The Galois Connection Between Syntax and Semantics
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GALOIS THEORY for ARBITRARY FIELD EXTENSIONS Contents 1
GALOIS THEORY FOR ARBITRARY FIELD EXTENSIONS PETE L. CLARK Contents 1. Introduction 1 1.1. Kaplansky's Galois Connection and Correspondence 1 1.2. Three flavors of Galois extensions 2 1.3. Galois theory for algebraic extensions 3 1.4. Transcendental Extensions 3 2. Galois Connections 4 2.1. The basic formalism 4 2.2. Lattice Properties 5 2.3. Examples 6 2.4. Galois Connections Decorticated (Relations) 8 2.5. Indexed Galois Connections 9 3. Galois Theory of Group Actions 11 3.1. Basic Setup 11 3.2. Normality and Stability 11 3.3. The J -topology and the K-topology 12 4. Return to the Galois Correspondence for Field Extensions 15 4.1. The Artinian Perspective 15 4.2. The Index Calculus 17 4.3. Normality and Stability:::and Normality 18 4.4. Finite Galois Extensions 18 4.5. Algebraic Galois Extensions 19 4.6. The J -topology 22 4.7. The K-topology 22 4.8. When K is algebraically closed 22 5. Three Flavors Revisited 24 5.1. Galois Extensions 24 5.2. Dedekind Extensions 26 5.3. Perfectly Galois Extensions 27 6. Notes 28 References 29 Abstract. 1. Introduction 1.1. Kaplansky's Galois Connection and Correspondence. For an arbitrary field extension K=F , define L = L(K=F ) to be the lattice of 1 2 PETE L. CLARK subextensions L of K=F and H = H(K=F ) to be the lattice of all subgroups H of G = Aut(K=F ). Then we have Φ: L!H;L 7! Aut(K=L) and Ψ: H!F;H 7! KH : For L 2 L, we write c(L) := Ψ(Φ(L)) = KAut(K=L): One immediately verifies: L ⊂ L0 =) c(L) ⊂ c(L0);L ⊂ c(L); c(c(L)) = c(L); these properties assert that L 7! c(L) is a closure operator on the lattice L in the sense of order theory. -
Simple Laws About Nonprominent Properties of Binary Relations
Simple Laws about Nonprominent Properties of Binary Relations Jochen Burghardt jochen.burghardt alumni.tu-berlin.de Nov 2018 Abstract We checked each binary relation on a 5-element set for a given set of properties, including usual ones like asymmetry and less known ones like Euclideanness. Using a poor man's Quine-McCluskey algorithm, we computed prime implicants of non-occurring property combinations, like \not irreflexive, but asymmetric". We considered the laws obtained this way, and manually proved them true for binary relations on arbitrary sets, thus contributing to the encyclopedic knowledge about less known properties. Keywords: Binary relation; Quine-McCluskey algorithm; Hypotheses generation arXiv:1806.05036v2 [math.LO] 20 Nov 2018 Contents 1 Introduction 4 2 Definitions 8 3 Reported law suggestions 10 4 Formal proofs of property laws 21 4.1 Co-reflexivity . 21 4.2 Reflexivity . 23 4.3 Irreflexivity . 24 4.4 Asymmetry . 24 4.5 Symmetry . 25 4.6 Quasi-transitivity . 26 4.7 Anti-transitivity . 28 4.8 Incomparability-transitivity . 28 4.9 Euclideanness . 33 4.10 Density . 38 4.11 Connex and semi-connex relations . 39 4.12 Seriality . 40 4.13 Uniqueness . 42 4.14 Semi-order property 1 . 43 4.15 Semi-order property 2 . 45 5 Examples 48 6 Implementation issues 62 6.1 Improved relation enumeration . 62 6.2 Quine-McCluskey implementation . 64 6.3 On finding \nice" laws . 66 7 References 69 List of Figures 1 Source code for transitivity check . .5 2 Source code to search for right Euclidean non-transitive relations . .5 3 Timing vs. universe cardinality . -
Formal Contexts, Formal Concept Analysis, and Galois Connections
Formal Contexts, Formal Concept Analysis, and Galois Connections Jeffrey T. Denniston Austin Melton Department of Mathematical Sciences Departments of Computer Science and Mathematical Sciences Kent State University Kent State University Kent, Ohio, USA 44242 Kent, Ohio, USA 44242 [email protected] [email protected] Stephen E. Rodabaugh College of Science, Technology, Engineering, Mathematics (STEM) Youngstown State University Youngstown, OH, USA 44555-3347 [email protected] Formal concept analysis (FCA) is built on a special type of Galois connections called polarities. We present new results in formal concept analysis and in Galois connections by presenting new Galois connection results and then applying these to formal concept analysis. We also approach FCA from the perspective of collections of formal contexts. Usually, when doing FCA, a formal context is fixed. We are interested in comparing formal contexts and asking what criteria should be used when determining when one formal context is better than another formal context. Interestingly, we address this issue by studying sets of polarities. 1 Formal Concept Analysis and Order-Reversing Galois Connections We study formal concept analysis (FCA) from a “larger” perspective than is commonly done. We em- phasize formal contexts. For example, we are interested in questions such as if we are working with a given formal context K , that is, we are working with a set of objects G, a set of properties M, and a relation R ⊂ G×M, what do we do if we want to replace K with a better formal context. Of course, this raises the question: what makes one formal context better than another formal context. -
Logics from Galois Connections
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector International Journal of Approximate Reasoning 49 (2008) 595–606 Contents lists available at ScienceDirect International Journal of Approximate Reasoning journal homepage: www.elsevier.com/locate/ijar Logics from Galois connections Jouni Järvinen a,*, Michiro Kondo b, Jari Kortelainen c a Turku Centre for Computer Science (TUCS), University of Turku, FI-20014 Turku, Finland b School of Information Environment, Tokyo Denki University, Inzai 270-1382, Japan c Mikkeli University of Applied Sciences, P.O. Box 181, FI-50101 Mikkeli, Finland article info abstract Article history: In this paper, Information Logic of Galois Connections (ILGC) suited for approximate rea- Received 13 June 2007 soning about knowledge is introduced. In addition to the three classical propositional logic Received in revised form 29 May 2008 axioms and the inference rule of modus ponens, ILGC contains only two auxiliary rules of Accepted 16 June 2008 inference mimicking the performance of Galois connections of lattice theory, and this Available online 27 June 2008 makes ILGC comfortable to use due to the flip-flop property of the modal connectives. Kripke-style semantics based on information relations is defined for ILGC. It is also shown that ILGC is equivalent to the minimal tense logic K , and decidability and completeness of Keywords: t ILGC follow from this observation. Additionally, relationship of ILGC to the so-called clas- Rough sets Fuzzy sets sical modal logics is studied. Namely, a certain composition of Galois connection mappings Approximate reasoning forms a lattice-theoretical interior operator, and this motivates us to axiomatize a logic of Knowledge representation these compositions. -
A Galois Connection Calculus for Abstract Interpretation∗
A Galois Connection Calculus for Abstract Interpretation⇤ Patrick Cousot Radhia Cousot CIMS⇤⇤, NYU, USA [email protected] CNRS Emeritus, ENS, France s [email protected] rfru Abstract We introduce a Galois connection calculus for language independent 3. Basic GC semantics Basic GCs are primitive abstractions of specification of abstract interpretations used in programming language semantics, properties. Classical examples are the identity abstraction 1[ , formal verification, and static analysis. This Galois connection calculus and its type λ Q . Q S hC system are typed by abstract interpretation. ] , , , , the top abstraction [ , vi hC vi −− − λ − −P − − −. − −P !−!− − hC vi S > hC Categories and Subject Descriptors D.2.4 [Software/Program Verification] λ Q . J General Terms Algorithms, Languages, Reliability, Security, Theory, Verification. , ] , , > , , the join abstraction [C] vi K> hC vi −−−−−λ P . hC vi S J[ Keywords Abstract Interpretation, Galois connection, Static Analysis, Verification. −−−−−!γ} > }(}(C)), }(C), with ↵}(P ) P , γ}(Q) In Abstract , } , , 1. Galois connections in Abstract Interpretation h K ✓i −−! −−↵ h ✓i J K interpretation [3, 4, 6, 7] concrete properties (for example (e.g.) }(Q), the complement abstraction [C] , }(SC), ¬ of computations) are related to abstract properties (e.g. types). The S ¬ h ✓i −−! −¬ }(C), , the finite/infinite sequence abstraction [C] , abstract properties are always sound approximations of the con- h ◆i γ S 1 1 J K crete properties (abstract proofs/static analyzes are always correct }(C1), }(C), with ↵1(P ) , σi σ P i h ✓i ↵ −1 −− h ✓i { | 2 ^ 2 in the concrete) and are sometimes complete (proofs/analyzes of −− − −! J K dom(σ) and γ1(Q) , σ C1 i dom(σ):σi Q , the abstract properties can all be done in the abstract only). -
A General Account of Coinduction Up-To Filippo Bonchi, Daniela Petrişan, Damien Pous, Jurriaan Rot
A General Account of Coinduction Up-To Filippo Bonchi, Daniela Petrişan, Damien Pous, Jurriaan Rot To cite this version: Filippo Bonchi, Daniela Petrişan, Damien Pous, Jurriaan Rot. A General Account of Coinduction Up-To. Acta Informatica, Springer Verlag, 2016, 10.1007/s00236-016-0271-4. hal-01442724 HAL Id: hal-01442724 https://hal.archives-ouvertes.fr/hal-01442724 Submitted on 20 Jan 2017 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. A General Account of Coinduction Up-To ∗ Filippo Bonchi Daniela Petrişan Damien Pous Jurriaan Rot May 2016 Abstract Bisimulation up-to enhances the coinductive proof method for bisimilarity, providing efficient proof techniques for checking properties of different kinds of systems. We prove the soundness of such techniques in a fibrational setting, building on the seminal work of Hermida and Jacobs. This allows us to systematically obtain up-to techniques not only for bisimilarity but for a large class of coinductive predicates modeled as coalgebras. The fact that bisimulations up to context can be safely used in any language specified by GSOS rules can also be seen as an instance of our framework, using the well-known observation by Turi and Plotkin that such languages form bialgebras. -
Introduction to Relations
CHAPTER 7 Introduction to Relations 1. Relations and Their Properties 1.1. Definition of a Relation. Definition:A binary relation from a set A to a set B is a subset R ⊆ A × B: If (a; b) 2 R we say a is related to b by R. A is the domain of R, and B is the codomain of R. If A = B, R is called a binary relation on the set A. Notation: • If (a; b) 2 R, then we write aRb. • If (a; b) 62 R, then we write aR6 b. Discussion Notice that a relation is simply a subset of A × B. If (a; b) 2 R, where R is some relation from A to B, we think of a as being assigned to b. In these senses students often associate relations with functions. In fact, a function is a special case of a relation as you will see in Example 1.2.4. Be warned, however, that a relation may differ from a function in two possible ways. If R is an arbitrary relation from A to B, then • it is possible to have both (a; b) 2 R and (a; b0) 2 R, where b0 6= b; that is, an element in A could be related to any number of elements of B; or • it is possible to have some element a in A that is not related to any element in B at all. 204 1. RELATIONS AND THEIR PROPERTIES 205 Often the relations in our examples do have special properties, but be careful not to assume that a given relation must have any of these properties. -
The Galois Correspondence Between a Ring and Its Spectrum
THE GALOIS CORRESPONDENCE BETWEEN A RING AND ITS SPECTRUM Let A and X be two sets equipped with a relation R ⊆ A × X. The notation is intended to remind you of the case where A is a commutative ring, X is its spectrum Spec A, and R is given by (f; x) 2 R () f(x) = 0 (i.e., f 2 px): But mathematics is full of other examples, including Galois theory (which is where the phrase \Galois correspondence" in the title comes from). For any subset S ⊆ A, define S0 ⊆ X by S0 := fx 2 X j (f; x) 2 R for all f 2 Sg : Similarly, for any subset Y ⊆ X, define Y 0 ⊆ A by Y 0 := ff 2 A j (f; x) 2 R for all x 2 Y g : In our canonical example, S0 = V (S) (the \zero set" of S), and Y 0 = I(Y ) := T 0 y2Y py. In more intuitive language, Y is the ideal of functions that vanish on Y . These \prime" operations are order reversing: S ⊆ T =) T 0 ⊆ S0; and similarly for subsets of X. Any subset of X of the form S0 will be called closed. (This gives the Zariski topology in our canonical example.) Similarly, any subset of A of the form Y 0 will be called closed. (So the closed subsets of A are the radical ideals in our canonical example.) Note that we always have S ⊆ S00 and Y ⊆ Y 00 for S ⊆ A and Y ⊆ X. I claim that equality holds for closed sets. -
Galois Connections
1 Galois Connections Roland Backhouse 3rd December, 2002 2 Fusion Many problems are expressed in the form evaluate generate ◦ where generate generates a (possibly infinite) candidate set of solutions, and evaluate selects a best solution. Examples: shortest path ; ◦ (x ) L: 2 ◦ Solution method is to fuse the generation and evaluation processes, eliminating the need to generate all candidate solutions. 3 Conditions for Fusion Fusion is made possible when evaluate is an adjoint in a Galois connection, • generate is expressed as a fixed point. • Solution method typically involves generalising the problem. 4 Definition Suppose = (A; ) and = (B; ) are partially ordered sets and A v B suppose F A B and G B A . Then (F;G) is a Galois connection 2 2 of and iff, for all x B and y A, A B 2 2 F:x y x G:y : v ≡ F is called the lower adjoint. G is the upper adjoint. 5 Examples | Propositional Calculus :p q p :q ≡ p ^ q r q (p r) ) ≡ ( p _ q r (p r) ^ (q r) ) ≡ ) ) p q _ r p ^ :q r ) ≡ ) ) ) ) Examples | Set Theory :S T S :T ⊆ ≡ ⊇ S T U T :S U \ ⊆ ≡ ⊆ [ S T U S U ^ T U [ ⊆ ≡ ⊆ ⊆ S T U S :T U ⊆ [ ≡ \ ⊆ 6 Examples | Number Theory -x y x -y ≤ ≡ ≥ x+y z y z-x ≤ ≡ ≤ x n x n d e ≤ ≡ ≤ x y z x z ^ y z ≤ ≡ ≤ ≤ x y z x z=y for all y > 0 ×" ≤ ≡ ≤ 7 Examples | predicates even:m b (if b then 2 else 1) n m ≡ odd:m b (if b then 1 else 2) n m ( ≡ x S b S if b then fxg else φ 2 ) ≡ ⊇ x S b S if b then U else Unfxg 2 ( ≡ ⊆ S = φ b S if b then φ else U ) ≡ ⊆ S = φ b S if b then U else φ 6 ( ≡ ⊆ ) 8 Examples | programming algebra Languages ("factors") L M N L N=M · ⊆ ≡ -
An Algebraic Theory of Complexity for Discrete Optimization Davis Cohen, Martin Cooper, Paidi Creed, Peter Jeavons, Stanislas Zivny
An Algebraic Theory of Complexity for Discrete Optimization Davis Cohen, Martin Cooper, Paidi Creed, Peter Jeavons, Stanislas Zivny To cite this version: Davis Cohen, Martin Cooper, Paidi Creed, Peter Jeavons, Stanislas Zivny. An Algebraic Theory of Complexity for Discrete Optimization. SIAM Journal on Computing, Society for Industrial and Applied Mathematics, 2013, vol. 42 (n° 5), pp. 1915-1939. 10.1137/130906398. hal-01122748 HAL Id: hal-01122748 https://hal.archives-ouvertes.fr/hal-01122748 Submitted on 4 Mar 2015 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. Open Archive TOULOUSE Archive Ouverte (OATAO) OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 12741 To link to this article : DOI :10.1137/130906398 URL : http://dx.doi.org/10.1137/130906398 To cite this version : Cohen, Davis and Cooper, Martin C. and Creed, Paidi and Jeavons, Peter and Zivny, Stanislas An Algebraic Theory of Complexity for Discrete Optimization. (2013) SIAM Journal on Computing, vol. 42 (n° 5). -
Constructive Galois Connections
ZU064-05-FPR main 23 July 2018 12:36 1 Constructive Galois Connections DAVID DARAIS University of Vermont, USA (e-mail: [email protected]) DAVID VAN HORN University of Maryland, College Park, USA (e-mail: [email protected]) Abstract Galois connections are a foundational tool for structuring abstraction in semantics and their use lies at the heart of the theory of abstract interpretation. Yet, mechanization of Galois connections using proof assistants remains limited to restricted modes of use, preventing their general application in mechanized metatheory and certified programming. This paper presents constructive Galois connections, a variant of Galois connections that is effective both on paper and in proof assistants; is complete with respect toa large subset of classical Galois connections; and enables more general reasoning principles, including the “calculational” style advocated by Cousot. To design constructive Galois connections we identify a restricted mode of use of classical ones which is both general and amenable to mechanization in dependently-typed functional programming languages. Crucial to our metatheory is the addition of monadic structure to Galois connections to control a “specification effect.” Effectful calculations may reason classically, while pure calculations have extractable computational content. Explicitly moving between the worlds of specification and implementation is enabled by our metatheory. To validate our approach, we provide two case studies in mechanizing existing proofs from the literature: the first uses calculational abstract interpretation to design a static analyzer; the second forms a semantic basis for gradual typing. Both mechanized proofs closely follow their original paper-and-pencil counterparts, employ reasoning principles arXiv:1807.08711v1 [cs.PL] 23 Jul 2018 not captured by previous mechanization approaches, support the extraction of verified algorithms, and are novel. -
From Peirce's Algebra of Relations to Tarski's Calculus of Relations
The Origin of Relation Algebras in the Development and Axiomatization of the Calculus of Relations Author(s): Roger D. Maddux Source: Studia Logica: An International Journal for Symbolic Logic, Vol. 50, No. 3/4, Algebraic Logic (1991), pp. 421-455 Published by: Springer Stable URL: http://www.jstor.org/stable/20015596 Accessed: 02/03/2009 14:54 Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/action/showPublisher?publisherCode=springer. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit organization founded in 1995 to build trusted digital archives for scholarship. We work with the scholarly community to preserve their work and the materials they rely upon, and to build a common research platform that promotes the discovery and use of these resources. For more information about JSTOR, please contact [email protected]. Springer is collaborating with JSTOR to digitize, preserve and extend access to Studia Logica: An International Journal for Symbolic Logic.