers in a form tion in R and C. Numbers are represented as elements of fields suitable for exact algebraic and symbolic computation. Numbers Q¹a1;:::; anº where the extension numbers ak are defined symbol- ically. The system constructs fields and discovers algebraic relations are represented as elements of fields Q¹a1;:::; anº where the exten- automatically, handling algebraic and transcendental number fields sion numbers ak may be algebraic or transcendental. The system combines efficient field operations with automatic discovery and in a unified way. -
On Basic Probability Logic Inequalities †
mathematics Article On Basic Probability Logic Inequalities † Marija Boriˇci´cJoksimovi´c Faculty of Organizational Sciences, University of Belgrade, Jove Ili´ca154, 11000 Belgrade, Serbia; [email protected] † The conclusions given in this paper were partially presented at the European Summer Meetings of the Association for Symbolic Logic, Logic Colloquium 2012, held in Manchester on 12–18 July 2012. Abstract: We give some simple examples of applying some of the well-known elementary probability theory inequalities and properties in the field of logical argumentation. A probabilistic version of the hypothetical syllogism inference rule is as follows: if propositions A, B, C, A ! B, and B ! C have probabilities a, b, c, r, and s, respectively, then for probability p of A ! C, we have f (a, b, c, r, s) ≤ p ≤ g(a, b, c, r, s), for some functions f and g of given parameters. In this paper, after a short overview of known rules related to conjunction and disjunction, we proposed some probabilized forms of the hypothetical syllogism inference rule, with the best possible bounds for the probability of conclusion, covering simultaneously the probabilistic versions of both modus ponens and modus tollens rules, as already considered by Suppes, Hailperin, and Wagner. Keywords: inequality; probability logic; inference rule MSC: 03B48; 03B05; 60E15; 26D20; 60A05 1. Introduction The main part of probabilization of logical inference rules is defining the correspond- Citation: Boriˇci´cJoksimovi´c,M. On ing best possible bounds for probabilities of propositions. Some of them, connected with Basic Probability Logic Inequalities. conjunction and disjunction, can be obtained immediately from the well-known Boole’s Mathematics 2021, 9, 1409. -
Propositional Logic - Basics
Outline Propositional Logic - Basics K. Subramani1 1Lane Department of Computer Science and Electrical Engineering West Virginia University 14 January and 16 January, 2013 Subramani Propositonal Logic Outline Outline 1 Statements, Symbolic Representations and Semantics Boolean Connectives and Semantics Subramani Propositonal Logic (i) The Law! (ii) Mathematics. (iii) Computer Science. Definition Statement (or Atomic Proposition) - A sentence that is either true or false. Example (i) The board is black. (ii) Are you John? (iii) The moon is made of green cheese. (iv) This statement is false. (Paradox). Statements, Symbolic Representations and Semantics Boolean Connectives and Semantics Motivation Why Logic? Subramani Propositonal Logic (ii) Mathematics. (iii) Computer Science. Definition Statement (or Atomic Proposition) - A sentence that is either true or false. Example (i) The board is black. (ii) Are you John? (iii) The moon is made of green cheese. (iv) This statement is false. (Paradox). Statements, Symbolic Representations and Semantics Boolean Connectives and Semantics Motivation Why Logic? (i) The Law! Subramani Propositonal Logic (iii) Computer Science. Definition Statement (or Atomic Proposition) - A sentence that is either true or false. Example (i) The board is black. (ii) Are you John? (iii) The moon is made of green cheese. (iv) This statement is false. (Paradox). Statements, Symbolic Representations and Semantics Boolean Connectives and Semantics Motivation Why Logic? (i) The Law! (ii) Mathematics. Subramani Propositonal Logic (iii) Computer Science. Definition Statement (or Atomic Proposition) - A sentence that is either true or false. Example (i) The board is black. (ii) Are you John? (iii) The moon is made of green cheese. (iv) This statement is false. -
Logic in Computer Science
P. Madhusudan Logic in Computer Science Rough course notes November 5, 2020 Draft. Copyright P. Madhusudan Contents 1 Logic over Structures: A Single Known Structure, Classes of Structures, and All Structures ................................... 1 1.1 Logic on a Fixed Known Structure . .1 1.2 Logic on a Fixed Class of Structures . .3 1.3 Logic on All Structures . .5 1.4 Logics over structures: Theories and Questions . .7 2 Propositional Logic ............................................. 11 2.1 Propositional Logic . 11 2.1.1 Syntax . 11 2.1.2 What does the above mean with ::=, etc? . 11 2.2 Some definitions and theorems . 14 2.3 Compactness Theorem . 15 2.4 Resolution . 18 3 Quantifier Elimination and Decidability .......................... 23 3.1 Quantifiier Elimination . 23 3.2 Dense Linear Orders without Endpoints . 24 3.3 Quantifier Elimination for rationals with addition: ¹Q, 0, 1, ¸, −, <, =º ......................................... 27 3.4 The Theory of Reals with Addition . 30 3.4.1 Aside: Axiomatizations . 30 3.4.2 Other theories that admit quantifier elimination . 31 4 Validity of FOL is undecidable and is r.e.-hard .................... 33 4.1 Validity of FOL is r.e.-hard . 34 4.2 Trakhtenbrot’s theorem: Validity of FOL over finite models is undecidable, and co-r.e. hard . 39 5 Quantifier-free theory of equality ................................ 43 5.1 Decidability using Bounded Models . 43 v vi Contents 5.2 An Algorithm for Conjunctive Formulas . 44 5.2.1 Computing ¹º ................................... 47 5.3 Axioms for The Theory of Equality . 49 6 Completeness Theorem: FO Validity is r.e. ........................ 53 6.1 Prenex Normal Form . -
Turing Degrees and Automorphism Groups of Substructure Lattices 3
TURING DEGREES AND AUTOMORPHISM GROUPS OF SUBSTRUCTURE LATTICES RUMEN DIMITROV, VALENTINA HARIZANOV, AND ANDREY MOROZOV Abstract. The study of automorphisms of computable and other structures connects computability theory with classical group theory. Among the non- computable countable structures, computably enumerable structures are one of the most important objects of investigation in computable model theory. In this paper, we focus on the lattice structure of computably enumerable substructures of a given canonical computable structure. In particular, for a Turing degree d, we investigate the groups of d-computable automorphisms of the lattice of d-computably enumerable vector spaces, of the interval Boolean algebra Bη of the ordered set of rationals, and of the lattice of d-computably enumerable subalgebras of Bη. For these groups we show that Turing reducibil- ity can be used to substitute the group-theoretic embedding. We also prove that the Turing degree of the isomorphism types for these groups is the second Turing jump of d, d′′. 1. Automorphisms of effective structures Computable model theory investigates algorithmic content (effectiveness) of notions, objects, and constructions in classical mathematics. In algebra this in- vestigation goes back to van der Waerden who in his Modern Algebra introduced an explicitly given field as one the elements of which are uniquely represented by distinguishable symbols with which we can perform the field operations algo- rithmically. The formalization of an explicitly given field led to the notion of a computable structure, one of the main objects of study in computable model the- ory. A structure is computable if its domain is computable and its relations and arXiv:1811.01224v1 [math.LO] 3 Nov 2018 functions are uniformly computable. -
CS245 Logic and Computation
CS245 Logic and Computation Alice Gao December 9, 2019 Contents 1 Propositional Logic 3 1.1 Translations .................................... 3 1.2 Structural Induction ............................... 8 1.2.1 A template for structural induction on well-formed propositional for- mulas ................................... 8 1.3 The Semantics of an Implication ........................ 12 1.4 Tautology, Contradiction, and Satisfiable but Not a Tautology ........ 13 1.5 Logical Equivalence ................................ 14 1.6 Analyzing Conditional Code ........................... 16 1.7 Circuit Design ................................... 17 1.8 Tautological Consequence ............................ 18 1.9 Formal Deduction ................................. 21 1.9.1 Rules of Formal Deduction ........................ 21 1.9.2 Format of a Formal Deduction Proof .................. 23 1.9.3 Strategies for writing a formal deduction proof ............ 23 1.9.4 And elimination and introduction .................... 25 1.9.5 Implication introduction and elimination ................ 26 1.9.6 Or introduction and elimination ..................... 28 1.9.7 Negation introduction and elimination ................. 30 1.9.8 Putting them together! .......................... 33 1.9.9 Putting them together: Additional exercises .............. 37 1.9.10 Other problems .............................. 38 1.10 Soundness and Completeness of Formal Deduction ............... 39 1.10.1 The soundness of inference rules ..................... 39 1.10.2 Soundness and Completeness -
Algebraic Aspects of the Computably Enumerable Degrees
Proc. Natl. Acad. Sci. USA Vol. 92, pp. 617-621, January 1995 Mathematics Algebraic aspects of the computably enumerable degrees (computability theory/recursive function theory/computably enumerable sets/Turing computability/degrees of unsolvability) THEODORE A. SLAMAN AND ROBERT I. SOARE Department of Mathematics, University of Chicago, Chicago, IL 60637 Communicated by Robert M. Solovay, University of California, Berkeley, CA, July 19, 1994 ABSTRACT A set A of nonnegative integers is computably equivalently represented by the set of Diophantine equations enumerable (c.e.), also called recursively enumerable (r.e.), if with integer coefficients and integer solutions, the word there is a computable method to list its elements. The class of problem for finitely presented groups, and a variety of other sets B which contain the same information as A under Turing unsolvable problems in mathematics and computer science. computability (<T) is the (Turing) degree ofA, and a degree is Friedberg (5) and independently Mucnik (6) solved Post's c.e. if it contains a c.e. set. The extension ofembedding problem problem by producing a noncomputable incomplete c.e. set. for the c.e. degrees Qk = (R, <, 0, 0') asks, given finite partially Their method is now known as the finite injury priority ordered sets P C Q with least and greatest elements, whether method. Restated now for c.e. degrees, the Friedberg-Mucnik every embedding ofP into Rk can be extended to an embedding theorem is the first and easiest extension of embedding result of Q into Rt. Many of the most significant theorems giving an for the well-known partial ordering of the c.e. -
Computability on the Real Numbers
4. Computability on the Real Numbers Real numbers are the basic objects in analysis. For most non-mathematicians a real number is an infinite decimal fraction, for example π = 3•14159 ... Mathematicians prefer to define the real numbers axiomatically as follows: · (R, +, , 0, 1,<) is, up to isomorphism, the only Archimedean ordered field satisfying the axiom of continuity [Die60]. The set of real numbers can also be constructed in various ways, for example by means of Dedekind cuts or by completion of the (metric space of) rational numbers. We will neglect all foundational problems and assume that the real numbers form a well-defined set R with all the properties which are proved in analysis. We will denote the R real line topology, that is, the set of all open subsets of ,byτR. In Sect. 4.1 we introduce several representations of the real numbers, three of which (and the equivalent ones) will survive as useful. We introduce a rep- n n resentation ρ of R by generalizing the definition of the main representation ρ of the set R of real numbers. In Sect. 4.2 we discuss the computable real numbers. Sect. 4.3 is devoted to computable real functions. We show that many well known functions are computable, and we show that partial sum- mation of sequences is computable and that limit operator on sequences of real numbers is computable, if a modulus of convergence is given. We also prove a computability theorem for power series. Convention 4.0.1. We still assume that Σ is a fixed finite alphabet con- taining all the symbols we will need.