An example of a capacity for which all positive Borel sets are thick
|
|
- Jemimah Janel King
- 7 years ago
- Views:
Transcription
1 An example of a capacity for which all positive Borel sets are thick Micha l Morayne, Szymon Żeberski Wroc law University of Technology Winter School in Abstract Analysis 2016 section Set Theory & Topology Jan 3 - Feb 6, 2016
2 Definition of Choquet s E-capacity on E Let E P(E) be any lattice, E. Choquet s E-capacity on E is any function c : P(E) [, ] such that: i. A B E implies c(a) c(b); ii. if A 1 A 2... is any ascending sequence of subsets of E, then lim n c(a n ) = c( n=1 A n); iii. if E 1 E 2... is any descending sequence of subsets from E, then lim n c(e n ) = c( n=1 E n).
3 Choquet s capacitability theorem For any set B from the σ-δ-lattice Ê (a family closed under countable unions and countable intersections) generated by the family E the capacity of B can be approximated from below by capacities of subsets of B which are elements of E.
4 Choquet s capacitability theorem For any set B from the σ-δ-lattice Ê (a family closed under countable unions and countable intersections) generated by the family E the capacity of B can be approximated from below by capacities of subsets of B which are elements of E. Definition of a thick set B Ê is called thick (with respect to a capacity c) if it contains uncountably many pairwise disjoint elements from Ê of positive capacity c
5 Examples of capacity X = R, λ : P(R) [0, ]
6 Examples of capacity X = R, λ : P(R) [0, ] X = [0, 1] ω 1, c : P(X ) {0, 1}, c(a) = 1 {α < ω 1 : A [0, 1] {α} } is uncountable
7 X is a Cantor cube, K(X ) is the family of all compact subsets of X, If E = K(X ) then Ê = B(X ) is the family of all Borel subsets of X.
8 X is a Cantor cube, K(X ) is the family of all compact subsets of X, If E = K(X ) then Ê = B(X ) is the family of all Borel subsets of X. We construct an example of a K(X )-capacity such that all Borel sets of positive capacity are thick.
9 Construction of a capacity µ - the standard probabilistic product measure on X Λ 1, Λ 2,... - a sequence of pairwise disjoint infinite subsets of N. Λ i = {n i,j : j N}, where j < k implies n i,j < n i,j.
10 Construction of a capacity µ - the standard probabilistic product measure on X Λ 1, Λ 2,... - a sequence of pairwise disjoint infinite subsets of N. Λ i = {n i,j : j N}, where j < k implies n i,j < n i,j. We will now define a family of perfect subsets of X, {C(ξ (1),..., ξ (n) ) : ξ (1),..., ξ (n) {0, 1} N, n N}. Let C( ) = X. For ξ (1),..., ξ (n) {0, 1} N we define C(ξ (1),..., ξ (n) ) as C(ξ (1),..., ξ (n) ) = k N D k, where D k = {ξ (i) j } if k = n i,j Λ i, i n, and D k = {0, 1} if k / i n Λ i. Let ν ξ (1),...,ξ (n) = η. k / i n Λ i
11 Let A C(ξ (1),..., ξ (n) ). Then A is of the form A = {ξ (i) j i n,j N } π Xn (A), where X n = k / i n Λ i {0, 1} and π Xn : X X n is a projection. Let A C(ξ (1),..., ξ (n) ) be a Borel set. Let µ ξ (1),...,ξ (n)(a) = ν ξ (1),...,ξ (n)(π X n (A)).
12 µ ξ (1),...,ξ (n) is a Borel measure on C(ξ(1),..., ξ (n) ). For A X let c(a) = sup { 1 n µ ξ (1),...,ξ (n) (A C(ξ (1),..., ξ (n) )) : ξ (1),..., ξ (n) {0, 1} N, n N }.
13 c(a) = sup { 1 n µ ξ (1),...,ξ (n) (A C(ξ (1),..., ξ (n) )) : ξ (1),..., ξ (n) {0, 1} N, n N }. Main Theorem The function c : P(X ) [0, 1] is non-negative Choquet s K(X )-capacity and if c(b) > 0, for a Borel subset B of X, then B contains continuuum many pairwise disjoint Borel subsets of positive capacity.
14 Proof. c is K(X )-Choquet s capacity. A B X implies c(a) c(b).
15 Proof. c is K(X )-Choquet s capacity. A B X implies c(a) c(b). For K 1 K 2... a sequence of compact subsets of X c( n=1 K n ) lim n c(k n).
16 Proof. c is K(X )-Choquet s capacity. A B X implies c(a) c(b). For K 1 K 2... a sequence of compact subsets of X c( n=1 K n ) lim n c(k n). If lim n c(k n ) = 0 we have c( n=1 K n) = lim n c(k n ).
17 Proof. c is K(X )-Choquet s capacity. A B X implies c(a) c(b). For K 1 K 2... a sequence of compact subsets of X c( n=1 K n ) lim n c(k n). If lim n c(k n ) = 0 we have c( n=1 K n) = lim n c(k n ). If lim n c(k n ) > 0, then there exists m N such that lim n 1 m µ ξ (1,n),...,ξ (m,n)(k n C(ξ (1,n),..., ξ (m,n) )) = lim n c(k n), for some ξ (1,n),..., ξ (m,n) {0, 1} N.
18 Proof. c is K(X )-Choquet s capacity... If lim n c(k n ) > 0, then there exists m N such that lim n 1 m µ ξ (1,n),...,ξ (m,n)(k n C(ξ (1,n),..., ξ (m,n) )) = lim n c(k n), for some ξ (1,n),..., ξ (m,n) {0, 1} N. Passing, if necessary, to a subsequence, we can assume that lim n (ξ(1,n),..., ξ (m,n) ) = (ξ (1),..., ξ (m) ).
19 Proof. c is K(X )-Choquet s capacity... If lim n c(k n ) > 0, then there exists m N such that lim n 1 m µ ξ (1,n),...,ξ (m,n)(k n C(ξ (1,n),..., ξ (m,n) )) = lim n c(k n), for some ξ (1,n),..., ξ (m,n) {0, 1} N. Passing, if necessary, to a subsequence, we can assume that lim n (ξ(1,n),..., ξ (m,n) ) = (ξ (1),..., ξ (m) ). For A 1 A 2... any subsets of X ( ) lim c(a n) = c A n. n n=1
20 Proof. Borel positive sets are thick. Now let B be any Borel subset of X such that c(b) > 0. Hence µ ξ (1),...,ξ (n)(b C(ξ(1),..., ξ (n) )) = = ν ξ (1),...,ξ (n)(π X n (B C(ξ (1),..., ξ (n) )) > 0, where X n = {0, 1} N. k / i n Λ i for some ξ (1),..., ξ (n) {0, 1} N and n N. We have ν ξ (1),...,ξ (n) = ν ξ (1),...,ξ (n) k Λ n+1 η.
21 Proof. Borel positive sets are thick... µ ξ (1),...,ξ (n),ξ (B C(ξ(1),..., ξ (n), ξ))) = = ν ξ (1),...,ξ,ξ(π (n) Xn+1 (B C(ξ (1),..., ξ (n), ξ)))d k Λ {0,1} N n+1 Thus the set of those ξ k Λ n+1 {0, 1} for which ν ξ (1),...,ξ (n),ξ (π X n+1 (B C(ξ (1),..., ξ (n), ξ))) > 0 has positive measure and hence also c(b C(ξ (1),..., ξ (n), ξ)) > 0, k Λ n+1 η must have positive measure and thus it must have cardinality c. (ξ).
22 Thank You for Your Attention!
MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES
MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES Contents 1. Random variables and measurable functions 2. Cumulative distribution functions 3. Discrete
More informationExtension of measure
1 Extension of measure Sayan Mukherjee Dynkin s π λ theorem We will soon need to define probability measures on infinite and possible uncountable sets, like the power set of the naturals. This is hard.
More information1. Prove that the empty set is a subset of every set.
1. Prove that the empty set is a subset of every set. Basic Topology Written by Men-Gen Tsai email: b89902089@ntu.edu.tw Proof: For any element x of the empty set, x is also an element of every set since
More informationCardinality. The set of all finite strings over the alphabet of lowercase letters is countable. The set of real numbers R is an uncountable set.
Section 2.5 Cardinality (another) Definition: The cardinality of a set A is equal to the cardinality of a set B, denoted A = B, if and only if there is a bijection from A to B. If there is an injection
More informationINTRODUCTION TO DESCRIPTIVE SET THEORY
INTRODUCTION TO DESCRIPTIVE SET THEORY ANUSH TSERUNYAN Mathematicians in the early 20 th century discovered that the Axiom of Choice implied the existence of pathological subsets of the real line lacking
More informationINTRODUCTORY SET THEORY
M.Sc. program in mathematics INTRODUCTORY SET THEORY Katalin Károlyi Department of Applied Analysis, Eötvös Loránd University H-1088 Budapest, Múzeum krt. 6-8. CONTENTS 1. SETS Set, equal sets, subset,
More informationLebesgue Measure on R n
8 CHAPTER 2 Lebesgue Measure on R n Our goal is to construct a notion of the volume, or Lebesgue measure, of rather general subsets of R n that reduces to the usual volume of elementary geometrical sets
More informationHow To Find Out How To Calculate A Premeasure On A Set Of Two-Dimensional Algebra
54 CHAPTER 5 Product Measures Given two measure spaces, we may construct a natural measure on their Cartesian product; the prototype is the construction of Lebesgue measure on R 2 as the product of Lebesgue
More informationDescriptive 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 Effective Descriptive Set Theory: The Arithmetic Hierarchy 27 4 Analytic
More informationSOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 3. Spaces with special properties
SOLUTIONS TO EXERCISES FOR MATHEMATICS 205A Part 3 Fall 2008 III. Spaces with special properties III.1 : Compact spaces I Problems from Munkres, 26, pp. 170 172 3. Show that a finite union of compact subspaces
More informationLecture Notes on Measure Theory and Functional Analysis
Lecture Notes on Measure Theory and Functional Analysis P. Cannarsa & T. D Aprile Dipartimento di Matematica Università di Roma Tor Vergata cannarsa@mat.uniroma2.it daprile@mat.uniroma2.it aa 2006/07 Contents
More informationElements of probability theory
2 Elements of probability theory Probability theory provides mathematical models for random phenomena, that is, phenomena which under repeated observations yield di erent outcomes that cannot be predicted
More informationMathematical Methods of Engineering Analysis
Mathematical Methods of Engineering Analysis Erhan Çinlar Robert J. Vanderbei February 2, 2000 Contents Sets and Functions 1 1 Sets................................... 1 Subsets.............................
More informationSOLVING POLYNOMIAL EQUATIONS
C SOLVING POLYNOMIAL EQUATIONS We will assume in this appendix that you know how to divide polynomials using long division and synthetic division. If you need to review those techniques, refer to an algebra
More informationNotes on descriptive set theory and applications to Banach spaces. Th. Schlumprecht
Notes on descriptive set theory and applications to Banach spaces Th. Schlumprecht Contents Chapter 1. Notation 5 Chapter 2. Polish spaces 7 1. Introduction 7 2. Transfer Theorems 9 3. Spaces of compact
More informationMEASURE AND INTEGRATION. Dietmar A. Salamon ETH Zürich
MEASURE AND INTEGRATION Dietmar A. Salamon ETH Zürich 12 May 2016 ii Preface This book is based on notes for the lecture course Measure and Integration held at ETH Zürich in the spring semester 2014. Prerequisites
More information9 More on differentiation
Tel Aviv University, 2013 Measure and category 75 9 More on differentiation 9a Finite Taylor expansion............... 75 9b Continuous and nowhere differentiable..... 78 9c Differentiable and nowhere monotone......
More informationINDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS
INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS STEVEN P. LALLEY AND ANDREW NOBEL Abstract. It is shown that there are no consistent decision rules for the hypothesis testing problem
More informationStatistics in Geophysics: Introduction and Probability Theory
Statistics in Geophysics: Introduction and Steffen Unkel Department of Statistics Ludwig-Maximilians-University Munich, Germany Winter Term 2013/14 1/32 What is Statistics? Introduction Statistics is the
More information8 Fractals: Cantor set, Sierpinski Triangle, Koch Snowflake, fractal dimension.
8 Fractals: Cantor set, Sierpinski Triangle, Koch Snowflake, fractal dimension. 8.1 Definitions Definition If every point in a set S has arbitrarily small neighborhoods whose boundaries do not intersect
More informationDISINTEGRATION OF MEASURES
DISINTEGRTION OF MESURES BEN HES Definition 1. Let (, M, λ), (, N, µ) be sigma-finite measure spaces and let T : be a measurable map. (T, µ)-disintegration is a collection {λ y } y of measures on M such
More informationRate of growth of D-frequently hypercyclic functions
Rate of growth of D-frequently hypercyclic functions A. Bonilla Departamento de Análisis Matemático Universidad de La Laguna Hypercyclic Definition A (linear and continuous) operator T in a topological
More informationBasic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011
Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011 A. Miller 1. Introduction. The definitions of metric space and topological space were developed in the early 1900 s, largely
More informationNotes on metric spaces
Notes on metric spaces 1 Introduction The purpose of these notes is to quickly review some of the basic concepts from Real Analysis, Metric Spaces and some related results that will be used in this course.
More informationSOLUTIONS TO ASSIGNMENT 1 MATH 576
SOLUTIONS TO ASSIGNMENT 1 MATH 576 SOLUTIONS BY OLIVIER MARTIN 13 #5. Let T be the topology generated by A on X. We want to show T = J B J where B is the set of all topologies J on X with A J. This amounts
More informationMetric Spaces Joseph Muscat 2003 (Last revised May 2009)
1 Distance J Muscat 1 Metric Spaces Joseph Muscat 2003 (Last revised May 2009) (A revised and expanded version of these notes are now published by Springer.) 1 Distance A metric space can be thought of
More informationk, then n = p2α 1 1 pα k
Powers of Integers An integer n is a perfect square if n = m for some integer m. Taking into account the prime factorization, if m = p α 1 1 pα k k, then n = pα 1 1 p α k k. That is, n is a perfect square
More informationFUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES
FUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES CHRISTOPHER HEIL 1. Cosets and the Quotient Space Any vector space is an abelian group under the operation of vector addition. So, if you are have studied
More informationGeometrical Characterization of RN-operators between Locally Convex Vector Spaces
Geometrical Characterization of RN-operators between Locally Convex Vector Spaces OLEG REINOV St. Petersburg State University Dept. of Mathematics and Mechanics Universitetskii pr. 28, 198504 St, Petersburg
More informationCHAPTER 1 BASIC TOPOLOGY
CHAPTER 1 BASIC TOPOLOGY Topology, sometimes referred to as the mathematics of continuity, or rubber sheet geometry, or the theory of abstract topological spaces, is all of these, but, above all, it is
More informationBasic Probability Concepts
page 1 Chapter 1 Basic Probability Concepts 1.1 Sample and Event Spaces 1.1.1 Sample Space A probabilistic (or statistical) experiment has the following characteristics: (a) the set of all possible outcomes
More informationGod created the integers and the rest is the work of man. (Leopold Kronecker, in an after-dinner speech at a conference, Berlin, 1886)
Chapter 2 Numbers God created the integers and the rest is the work of man. (Leopold Kronecker, in an after-dinner speech at a conference, Berlin, 1886) God created the integers and the rest is the work
More informationToday s Topics. Primes & Greatest Common Divisors
Today s Topics Primes & Greatest Common Divisors Prime representations Important theorems about primality Greatest Common Divisors Least Common Multiples Euclid s algorithm Once and for all, what are prime
More informationCODING TRUE ARITHMETIC IN THE MEDVEDEV AND MUCHNIK DEGREES
CODING TRUE ARITHMETIC IN THE MEDVEDEV AND MUCHNIK DEGREES PAUL SHAFER Abstract. We prove that the first-order theory of the Medvedev degrees, the first-order theory of the Muchnik degrees, and the third-order
More informationDEGREES OF ORDERS ON TORSION-FREE ABELIAN GROUPS
DEGREES OF ORDERS ON TORSION-FREE ABELIAN GROUPS ASHER M. KACH, KAREN LANGE, AND REED SOLOMON Abstract. We construct two computable presentations of computable torsion-free abelian groups, one of isomorphism
More informationCommentationes Mathematicae Universitatis Carolinae
Commentationes Mathematicae Universitatis Carolinae Adam Emeryk; Władysław Kulpa The Sorgenfrey line has no connected compactification Commentationes Mathematicae Universitatis Carolinae, Vol. 18 (1977),
More informationBasic Measure Theory. 1.1 Classes of Sets
1 Basic Measure Theory In this chapter, we introduce the classes of sets that allow for a systematic treatment of events and random observations in the framework of probability theory. Furthermore, we
More informationAn algorithmic classification of open surfaces
An algorithmic classification of open surfaces Sylvain Maillot January 8, 2013 Abstract We propose a formulation for the homeomorphism problem for open n-dimensional manifolds and use the Kerekjarto classification
More informationCANTOR SYSTEMS DIMENSION GROUPS AND BRATTELI DIAGRAMS
CANTOR SYSTEMS DIMENSION GROUPS AND BRATTELI DIAGRAMS Cand. Scient. oppgave i matematikk Ørjan Johansen December 1994 Acknowledgements I want to thank my advisor, Professor Christian Skau, and also doctorate
More informationarxiv:math/0510680v3 [math.gn] 31 Oct 2010
arxiv:math/0510680v3 [math.gn] 31 Oct 2010 MENGER S COVERING PROPERTY AND GROUPWISE DENSITY BOAZ TSABAN AND LYUBOMYR ZDOMSKYY Abstract. We establish a surprising connection between Menger s classical covering
More informationPoint Set Topology. A. Topological Spaces and Continuous Maps
Point Set Topology A. Topological Spaces and Continuous Maps Definition 1.1 A topology on a set X is a collection T of subsets of X satisfying the following axioms: T 1.,X T. T2. {O α α I} T = α IO α T.
More informationMA651 Topology. Lecture 6. Separation Axioms.
MA651 Topology. Lecture 6. Separation Axioms. This text is based on the following books: Fundamental concepts of topology by Peter O Neil Elements of Mathematics: General Topology by Nicolas Bourbaki Counterexamples
More informationLecture 4: BK inequality 27th August and 6th September, 2007
CSL866: Percolation and Random Graphs IIT Delhi Amitabha Bagchi Scribe: Arindam Pal Lecture 4: BK inequality 27th August and 6th September, 2007 4. Preliminaries The FKG inequality allows us to lower bound
More informationOn an anti-ramsey type result
On an anti-ramsey type result Noga Alon, Hanno Lefmann and Vojtĕch Rödl Abstract We consider anti-ramsey type results. For a given coloring of the k-element subsets of an n-element set X, where two k-element
More informationThe Ergodic Theorem and randomness
The Ergodic Theorem and randomness Peter Gács Department of Computer Science Boston University March 19, 2008 Peter Gács (Boston University) Ergodic theorem March 19, 2008 1 / 27 Introduction Introduction
More informationZORN S LEMMA AND SOME APPLICATIONS
ZORN S LEMMA AND SOME APPLICATIONS KEITH CONRAD 1. Introduction Zorn s lemma is a result in set theory that appears in proofs of some non-constructive existence theorems throughout mathematics. We will
More informationGENTLY KILLING S SPACES TODD EISWORTH, PETER NYIKOS, AND SAHARON SHELAH
GENTLY KILLING S SPACES TODD EISWORTH, PETER NYIKOS, AND SAHARON SHELAH Abstract. We produce a model of ZFC in which there are no locally compact first countable S spaces, and in which 2 ℵ 0 < 2 ℵ 1. A
More informationMathematics for Econometrics, Fourth Edition
Mathematics for Econometrics, Fourth Edition Phoebus J. Dhrymes 1 July 2012 1 c Phoebus J. Dhrymes, 2012. Preliminary material; not to be cited or disseminated without the author s permission. 2 Contents
More informationINTRODUCTION TO TOPOLOGY
INTRODUCTION TO TOPOLOGY ALEX KÜRONYA In preparation January 24, 2010 Contents 1. Basic concepts 1 2. Constructing topologies 13 2.1. Subspace topology 13 2.2. Local properties 18 2.3. Product topology
More information1 if 1 x 0 1 if 0 x 1
Chapter 3 Continuity In this chapter we begin by defining the fundamental notion of continuity for real valued functions of a single real variable. When trying to decide whether a given function is or
More informationNo: 10 04. Bilkent University. Monotonic Extension. Farhad Husseinov. Discussion Papers. Department of Economics
No: 10 04 Bilkent University Monotonic Extension Farhad Husseinov Discussion Papers Department of Economics The Discussion Papers of the Department of Economics are intended to make the initial results
More informationPSEUDOARCS, PSEUDOCIRCLES, LAKES OF WADA AND GENERIC MAPS ON S 2
PSEUDOARCS, PSEUDOCIRCLES, LAKES OF WADA AND GENERIC MAPS ON S 2 Abstract. We prove a Bruckner-Garg type theorem for the fiber structure of a generic map from a continuum X into the unit interval I. We
More informationThe Banach-Tarski Paradox
University of Oslo MAT2 Project The Banach-Tarski Paradox Author: Fredrik Meyer Supervisor: Nadia S. Larsen Abstract In its weak form, the Banach-Tarski paradox states that for any ball in R, it is possible
More informationON COMPLETELY CONTINUOUS INTEGRATION OPERATORS OF A VECTOR MEASURE. 1. Introduction
ON COMPLETELY CONTINUOUS INTEGRATION OPERATORS OF A VECTOR MEASURE J.M. CALABUIG, J. RODRÍGUEZ, AND E.A. SÁNCHEZ-PÉREZ Abstract. Let m be a vector measure taking values in a Banach space X. We prove that
More informationThe Henstock-Kurzweil-Stieltjes type integral for real functions on a fractal subset of the real line
The Henstock-Kurzweil-Stieltjes type integral for real functions on a fractal subset of the real line D. Bongiorno, G. Corrao Dipartimento di Ingegneria lettrica, lettronica e delle Telecomunicazioni,
More informationUniversity of Miskolc
University of Miskolc The Faculty of Mechanical Engineering and Information Science The role of the maximum operator in the theory of measurability and some applications PhD Thesis by Nutefe Kwami Agbeko
More information16.3 Fredholm Operators
Lectures 16 and 17 16.3 Fredholm Operators A nice way to think about compact operators is to show that set of compact operators is the closure of the set of finite rank operator in operator norm. In this
More informationand s n (x) f(x) for all x and s.t. s n is measurable if f is. REAL ANALYSIS Measures. A (positive) measure on a measurable space
RAL ANALYSIS A survey of MA 641-643, UAB 1999-2000 M. Griesemer Throughout these notes m denotes Lebesgue measure. 1. Abstract Integration σ-algebras. A σ-algebra in X is a non-empty collection of subsets
More informationHOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)!
Math 7 Fall 205 HOMEWORK 5 SOLUTIONS Problem. 2008 B2 Let F 0 x = ln x. For n 0 and x > 0, let F n+ x = 0 F ntdt. Evaluate n!f n lim n ln n. By directly computing F n x for small n s, we obtain the following
More informationMath/Stats 425 Introduction to Probability. 1. Uncertainty and the axioms of probability
Math/Stats 425 Introduction to Probability 1. Uncertainty and the axioms of probability Processes in the real world are random if outcomes cannot be predicted with certainty. Example: coin tossing, stock
More informationLECTURE NOTES IN MEASURE THEORY. Christer Borell Matematik Chalmers och Göteborgs universitet 412 96 Göteborg (Version: January 12)
1 LECTURE NOTES IN MEASURE THEORY Christer Borell Matematik Chalmers och Göteborgs universitet 412 96 Göteborg (Version: January 12) 2 PREFACE These are lecture notes on integration theory for a eight-week
More informationIAM 530 ELEMENTS OF PROBABILITY AND STATISTICS INTRODUCTION
IAM 530 ELEMENTS OF PROBABILITY AND STATISTICS INTRODUCTION 1 WHAT IS STATISTICS? Statistics is a science of collecting data, organizing and describing it and drawing conclusions from it. That is, statistics
More informationTHE REGULAR OPEN CONTINUOUS IMAGES OF COMPLETE METRIC SPACES
PACIFIC JOURNAL OF MATHEMATICS Vol 23 No 3, 1967 THE REGULAR OPEN CONTINUOUS IMAGES OF COMPLETE METRIC SPACES HOWARD H WICKE This article characterizes the regular T o open continuous images of complete
More informationx < y iff x < y, or x and y are incomparable and x χ(x,y) < y χ(x,y).
12. Large cardinals The study, or use, of large cardinals is one of the most active areas of research in set theory currently. There are many provably different kinds of large cardinals whose descriptions
More informationFollow links for Class Use and other Permissions. For more information send email to: permissions@pupress.princeton.edu
COPYRIGHT NOTICE: Ariel Rubinstein: Lecture Notes in Microeconomic Theory is published by Princeton University Press and copyrighted, c 2006, by Princeton University Press. All rights reserved. No part
More informationn k=1 k=0 1/k! = e. Example 6.4. The series 1/k 2 converges in R. Indeed, if s n = n then k=1 1/k, then s 2n s n = 1 n + 1 +...
6 Series We call a normed space (X, ) a Banach space provided that every Cauchy sequence (x n ) in X converges. For example, R with the norm = is an example of Banach space. Now let (x n ) be a sequence
More informationGENERIC COMPUTABILITY, TURING DEGREES, AND ASYMPTOTIC DENSITY
GENERIC COMPUTABILITY, TURING DEGREES, AND ASYMPTOTIC DENSITY CARL G. JOCKUSCH, JR. AND PAUL E. SCHUPP Abstract. Generic decidability has been extensively studied in group theory, and we now study it in
More informationSystems of Linear Equations
Systems of Linear Equations Beifang Chen Systems of linear equations Linear systems A linear equation in variables x, x,, x n is an equation of the form a x + a x + + a n x n = b, where a, a,, a n and
More informationBANACH AND HILBERT SPACE REVIEW
BANACH AND HILBET SPACE EVIEW CHISTOPHE HEIL These notes will briefly review some basic concepts related to the theory of Banach and Hilbert spaces. We are not trying to give a complete development, but
More informationProbability and Statistics Vocabulary List (Definitions for Middle School Teachers)
Probability and Statistics Vocabulary List (Definitions for Middle School Teachers) B Bar graph a diagram representing the frequency distribution for nominal or discrete data. It consists of a sequence
More informationTail inequalities for order statistics of log-concave vectors and applications
Tail inequalities for order statistics of log-concave vectors and applications Rafał Latała Based in part on a joint work with R.Adamczak, A.E.Litvak, A.Pajor and N.Tomczak-Jaegermann Banff, May 2011 Basic
More informationColumbia University in the City of New York New York, N.Y. 10027
Columbia University in the City of New York New York, N.Y. 10027 DEPARTMENT OF MATHEMATICS 508 Mathematics Building 2990 Broadway Fall Semester 2005 Professor Ioannis Karatzas W4061: MODERN ANALYSIS Description
More informationTHE BANACH CONTRACTION PRINCIPLE. Contents
THE BANACH CONTRACTION PRINCIPLE ALEX PONIECKI Abstract. This paper will study contractions of metric spaces. To do this, we will mainly use tools from topology. We will give some examples of contractions,
More informationMetric Spaces. Chapter 1
Chapter 1 Metric Spaces Many of the arguments you have seen in several variable calculus are almost identical to the corresponding arguments in one variable calculus, especially arguments concerning convergence
More informationThe sample space for a pair of die rolls is the set. The sample space for a random number between 0 and 1 is the interval [0, 1].
Probability Theory Probability Spaces and Events Consider a random experiment with several possible outcomes. For example, we might roll a pair of dice, flip a coin three times, or choose a random real
More information0 <β 1 let u(x) u(y) kuk u := sup u(x) and [u] β := sup
456 BRUCE K. DRIVER 24. Hölder Spaces Notation 24.1. Let Ω be an open subset of R d,bc(ω) and BC( Ω) be the bounded continuous functions on Ω and Ω respectively. By identifying f BC( Ω) with f Ω BC(Ω),
More informationPUTNAM TRAINING POLYNOMIALS. Exercises 1. Find a polynomial with integral coefficients whose zeros include 2 + 5.
PUTNAM TRAINING POLYNOMIALS (Last updated: November 17, 2015) Remark. This is a list of exercises on polynomials. Miguel A. Lerma Exercises 1. Find a polynomial with integral coefficients whose zeros include
More information(IALC, Chapters 8 and 9) Introduction to Turing s life, Turing machines, universal machines, unsolvable problems.
3130CIT: Theory of Computation Turing machines and undecidability (IALC, Chapters 8 and 9) Introduction to Turing s life, Turing machines, universal machines, unsolvable problems. An undecidable problem
More informationInner Product Spaces
Math 571 Inner Product Spaces 1. Preliminaries An inner product space is a vector space V along with a function, called an inner product which associates each pair of vectors u, v with a scalar u, v, and
More informationLecture Note 1 Set and Probability Theory. MIT 14.30 Spring 2006 Herman Bennett
Lecture Note 1 Set and Probability Theory MIT 14.30 Spring 2006 Herman Bennett 1 Set Theory 1.1 Definitions and Theorems 1. Experiment: any action or process whose outcome is subject to uncertainty. 2.
More informationI. Pointwise convergence
MATH 40 - NOTES Sequences of functions Pointwise and Uniform Convergence Fall 2005 Previously, we have studied sequences of real numbers. Now we discuss the topic of sequences of real valued functions.
More informationDuality of linear conic problems
Duality of linear conic problems Alexander Shapiro and Arkadi Nemirovski Abstract It is well known that the optimal values of a linear programming problem and its dual are equal to each other if at least
More informationLogic, Combinatorics and Topological Dynamics, II
Logic, Combinatorics and Topological Dynamics, II Alexander S. Kechris January 9, 2009 Part II. Generic symmetries Generic properties Let X be a topological space and P X a subset of X viewed as a property
More informationMetric Spaces. Chapter 7. 7.1. Metrics
Chapter 7 Metric Spaces A metric space is a set X that has a notion of the distance d(x, y) between every pair of points x, y X. The purpose of this chapter is to introduce metric spaces and give some
More informationIntroduction to Topology
Introduction to Topology Tomoo Matsumura November 30, 2010 Contents 1 Topological spaces 3 1.1 Basis of a Topology......................................... 3 1.2 Comparing Topologies.......................................
More informationSET-THEORETIC CONSTRUCTIONS OF TWO-POINT SETS
SET-THEORETIC CONSTRUCTIONS OF TWO-POINT SETS BEN CHAD AND ROBIN KNIGHT AND ROLF SUABEDISSEN Abstract. A two-point set is a subset of the plane which meets every line in exactly two points. By working
More informationOn Winning Conditions of High Borel Complexity in Pushdown Games
Fundamenta Informaticae (2005) 1 22 1 IOS Press On Winning Conditions of High Borel Complexity in Pushdown Games Olivier Finkel Equipe de Logique Mathématique U.F.R. de Mathématiques, Université Paris
More informationMinimal R 1, minimal regular and minimal presober topologies
Revista Notas de Matemática Vol.5(1), No. 275, 2009, pp.73-84 http://www.saber.ula.ve/notasdematematica/ Comisión de Publicaciones Departamento de Matemáticas Facultad de Ciencias Universidad de Los Andes
More informationThis chapter is all about cardinality of sets. At first this looks like a
CHAPTER Cardinality of Sets This chapter is all about cardinality of sets At first this looks like a very simple concept To find the cardinality of a set, just count its elements If A = { a, b, c, d },
More informationThe Ideal Class Group
Chapter 5 The Ideal Class Group We will use Minkowski theory, which belongs to the general area of geometry of numbers, to gain insight into the ideal class group of a number field. We have already mentioned
More informationCHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e.
CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e. This chapter contains the beginnings of the most important, and probably the most subtle, notion in mathematical analysis, i.e.,
More informationMATH PROBLEMS, WITH SOLUTIONS
MATH PROBLEMS, WITH SOLUTIONS OVIDIU MUNTEANU These are free online notes that I wrote to assist students that wish to test their math skills with some problems that go beyond the usual curriculum. These
More informationLecture 7: Continuous Random Variables
Lecture 7: Continuous Random Variables 21 September 2005 1 Our First Continuous Random Variable The back of the lecture hall is roughly 10 meters across. Suppose it were exactly 10 meters, and consider
More informationMATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set.
MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set. Vector space A vector space is a set V equipped with two operations, addition V V (x,y) x + y V and scalar
More informationMath 104: Introduction to Analysis
Math 104: Introduction to Analysis Evan Chen UC Berkeley Notes for the course MATH 104, instructed by Charles Pugh. 1 1 August 29, 2013 Hard: #22 in Chapter 1. Consider a pile of sand principle. You wish
More informationInvariant random subgroups and applications
Department of Mathematics Ben-Gurion university of the Negev. Spa, April 2013. Plan 1 Plan 2 IRS Definitions, Examples, Theorems 3 Essential subgroups 4 Proof of the main theorem IRS Definition Γ a l.c
More informationGeorg Cantor and Set Theory
Georg Cantor and Set Theory. Life Father, Georg Waldemar Cantor, born in Denmark, successful merchant, and stock broker in St Petersburg. Mother, Maria Anna Böhm, was Russian. In 856, because of father
More informationON SEQUENTIAL CONTINUITY OF COMPOSITION MAPPING. 0. Introduction
ON SEQUENTIAL CONTINUITY OF COMPOSITION MAPPING Abstract. In [1] there was proved a theorem concerning the continuity of the composition mapping, and there was announced a theorem on sequential continuity
More informationProbability Theory. Florian Herzog. A random variable is neither random nor variable. Gian-Carlo Rota, M.I.T..
Probability Theory A random variable is neither random nor variable. Gian-Carlo Rota, M.I.T.. Florian Herzog 2013 Probability space Probability space A probability space W is a unique triple W = {Ω, F,
More informationHomework #2 Solutions
MAT Spring Problems Section.:, 8,, 4, 8 Section.5:,,, 4,, 6 Extra Problem # Homework # Solutions... Sketch likely solution curves through the given slope field for dy dx = x + y...8. Sketch likely solution
More information