DISINTEGRATION OF MEASURES



Similar documents
How To Find Out How To Calculate A Premeasure On A Set Of Two-Dimensional Algebra

Extension of measure

and 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

Notes on metric spaces

FUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES

Mathematical Methods of Engineering Analysis

MA651 Topology. Lecture 6. Separation Axioms.

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES

Lecture Notes on Measure Theory and Functional Analysis

Mathematics for Econometrics, Fourth Edition

MEASURE AND INTEGRATION. Dietmar A. Salamon ETH Zürich

SOLUTIONS TO ASSIGNMENT 1 MATH 576

Lecture 15 An Arithmetic Circuit Lowerbound and Flows in Graphs

INTEGRAL OPERATORS ON THE PRODUCT OF C(K) SPACES

1 = (a 0 + b 0 α) (a m 1 + b m 1 α) 2. for certain elements a 0,..., a m 1, b 0,..., b m 1 of F. Multiplying out, we obtain

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 3. Spaces with special properties

1. Prove that the empty set is a subset of every set.

CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e.

Mathematics Course 111: Algebra I Part IV: Vector Spaces

16.3 Fredholm Operators

Metric Spaces. Chapter 1

Separation Properties for Locally Convex Cones

ON COMPLETELY CONTINUOUS INTEGRATION OPERATORS OF A VECTOR MEASURE. 1. Introduction

BANACH AND HILBERT SPACE REVIEW

LEARNING OBJECTIVES FOR THIS CHAPTER

INTRODUCTORY SET THEORY

it is easy to see that α = a

Chapter 5. Banach Spaces

Follow links for Class Use and other Permissions. For more information send to:

ON SEQUENTIAL CONTINUITY OF COMPOSITION MAPPING. 0. Introduction

PROBLEM SET 6: POLYNOMIALS

DEGREES OF ORDERS ON TORSION-FREE ABELIAN GROUPS

GENERIC COMPUTABILITY, TURING DEGREES, AND ASYMPTOTIC DENSITY

9 More on differentiation

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics

Metric Spaces. Chapter Metrics

MATH 425, PRACTICE FINAL EXAM SOLUTIONS.

No: Bilkent University. Monotonic Extension. Farhad Husseinov. Discussion Papers. Department of Economics

T ( a i x i ) = a i T (x i ).

Turing Degrees and Definability of the Jump. Theodore A. Slaman. University of California, Berkeley. CJuly, 2005

Prime Numbers and Irreducible Polynomials

PSEUDOARCS, PSEUDOCIRCLES, LAKES OF WADA AND GENERIC MAPS ON S 2

Integer roots of quadratic and cubic polynomials with integer coefficients

I. Pointwise convergence

An example of a computable

Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011

A CHARACTERIZATION OF C k (X) FOR X NORMAL AND REALCOMPACT

The Banach-Tarski Paradox

On a conjecture by Palis

Point Set Topology. A. Topological Spaces and Continuous Maps

FUNCTIONAL ANALYSIS LECTURE NOTES CHAPTER 2. OPERATORS ON HILBERT SPACES

FIRST YEAR CALCULUS. Chapter 7 CONTINUITY. It is a parabola, and we can draw this parabola without lifting our pencil from the paper.

1 if 1 x 0 1 if 0 x 1

Lebesgue Measure on R n

Lectures 5-6: Taylor Series

Fixed Point Theorems

n 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

F. ABTAHI and M. ZARRIN. (Communicated by J. Goldstein)

ON GALOIS REALIZATIONS OF THE 2-COVERABLE SYMMETRIC AND ALTERNATING GROUPS

Finite dimensional topological vector spaces

A UNIQUENESS RESULT FOR THE CONTINUITY EQUATION IN TWO DIMENSIONS. Dedicated to Constantine Dafermos on the occasion of his 70 th birthday

THE FUNDAMENTAL THEOREM OF ALGEBRA VIA PROPER MAPS

x a x 2 (1 + x 2 ) n.

1 Norms and Vector Spaces

INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS

Lecture 13: Martingales

ALMOST COMMON PRIORS 1. INTRODUCTION

The Ideal Class Group

Lecture 4: AC 0 lower bounds and pseudorandomness

INTRODUCTION TO TOPOLOGY

Sums of Independent Random Variables

Reference: Introduction to Partial Differential Equations by G. Folland, 1995, Chap. 3.

Recall that two vectors in are perpendicular or orthogonal provided that their dot

University of Miskolc

Convex analysis and profit/cost/support functions

Inner Product Spaces

Handout #1: Mathematical Reasoning

CHAPTER 1 BASIC TOPOLOGY

Basic Measure Theory. 1.1 Classes of Sets

MATH10212 Linear Algebra. Systems of Linear Equations. Definition. An n-dimensional vector is a row or a column of n numbers (or letters): a 1.

Ideal Class Group and Units

5. Factoring by the QF method

Unique Factorization

HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)!

GROUPS ACTING ON A SET

Probability: Theory and Examples. Rick Durrett. Edition 4.1, April 21, 2013

SET-THEORETIC CONSTRUCTIONS OF TWO-POINT SETS

NOTES ON LINEAR TRANSFORMATIONS

SHARP BOUNDS FOR THE SUM OF THE SQUARES OF THE DEGREES OF A GRAPH

Columbia University in the City of New York New York, N.Y

Metric Spaces. Lecture Notes and Exercises, Fall M.van den Berg

Introduction to Finite Fields (cont.)

How To Prove The Dirichlet Unit Theorem

1. (First passage/hitting times/gambler s ruin problem:) Suppose that X has a discrete state space and let i be a fixed state. Let

God created the integers and the rest is the work of man. (Leopold Kronecker, in an after-dinner speech at a conference, Berlin, 1886)

THE KADISON-SINGER PROBLEM IN MATHEMATICS AND ENGINEERING: A DETAILED ACCOUNT

H/wk 13, Solutions to selected problems

Transcription:

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 that: (i) each λ y is a sigma-finite measure and λ y ({x : T(x) y}) = 0 for almost every x. and for each nonnegative measurable function on f on : : (ii) The function y f(x)dλ y (x) is µ-measurable and (iii) f(x)dλ(x) = ( f(x)dλ y(x) ) dµ(y). Our aim is to establish the following: Theorem 2. Let λ be a sigma-finite regular Borel measure on a metric space and let T be measurable map from into (, M, µ), where µ is sigma-finite and such that T λ << µ. If M is countably generated and contains all singletons, then λ has a (T, µ) disintegration. If {λ y}, {λ y } are two such disintegrations then λ y = λ y almost everywhere, further if T λ = µ, then λ y is a probability measure for almost every y. Lemma 3. Let be a compact metric space, then there exists a countable set C C(, [0, )) which is closed under addition and scaling by non-negative rational numbers and contains the constant function 1, with the following property. If l: C [0, ) satisfies l(f+g) = l(f)+l(g), and l(qf) = ql(f) for every q Q [0, ), f, g C then there exists a unique positive regular Borel measure µ on such that l(f) = f dµ. Proof. Since is compact metric we know that C() and hence C(, [0, )) is separable (since subsets of separable metric spaces are separable) and thus we can find a countable dense subset of C(, [0, )) which contains 1, let C be the nonnegative functions in the Q-linear span of such a set. Then C is countable and contained in C(, [0, )), is closed under addition and positive scaling, and the closed R-linear span of C is C(, R). Suppose l : C [0, ) is additive and l(qf) = ql(f) for q Q [0, ). Extend l to C C (which is the Q-linear span of C) by l(g f) = l(g) l(f) for f, g C. If g f = g f, then g + f = g + f and applying l gives l(g) + l(f ) = l(g ) + l(f) subtracting l(g) l(f) = l(g ) l(f ) so the extension is well-defined. It is easy to see that l is now Q-linear and additive. We claim that there exists some constant such that l(f) f, for all f C Date: December 16, 2010. 1

2 BEN HES (where the norm is the supremum norm). Indeed for fixed f C we can find q Q such that f q 2 f, then q f is nonnegative. Since C is by construction the nonnegative elements in its closed linear span we have that q f C and so 0 l(q f) = l(q) l(f) = ql(1) l(f) 2 f l(1) l(f) thus 0 l(f) 2 f l(1). It then follows that there exists a constant (possibly different than the first) so that l(f) f for all f C C. This implies that l is a uniformly continuous map from C C into R, and thus by completeness of R extends to a continuous map l: C(, R) R. Existence of µ now follows from the Riesz Representation Theorem, and uniqueness is clear since the closed linear span of C is C(). We now establish an easier version of Theorem 2, and reduce Theorem T : disint to this case. Theorem 4. Let λ be a regular Borel measure on a compact metric space and let T be measurable map from into (, M, µ) wher µ is finite and such that T λ << µ. If M is countably generated and contains all singletons, then λ has a (T, µ) disintegration. If {λ y}, {λ y } are two such disintegrations then λ y = λ y almost everywhere, further if µ is a probability measures and T λ = µ, then λ y is a probability measure for almost every y. Proof. Define a measure ν on B M (here B denotes the Borel sets) by ν(e) = χ E (x, Tx)dλ(x) using the monotone convergence theorem and that λ is finite it is easy to that ν is a finite measure. By standard arguments, f dν(x, y) = f(x, T x)dλ(x) for any measurable h: [0, ). Let Γ = {(x, y) : y = T(x)} we claim that Γ is measurable. To see this, let be a countable family which generates M. Let B be the algebra over Q generated by {χ : }. Replacing with the collection of sets whose characteristic function is in B, we see that we may assume that is an algebra, i.e. is closed under finite unions, complements and contains and. We claim that (1) {y} = B,y B B. Indeed, let be the set on the right-hand side. If {y}, let z \ {y}, then every set in which contains y also contains z, but by taking complements it also easy to see that every set in which contains z must contain y. Thus δ y and 1 2 δ y + 1 2 δ z are two measures which agree on. Since generates M as a sigmaalgebra, the uniqueness in Caratheodory s theorem implies that δ y = 1 2 δ y + 1 2 δ z on M. But this is impossible since {y} M. This establishes (1), thus Γ = {(x, y) : x T 1 (), y }. Thus Γ and hence Γ c is measurable and ν(γ c ) = χ Γ c(x, Tx)dλ(x) = 0.

DISINTEGRTION OF MESURES 3 Let C C(, [0, )) be as in Lemma 3. For fixed f C we have a measure ν f on M where ν f (E) = f(x)χ E (y)dν(x, y) = f(x)χ E (Tx)dλ(x). If µ(e) = 0 then we have ν f (E) f χ E (Tx)dλ x = f (T λ)(e) = 0 since T λ << µ. Let λ y f be the value of the Radon-Nikodym derivative of ν f with respect to µ at y. Since C is countable we may choose a co-null subset 0 of such that f λ y f is additive and λ y (qf) = qλ y f for all q Q [0, ) and y 0. Thus by the Lemma, for y 0 there exists a unique measure λ y on such that f(x)dλ y (x) = λ yf. In particular on 0 we have that λ y () = λ y1 = dν 1 dµ = dt λ dµ which is 1 if dt λ = dµ. So λ y is a probability measure if T λ = µ. Setting λ y = 0 off 0 we claim that {λ y } y is the desired disintegration. We show a more general version of (ii) namely we show that for f : [0, ), g: [0, ) measurable that (ii) f(x)g(y)dλ y (x)dµ(y) is measurable and (iii) f(x)g(y)dλ y (x)dµ(y) = f(x)g(y) dν(x, y) Let us first verify that (ii) and (iii) hold for f continuous. By linearity, and our choice of C, we see that it suffices to show (ii) and (iii) for f in C. For f C, and almost every y f(x)g(y)dλ y (x) = g(y)λ yf and is thus measurable. Further for f C, f(x)g(y)dλ y (x)dµ(y) = g(y) dν f dµ (y)dµ(y) = f(x)g(y) dν(x, y). g(y)dν f (y) = This verifies (ii) and (iii) for f C(). We now verify (ii) and (iii) for characteristic functions of Borel sets. Let N be the class of Borel sets in satisfying (ii) and (iii) for all g: [0, ) measurable. We have that, N since we verified (ii), (iii) for constant functions. By linearity and the monotone convergence theorem we have that N is closed under differences and disjoint unions so N is a sigma-algebra. Thus we only have to verify (ii) and (iii) for χ U, where U is open, in fact since is a compact metric space and thus second countable. We only have to verify (ii) and (iii) for χ B(x,ε) where x and ε > 0. Since is compact by Uryshon s Lemma we can find a sequence (f n ) n 1 in C() such that 0 f n 1, f B(x,ε) n = 1 and

4 BEN HES f n = 0 outside B(x, ε + 1/n). Then f n χ B(ε,x) pointwise and is dominated by 1 thus a double use of the dominated convergence theorem implies (ii) and (iii) for B(ε, x). n entirely similar argument using that B M is generated by sets of the form B, B, B M establishes the stronger claim that f(x, y) = f(x, y)dλ y (x)dµ(y) for f non-negative and B M measurable. In particular by what we saw earlier 0 = ν(γ c ) = χ Γ c(x, y)dλ y (x)dµ(y) = λ y ({x : T(x) y})dµ(y) so that λ y ({x : T(x) y}) = 0 for µ-almost every y. Finally we have to establish uniqueness. If {λ y }, { λ y } are two disintegrations, by symmetry it suffices to show that λ y λ y almost everywhere. Fix f C, and let be measurable. Since λ y, λ y are concentrated on {x : T(x) = y} we have f(x)dλ y (x)dµ(y) = f(x)χ (y)dλ y (x)dµ(y) = f(x)χ (Tx)dλ y (x)dµ(y) = So f(x)χ (Tx)dλ(x) = f(x)dλ y (x) = f(x)d λ y (x). f(x)d λ y (x) for µ almost all y. Since there are countably many f C we can find a conull 0 such that the above holds for all y 0 and f C. Since the closed linear span of C is C() we have that f(x)dλ y (x) = f(x)d λ y (x) for all y 0. So λ y = λ y for all y 0. We are now in a position to prove Theorem 2. Proof of Theorem 2. First assume that µ is finite. In this case, by regularity and since λ is sigma-finite we can find a null set N in and countably many disjoint compact sets K 1, K 2,... such that = n=1k n N applying Theorem 4 to each K n gives a disintegration, add them all together to get a disintegration for. pplying uniqueness to each K n gives uniqueness of the disintegration as well. The sigma-finite case is similar, just reduce it to the finite case. For the last part, assume that T λ = µ. We have for all that µ() = χ (y)dt λ(y) = χ (Tx)dλ(x) = χ (Tx)dλ y (x)dµ(y) since λ y is concentrated on {x : T(x) = y} the above is χ (y)dλ y (x)dµ(y) = λ y ()χ (y)dµ(y) = λ y ()dµ(y).

DISINTEGRTION OF MESURES 5 Thus λ y () have the same integral over any set and thus are equal almost everywhere.