On the Complexity of the Relations of Isomorphism and Bi-Embeddability
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Set Theory, Including the Axiom of Choice) Plus the Negation of CH
ANNALS OF ~,IATltEMATICAL LOGIC - Volume 2, No. 2 (1970) pp. 143--178 INTERNAL COHEN EXTENSIONS D.A.MARTIN and R.M.SOLOVAY ;Tte RockeJ~'ller University and University (.~t CatiJbrnia. Berkeley Received 2 l)ecemt)er 1969 Introduction Cohen [ !, 2] has shown that tile continuum hypothesis (CH) cannot be proved in Zermelo-Fraenkel set theory. Levy and Solovay [9] have subsequently shown that CH cannot be proved even if one assumes the existence of a measurable cardinal. Their argument in tact shows that no large cardinal axiom of the kind present;y being considered by set theorists can yield a proof of CH (or of its negation, of course). Indeed, many set theorists - including the authors - suspect that C1t is false. But if we reject CH we admit Gurselves to be in a state of ignorance about a great many questions which CH resolves. While CH is a power- full assertion, its negation is in many ways quite weak. Sierpinski [ 1 5 ] deduces propcsitions there called C l - C82 from CH. We know of none of these propositions which is decided by the negation of CH and only one of them (C78) which is decided if one assumes in addition that a measurable cardinal exists. Among the many simple questions easily decided by CH and which cannot be decided in ZF (Zerme!o-Fraenkel set theory, including the axiom of choice) plus the negation of CH are tile following: Is every set of real numbers of cardinality less than tha't of the continuum of Lebesgue measure zero'? Is 2 ~0 < 2 ~ 1 ? Is there a non-trivial measure defined on all sets of real numbers? CIhis third question could be decided in ZF + not CH only in the unlikely event t Tile second author received support from a Sloan Foundation fellowship and tile National Science Foundation Grant (GP-8746). -
Lecture Notes
MEASURE THEORY AND STOCHASTIC PROCESSES Lecture Notes José Melo, Susana Cruz Faculdade de Engenharia da Universidade do Porto Programa Doutoral em Engenharia Electrotécnica e de Computadores March 2011 Contents 1 Probability Space3 1 Sample space Ω .....................................4 2 σ-eld F .........................................4 3 Probability Measure P .................................6 3.1 Measure µ ....................................6 3.2 Probability Measure P .............................7 4 Learning Objectives..................................7 5 Appendix........................................8 2 Chapter 1 Probability Space Let's consider the experience of throwing a dart on a circular target with radius r (assuming the dart always hits the target), divided in 4 dierent areas as illustrated in Figure 1.1. 4 3 2 1 Figure 1.1: Circular Target The circles that bound the regions 1, 2, 3, and 4, have radius of, respectively, r , r , 3r , and . 4 2 4 r Therefore, the probability that a dart lands in each region is: 1 , 3 , 5 , P (1) = 16 P (2) = 16 P (3) = 16 7 . P (4) = 16 For this kind of problems, the theory of discrete probability spaces suces. However, when it comes to problems involving either an innitely repeated operation or an innitely ne op- eration, this mathematical framework does not apply. This motivates the introduction of a measure-theoretic probability approach to correctly describe those cases. We dene the proba- bility space (Ω; F;P ), where Ω is the sample space, F is the event space, and P is the probability 3 measure. Each of them will be described in the following subsections. 1 Sample space Ω The sample space Ω is the set of all the possible results or outcomes ! of an experiment or observation. -
Borel Structure in Groups and Their Dualso
BOREL STRUCTURE IN GROUPS AND THEIR DUALSO GEORGE W. MACKEY Introduction. In the past decade or so much work has been done toward extending the classical theory of finite dimensional representations of com- pact groups to a theory of (not necessarily finite dimensional) unitary repre- sentations of locally compact groups. Among the obstacles interfering with various aspects of this program is the lack of a suitable natural topology in the "dual object"; that is in the set of equivalence classes of irreducible representations. One can introduce natural topologies but none of them seem to have reasonable properties except in extremely special cases. When the group is abelian for example the dual object itself is a locally compact abelian group. This paper is based on the observation that for certain purposes one can dispense with a topology in the dual object in favor of a "weaker struc- ture" and that there is a wide class of groups for which this weaker structure has very regular properties. If .S is any topological space one defines a Borel (or Baire) subset of 5 to be a member of the smallest family of subsets of 5 which includes the open sets and is closed with respect to the formation of complements and countable unions. The structure defined in 5 by its Borel sets we may call the Borel structure of 5. It is weaker than the topological structure in the sense that any one-to-one transformation of S onto 5 which preserves the topological structure also preserves the Borel structure whereas the converse is usually false. -
Relations-Handoutnonotes.Pdf
Introduction Relations Recall that a relation between elements of two sets is a subset of their Cartesian product (of ordered pairs). Slides by Christopher M. Bourke Instructor: Berthe Y. Choueiry Definition A binary relation from a set A to a set B is a subset R ⊆ A × B = {(a, b) | a ∈ A, b ∈ B} Spring 2006 Note the difference between a relation and a function: in a relation, each a ∈ A can map to multiple elements in B. Thus, Computer Science & Engineering 235 relations are generalizations of functions. Introduction to Discrete Mathematics Sections 7.1, 7.3–7.5 of Rosen If an ordered pair (a, b) ∈ R then we say that a is related to b. We [email protected] may also use the notation aRb and aRb6 . Relations Relations Graphical View To represent a relation, you can enumerate every element in R. A B Example a1 b1 a Let A = {a1, a2, a3, a4, a5} and B = {b1, b2, b3} let R be a 2 relation from A to B as follows: a3 b2 R = {(a1, b1), (a1, b2), (a1, b3), (a2, b1), a4 (a3, b1), (a3, b2), (a3, b3), (a5, b1)} b3 a5 You can also represent this relation graphically. Figure: Graphical Representation of a Relation Relations Reflexivity On a Set Definition Definition A relation on the set A is a relation from A to A. I.e. a subset of A × A. There are several properties of relations that we will look at. If the ordered pairs (a, a) appear in a relation on a set A for every a ∈ A Example then it is called reflexive. -
STAT 571 Assignment 1 Solutions 1. If Ω Is a Set and C a Collection Of
STAT 571 Assignment 1 solutions 1. If Ω is a set and a collection of subsets of Ω, let be the intersection of all σ-algebras that contain . ProveC that is the σ-algebra generatedA by . C A C Solution: Let α α A be the collection of all σ-algebras that contain , and fA j 2 g C set = α. We first show that is a σ-algebra. There are three things to A \ A A α A prove. 2 (a) For every α A, α is a σ-algebra, so Ω α, and hence Ω α A α = . 2 A 2 A 2 \ 2 A A (b) If B , then B α for every α A. Since α is a σ-algebra, we have c 2 A 2 A 2 A c B α. But this is true for every α A, so we have B . 2 A 2 2 A (c) If B1;B2;::: are sets in , then B1;B2;::: belong to α for each α A. A A 2 Since α is a σ-algebra, we have 1 Bn α. But this is true for every A [n=1 2 A α A, so we have 1 Bn . 2 [n=1 2 A Thus is a σ-algebra that contains , and it must be the smallest one since α for everyA α A. C A ⊆ A 2 2. Prove that the set of rational numbers Q is a Borel set in R. Solution: For every x R, the set x is the complement of an open set, and hence Borel. -
(Measure Theory for Dummies) UWEE Technical Report Number UWEETR-2006-0008
A Measure Theory Tutorial (Measure Theory for Dummies) Maya R. Gupta {gupta}@ee.washington.edu Dept of EE, University of Washington Seattle WA, 98195-2500 UWEE Technical Report Number UWEETR-2006-0008 May 2006 Department of Electrical Engineering University of Washington Box 352500 Seattle, Washington 98195-2500 PHN: (206) 543-2150 FAX: (206) 543-3842 URL: http://www.ee.washington.edu A Measure Theory Tutorial (Measure Theory for Dummies) Maya R. Gupta {gupta}@ee.washington.edu Dept of EE, University of Washington Seattle WA, 98195-2500 University of Washington, Dept. of EE, UWEETR-2006-0008 May 2006 Abstract This tutorial is an informal introduction to measure theory for people who are interested in reading papers that use measure theory. The tutorial assumes one has had at least a year of college-level calculus, some graduate level exposure to random processes, and familiarity with terms like “closed” and “open.” The focus is on the terms and ideas relevant to applied probability and information theory. There are no proofs and no exercises. Measure theory is a bit like grammar, many people communicate clearly without worrying about all the details, but the details do exist and for good reasons. There are a number of great texts that do measure theory justice. This is not one of them. Rather this is a hack way to get the basic ideas down so you can read through research papers and follow what’s going on. Hopefully, you’ll get curious and excited enough about the details to check out some of the references for a deeper understanding. -
On the Satisfiability Problem for Fragments of the Two-Variable Logic
ON THE SATISFIABILITY PROBLEM FOR FRAGMENTS OF TWO-VARIABLE LOGIC WITH ONE TRANSITIVE RELATION WIESLAW SZWAST∗ AND LIDIA TENDERA Abstract. We study the satisfiability problem for two-variable first- order logic over structures with one transitive relation. We show that the problem is decidable in 2-NExpTime for the fragment consisting of formulas where existential quantifiers are guarded by transitive atoms. As this fragment enjoys neither the finite model property nor the tree model property, to show decidability we introduce a novel model con- struction technique based on the infinite Ramsey theorem. We also point out why the technique is not sufficient to obtain decid- ability for the full two-variable logic with one transitive relation, hence contrary to our previous claim, [FO2 with one transitive relation is de- cidable, STACS 2013: 317-328], the status of the latter problem remains open. 1. Introduction The two-variable fragment of first-order logic, FO2, is the restriction of classical first-order logic over relational signatures to formulas with at most two variables. It is well-known that FO2 enjoys the finite model prop- erty [23], and its satisfiability (hence also finite satisfiability) problem is NExpTime-complete [7]. One drawback of FO2 is that it can neither express transitivity of a bi- nary relation nor say that a binary relation is a partial (or linear) order, or an equivalence relation. These natural properties are important for prac- arXiv:1804.09447v3 [cs.LO] 9 Apr 2019 tical applications, thus attempts have been made to investigate FO2 over restricted classes of structures in which some distinguished binary symbols are required to be interpreted as transitive relations, orders, equivalences, etc. -
Math 475 Homework #3 March 1, 2010 Section 4.6
Student: Yu Cheng (Jade) Math 475 Homework #3 March 1, 2010 Section 4.6 Exercise 36-a Let ͒ be a set of ͢ elements. How many different relations on ͒ are there? Answer: On set ͒ with ͢ elements, we have the following facts. ) Number of two different element pairs ƳͦƷ Number of relations on two different elements ) ʚ͕, ͖ʛ ∈ ͌, ʚ͖, ͕ʛ ∈ ͌ 2 Ɛ ƳͦƷ Number of relations including the reflexive ones ) ʚ͕, ͕ʛ ∈ ͌ 2 Ɛ ƳͦƷ ƍ ͢ ġ Number of ways to select these relations to form a relation on ͒ 2ͦƐƳvƷͮ) ͦƐ)! ġ ͮ) ʚ ʛ v 2ͦƐƳvƷͮ) Ɣ 2ʚ)ͯͦʛ!Ɛͦ Ɣ 2) )ͯͥ ͮ) Ɣ 2) . b. How many of these relations are reflexive? Answer: We still have ) number of relations on element pairs to choose from, but we have to 2 Ɛ ƳͦƷ ƍ ͢ include the reflexive one, ʚ͕, ͕ʛ ∈ ͌. There are ͢ relations of this kind. Therefore there are ͦƐ)! ġ ġ ʚ ʛ 2ƳͦƐƳvƷͮ)Ʒͯ) Ɣ 2ͦƐƳvƷ Ɣ 2ʚ)ͯͦʛ!Ɛͦ Ɣ 2) )ͯͥ . c. How many of these relations are symmetric? Answer: To select only the symmetric relations on set ͒ with ͢ elements, we have the following facts. ) Number of symmetric relation pairs between two elements ƳͦƷ Number of relations including the reflexive ones ) ʚ͕, ͕ʛ ∈ ͌ ƳͦƷ ƍ ͢ ġ Number of ways to select these relations to form a relation on ͒ 2ƳvƷͮ) )! )ʚ)ͯͥʛ )ʚ)ͮͥʛ ġ ͮ) ͮ) 2ƳvƷͮ) Ɣ 2ʚ)ͯͦʛ!Ɛͦ Ɣ 2 ͦ Ɣ 2 ͦ . d. -
PROBLEM SET THREE: RELATIONS and FUNCTIONS Problem 1
PROBLEM SET THREE: RELATIONS AND FUNCTIONS Problem 1 a. Prove that the composition of two bijections is a bijection. b. Prove that the inverse of a bijection is a bijection. c. Let U be a set and R the binary relation on ℘(U) such that, for any two subsets of U, A and B, ARB iff there is a bijection from A to B. Prove that R is an equivalence relation. Problem 2 Let A be a fixed set. In this question “relation” means “binary relation on A.” Prove that: a. The intersection of two transitive relations is a transitive relation. b. The intersection of two symmetric relations is a symmetric relation, c. The intersection of two reflexive relations is a reflexive relation. d. The intersection of two equivalence relations is an equivalence relation. Problem 3 Background. For any binary relation R on a set A, the symmetric interior of R, written Sym(R), is defined to be the relation R ∩ R−1. For example, if R is the relation that holds between a pair of people when the first respects the other, then Sym(R) is the relation of mutual respect. Another example: if R is the entailment relation on propositions (the meanings expressed by utterances of declarative sentences), then the symmetric interior is truth- conditional equivalence. Prove that the symmetric interior of a preorder is an equivalence relation. Problem 4 Background. If v is a preorder, then Sym(v) is called the equivalence rela- tion induced by v and written ≡v, or just ≡ if it’s clear from the context which preorder is under discussion. -
Probability Measures on Metric Spaces
Probability measures on metric spaces Onno van Gaans These are some loose notes supporting the first sessions of the seminar Stochastic Evolution Equations organized by Dr. Jan van Neerven at the Delft University of Technology during Winter 2002/2003. They contain less information than the common textbooks on the topic of the title. Their purpose is to present a brief selection of the theory that provides a basis for later study of stochastic evolution equations in Banach spaces. The notes aim at an audience that feels more at ease in analysis than in probability theory. The main focus is on Prokhorov's theorem, which serves both as an important tool for future use and as an illustration of techniques that play a role in the theory. The field of measures on topological spaces has the luxury of several excellent textbooks. The main source that has been used to prepare these notes is the book by Parthasarathy [6]. A clear exposition is also available in one of Bour- baki's volumes [2] and in [9, Section 3.2]. The theory on the Prokhorov metric is taken from Billingsley [1]. The additional references for standard facts on general measure theory and general topology have been Halmos [4] and Kelley [5]. Contents 1 Borel sets 2 2 Borel probability measures 3 3 Weak convergence of measures 6 4 The Prokhorov metric 9 5 Prokhorov's theorem 13 6 Riesz representation theorem 18 7 Riesz representation for non-compact spaces 21 8 Integrable functions on metric spaces 24 9 More properties of the space of probability measures 26 1 The distribution of a random variable in a Banach space X will be a probability measure on X. -
Descriptive Set Theory
Descriptive Set Theory David Marker Fall 2002 Contents I Classical Descriptive Set Theory 2 1 Polish Spaces 2 2 Borel Sets 14 3 E®ective Descriptive Set Theory: The Arithmetic Hierarchy 27 4 Analytic Sets 34 5 Coanalytic Sets 43 6 Determinacy 54 7 Hyperarithmetic Sets 62 II Borel Equivalence Relations 73 1 8 ¦1-Equivalence Relations 73 9 Tame Borel Equivalence Relations 82 10 Countable Borel Equivalence Relations 87 11 Hyper¯nite Equivalence Relations 92 1 These are informal notes for a course in Descriptive Set Theory given at the University of Illinois at Chicago in Fall 2002. While I hope to give a fairly broad survey of the subject we will be concentrating on problems about group actions, particularly those motivated by Vaught's conjecture. Kechris' Classical Descriptive Set Theory is the main reference for these notes. Notation: If A is a set, A<! is the set of all ¯nite sequences from A. Suppose <! σ = (a0; : : : ; am) 2 A and b 2 A. Then σ b is the sequence (a0; : : : ; am; b). We let ; denote the empty sequence. If σ 2 A<!, then jσj is the length of σ. If f : N ! A, then fjn is the sequence (f(0); : : :b; f(n ¡ 1)). If X is any set, P(X), the power set of X is the set of all subsets X. If X is a metric space, x 2 X and ² > 0, then B²(x) = fy 2 X : d(x; y) < ²g is the open ball of radius ² around x. Part I Classical Descriptive Set Theory 1 Polish Spaces De¯nition 1.1 Let X be a topological space. -
Relations April 4
math 55 - Relations April 4 Relations Let A and B be two sets. A (binary) relation on A and B is a subset R ⊂ A × B. We often write aRb to mean (a; b) 2 R. The following are properties of relations on a set S (where above A = S and B = S are taken to be the same set S): 1. Reflexive: (a; a) 2 R for all a 2 S. 2. Symmetric: (a; b) 2 R () (b; a) 2 R for all a; b 2 S. 3. Antisymmetric: (a; b) 2 R and (b; a) 2 R =) a = b. 4. Transitive: (a; b) 2 R and (b; c) 2 R =) (a; c) 2 R for all a; b; c 2 S. Exercises For each of the following relations, which of the above properties do they have? 1. Let R be the relation on Z+ defined by R = f(a; b) j a divides bg. Reflexive, antisymmetric, and transitive 2. Let R be the relation on Z defined by R = f(a; b) j a ≡ b (mod 33)g. Reflexive, symmetric, and transitive 3. Let R be the relation on R defined by R = f(a; b) j a < bg. Symmetric and transitive 4. Let S be the set of all convergent sequences of rational numbers. Let R be the relation on S defined by f(a; b) j lim a = lim bg. Reflexive, symmetric, transitive 5. Let P be the set of all propositional statements. Let R be the relation on P defined by R = f(a; b) j a ! b is trueg.