Equivalences of Determinacy Between Levels of the Borel Hierarchy and Long Games, and Some Generalizations
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Calibrating Determinacy Strength in Levels of the Borel Hierarchy
CALIBRATING DETERMINACY STRENGTH IN LEVELS OF THE BOREL HIERARCHY SHERWOOD J. HACHTMAN Abstract. We analyze the set-theoretic strength of determinacy for levels of the Borel 0 hierarchy of the form Σ1+α+3, for α < !1. Well-known results of H. Friedman and D.A. Martin have shown this determinacy to require α+1 iterations of the Power Set Axiom, but we ask what additional ambient set theory is strictly necessary. To this end, we isolate a family of Π1-reflection principles, Π1-RAPα, whose consistency strength corresponds 0 CK exactly to that of Σ1+α+3-Determinacy, for α < !1 . This yields a characterization of the levels of L by or at which winning strategies in these games must be constructed. When α = 0, we have the following concise result: the least θ so that all winning strategies 0 in Σ4 games belong to Lθ+1 is the least so that Lθ j= \P(!) exists + all wellfounded trees are ranked". x1. Introduction. Given a set A ⊆ !! of sequences of natural numbers, consider a game, G(A), where two players, I and II, take turns picking elements of a sequence hx0; x1; x2;::: i of naturals. Player I wins the game if the sequence obtained belongs to A; otherwise, II wins. For a collection Γ of subsets of !!, Γ determinacy, which we abbreviate Γ-DET, is the statement that for every A 2 Γ, one of the players has a winning strategy in G(A). It is a much-studied phenomenon that Γ -DET has mathematical strength: the bigger the pointclass Γ, the stronger the theory required to prove Γ -DET. -
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. -
Topology and Descriptive Set Theory
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector TOPOLOGY AND ITS APPLICATIONS ELSEVIER Topology and its Applications 58 (1994) 195-222 Topology and descriptive set theory Alexander S. Kechris ’ Department of Mathematics, California Institute of Technology, Pasadena, CA 91125, USA Received 28 March 1994 Abstract This paper consists essentially of the text of a series of four lectures given by the author in the Summer Conference on General Topology and Applications, Amsterdam, August 1994. Instead of attempting to give a general survey of the interrelationships between the two subjects mentioned in the title, which would be an enormous and hopeless task, we chose to illustrate them in a specific context, that of the study of Bore1 actions of Polish groups and Bore1 equivalence relations. This is a rapidly growing area of research of much current interest, which has interesting connections not only with topology and set theory (which are emphasized here), but also to ergodic theory, group representations, operator algebras and logic (particularly model theory and recursion theory). There are four parts, corresponding roughly to each one of the lectures. The first contains a brief review of some fundamental facts from descriptive set theory. In the second we discuss Polish groups, and in the third the basic theory of their Bore1 actions. The last part concentrates on Bore1 equivalence relations. The exposition is essentially self-contained, but proofs, when included at all, are often given in the barest outline. Keywords: Polish spaces; Bore1 sets; Analytic sets; Polish groups; Bore1 actions; Bore1 equivalence relations 1. -
Abstract Determinacy in the Low Levels of The
ABSTRACT DETERMINACY IN THE LOW LEVELS OF THE PROJECTIVE HIERARCHY by Michael R. Cotton We give an expository introduction to determinacy for sets of reals. If we are to assume the Axiom of Choice, then not all sets of reals can be determined. So we instead establish determinacy for sets according to their levels in the usual hierarchies of complexity. At a certain point ZFC is no longer strong enough, and we must begin to assume large cardinals. The primary results of this paper are Martin's theorems that Borel sets are determined, homogeneously Suslin sets are determined, and if a measurable cardinal κ exists then the complements of analytic sets are κ-homogeneously Suslin. We provide the necessary preliminaries, prove Borel determinacy, introduce measurable cardinals and ultrapowers, and then prove analytic determinacy from the existence of a measurable cardinal. Finally, we give a very brief overview of some further results which provide higher levels of determinacy relative to larger cardinals. DETERMINACY IN THE LOW LEVELS OF THE PROJECTIVE HIERARCHY A Thesis Submitted to the Faculty of Miami University in partial fulfillment of the requirements for the degree of Master of Arts Department of Mathematics by Michael R. Cotton Miami University Oxford, Ohio 2012 Advisor: Dr. Paul Larson Reader: Dr. Dennis K. Burke Reader: Dr. Tetsuya Ishiu Contents Introduction 1 0.1 Some notation and conventions . 2 1 Reals, trees, and determinacy 3 1.1 The reals as !! .............................. 3 1.2 Determinacy . 5 1.3 Borel sets . 8 1.4 Projective sets . 10 1.5 Tree representations . 12 2 Borel determinacy 14 2.1 Games with a tree of legal positions . -
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. -
MS Word Template for CAD Conference Papers
382 Title: Regularized Set Operations in Solid Modeling Revisited Authors: K. M. Yu, [email protected], The Hong Kong Polytechnic University K. M. Lee, [email protected], The Hong Kong Polytechnic University K. M. Au, [email protected], HKU SPACE Community College Keywords: Regularised Set Operations, CSG, Solid Modeling, Manufacturing, General Topology DOI: 10.14733/cadconfP.2019.382-386 Introduction: The seminal works of Tilove and Requicha [8],[13],[14] first introduced the use of general topology concepts in solid modeling. However, their works are brute-force approach from mathematicians’ perspective and are not easy to be comprehended by engineering trained personnels. This paper reviewed the point set topological approach using operational formulation. Essential topological concepts are described and visualized in easy to understand directed graphs. These facilitate subtle differentiation of key concepts to be recognized. In particular, some results are restated in a more mathematically correct version. Examples to use the prefix unary operators are demonstrated in solid modeling properties derivations and proofs as well as engineering applications. Main Idea: This paper is motivated by confusion in the use of mathematical terms like boundedness, boundary, interior, open set, exterior, complement, closed set, closure, regular set, etc. Hasse diagrams are drawn by mathematicians to study different topologies. Instead, directed graph using elementary operators of closure and complement are drawn to show their inter-relationship in the Euclidean three- dimensional space (E^3 is a special metric space formed from Cartesian product R^3 with Euclid’s postulates [11] and inheriting all general topology properties.) In mathematics, regular, regular open and regular closed are similar but different concepts. -
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. -
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. -
A Concise Form of Continuity in Fine Topological Space
Advances in Computational Sciences and Technology (ACST). ISSN 0973-6107 Volume 10, Number 6 (2017), pp. 1785–1805 © Research India Publications http://www.ripublication.com/acst.htm A Concise form of Continuity in Fine Topological Space P.L. Powar and Pratibha Dubey Department of Mathematics and Computer Science, R.D.V.V., Jabalpur, India. Abstract By using the topology on a space X, a wide class of sets called fine open sets have been studied earlier. In the present paper, it has been noticed and verified that the class of fine open sets contains the entire class of A-sets, AC-sets and αAB-sets, which are already defined. Further, this observation leads to define a more general continuous function which in tern reduces to the four continuous functions namely A-continuity, AB-continuity, AC-continuity and αAB-continuity as special cases. AMS subject classification: primary54XX; secondry 54CXX. Keywords: fine αAB-sets, fine A-sets, fine topology. 1. Introduction The concept of fine space has been introduced by Powar and Rajak in [1] is the special case of generalized topological space (see[2]). The major difference between the two spaces is that the open sets in the fine space are not the random collection of subsets of X satisfying certain conditions but the open sets (known as fine sets) have been generated with the help of topology already defined over X. It has been studied in [1] that this collection of fine open sets is really a magical class of subsets of X containing semi-open sets, pre-open sets, α-open sets, β-open sets etc.