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Lectures on Fractal Geometry and Dynamics
Lectures on fractal geometry and dynamics Michael Hochman∗ March 25, 2012 Contents 1 Introduction 2 2 Preliminaries 3 3 Dimension 3 3.1 A family of examples: Middle-α Cantor sets . 3 3.2 Minkowski dimension . 4 3.3 Hausdorff dimension . 9 4 Using measures to compute dimension 13 4.1 The mass distribution principle . 13 4.2 Billingsley's lemma . 15 4.3 Frostman's lemma . 18 4.4 Product sets . 22 5 Iterated function systems 24 5.1 The Hausdorff metric . 24 5.2 Iterated function systems . 26 5.3 Self-similar sets . 31 5.4 Self-affine sets . 36 6 Geometry of measures 39 6.1 The Besicovitch covering theorem . 39 6.2 Density and differentiation theorems . 45 6.3 Dimension of a measure at a point . 48 6.4 Upper and lower dimension of measures . 50 ∗Send comments to [email protected] 1 6.5 Hausdorff measures and their densities . 52 1 Introduction Fractal geometry and its sibling, geometric measure theory, are branches of analysis which study the structure of \irregular" sets and measures in metric spaces, primarily d R . The distinction between regular and irregular sets is not a precise one but informally, k regular sets might be understood as smooth sub-manifolds of R , or perhaps Lipschitz graphs, or countable unions of the above; whereas irregular sets include just about 1 everything else, from the middle- 3 Cantor set (still highly structured) to arbitrary d Cantor sets (irregular, but topologically the same) to truly arbitrary subsets of R . d For concreteness, let us compare smooth sub-manifolds and Cantor subsets of R . -
Reasoning About Equations Using Equality
Mathematics Instructional Plan – Grade 4 Reasoning About Equations Using Equality Strand: Patterns, Functions, Algebra Topic: Using reasoning to assess the equality in closed and open arithmetic equations Primary SOL: 4.16 The student will recognize and demonstrate the meaning of equality in an equation. Related SOL: 4.4a Materials: Partners Explore Equality and Equations activity sheet (attached) Vocabulary equal symbol (=), equality, equation, expression, not equal symbol (≠), number sentence, open number sentence, reasoning Student/Teacher Actions: What should students be doing? What should teachers be doing? 1. Activate students’ prior knowledge about the equal sign. Formally assess what students already know and what misconceptions they have. Ask students to open their notebooks to a clean sheet of paper and draw lines to divide the sheet into thirds as shown below. Create a poster of the same graphic organizer for the room. This activity should take no more than 10 minutes; it is not a teaching opportunity but simply a data- collection activity. Equality and the Equal Sign (=) I know that- I wonder if- I learned that- 1 1 1 a. Let students know they will be creating a graphic organizer about equality and the equal sign; that is, what it means and how it is used. The organizer is to help them keep track of what they know, what they wonder, and what they learn. The “I know that” column is where they can write things they are pretty sure are correct. The “I wonder if” column is where they can write things they have questions about and also where they can put things they think may be true but they are not sure. -
1 Elementary Set Theory
1 Elementary Set Theory Notation: fg enclose a set. f1; 2; 3g = f3; 2; 2; 1; 3g because a set is not defined by order or multiplicity. f0; 2; 4;:::g = fxjx is an even natural numberg because two ways of writing a set are equivalent. ; is the empty set. x 2 A denotes x is an element of A. N = f0; 1; 2;:::g are the natural numbers. Z = f:::; −2; −1; 0; 1; 2;:::g are the integers. m Q = f n jm; n 2 Z and n 6= 0g are the rational numbers. R are the real numbers. Axiom 1.1. Axiom of Extensionality Let A; B be sets. If (8x)x 2 A iff x 2 B then A = B. Definition 1.1 (Subset). Let A; B be sets. Then A is a subset of B, written A ⊆ B iff (8x) if x 2 A then x 2 B. Theorem 1.1. If A ⊆ B and B ⊆ A then A = B. Proof. Let x be arbitrary. Because A ⊆ B if x 2 A then x 2 B Because B ⊆ A if x 2 B then x 2 A Hence, x 2 A iff x 2 B, thus A = B. Definition 1.2 (Union). Let A; B be sets. The Union A [ B of A and B is defined by x 2 A [ B if x 2 A or x 2 B. Theorem 1.2. A [ (B [ C) = (A [ B) [ C Proof. Let x be arbitrary. x 2 A [ (B [ C) iff x 2 A or x 2 B [ C iff x 2 A or (x 2 B or x 2 C) iff x 2 A or x 2 B or x 2 C iff (x 2 A or x 2 B) or x 2 C iff x 2 A [ B or x 2 C iff x 2 (A [ B) [ C Definition 1.3 (Intersection). -
Mathematics 144 Set Theory Fall 2012 Version
MATHEMATICS 144 SET THEORY FALL 2012 VERSION Table of Contents I. General considerations.……………………………………………………………………………………………………….1 1. Overview of the course…………………………………………………………………………………………………1 2. Historical background and motivation………………………………………………………….………………4 3. Selected problems………………………………………………………………………………………………………13 I I. Basic concepts. ………………………………………………………………………………………………………………….15 1. Topics from logic…………………………………………………………………………………………………………16 2. Notation and first steps………………………………………………………………………………………………26 3. Simple examples…………………………………………………………………………………………………………30 I I I. Constructions in set theory.………………………………………………………………………………..……….34 1. Boolean algebra operations.……………………………………………………………………………………….34 2. Ordered pairs and Cartesian products……………………………………………………………………… ….40 3. Larger constructions………………………………………………………………………………………………..….42 4. A convenient assumption………………………………………………………………………………………… ….45 I V. Relations and functions ……………………………………………………………………………………………….49 1.Binary relations………………………………………………………………………………………………………… ….49 2. Partial and linear orderings……………………………..………………………………………………… ………… 56 3. Functions…………………………………………………………………………………………………………… ….…….. 61 4. Composite and inverse function.…………………………………………………………………………… …….. 70 5. Constructions involving functions ………………………………………………………………………… ……… 77 6. Order types……………………………………………………………………………………………………… …………… 80 i V. Number systems and set theory …………………………………………………………………………………. 84 1. The Natural Numbers and Integers…………………………………………………………………………….83 2. Finite induction -
The Matroid Theorem We First Review Our Definitions: a Subset System Is A
CMPSCI611: The Matroid Theorem Lecture 5 We first review our definitions: A subset system is a set E together with a set of subsets of E, called I, such that I is closed under inclusion. This means that if X ⊆ Y and Y ∈ I, then X ∈ I. The optimization problem for a subset system (E, I) has as input a positive weight for each element of E. Its output is a set X ∈ I such that X has at least as much total weight as any other set in I. A subset system is a matroid if it satisfies the exchange property: If i and i0 are sets in I and i has fewer elements than i0, then there exists an element e ∈ i0 \ i such that i ∪ {e} ∈ I. 1 The Generic Greedy Algorithm Given any finite subset system (E, I), we find a set in I as follows: • Set X to ∅. • Sort the elements of E by weight, heaviest first. • For each element of E in this order, add it to X iff the result is in I. • Return X. Today we prove: Theorem: For any subset system (E, I), the greedy al- gorithm solves the optimization problem for (E, I) if and only if (E, I) is a matroid. 2 Theorem: For any subset system (E, I), the greedy al- gorithm solves the optimization problem for (E, I) if and only if (E, I) is a matroid. Proof: We will show first that if (E, I) is a matroid, then the greedy algorithm is correct. Assume that (E, I) satisfies the exchange property. -
TOPOLOGY and ITS APPLICATIONS the Number of Complements in The
TOPOLOGY AND ITS APPLICATIONS ELSEVIER Topology and its Applications 55 (1994) 101-125 The number of complements in the lattice of topologies on a fixed set Stephen Watson Department of Mathematics, York Uniuersity, 4700 Keele Street, North York, Ont., Canada M3J IP3 (Received 3 May 1989) (Revised 14 November 1989 and 2 June 1992) Abstract In 1936, Birkhoff ordered the family of all topologies on a set by inclusion and obtained a lattice with 1 and 0. The study of this lattice ought to be a basic pursuit both in combinatorial set theory and in general topology. In this paper, we study the nature of complementation in this lattice. We say that topologies 7 and (T are complementary if and only if 7 A c = 0 and 7 V (T = 1. For simplicity, we call any topology other than the discrete and the indiscrete a proper topology. Hartmanis showed in 1958 that any proper topology on a finite set of size at least 3 has at least two complements. Gaifman showed in 1961 that any proper topology on a countable set has at least two complements. In 1965, Steiner showed that any topology has a complement. The question of the number of distinct complements a topology on a set must possess was first raised by Berri in 1964 who asked if every proper topology on an infinite set must have at least two complements. In 1969, Schnare showed that any proper topology on a set of infinite cardinality K has at least K distinct complements and at most 2” many distinct complements. -
Determinacy in Linear Rational Expectations Models
Journal of Mathematical Economics 40 (2004) 815–830 Determinacy in linear rational expectations models Stéphane Gauthier∗ CREST, Laboratoire de Macroéconomie (Timbre J-360), 15 bd Gabriel Péri, 92245 Malakoff Cedex, France Received 15 February 2002; received in revised form 5 June 2003; accepted 17 July 2003 Available online 21 January 2004 Abstract The purpose of this paper is to assess the relevance of rational expectations solutions to the class of linear univariate models where both the number of leads in expectations and the number of lags in predetermined variables are arbitrary. It recommends to rule out all the solutions that would fail to be locally unique, or equivalently, locally determinate. So far, this determinacy criterion has been applied to particular solutions, in general some steady state or periodic cycle. However solutions to linear models with rational expectations typically do not conform to such simple dynamic patterns but express instead the current state of the economic system as a linear difference equation of lagged states. The innovation of this paper is to apply the determinacy criterion to the sets of coefficients of these linear difference equations. Its main result shows that only one set of such coefficients, or the corresponding solution, is locally determinate. This solution is commonly referred to as the fundamental one in the literature. In particular, in the saddle point configuration, it coincides with the saddle stable (pure forward) equilibrium trajectory. © 2004 Published by Elsevier B.V. JEL classification: C32; E32 Keywords: Rational expectations; Selection; Determinacy; Saddle point property 1. Introduction The rational expectations hypothesis is commonly justified by the fact that individual forecasts are based on the relevant theory of the economic system. -
Fast and Private Computation of Cardinality of Set Intersection and Union
Fast and Private Computation of Cardinality of Set Intersection and Union Emiliano De Cristofaroy, Paolo Gastiz, and Gene Tsudikz yPARC zUC Irvine Abstract. With massive amounts of electronic information stored, trans- ferred, and shared every day, legitimate needs for sensitive information must be reconciled with natural privacy concerns. This motivates var- ious cryptographic techniques for privacy-preserving information shar- ing, such as Private Set Intersection (PSI) and Private Set Union (PSU). Such techniques involve two parties { client and server { each with a private input set. At the end, client learns the intersection (or union) of the two respective sets, while server learns nothing. However, if desired functionality is private computation of cardinality rather than contents, of set intersection, PSI and PSU protocols are not appropriate, as they yield too much information. In this paper, we design an efficient crypto- graphic protocol for Private Set Intersection Cardinality (PSI-CA) that yields only the size of set intersection, with security in the presence of both semi-honest and malicious adversaries. To the best of our knowl- edge, it is the first protocol that achieves complexities linear in the size of input sets. We then show how the same protocol can be used to pri- vately compute set union cardinality. We also design an extension that supports authorization of client input. 1 Introduction Proliferation of, and growing reliance on, electronic information trigger the increase in the amount of sensitive data stored and processed in cyberspace. Consequently, there is a strong need for efficient cryptographic techniques that allow sharing information with privacy. Among these, Private Set Intersection (PSI) [11, 24, 14, 21, 15, 22, 9, 8, 18], and Private Set Union (PSU) [24, 15, 17, 12, 32] have attracted a lot of attention from the research community. -
PROBLEM SET 1. the AXIOM of FOUNDATION Early on in the Book
PROBLEM SET 1. THE AXIOM OF FOUNDATION Early on in the book (page 6) it is indicated that throughout the formal development ‘set’ is going to mean ‘pure set’, or set whose elements, elements of elements, and so on, are all sets and not items of any other kind such as chairs or tables. This convention applies also to these problems. 1. A set y is called an epsilon-minimal element of a set x if y Î x, but there is no z Î x such that z Î y, or equivalently x Ç y = Ø. The axiom of foundation, also called the axiom of regularity, asserts that any set that has any element at all (any nonempty set) has an epsilon-minimal element. Show that this axiom implies the following: (a) There is no set x such that x Î x. (b) There are no sets x and y such that x Î y and y Î x. (c) There are no sets x and y and z such that x Î y and y Î z and z Î x. 2. In the book the axiom of foundation or regularity is considered only in a late chapter, and until that point no use of it is made of it in proofs. But some results earlier in the book become significantly easier to prove if one does use it. Show, for example, how to use it to give an easy proof of the existence for any sets x and y of a set x* such that x* and y are disjoint (have empty intersection) and there is a bijection (one-to-one onto function) from x to x*, a result called the exchange principle. -
1 Measurable Sets
Math 4351, Fall 2018 Chapter 11 in Goldberg 1 Measurable Sets Our goal is to define what is meant by a measurable set E ⊆ [a; b] ⊂ R and a measurable function f :[a; b] ! R. We defined the length of an open set and a closed set, denoted as jGj and jF j, e.g., j[a; b]j = b − a: We will use another notation for complement and the notation in the Goldberg text. Let Ec = [a; b] n E = [a; b] − E. Also, E1 n E2 = E1 − E2: Definitions: Let E ⊆ [a; b]. Outer measure of a set E: m(E) = inffjGj : for all G open and E ⊆ Gg. Inner measure of a set E: m(E) = supfjF j : for all F closed and F ⊆ Eg: 0 ≤ m(E) ≤ m(E). A set E is a measurable set if m(E) = m(E) and the measure of E is denoted as m(E). The symmetric difference of two sets E1 and E2 is defined as E1∆E2 = (E1 − E2) [ (E2 − E1): A set is called an Fσ set (F-sigma set) if it is a union of a countable number of closed sets. A set is called a Gδ set (G-delta set) if it is a countable intersection of open sets. Properties of Measurable Sets on [a; b]: 1. If E1 and E2 are subsets of [a; b] and E1 ⊆ E2, then m(E1) ≤ m(E2) and m(E1) ≤ m(E2). In addition, if E1 and E2 are measurable subsets of [a; b] and E1 ⊆ E2, then m(E1) ≤ m(E2). -
Cardinality of Sets
Cardinality of Sets MAT231 Transition to Higher Mathematics Fall 2014 MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 1 / 15 Outline 1 Sets with Equal Cardinality 2 Countable and Uncountable Sets MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 2 / 15 Sets with Equal Cardinality Definition Two sets A and B have the same cardinality, written jAj = jBj, if there exists a bijective function f : A ! B. If no such bijective function exists, then the sets have unequal cardinalities, that is, jAj 6= jBj. Another way to say this is that jAj = jBj if there is a one-to-one correspondence between the elements of A and the elements of B. For example, to show that the set A = f1; 2; 3; 4g and the set B = {♠; ~; }; |g have the same cardinality it is sufficient to construct a bijective function between them. 1 2 3 4 ♠ ~ } | MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 3 / 15 Sets with Equal Cardinality Consider the following: This definition does not involve the number of elements in the sets. It works equally well for finite and infinite sets. Any bijection between the sets is sufficient. MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 4 / 15 The set Z contains all the numbers in N as well as numbers not in N. So maybe Z is larger than N... On the other hand, both sets are infinite, so maybe Z is the same size as N... This is just the sort of ambiguity we want to avoid, so we appeal to the definition of \same cardinality." The answer to our question boils down to \Can we find a bijection between N and Z?" Does jNj = jZj? True or false: Z is larger than N. -
Formal Construction of a Set Theory in Coq
Saarland University Faculty of Natural Sciences and Technology I Department of Computer Science Masters Thesis Formal Construction of a Set Theory in Coq submitted by Jonas Kaiser on November 23, 2012 Supervisor Prof. Dr. Gert Smolka Advisor Dr. Chad E. Brown Reviewers Prof. Dr. Gert Smolka Dr. Chad E. Brown Eidesstattliche Erklarung¨ Ich erklare¨ hiermit an Eides Statt, dass ich die vorliegende Arbeit selbststandig¨ verfasst und keine anderen als die angegebenen Quellen und Hilfsmittel verwendet habe. Statement in Lieu of an Oath I hereby confirm that I have written this thesis on my own and that I have not used any other media or materials than the ones referred to in this thesis. Einverstandniserkl¨ arung¨ Ich bin damit einverstanden, dass meine (bestandene) Arbeit in beiden Versionen in die Bibliothek der Informatik aufgenommen und damit vero¨ffentlicht wird. Declaration of Consent I agree to make both versions of my thesis (with a passing grade) accessible to the public by having them added to the library of the Computer Science Department. Saarbrucken,¨ (Datum/Date) (Unterschrift/Signature) iii Acknowledgements First of all I would like to express my sincerest gratitude towards my advisor, Chad Brown, who supported me throughout this work. His extensive knowledge and insights opened my eyes to the beauty of axiomatic set theory and foundational mathematics. We spent many hours discussing the minute details of the various constructions and he taught me the importance of mathematical rigour. Equally important was the support of my supervisor, Prof. Smolka, who first introduced me to the topic and was there whenever a question arose.