Coalgebras on Measurable Spaces
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Integral Representation of a Linear Functional on Function Spaces
INTEGRAL REPRESENTATION OF LINEAR FUNCTIONALS ON FUNCTION SPACES MEHDI GHASEMI Abstract. Let A be a vector space of real valued functions on a non-empty set X and L : A −! R a linear functional. Given a σ-algebra A, of subsets of X, we present a necessary condition for L to be representable as an integral with respect to a measure µ on X such that elements of A are µ-measurable. This general result then is applied to the case where X carries a topological structure and A is a family of continuous functions and naturally A is the Borel structure of X. As an application, short solutions for the full and truncated K-moment problem are presented. An analogue of Riesz{Markov{Kakutani representation theorem is given where Cc(X) is replaced with whole C(X). Then we consider the case where A only consists of bounded functions and hence is equipped with sup-norm. 1. Introduction A positive linear functional on a function space A ⊆ RX is a linear map L : A −! R which assigns a non-negative real number to every function f 2 A that is globally non-negative over X. The celebrated Riesz{Markov{Kakutani repre- sentation theorem states that every positive functional on the space of continuous compactly supported functions over a locally compact Hausdorff space X, admits an integral representation with respect to a regular Borel measure on X. In symbols R L(f) = X f dµ, for all f 2 Cc(X). Riesz's original result [12] was proved in 1909, for the unit interval [0; 1]. -
1 Sets and Classes
Prerequisites Topological spaces. A set E in a space X is σ-compact if there exists a S1 sequence of compact sets such that E = n=1 Cn. A space X is locally compact if every point of X has a neighborhood whose closure is compact. A subset E of a locally compact space is bounded if there exists a compact set C such that E ⊂ C. Topological groups. The set xE [or Ex] is called a left translation [or right translation.] If Y is a subgroup of X, the sets xY and Y x are called (left and right) cosets of Y . A topological group is a group X which is a Hausdorff space such that the transformation (from X ×X onto X) which sends (x; y) into x−1y is continuous. A class N of open sets containing e in a topological group is a base at e if (a) for every x different form e there exists a set U in N such that x2 = U, (b) for any two sets U and V in N there exists a set W in N such that W ⊂ U \ V , (c) for any set U 2 N there exists a set W 2 N such that V −1V ⊂ U, (d) for any set U 2 N and any element x 2 X, there exists a set V 2 N such that V ⊂ xUx−1, and (e) for any set U 2 N there exists a set V 2 N such that V x ⊂ U. If N is a satisfies the conditions described above, and if the class of all translation of sets of N is taken for a base, then, with respect to the topology so defined, X becomes a topological group. -
On Families of Mutually Exclusive Sets
ANNALS OF MATHEMATICS Vol. 44, No . 2, April, 1943 ON FAMILIES OF MUTUALLY EXCLUSIVE SETS BY P . ERDÖS AND A. TARSKI (Received August 11, 1942) In this paper we shall be concerned with a certain particular problem from the general theory of sets, namely with the problem of the existence of families of mutually exclusive sets with a maximal power . It will turn out-in a rather unexpected way that the solution of these problems essentially involves the notion of the so-called "inaccessible numbers ." In this connection we shall make some general remarks regarding inaccessible numbers in the last section of our paper . §1. FORMULATION OF THE PROBLEM . TERMINOLOGY' The problem in which we are interested can be stated as follows : Is it true that every field F of sets contains a family of mutually exclusive sets with a maximal power, i .e . a family O whose cardinal number is not smaller than the cardinal number of any other family of mutually exclusive sets contained in F . By a field of sets we understand here as usual a family F of sets which to- gether with every two sets X and Y contains also their union X U Y and their difference X - Y (i.e. the set of those elements of X which do not belong to Y) among its elements . A family O is called a family of mutually exclusive sets if no set X of X of O is empty and if any two different sets of O have an empty inter- section. A similar problem can be formulated for other families e .g . -
Completely Representable Lattices
Completely representable lattices Robert Egrot and Robin Hirsch Abstract It is known that a lattice is representable as a ring of sets iff the lattice is distributive. CRL is the class of bounded distributive lattices (DLs) which have representations preserving arbitrary joins and meets. jCRL is the class of DLs which have representations preserving arbitrary joins, mCRL is the class of DLs which have representations preserving arbitrary meets, and biCRL is defined to be jCRL ∩ mCRL. We prove CRL ⊂ biCRL = mCRL ∩ jCRL ⊂ mCRL =6 jCRL ⊂ DL where the marked inclusions are proper. Let L be a DL. Then L ∈ mCRL iff L has a distinguishing set of complete, prime filters. Similarly, L ∈ jCRL iff L has a distinguishing set of completely prime filters, and L ∈ CRL iff L has a distinguishing set of complete, completely prime filters. Each of the classes above is shown to be pseudo-elementary hence closed under ultraproducts. The class CRL is not closed under elementary equivalence, hence it is not elementary. 1 Introduction An atomic representation h of a Boolean algebra B is a representation h: B → ℘(X) (some set X) where h(1) = {h(a): a is an atom of B}. It is known that a representation of a Boolean algebraS is a complete representation (in the sense of a complete embedding into a field of sets) if and only if it is an atomic repre- sentation and hence that the class of completely representable Boolean algebras is precisely the class of atomic Boolean algebras, and hence is elementary [6]. arXiv:1201.2331v3 [math.RA] 30 Aug 2016 This result is not obvious as the usual definition of a complete representation is thoroughly second order. -
(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. -
Section 17.5. the Carathéodry-Hahn Theorem: the Extension of A
17.5. The Carath´eodory-Hahn Theorem 1 Section 17.5. The Carath´eodry-Hahn Theorem: The Extension of a Premeasure to a Measure Note. We have µ defined on S and use µ to define µ∗ on X. We then restrict µ∗ to a subset of X on which µ∗ is a measure (denoted µ). Unlike with Lebesgue measure where the elements of S are measurable sets themselves (and S is the set of open intervals), we may not have µ defined on S. In this section, we look for conditions on µ : S → [0, ∞] which imply the measurability of the elements of S. Under these conditions, µ is then an extension of µ from S to M (the σ-algebra of measurable sets). ∞ Definition. A set function µ : S → [0, ∞] is finitely additive if whenever {Ek}k=1 ∞ is a finite disjoint collection of sets in S and ∪k=1Ek ∈ S, we have n n µ · Ek = µ(Ek). k=1 ! k=1 [ X Note. We have previously defined finitely monotone for set functions and Propo- sition 17.6 gives finite additivity for an outer measure on M, but this is the first time we have discussed a finitely additive set function. Proposition 17.11. Let S be a collection of subsets of X and µ : S → [0, ∞] a set function. In order that the Carath´eodory measure µ induced by µ be an extension of µ (that is, µ = µ on S) it is necessary that µ be both finitely additive and countably monotone and, if ∅ ∈ S, then µ(∅) = 0. -
Real Analysis II, Winter 2018
Real Analysis II, Winter 2018 From the Finnish original “Moderni reaalianalyysi”1 by Ilkka Holopainen adapted by Tuomas Hytönen February 22, 2018 1Version dated September 14, 2011 Contents 1 General theory of measure and integration 2 1.1 Measures . 2 1.11 Metric outer measures . 4 1.20 Regularity of measures, Radon measures . 7 1.31 Uniqueness of measures . 9 1.36 Extension of measures . 11 1.45 Product measure . 14 1.52 Fubini’s theorem . 16 2 Hausdorff measures 21 2.1 Basic properties of Hausdorff measures . 21 2.12 Hausdorff dimension . 24 2.17 Hausdorff measures on Rn ...................... 25 3 Compactness and convergence of Radon measures 30 3.1 Riesz representation theorem . 30 3.13 Weak convergence of measures . 35 3.17 Compactness of measures . 36 4 On the Hausdorff dimension of fractals 39 4.1 Mass distribution and Frostman’s lemma . 39 4.16 Self-similar fractals . 43 5 Differentiation of measures 52 5.1 Besicovitch and Vitali covering theorems . 52 1 Chapter 1 General theory of measure and integration 1.1 Measures Let X be a set and P(X) = fA : A ⊂ Xg its power set. Definition 1.2. A collection M ⊂ P (X) is a σ-algebra of X if 1. ? 2 M; 2. A 2 M ) Ac = X n A 2 M; S1 3. Ai 2 M, i 2 N ) i=1 Ai 2 M. Example 1.3. 1. P(X) is the largest σ-algebra of X; 2. f?;Xg is the smallest σ-algebra of X; 3. Leb(Rn) = the Lebesgue measurable subsets of Rn; 4. -
EXISTENCE of HAAR MEASURE Most of the Measure Theory We've Done in This Class Has Been Within Subsets of Rn, Even Though Measu
EXISTENCE OF HAAR MEASURE ARUN DEBRAY NOVEMBER 19, 2015 Abstract. In this presentation, I will prove that every compact topological group has a unique left-invariant measure with total measure 1. This presentation is for UT’s real analysis prelim class. Most of the measure theory we’ve done in this class has been within subsets of Rn, even though measures are very general tools. Today, we will talk about a measure defined on a larger class of spaces, which generalizes the usual Lesbegue measure. I will define and prove its existence; Spencer will prove its uniqueness and provide some interesting examples; and Gill will talk about an application to harmonic analysis. Definition. A topological group is a topological space G with a group structure: an identity, an associative multiplication map, and an inverse map, such that multiplication G G G and inversion G G are both continuous. × ! ! There are many examples, including Rn under addition; all Lie groups; and all finite groups (with the discrete topology). Since a topological group G has a topology, we can talk about the σ-algebra of Borel sets on it, as usual generated by the open sets. But the group structure means we can also talk about left- and right-invariance: for every g G, we have continuous maps ` : G G and r : G G, sending x gx and x xg, respectively. 2 g ! g ! 7! 7! These should be read “left (resp. right) translation by g” (or “multiplication,” or “action”). Often, we want something to be invariant under these maps. Specifically, we say that a measure is left-invariant if µ(S) = µ(g S) for all g G, and define right-invariance similarly. -
Rings of Integer-Valued Continuous Functions
RINGS OF INTEGER-VALUED CONTINUOUS FUNCTIONS BY R. S. PIERCE« Introduction. The purpose of this paper is to study the ring C(X, Z) of all integer-valued continuous functions on a topological space X. Our subject is similar in many ways to the ring C(X) of all real-valued continuous functions on X. It is not surprising therefore that the development of the paper closely follows the theory of C(X). During the past twenty years extensive work has been done on the ring C(X). The pioneer papers in the subject are [8] for compact X and [3] for arbitrary X. A significant part of this work has recently been summarized in the book [2]. Concerning the ring C(X, Z), very little has been written. This is natural, since C(X, Z) is less important in problems of topology and analy- sis than C(X). Nevertheless, for some problems of topology, analysis and algebra, C(X, Z) is a useful tool. Moreover, a comparison of the theories of C(X) and C(X, Z) should illuminate those aspects of the theory of C(X) which derive from the special properties of the field of real numbers. For these reasons it seems worthwhile to devote some attention to C(X, Z). The paper is divided into six sections. The first of these treats topological questions. An analogue of the Stone-Cech compactification is developed and studied. In §2, the ideals in C(X, Z) are related to the filters in a certain lattice of sets. The correspondence is similar to that which exists between the ideals of C(X) and the filters in the lattice of zero sets of continuous functions on X. -
5.2 Complex Borel Measures on R
MATH 245A (17F) (L) M. Bonk / (TA) A. Wu Real Analysis Contents 1 Measure Theory 3 1.1 σ-algebras . .3 1.2 Measures . .4 1.3 Construction of non-trivial measures . .5 1.4 Lebesgue measure . 10 1.5 Measurable functions . 14 2 Integration 17 2.1 Integration of simple non-negative functions . 17 2.2 Integration of non-negative functions . 17 2.3 Integration of real and complex valued functions . 19 2.4 Lp-spaces . 20 2.5 Relation to Riemann integration . 22 2.6 Modes of convergence . 23 2.7 Product measures . 25 2.8 Polar coordinates . 28 2.9 The transformation formula . 31 3 Signed and Complex Measures 35 3.1 Signed measures . 35 3.2 The Radon-Nikodym theorem . 37 3.3 Complex measures . 40 4 More on Lp Spaces 43 4.1 Bounded linear maps and dual spaces . 43 4.2 The dual of Lp ....................................... 45 4.3 The Hardy-Littlewood maximal functions . 47 5 Differentiability 51 5.1 Lebesgue points . 51 5.2 Complex Borel measures on R ............................... 54 5.3 The fundamental theorem of calculus . 58 6 Functional Analysis 61 6.1 Locally compact Hausdorff spaces . 61 6.2 Weak topologies . 62 6.3 Some theorems in functional analysis . 65 6.4 Hilbert spaces . 67 1 CONTENTS MATH 245A (17F) 7 Fourier Analysis 73 7.1 Trigonometric series . 73 7.2 Fourier series . 74 7.3 The Dirichlet kernel . 75 7.4 Continuous functions and pointwise convergence properties . 77 7.5 Convolutions . 78 7.6 Convolutions and differentiation . 78 7.7 Translation operators . -
Math 595: Geometric Measure Theory
MATH 595: GEOMETRIC MEASURE THEORY FALL 2015 0. Introduction Geometric measure theory considers the structure of Borel sets and Borel measures in metric spaces. It lies at the border between differential geometry and topology, and services a variety of areas: partial differential equations and the calculus of variations, geometric function theory, number theory, etc. The emphasis is on sets with a fine, irregular structure which cannot be well described by the classical tools of geometric analysis. Mandelbrot introduced the term \fractal" to describe sets of this nature. Dynamical systems provide a rich source of examples: Julia sets for rational maps of one complex variable, limit sets of Kleinian groups, attractors of iterated function systems and nonlinear differential systems, and so on. In addition to its intrinsic interest, geometric measure theory has been a valuable tool for problems arising from real and complex analysis, harmonic analysis, PDE, and other fields. For instance, rectifiability criteria and metric curvature conditions played a key role in Tolsa's resolution of the longstanding Painlev´eproblem on removable sets for bounded analytic functions. Major topics within geometric measure theory which we will discuss include Hausdorff measure and dimension, density theorems, energy and capacity methods, almost sure di- mension distortion theorems, Sobolev spaces, tangent measures, and rectifiability. Rectifiable sets and measures provide a rich measure-theoretic generalization of smooth differential submanifolds and their volume measures. The theory of rectifiable sets can be viewed as an extension of differential geometry in which the basic machinery and tools of the subject (tangent spaces, differential operators, vector bundles) are replaced by approxi- mate, measure-theoretic analogs.