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Mathematics LibreTexts

8.11: The Radon–Nikodym Theorem. Lebesgue Decomposition

( \newcommand{\kernel}{\mathrm{null}\,}\)

I. As you know, the indefinite integral

fdm

is a generalized measure. We now seek conditions under which a given generalized measure μ can be represented as

μ=fdm

for some f (to be found). We start with two lemmas.

Lemma 8.11.1

Let m,μ:M[0,) be finite measures in S. Suppose SM,μS>0 (i.e., μ0) and μ is m-continuous (Chapter 7, §11).

Then there is δ>0 and a set PM such that mP>0 and

(XM)μXδm(XP).

Proof

As m< and μS>0, there is δ>0 such that

μSδmS>0.

Fix such a δ and define a signed measure (Lemma 2 of Chapter 7, §11)

Φ=μδm,

so that

(YM)ΦY=μYδmY;

hence

ΦS=μSδmS>0.

By Theorem 3 in Chapter 7, §11 (Hahn decomposition), there is a Φ-positive set PM with a Φ-negative complement P=SPM.

Clearly, mP>0; for if mP=0, the m-continuity of μ would imply μP=0, hence

ΦP=μPδmP=0,

contrary to ΦPΦS>0.

Also, PY and YM implies ΦY0; so by (1),

0μYδmY.

Taking Y=XP, we get

δm(XP)μ(XP)μX,

as required.

Lemma 8.11.2

With m,μ, and S as in Lemma 1, let H be the set of all maps g:SE,M-measurable and nonnegative on S, such that

XgdmμX

for every set X from M.

Then there is fH with

Sfdm=maxgHSgdm.

Proof

H is not empty; e.g., g=0 is in H. We now show that

(g,hH)gh=max(g,h)H.

Indeed, gh is 0 and M-measurable on S, as g and h are.

Now, given XM, let Y=X(g>h) and Z=X(gh). Dropping "dm" for brevity, we have

X(gh)=Y(gh)+Z(gh)=Yg+ZhμY+μZ=μX,

proving (2).

Let

k=supgHSgdmE.

Proceeding as in Problem 13 of Chapter 7, §6, and using (2), one easily finds a sequence \left\{g_{n}\right\} \uparrow, g_{n} \in \mathcal{H}, such that

\lim _{n \rightarrow \infty} \int_{S} g_{n} dm=k.

(Verify!) Set

f=\lim _{n \rightarrow \infty} g_{n}.

(It exists since \left\{g_{n}\right\} \uparrow.) By Theorem 4 in §6,

k=\lim _{n \rightarrow \infty} \int_{S} g_{n}=\int_{S} f.

Also, f is \mathcal{M}-measurable and \geq 0 on S, as all g_{n} are; and if X \in \mathcal{M}, then

(\forall n) \quad \int_{X} g_{n} \leq \mu X;

hence

\int_{X} f=\lim _{n \rightarrow \infty} \int_{X} g_{n} \leq \mu X.

Thus f \in \mathcal{H} and

\int_{S} f=k=\sup _{g \in H} \int_{S} g,

i.e.,

\int_{S} f=\max _{g \in \mathcal{H}} \int_{S} g \leq \mu S<\infty.

This completes the proof.\quad \square

Note 1. As \mu<\infty and f \geq 0, Corollary 1 in §5 shows that f can be made finite on all of S. Also, f is m-integrable on S.

Theorem \PageIndex{1} (Radon-Nikodym)

If (S, \mathcal{M}, m) is a \sigma-finite measure space, if S \in \mathcal{M}, and if

\mu : \mathcal{M} \rightarrow E^{n}\left(C^{n}\right)

is a generalized m-continuous measure, then

\mu=\int f dm \text { on } \mathcal{M}

for at least one map

f : S \rightarrow E^{n}\left(C^{n}\right),

\mathcal{M}-measurable on S.

Moreover, if h is another such map, then m S (f \neq h)=0

The last part of Theorem 1 means that f is "essentially unique." We call f the Radon-Nikodym (RN) derivative of \mu, with respect to m.

Proof

Via components (Theorem 5 in Chapter 7, §11), all reduces to the case

\mu : \mathcal{M} \rightarrow E^{1}.

Then Theorem 4 (Jordan decomposition) in Chapter 7, §11, yields

\mu=\mu^{+}-\mu^{-},

where \mu^{+} and \mu^{-} are finite measures (\geq 0), both m-continuous (Corollary 3 from Chapter 7, §11). Therefore, all reduces to the case 0 \leq \mu<\infty.

Suppose first that m, too, is finite. Then if \mu=0, just take f=0.

If, however, \mu S>0, take f \in \mathcal{H} as in Lemma 2 and Note 1; f is nonnegative, bounded, and \mathcal{M}-measurable on S,

\int f \leq \mu<\infty,

and

\int_{S} f dm=k=\sup _{g \in \mathcal{H}} \int_{S} g dm.

We claim that f is the required map.

Indeed, let

\nu=\mu-\int f dm;

so \nu is a finite m-continuous measure (\geq 0) on \mathcal{M}. (Why?) We must show that \nu=0.

Seeking a contradiction, suppose \nu S>0. Then by Lemma 1, there are P \in \mathcal{M} and \delta>0 such that m P>0 and

(\forall X \in \mathcal{M}) \quad \nu X \geq \delta \cdot m(X \cap P).

Now let

g=f+\delta \cdot C_{P};

so g is \mathcal{M}-measurable and \geq 0. Also,

\begin{aligned}(\forall X \in \mathcal{M}) \quad \int_{X} g=\int_{X} f+\delta \int_{X} C_{P} &=\int_{X} f+\delta \cdot m(X \cap P) \\ & \leq \int_{X} f+\nu(X \cap P) \\ & \leq \int_{X} f+\nu X=\mu X \end{aligned}

by our choice of \delta and \nu. Thus g \in \mathcal{H}. On the other hand,

\int_{S} g=\int_{S} f+\delta \int_{S} C_{P}=k+\delta m P>k,

contrary to

k=\sup _{g \in \mathcal{H}} \int_{S} g.

This proves that \int f=\mu, indeed.

Now suppose there is another map h \in \mathcal{H} with

\mu=\int h d m=\int f d m \neq \infty;

so

\int(f-h) dm=0.

(Why?) Let

Y=S(f \geq h) \text { and } Z=S(f<h);

so Y, Z \in \mathcal{M} (Theorem 3 of §2) and f-h is sign-constant on Y and Z. Also, by construction,

\int_{Y}(f-h) dm=0=\int_{Z}(f-h) dm.

Thus by Theorem 1(h) in §5, f-h=0 a.e. on Y, on Z, and hence on S=Y \cup Z that is,

mS(f \neq h)=0.

Thus all is proved for the case mS<\infty.

Next, let m be \sigma-finite:

S=\bigcup_{k=1}^{\infty} S_{k} \text { (disjoint)}

for some sets S_{k} \in \mathcal{M} with m S_{k}<\infty.

By what was shown above, on each S_{k} there is an \mathcal{M}-measurable map f_{k} \geq 0 such that

\int_{X} f_{k} dm=\mu X

for all \mathcal{M}-sets X \subseteq S_{k}. Fixing such an f_{k} for each k, define f : S \rightarrow E^{1} by

f=f_{k} \quad \text { on } S_{k}, \quad k=1,2, \ldots.

Then (Corollary 3 in §1) f is \mathcal{M}-measurable and \geq 0 on S.

Taking any X \in \mathcal{M}, set X_{k}=X \cap S_{k}. Then

X=\bigcup_{k=1}^{\infty} X_{k} \text { (disjoint)}

and X_{k} \in \mathcal{M}. Also,

(\forall k) \quad \int_{X_{k}} f d m=\int_{X_{k}} f_{k} d m=\mu X_{k}.

Thus by \sigma-additivity (Theorem 2 in §5),

\int_{X} f d m=\sum_{k=1}^{\infty} \int_{X_{k}} f d m=\sum_{k} \mu X_{k}=\mu X<\infty \quad (\mu \text { is finite!}).

Thus f is as required, and its "uniqueness" follows as before.\quad \square

Note 2. By Definition 3 in §10, we may write

"d \mu=f dm"

for

"\int f dm=\mu."

Note 3. Using Definition 2 in §10 and an easy "componentwise" proof, one shows that Theorem 1 holds also with m replaced by a generalized measure s. The formulas

\mu=\int f dm \text { and } mS(f \neq h)=0

then are replaced by

\mu=\int f ds \text { and } v_{s}S(f \neq h)=0.

II. Theorem 1 requires \mu to be m-continuous (\mu \ll m). We want to generalize Theorem 1 so as to lift this restriction. First, we introduce a new concept.

Definition

Given two set functions s, t : \mathcal{M} \rightarrow E\left(\mathcal{M} \subseteq 2^{S}\right), we say that s is t-singular (s \perp t) iff there is a set P \in \mathcal{M} such that v_{t} P=0 and

(\forall X \in \mathcal{M} | X \subseteq-P) \quad s X=0.

(We then briefly say "s resides in P.")

For generalized measures, this means that

(\forall X \in \mathcal{M}) \quad s X=s(X \cap P).

Why?

Corollary \PageIndex{1}

If the generalized measures s, u : \mathcal{M} \rightarrow E are t-singular, so is k s for any scalar k (if s is scalar valued, k may be a vector).

So also are s \pm u, provided t is additive.

Proof

(Exercise! See Problem 3 below.)

Corollary \PageIndex{2}

If a generalized measure s : \mathcal{M} \rightarrow E is t-continuous (s \ll t) and also t-singular (s \perp t), then s=0 on \mathcal{M}.

Proof

As s \perp t, formula (3) holds for some P \in \mathcal{M}, v_{t} P=0. Hence for all X \in \mathcal{M},

s(X-P)=0 \text { (for } X-P \subseteq-P \text{)}

and

v_{t}(X \cap P)=0 \text { (for } X \cap P \subseteq P \text{).}

As s \ll t, we also have s(X \cap P)=0 by Definition 3(i) in Chapter 7, §11. Thus by additivity,

sX=s(X \cap P)+s(X-P)=0,

as claimed.\quad \square

Theorem \PageIndex{2} (Lebesgue decomposition)

Let s, t : \mathcal{M} \rightarrow E be generalized measures.

If v_{s} is t-finite (Definition 3(iii) in Chapter 7, §11), there are generalized measures s^{\prime}, s^{\prime \prime} : \mathcal{M} \rightarrow E such that

s^{\prime} \ll t \text { and } s^{\prime \prime} \perp t

and

s=s^{\prime}+s^{\prime \prime}.

Proof

Let v_{0} be the restriction of v_{s} to

\mathcal{M}_{o}=\left\{X \in \mathcal{M} | v_{t} X=0\right\}.

As v_{s} is a measure (Theorem 1 of Chapter 7, §11), so is v_{0} (for \mathcal{M}_{0} is a \sigma-ring; verify!).

Thus by Problem 13 in Chapter 7, §6, we fix P \in \mathcal{M}_{0}, with

v_{s} P=v_{0} P=\max \left\{v_{s} X | X \in \mathcal{M}_{0}\right\}.

As P \in \mathcal{M}_{0}, we have v_{t} P=0; hence

|sP| \leq v_{s} P<\infty

(for v_{s} is t-finite).

Now define s^{\prime}, s^{\prime \prime}, v^{\prime}, and v^{\prime \prime} by setting, for each X \in \mathcal{M},

\begin{aligned} s^{\prime} X &=s(X-P); \\ s^{\prime \prime} X &=s(X \cap P); \\ v^{\prime} X &=v_{s}(X-P); \\ v^{\prime \prime} X &=v_{s}(X \cap P). \end{aligned}

As s and v_{s} are \sigma-additive, so are s^{\prime}, s^{\prime \prime}, v^{\prime}, and v^{\prime \prime}. (Verify!) Thus s^{\prime}, s^{\prime \prime} : \mathcal{M} \rightarrow E are generalized measures, while v^{\prime} and v^{\prime \prime} are measures (\geq 0).

We have

(\forall X \in \mathcal{M}) \quad s X=s(X-P)+s(X \cap P)=s^{\prime} X+s^{\prime \prime} X;

i.e.,

s=s^{\prime}+s^{\prime \prime}.

Similarly one obtains v_{s}=v^{\prime}+v^{\prime \prime}.

Also, by (5), since X \cap P=\emptyset,

-P \supseteq X \text { and } X \in \mathcal{M} \Longrightarrow s^{\prime \prime} X=0,

while v_{t} P=0 (see above). Thus s^{\prime \prime} is t-singular, residing in P.

To prove s^{\prime} \ll t, it suffices to show that v^{\prime} \ll t (for by (4) and (6), v^{\prime} X=0 implies \left|s^{\prime} X\right|=0).

Assume the opposite. Then

(\exists Y \in \mathcal{M}) \quad v_{t} Y=0

(i.e., Y \in \mathcal{M}_{0}), but

0<v^{\prime} Y=v_{s}(Y-P).

So by additivity,

v_{s}(Y \cup P)=v_{s} P+v_{s}(Y-P)>v_{s} P,

with Y \cup P \in \mathcal{M}_{0}, contrary to

v_{s} P=\max \left\{v_{s} X | X \in \mathcal{M}_{0}\right\}.

This contradiction completes the proof.\quad \square

Note 4. The set function s^{\prime \prime} in Theorem 2 is bounded on \mathcal{M}. Indeed, s^{\prime \prime} \perp t yields a set P \in \mathcal{M} such that

(\forall X \in \mathcal{M}) \quad s^{\prime \prime}(X-P)=0;

and v_{t} P=0 implies v_{s} P<\infty. (Why?) Hence

s^{\prime \prime} X=s^{\prime \prime}(X \cap P)+s^{\prime \prime}(X-P)=s^{\prime \prime}(X \cap P).

As s=s^{\prime}+s^{\prime \prime}, we have

\left|s^{\prime \prime}\right| \leq|s|+\left|s^{\prime}\right| \leq v_{s}+v_{s^{\prime}};

so

\left|s^{\prime \prime} X\right|=\left|s^{\prime \prime}(X \cap P)\right| \leq v_{s} P+v_{s^{\prime}} P.

But v_{s^{\prime}} P=0 by t-continuity (Theorem 2 of Chapter 7, §11). Thus \left|s^{\prime \prime}\right| \leq v_{s} P<\infty on \mathcal{M}.

Note 5. The Lebesgue decomposition s=s^{\prime}+s^{\prime \prime} in Theorem 2 is unique. For if also

u^{\prime} \ll t \text { and } u^{\prime \prime} \perp t

and

u^{\prime}+u^{\prime \prime}=s=s^{\prime}+s^{\prime \prime},

then with P as in Problem 3, (\forall X \in \mathcal{M})

s^{\prime}(X \cap P)+s^{\prime \prime}(X \cap P)=u^{\prime}(X \cap P)+u^{\prime \prime}(X \cap P)

and v_{t}(X \cap P)=0. But

s^{\prime}(X \cap P)=0=u^{\prime}(X \cap P)

by t-continuity; so (8) reduces to

s^{\prime \prime}(X \cap P)=u^{\prime \prime}(X \cap P),

or s^{\prime \prime} X=u^{\prime \prime} X (for s^{\prime \prime} and u^{\prime \prime} reside in P). Thus s^{\prime \prime}=u^{\prime \prime} on \mathcal{M}.

By Note 4, we may cancel s^{\prime \prime} and u^{\prime \prime} in

s^{\prime}+s^{\prime \prime}=u^{\prime}+u^{\prime \prime}

to obtain s^{\prime}=u^{\prime} also.

Note 6. If E=E^{n}\left(C^{n}\right), the t-finiteness of v_{s} in Theorem 2 is redundant, for v_{s} is even bounded (Theorem 6 in Chapter 7, §11).

We now obtain the desired generalization of Theorem 1.

Corollary \PageIndex{3}

If (S, \mathcal{M}, m) is a \sigma-finite measure space (S \in \mathcal{M}), then for any generalized measure

\mu : \mathcal{M} \rightarrow E^{n}\left(C^{n}\right),

there is a unique m-singular generalized measure

s^{\prime \prime} : \mathcal{M} \rightarrow E^{n}\left(C^{n}\right)

and a ("essentially" unique) map

f : S \rightarrow E^{n}\left(C^{n}\right),

\mathcal{M}-measurable and m-integrable on S, with

\mu=\int f dm+s^{\prime \prime}.

(Note 3 applies here.)

Proof

By Theorem 2 and Note 5, \mu=s^{\prime}+s^{\prime \prime} for some (unique) generalized measures s^{\prime}, s^{\prime \prime} : \mathcal{M} \rightarrow E^{n}\left(C^{n}\right), with s^{\prime} \ll m and s^{\prime \prime} \perp m.

Now use Theorem 1 to represent s^{\prime} as \int f dm, with f as stated. This yields the result.\quad \square


8.11: The Radon–Nikodym Theorem. Lebesgue Decomposition is shared under a CC BY 1.0 license and was authored, remixed, and/or curated by LibreTexts.

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