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Fubini’s Theorem

Dalam dokumen Essentials of Integration Theory for Analysis (Halaman 113-119)

Chapter 4 Products of Measures

4.1 Fubini’s Theorem

The key to the construction of µ1×µ2 is found in the following function analogue of Λ-systems (cf. Lemma 2.1.12). Namely, given a spaceE, say that a collectionL of functionsf :E−→(−∞,∞] is avector semi-lattice if (a) Bothf+ andf are in Lwheneverf ∈ L.

(b) For boundedf, g∈ L withf ≤g, g−f ∈ L.

(c) Forα, β ∈[0,∞) andf, g∈ L,αf+βg∈ L.

(d) For{fn: n≥1} ⊆ Lwith 0≤fn%f, f ∈ Lwheneverf is bounded.

A sub-collectionKof a vector semi-latticeLis called anL-system ifKis a vector semi-lattice with the additional property that

(d0) 1∈ K and, for{fn : n≥ 1} ⊆ K, 0≤fn % f =⇒ f ∈ K whenever f ∈ L.

The analogue of Lemma 2.1.12 in this context is the following.

Lemma 4.1.1. Let C be a Π-system that generates the σ-algebra B over E, and let L be a semi-lattice of functions f : E −→ (−∞,∞]. If K is an L-system for which 1Γ ∈ K wheneverΓ ∈ C, thenK contains every f ∈ L that is measurable on (E,B).

Proof: First note that {Γ ⊆ E : 1Γ ∈ K} is a Λ-system that contains C.

Hence, by Lemma 2.1.12,1Γ∈ Kfor every Γ∈ B. Combined with (c) above, this means that K contains every non-negative, measurable, simple function on (E,B).

DOI 10.1007/978-1-4614-1135-2_4, © Springer Science+Business Media, LLC 2011

D.W. Stroock, Essentials of Integration Theory for Analysis, Graduate Texts in Mathematics 262, 100

Next, suppose thatf ∈ Lis measurable on (E,B). Then, by (a), both f+ andfare elements ofL, and so, by (c), it is enough to show thatf+, f∈ K in order to know that f ∈ K. Thus, without loss of generality, assume that f ∈ L is a non-negative measurable function on (E,B). But in that case f is the non-decreasing limit of non-negative measurable simple functions, and therefore, by the preceding and (d0),f ∈ K.

The power of Lemma 4.1.1 to handle questions involving products is already apparent in the following.

Lemma 4.1.2. Let(E1,B1)and(E2,B2)be measurable spaces, and suppose that f is an R-valued measurable function on(E1×E2,B1× B2). Then for each x1 ∈ E1 and x2 ∈ E2, f(x1,·) and f(·, x2) are measurable functions on(E2,B2)and(E1,B1), respectively. Next, suppose thatµi,i∈ {1,2}, is a finite measure on (Ei,Bi). Then for every non-negative, measurable function f on(E1×E2,B1× B2), the functions

Z

E2

f(·, x22(dx2) and Z

E1

f(x1,·)µ1(dx1) are measurable on(E1,B1)and(E2,B2), respectively.

Proof: Clearly, by the Monotone Convergence Theorem, it is enough to check all these assertions whenf is bounded.

LetLbe the collection of all bounded functions onE1×E2, and defineKto be theB1× B2-measurable elements ofLthat have all the asserted properties.

It is clear that1Γ1×Γ2 ∈ Kfor all Γi∈ Bi, and it is easy to check thatK is an L-system. Hence, by Lemma 4.1.1 withC=

Γ1×Γ2: Γi∈ Bi fori∈ {1,2} , we are done.

Lemma 4.1.3. Given a pair (E1,B1, µ1)and (E2,B2, µ2) of finite measure spaces, there exists a unique measureν on(E1×E2,B1× B2)for which

ν(Γ1×Γ2) =µ1122) for all Γi∈ Bi.

Moreover, for every non-negative, measurable functionfon(E1×E2,B1×B2),

(4.1.4)

Z

E1×E2

f(x1, x2)ν(dx1×dx2)

= Z

E2

Z

E1

f(x1, x21(dx1)

µ2(dx2)

= Z

E1

Z

E2

f(x1, x22(dx2)

µ1(dx1).

Proof: The uniqueness ofν is guaranteed by Theorem 2.1.13. To prove the existence ofν, define

ν1,2(Γ) = Z

E2

Z

E1

1Γ(x1, x21(dx1)

µ2(dx2)

4 Products of Measures and

ν2,1(Γ) = Z

E1

Z

E2

1Γ(x1, x22(dx2)

µ1(dx1)

for Γ ∈ B1× B2. Using the Monotone Convergence Theorem, one sees that both ν1,2 and ν2,1 are finite measures on (E1×E2,B1× B2). Moreover, by the same sort of argument as was used to prove Lemma 4.1.2, for every non- negative measurable functionf on (E1×E2,B1× B2),

Z

f dν1,2= Z

E1

Z

E2

f(x1, x21(dx1)

µ2(dx2) and

Z

f dν2,1= Z

E2

Z

E1

f(x1, x22(dx2)

µ1(dx1).

Finally, sinceν1,21×Γ2) =µ(Γ1)µ(Γ2) =ν2,11×Γ2) for all Γi∈ Bi, we see that both ν1,2 andν2,1 fulfill the requirements placed on ν. Hence, not only does ν exist, but it is also equal to bothν1,2 and ν2,1; and so the preceding equalities lead to (4.1.4).

Recall that a measure space (E,B, µ) is said to beσ-finite ifEis the count- able union of B-measurable sets having finiteµ-measure.

Theorem 4.1.5 (Tonelli’s Theorem). Let(E1,B1, µ1)and(E2,B2, µ2)be σ-finite measure spaces. Then there is a unique measureνon(E1×E2,B1×B2) such that ν(Γ1×Γ2) = µ1122) for all Γi ∈ Bi. In addition, for every non-negative measurable functionf on(E1×E2,B1× B2),R

f(·, x22(dx2) andR

f(x1,·)µ1(dx1)are measurable on(E1,B1)and (E2,B2), respectively, and(4.1.4)continues to hold.

Proof: Choose {Ei,n : n≥1} ⊆ Bi fori ∈ {1,2} such that µi(Ei,n)<∞ for each n≥1 andEi =S

n=1Ei,n. Without loss of generality, assume that Ei,m∩Ei,n=∅ form6=n. For eachn∈Z+, defineµi,ni) =µii∩Ei,n), Γi∈ Bi; and, for (m, n)∈Z+2,letν(m,n)on (E1×E2,B1× B2) be the measure constructed fromµ1,m andµ2,n as in Lemma 4.1.3.

Clearly, by Lemma 4.1.2, for any non-negative measurable function f on (E1×E2,B1× B2),

Z

E2

f(·, x22(dx2) =

X

n=1

Z

E2,n

f(·, x22,n(dx2)

is measurable on (E1,B1); and, similarly, R

E1f(x1, ·)µ1(dx1) is measurable on (E2,B2). Finally, the map Γ ∈ B1× B2 7−→ P

m,n=1ν(m,n)(Γ) defines a measure ν0 on (E1×E2,B1× B2), and it is easy to check that ν0 has all the required properties. At the same time, if ν is any other measure on (E1×E2,B1× B2) for whichν(Γ1×Γ2) =µ1122), Γi∈ Bi, then, by the

uniqueness assertion in Lemma 4.1.3, for each (m, n)∈Z+2,ν coincides with ν(m,n)onB1× B2

E1,m×E2,n

and is therefore equal toν0onB1× B2. The measure ν constructed in Theorem 4.1.5 is called theproduct of µ1

and µ2and is denoted by µ1×µ2.

Theorem 4.1.6 (Fubini’s Theorem). Let(E1,B1, µ1)and(E2,B2, µ2)be σ-finite measure spaces andf a measurable function on (E1×E2,B1× B2).

Thenf isµ1×µ2-integrable if and only if Z

E1

Z

E2

|f(x1, x2)|µ2(dx2)

µ1(dx1)<∞ if and only if

Z

E2

Z

E1

|f(x1, x2)|µ1(dx1)

µ2(dx2)<∞.

Next, set

Λ1=

x1∈E1: Z

E2

|f(x1, x2)|µ2(dx2)<∞

and

Λ2=

x2∈E2: Z

E1

|f(x1, x2)|µ1(dx1)<∞

; and define fi onEi,i∈ {1,2}, by

f1(x1) = R

E2f(x1, x22(dx2) if x1∈Λ1

0 otherwise

and

f2(x2) = R

E1f(x1, x21(dx1) if x2∈Λ2

0 otherwise.

Then fi is an R-valued, measurable function on Ei,Bi

. Finally, if f is µ1×µ2-integrable, thenµii{) = 0,fi∈L1i;R), and

Z

Ei

fi(xii(dxi) = Z

E1×E2

f(x1, x2) µ1×µ2

(dx1×dx2) fori∈ {1,2}.

Proof: The first assertion is an immediate consequence of Theorem 4.1.5.

Moreover, because Λi ∈ Bi, it is easy (cf. Lemma 4.1.2) to check thatfi is an R-valued, measurable function on (Ei,Bi). Finally, iff isµ1×µ2-integrable,

4 Products of Measures

then, by the first assertion,µi{i) = 0 andfi∈L1i;R). Hence, by Theorem 4.1.5 applied to f+and f, we see that

Z

E1×E2

f(x1, x2) (µ1×µ2)(dx1×dx2)

= Z

Λ1×E2

f+(x1, x2) (µ1×µ2)(dx1×dx2)

− Z

Λ1×E2

f(x1, x2) (µ1×µ2)(dx1×dx2)

= Z

Λ1

Z

E2

f+(x1, x21(dx2)

µ1(dx1)

− Z

Λ1

Z

E2

f(x1, x22(dx2)

µ1(dx1)

= Z

Λ1

f1(x11(dx1) = Z

E1

f1(x11(dx1), and the same line of reasoning applies to f2.

One may well wonder why I have separated the statement in Tonelli’s The- orem from the statement in Fubini’s Theorem. The reason is that Tonelli’s Theorem requires no a priori information about integrability. Thus, for ex- ample, Tonelli’s Theorem allowed me to show that f is µ1×µ2-integrable if and only if

Z

E2

Z

E1

|f(x1, x2)|µ1(dx1)

µ2(dx2)

∧ Z

E1

Z

E2

|f(x1, x2)|µ2(dx2)

µ1(dx1)

<∞.

Exercises for §4.1

Exercise 4.1.7. Let (E,B, µ) be a σ-finite measure space. Given a non- negative measurable functionf on (E,B), define

Γ(f) =

(x, t)∈E×[0,∞) :t≤f(x) and

Γ(fb ) =

(x, t)∈E×[0,∞) :t < f(x) .

Show that both Γ(f) andΓ(f) are elements ofb B × B[0,∞) and, in addition, that

(∗) µ×λR Γ(fb )

= Z

E

f dµ=µ×λR Γ(f) .

Clearly (∗) can be interpreted as the statement that the integral of a non- negative function is the area under its graph.

Hint: In proving measurability, consider the function (x, t)∈E×[0,∞)7−→

f(x)−t∈(−∞,∞], and get (∗) as an application of Tonelli’s Theorem.

Exercise 4.1.8. Let (E1,B1, µ1) and (E2,B2, µ2) beσ-finite measure spaces and assume that, fori∈ {1,2},Bi=σ(Ei;Ci), whereCiis a Π-system contain- ing a sequence {Ei,n : n≥1} for which Ei =S

n=1Ei,n and µi(Ei,n)<∞, n≥1. Show that ifνis a measure on (E1×E2,B1×B2) with the property that ν(Γ1×Γ2) =µ1122) for all Γi∈ Ci, thenν =µ1×µ2. Use this fact to show that, for anyM, N ∈Z+RM+NRM×λRN onBRM+N =BRM× BRN. Exercise 4.1.9. Let (E1,B1, µ1) and (E2,B2, µ2) beσ-finite measure spaces.

Given Γ∈ B1× B2, define Γ(1)(x2)≡

x1∈E1: x1, x2

∈Γ for x2∈E2 and

Γ(2)(x1)≡

x2∈E2: x1, x2

∈Γ for x1∈E1.

If i 6= j, check both that Γ(i)(xj) ∈ Bi for each xj ∈ Ej and that xj ∈ Ej 7−→ µi Γ(i)(xj)

∈ [0,∞] is measurable on (Ej,Bj). Finally, show that µ1×µ2(Γ) = 0 if and only ifµi Γ(i)(xj)

= 0 for µj-almost everyxj ∈Ej, and conclude that µ1 Γ(1)(x2)

= 0 forµ2-almost every x2 ∈E2 if and only ifµ2 Γ(2)(x1)

= 0 forµ1-almost everyx1∈E1. In other words, Γ∈ B1× B2

hasµ1×µ2-measure 0 if and only ifµ1-almost everyvertical slice(µ2-almost every horizontal slice) has µ2-measure (µ1-measure) 0. In particular, µ2- almost every horizontal slice has µ1-measure 0 if and only ifµ1-almost every vertical slice has µ2-measure 0.

Exercise 4.1.10. The condition that the measure spaces of which one is taking a product beσ-finite is essential if one wants to carry out the program in this section. To see this, let E1=E2= (0,1) andB1=B2 =B(0,1). Take µ1 to be the counting measure (i.e.,µ(Γ) = card(Γ)) andµ2 to be Lebesgue measure λ(0,1) on (E(0,1),B(0,1)). Show that there is a set Γ∈ B1× B2 such that

Z

E2

1Γ(x1, x22(dx2) = 0 for everyx1∈E1 but

Z

E1

1Γ(x1, x21(dx1) = 1 for everyx2∈E2.

Notice that what fails is not so much the existence statement as the uniqueness in Lemma 4.1.3.

4 Products of Measures

Dalam dokumen Essentials of Integration Theory for Analysis (Halaman 113-119)