Mathematics · Book 5 · Bachelor Year 3

University Mathematics — Year 3

University Mathematics — Year 3 · Bachelor Year 3

9Measure Theory

How long is a subset of R\R? The naive answer — assign to every set a translation-invariant length extending that of intervals — is impossible: Vitali’s construction, at the end of this chapter, produces a set with no consistent length. Measure theory is the disciplined retreat: restrict attention to a rich class of measurable sets, on which a countably additive length exists and is unique. The rewards are immense — Lebesgue’s integral (Chapter 10), the LpL^p spaces of functional analysis, and the whole of modern probability (Chapter 22) are built on the three theorems proved here: Dynkin’s uniqueness lemma, Carathéodory’s extension theorem, and the existence of Lebesgue measure.

9.1 σ\sigma-algebras

Definition 9.1

A σ\sigma-algebra on a set XX is a family A\mathcal A of subsets containing ∅\varnothing, stable under complement and under countable unions (hence countable intersections, set differences, and it contains XX). The pair (X,A)(X, \mathcal A) is a measurable space; members of A\mathcal A are measurable sets. For any family E\mathcal E of subsets, σ(E)\sigma(\mathcal E) denotes the smallest σ\sigma-algebra containing E\mathcal E (the intersection of all of them — an intersection of σ\sigma-algebras is one).

Definition 9.2

The Borel σ\sigma-algebra of a topological space is B(X)=σ({open sets})\mathcal B(X) = \sigma(\{\text{open sets}\}). On R\R: B(R)\mathcal B(\R) is also generated by the open intervals, by the closed intervals, by the rays (−∞,a](-\infty, a], and by rays with rational endpoints (Exercise 9.1) — each family generates the opens by countable operations, e.g. every open set of R\R is a countable union of open intervals with rational data.

Definition 9.3

A π\pi-system is a family stable under finite intersections. A λ\lambda-system (Dynkin class) is a family D\mathcal D with: X∈DX \in \mathcal D; A,B∈DA, B \in \mathcal D, A⊆BA \subseteq B ⇒\Rightarrow B∖A∈DB \setminus A \in \mathcal D; and An↑AA_n \uparrow A, An∈DA_n \in \mathcal D ⇒\Rightarrow A∈DA \in \mathcal D.

Theorem 9.4 (Dynkin’s π\pi–λ\lambda lemma)

If a λ\lambda-system D\mathcal D contains a π\pi-system P\mathcal P, then D⊇σ(P)\mathcal D \supseteq \sigma(\mathcal P).

Proof. Let D0\mathcal D_0 be the smallest λ\lambda-system containing P\mathcal P (intersection of all such); it suffices to show D0\mathcal D_0 is a σ\sigma-algebra, since then σ(P)⊆D0⊆D\sigma(\mathcal P) \subseteq \mathcal D_0 \subseteq \mathcal D. A λ\lambda-system stable under finite intersections is a σ\sigma-algebra: complements (X∖A=X∖AX \setminus A = X \setminus A with A⊆XA \subseteq X), finite unions (A∪B=X∖((X∖A)∩(X∖B))A \cup B = X \setminus ((X\setminus A)\cap(X\setminus B))), and countable unions via ⋃k≤nAk↑⋃kAk\bigcup_{k \leq n}A_k \uparrow \bigcup_kA_k. So we prove D0\mathcal D_0 is a π\pi-system, in two steps. Let

D1={A∈D0:A∩P∈D0 ∀P∈P}.\mathcal D_1 = \{A \in \mathcal D_0 : A \cap P \in \mathcal D_0 \ \forall P \in \mathcal P\}.

D1\mathcal D_1 is a λ\lambda-system (all three axioms are verified by intersecting with PP: e.g. (B∖A)∩P=(B∩P)∖(A∩P)(B\setminus A)\cap P = (B \cap P)\setminus(A \cap P), a proper difference within D0\mathcal D_0) and contains P\mathcal P (π\pi-system): D1=D0\mathcal D_1 = \mathcal D_0. Now let

D2={A∈D0:A∩D∈D0 ∀D∈D0}.\mathcal D_2 = \{A \in \mathcal D_0 : A \cap D \in \mathcal D_0\ \forall D \in \mathcal D_0\}.

By the previous step, D2⊇P\mathcal D_2 \supseteq \mathcal P; and D2\mathcal D_2 is a λ\lambda-system by the same verification: D2=D0\mathcal D_2 = \mathcal D_0, which says exactly that D0\mathcal D_0 is stable under intersections. ∎

9.2 Measures

Definition 9.5

A measure on (X,A)(X, \mathcal A) is a map μ ⁣:A→[0,+∞]\mu \colon \mathcal A \to [0, +\infty] with μ(∅)=0\mu(\varnothing) = 0 that is σ\sigma-additive: for pairwise disjoint (An)n∈N(A_n)_{n\in\N},

μ(⨆nAn)=∑nμ(An).\mu\Bigl(\bigsqcup_n A_n\Bigr) = \sum_n \mu(A_n).

(X,A,μ)(X, \mathcal A, \mu) is a measure space; μ\mu is finite if μ(X)<∞\mu(X) < \infty, a probability measure if μ(X)=1\mu(X) = 1, σ\sigma-finite if XX is a countable union of sets of finite measure. Examples: counting measure on (N,P(N))(\N, \mathcal P(\N)); the Dirac mass δa(A)=1a∈A\delta_a(A) = \mathbf 1_{a \in A}; and, the object of this chapter, Lebesgue measure.

Proposition 9.6

Let μ\mu be a measure. (a) Monotonicity: A⊆B⇒μ(A)≤μ(B)A \subseteq B \Rightarrow \mu(A) \leq \mu(B). (b) Countable subadditivity: μ(⋃An)≤∑μ(An)\mu(\bigcup A_n) \leq \sum\mu(A_n). (c) Continuity from below: An↑A⇒μ(An)→μ(A)A_n \uparrow A \Rightarrow \mu(A_n) \to \mu(A). (d) Continuity from above: An↓AA_n \downarrow A with μ(A1)<∞\mu(A_1) < \infty ⇒μ(An)→μ(A)\Rightarrow \mu(A_n) \to \mu(A).

Proof. (a) B=A⊔(B∖A)B = A \sqcup (B\setminus A). (b) Disjointify: Bn=An∖⋃k<nAkB_n = A_n \setminus \bigcup_{k<n}A_k are disjoint with the same union, and μ(Bn)≤μ(An)\mu(B_n) \leq \mu(A_n). (c) A=⨆n(An∖An−1)A = \bigsqcup_n (A_n \setminus A_{n-1}) (A0=∅A_0 = \varnothing): the partial sums of ∑μ(An∖An−1)\sum\mu(A_n\setminus A_{n-1}) are μ(An)\mu(A_n). (d) Apply (c) to A1∖An↑A1∖AA_1 \setminus A_n \uparrow A_1 \setminus A and subtract from μ(A1)\mu(A_1) — finiteness makes the subtraction legitimate. Counterexample without it: An=[n,∞)A_n = [n, \infty) for Lebesgue measure: An↓∅A_n \downarrow \varnothing but μ(An)=∞\mu(A_n) = \infty. ∎

Theorem 9.7 (Uniqueness)

Let μ,ν\mu, \nu be measures on σ(P)\sigma(\mathcal P), P\mathcal P a π\pi-system, with μ=ν\mu = \nu on P\mathcal P. If there are sets Pk∈PP_k \in \mathcal P with Pk↑XP_k \uparrow X and μ(Pk)<∞\mu(P_k) < \infty, then μ=ν\mu = \nu on all of σ(P)\sigma(\mathcal P).

Proof. Fix kk and consider the finite measures μk(A)=μ(A∩Pk)\mu_k(A) = \mu(A \cap P_k) and νk(A)=ν(A∩Pk)\nu_k(A) = \nu(A \cap P_k) on σ(P)\sigma(\mathcal P): they agree on P\mathcal P, since P∩Pk∈PP \cap P_k \in \mathcal P (π\pi-system), and they assign XX the same finite value μ(Pk)\mu(P_k). The class D={A:μk(A)=νk(A)}\mathcal D = \{A : \mu_k(A) = \nu_k(A)\} is a λ\lambda-system: X∈DX \in \mathcal D; proper differences by subtraction (finite values); increasing limits by continuity from below (Proposition 9.6(c)). It contains the π\pi-system P\mathcal P, so Dynkin (Theorem 9.4) gives D⊇σ(P)\mathcal D \supseteq \sigma(\mathcal P): μk=νk\mu_k = \nu_k everywhere. Finally, for any A∈σ(P)A \in \sigma(\mathcal P), continuity from below along A∩Pk↑AA \cap P_k \uparrow A gives μ(A)=lim⁡kμk(A)=lim⁡kνk(A)=ν(A)\mu(A) = \lim_k\mu_k(A) = \lim_k\nu_k(A) = \nu(A). ∎

9.3 Outer measures and Carathéodory’s theorem

Definition 9.8

An outer measure on XX is a map μ∗ ⁣:P(X)→[0,∞]\mu^* \colon \mathcal P(X) \to [0, \infty] with μ∗(∅)=0\mu^*(\varnothing) = 0, monotone, and countably subadditive. A set AA is μ∗\mu^*-measurable (Carathéodory) if it splits every set additively:

μ∗(E)=μ∗(E∩A)+μ∗(E∖A)for every E⊆X\mu^*(E) = \mu^*(E \cap A) + \mu^*(E \setminus A) \qquad \text{for every } E \subseteq X

(≤\leq always holds by subadditivity; the content is ≥\geq).

Theorem 9.9 (Carathéodory)

The μ∗\mu^*-measurable sets form a σ\sigma-algebra M\mathcal M, and μ∗↾M\mu^*\restriction_{\mathcal M} is a measure. Moreover every set with μ∗(N)=0\mu^*(N) = 0 belongs to M\mathcal M (the measure is complete).

Proof. M\mathcal M contains ∅\varnothing and is stable under complement (the defining condition is symmetric in AA, X∖AX\setminus A). Finite unions: let A,B∈MA, B \in \mathcal M and EE arbitrary; splitting EE by AA, then each piece by BB:

μ∗(E)=μ∗(E∩A∩B)+μ∗(E∩A∖B)+μ∗(E∩B∖A)+μ∗(E∖(A∪B)).\mu^*(E) = \mu^*(E\cap A\cap B) + \mu^*(E\cap A\setminus B) + \mu^*(E\cap B\setminus A) + \mu^*(E\setminus(A\cup B)).

The first three pieces cover E∩(A∪B)E \cap (A \cup B), so subadditivity gives μ∗(E)≥μ∗(E∩(A∪B))+μ∗(E∖(A∪B))\mu^*(E) \geq \mu^*(E\cap(A\cup B)) + \mu^*(E\setminus(A\cup B)): A∪B∈MA \cup B \in \mathcal M. By induction, finite unions; with complements, finite disjointness manipulations are available.

Additivity on M\mathcal M: for disjoint A,B∈MA, B \in \mathcal M and any EE: μ∗(E∩(A⊔B))=μ∗(E∩A)+μ∗(E∩B)\mu^*(E\cap(A\sqcup B)) = \mu^*(E\cap A) + \mu^*(E \cap B) (split by AA); by induction,

μ∗(E∩⨆k≤nAk)=∑k≤nμ∗(E∩Ak).(∗)\mu^*\Bigl(E \cap \bigsqcup_{k\leq n}A_k\Bigr) = \sum_{k\leq n}\mu^*(E\cap A_k). \tag{$*$}

Countable unions: let (Ak)⊆M(A_k) \subseteq \mathcal M be disjoint (suffices, by disjointification within the algebra M\mathcal M), A=⨆AkA = \bigsqcup A_k, EE arbitrary. Using ⨆k≤nAk∈M\bigsqcup_{k\leq n}A_k \in \mathcal M and monotonicity:

μ∗(E)=μ∗(E∩⨆k≤nAk)+μ∗(E∖⨆k≤nAk)≥∑k≤nμ∗(E∩Ak)+μ∗(E∖A)\mu^*(E) = \mu^*\Bigl(E\cap\bigsqcup_{k\leq n}A_k\Bigr) + \mu^*\Bigl(E\setminus\bigsqcup_{k\leq n}A_k\Bigr) \geq \sum_{k \leq n}\mu^*(E\cap A_k) + \mu^*(E\setminus A)

by (∗*). Let n→∞n \to \infty and use countable subadditivity backwards:

μ∗(E)≥∑kμ∗(E∩Ak)+μ∗(E∖A)≥μ∗(E∩A)+μ∗(E∖A)≥μ∗(E):\mu^*(E) \geq \sum_{k}\mu^*(E\cap A_k) + \mu^*(E\setminus A) \geq \mu^*(E \cap A) + \mu^*(E\setminus A) \geq \mu^*(E):

all inequalities are equalities. This proves both A∈MA \in \mathcal M and, taking E=AE = A, countable additivity of μ∗\mu^* on M\mathcal M.

Null sets: if μ∗(N)=0\mu^*(N) = 0, then for any EE: μ∗(E∩N)+μ∗(E∖N)≤0+μ∗(E)\mu^*(E \cap N) + \mu^*(E\setminus N) \leq 0 + \mu^*(E): N∈MN \in \mathcal M. ∎

9.4 Lebesgue measure on R\R

Definition 9.10

The Lebesgue outer measure of A⊆RA \subseteq \R is

λ∗(A)=inf⁡{∑n(bn−an):A⊆⋃n(an, bn)}\lambda^*(A) = \inf\Bigl\{\sum_{n} (b_n - a_n) : A \subseteq \bigcup_n \intoo{a_n}{b_n}\Bigr\}

(countable covers by open intervals).

Lemma 9.11

λ∗\lambda^* is an outer measure, invariant under translations, and λ∗(I)=ℓ(I)\lambda^*(I) = \ell(I) (the length) for every interval II.

Proof. Outer measure: ∅\varnothing is covered by arbitrarily small intervals; monotonicity is clear; subadditivity: given covers of each AnA_n within ε2−n\varepsilon 2^{-n} of the infimum, their union covers ⋃An\bigcup A_n with total length ≤∑λ∗(An)+ε\leq \sum \lambda^*(A_n) + \varepsilon. Translation invariance: translate the covers.

Length: it suffices to treat I=[a, b]I = \intcc ab (other types differ by endpoints, which have outer measure 00: cover by tiny intervals; then squeeze [a+ε, b−ε]⊆(a, b)\intcc{a+\varepsilon}{b - \varepsilon} \subseteq \intoo ab-type comparisons). λ∗([a, b])≤b−a\lambda^*(\intcc ab) \leq b - a: cover by (a−ε, b+ε)\intoo{a-\varepsilon}{b+\varepsilon}. Conversely let [a, b]⊆⋃n(an, bn)\intcc ab \subseteq \bigcup_n\intoo{a_n}{b_n}: by compactness (Borel–Lebesgue, Theorem 6.16), finitely many intervals suffice, say I1,…,INI_1, \dots, I_N. We show ∑k≤N(bk−ak)≥b−a\sum_{k\leq N}(b_k - a_k) \geq b - a by induction on NN: choose Ik1∋aI_{k_1} \ni a; if bk1>bb_{k_1} > b done (bk1−ak1>b−ab_{k_1} - a_{k_1} > b - a); else the segment [bk1, b]\intcc{b_{k_1}}b is covered by the remaining N−1N - 1 intervals, and induction gives ∑k≠k1(bk−ak)≥b−bk1\sum_{k \neq k_1}(b_k - a_k) \geq b - b_{k_1}, while bk1−ak1>bk1−ab_{k_1} - a_{k_1} > b_{k_1} - a: sum up. ∎

Theorem 9.12 (Lebesgue measure)

Every Borel set of R\R is λ∗\lambda^*-measurable. The restriction λ\lambda of λ∗\lambda^* to the σ\sigma-algebra L=Mλ∗⊇B(R)\mathcal L = \mathcal M_{\lambda^*} \supseteq \mathcal B(\R) (the Lebesgue σ\sigma-algebra) is the unique measure on B(R)\mathcal B(\R) assigning to each interval its length; it is translation-invariant and σ\sigma-finite.

Proof. By Theorem 9.9 it suffices to show each ray A=(−∞, c)A = \intoo{-\infty}c is λ∗\lambda^*-measurable (rays generate B\mathcal B, Definition 9.2). Let E⊆RE \subseteq \R with λ∗(E)<∞\lambda^*(E) < \infty and ⋃In⊇E\bigcup I_n \supseteq E a cover with ∑ℓ(In)≤λ∗(E)+ε\sum\ell(I_n) \leq \lambda^*(E) + \varepsilon. Each InI_n splits into the two intervals In′=In∩AI_n' = I_n \cap A and In′′=In∖AI_n'' = I_n\setminus A (an interval minus a ray is an interval) with ℓ(In′)+ℓ(In′′)=ℓ(In)\ell(I_n') + \ell(I_n'') = \ell(I_n); the In′I_n' cover E∩AE \cap A and the In′′I_n'' cover E∖AE \setminus A (enlarge each to an open interval of length ℓ+ε2−n\ell + \varepsilon2^{-n} to stay within the definition), so

λ∗(E∩A)+λ∗(E∖A)≤∑n(ℓ(In′)+ℓ(In′′))+2ε≤λ∗(E)+3ε.\lambda^*(E\cap A) + \lambda^*(E\setminus A) \leq \sum_n\bigl(\ell(I_n') + \ell(I_n'')\bigr) + 2\varepsilon \leq \lambda^*(E) + 3\varepsilon .

Uniqueness: two measures agreeing with length on the π\pi-system of intervals (a, b]\intoc ab (finite on them) agree on σ(intervals)=B\sigma(\text{intervals}) = \mathcal B by Theorem 9.7 with Pk=(−k, k]P_k = \intoc{-k}k. σ\sigma-finiteness: R=⋃(−k,k]\R = \bigcup(-k, k]. ∎

Theorem 9.13 (Regularity)

For every A∈LA \in \mathcal L:

λ(A)=inf⁡{λ(U):U⊇A open}=sup⁡{λ(K):K⊆A compact}.\lambda(A) = \inf\{\lambda(U) : U \supseteq A \text{ open}\} = \sup\{\lambda(K) : K \subseteq A \text{ compact}\}.

Proof. Outer: a cover ⋃In\bigcup I_n with ∑ℓ(In)≤λ(A)+ε\sum\ell(I_n) \leq \lambda(A) + \varepsilon is an open set U⊇AU \supseteq A with λ(U)≤λ(A)+ε\lambda(U) \leq \lambda(A) + \varepsilon (subadditivity); if λ(A)=∞\lambda(A) = \infty the statement is trivial. Inner: first let AA be bounded, A⊆[−M,M]A \subseteq [-M, M]. Choose an open U⊇([−M,M]∖A)U \supseteq ([-M,M]\setminus A) with λ(U)≤λ([−M,M]∖A)+ε\lambda(U) \leq \lambda([-M,M]\setminus A) + \varepsilon; then K=[−M,M]∖UK = [-M, M]\setminus U is compact, K⊆AK \subseteq A, and

λ(K)=λ([−M,M])−λ([−M,M]∩U)≥λ([−M,M])−(λ([−M,M])−λ(A)+ε)=λ(A)−ε.\lambda(K) = \lambda([-M,M]) - \lambda([-M,M]\cap U) \geq \lambda([-M,M]) - \bigl(\lambda([-M,M]) - \lambda(A) + \varepsilon\bigr) = \lambda(A) - \varepsilon .

For general AA: λ(A)=lim⁡Mλ(A∩[−M,M])\lambda(A) = \lim_M\lambda(A\cap[-M,M]) (continuity from below) and apply the bounded case inside. ∎

Example 9.14

The Cantor set (Exercise 6.10) has λ(C)=0\lambda(C) = 0: C⊆CnC \subseteq C_n, a union of 2n2^n intervals of length 3−n3^{-n}, so λ(C)≤(2/3)n→0\lambda(C) \leq (2/3)^n \to 0. An uncountable null set — cardinality does not see measure. Conversely, fat Cantor sets (Exercise 9.5) are nowhere dense with positive measure: topology does not see measure either. The weekend problem pushes this interplay to its striking conclusion: there are Lebesgue-measurable sets that are not Borel.

Theorem 9.15 (Vitali)

There is no measure on all subsets of R\R that is translation-invariant and assigns to each interval its length. In particular L≠P(R)\mathcal L \neq \mathcal P(\R): non-measurable sets exist.

Proof. Suppose μ\mu were one. On [0, 1]\intcc01, consider the equivalence x∼y  ⟺  x−y∈Qx \sim y \iff x - y \in \Q; by the axiom of choice pick one representative in [0, 1]\intcc01 per class: a set VV. For q∈Q∩[−1, 1]q \in \Q\cap\intcc{-1}1, the translates V+qV + q are pairwise disjoint (two points of VV differing by a rational would be equivalent yet distinct representatives) and

[0, 1]⊆⨆q∈Q∩[−1, 1](V+q)⊆[−1, 2]:\intcc01 \subseteq \bigsqcup_{q \in \Q\cap\intcc{-1}1}(V + q) \subseteq \intcc{-1}2 :

the first inclusion since every x∈[0, 1]x \in \intcc01 differs from its representative vv by a rational q=x−v∈[−1, 1]q = x - v \in \intcc{-1}1. Monotonicity and σ\sigma-additivity give

1≤∑qμ(V+q)≤3,with μ(V+q)=μ(V) for all q.1 \leq \sum_{q}\mu(V + q) \leq 3, \qquad\text{with } \mu(V + q) = \mu(V) \text{ for all } q .

An infinite sum of the constant μ(V)\mu(V) is 00 or ∞\infty: both bounds cannot hold. So no such μ\mu exists — and V∉LV \notin \mathcal L, since λ\lambda on L\mathcal L has all the properties used. ∎

Remark 9.16

In R3\R^3 the failure is more dramatic: the Banach–Tarski paradox decomposes a ball into five pieces that reassemble, by rotations and translations, into two balls of the same radius — so not even a finitely additive rotation-invariant volume on all subsets of R3\R^3 exists. The pieces are, of course, non-measurable. Measurability is not bureaucratic caution; it is the boundary of coherence.

Method 9.17

The good sets principle: to prove that all sets of σ(E)\sigma(\mathcal E) have a property, show that the good sets form a σ\sigma-algebra (or a λ\lambda-system, if the property is measure-theoretic and E\mathcal E is a π\pi-system — then Dynkin) containing E\mathcal E. Almost every proof of this chapter and the next is an instance. To prove two measures equal: check them on a generating π\pi-system plus σ\sigma-finiteness (Theorem 9.7). To build a measure: build an outer measure by covers and quote Carathéodory.

9.5 Exercises

Exercise 9.1 ★

(a) Show that {A⊆X:A\{A \subseteq X : A or X∖AX\setminus A is countable}\} is a σ\sigma-algebra: the one generated by singletons. (b) Show that B(R)\mathcal B(\R) is generated by each of: open intervals; closed intervals; rays (−∞, a]\intoc{-\infty}a; rays with a∈Qa \in \Q. (c) Is the family of finite disjoint unions of intervals (a, b]\intoc ab a σ\sigma-algebra? An algebra (stable under complement and finite unions)?

Solution

Solution of Exercise 9.1.

(a) Complementation swaps the two defining cases. A countable union of countable sets is countable; if one member is co-countable, the union is co-countable: stability holds. It contains the singletons, and any σ\sigma-algebra containing them contains all countable sets (countable unions) and their complements: it is σ({singletons})\sigma(\{\text{singletons}\}).

(b) Write B=σ(opens)\mathcal B = \sigma(\text{opens}). Every open subset of R\R is a countable union of open intervals with rational endpoints (around each rational point of the open set, a rational-radius interval inside it), so opens ∈σ(open intervals)⊆σ(rational data)\in \sigma(\text{open intervals}) \subseteq \sigma(\text{rational data}). Conversions: (a, b)=⋃n[a+1n, b−1n]\intoo ab = \bigcup_n\intcc{a + \frac1n}{b - \frac1n}; [a, b]=⋂n(a−1n, b+1n)\intcc ab = \bigcap_n \intoo{a - \frac1n}{b + \frac1n}; (−∞, a]=⋂n(−∞, a+1n)\intoc{-\infty}a = \bigcap_n \intoo{-\infty}{a + \frac1n} and conversely (a, b)=(−∞, b)∖(−∞, a]\intoo ab = \intoo{-\infty}b \setminus \intoc{-\infty}a; rational rays: (−∞, a]=⋂q∈Q, q>a(−∞, q]\intoc{-\infty}a = \bigcap_{q \in \Q,\, q > a}\intoc{-\infty}q. Each family generates the others by countable operations: all four generate B\mathcal B.

(c) With finite endpoints only, the family is not even an algebra: the complement of (0, 1]\intoc01 contains unbounded rays. Allowing infinite endpoints ((−∞, b]\intoc{-\infty}b, (a, +∞)\intoo a{+\infty}) it becomes an algebra (complements and finite unions of such unions are such), but not a σ\sigma-algebra: {0}=⋂n(−1n, 0]\{0\} = \bigcap_n\intoc{-\frac1n}0 is not a finite union of nondegenerate intervals.

Exercise 9.2 ★

(a) Prove inclusion–exclusion for a finite measure: μ(A∪B)=μ(A)+μ(B)−μ(A∩B)\mu(A\cup B) = \mu(A) + \mu(B) - \mu(A\cap B), and the three-set version. (b) Give an example showing that continuity from above (Proposition 9.6(d)) fails without the finiteness assumption. (c) Show that a countable set has Lebesgue measure zero. Deduce λ(Q)=0\lambda(\Q) = 0 and λ([0, 1]∖Q)=1\lambda(\intcc01\setminus\Q) = 1.

Solution

Solution of Exercise 9.2.

(a) A∪B=A⊔(B∖(A∩B))A \cup B = A \sqcup (B \setminus (A\cap B)), so μ(A∪B)=μ(A)+μ(B)−μ(A∩B)\mu(A\cup B) = \mu(A) + \mu(B) - \mu(A\cap B) (finiteness permits the subtraction). Three sets: apply the two-set formula twice,

μ(A∪B∪C)=∑μ(A)−∑μ(A∩B)+μ(A∩B∩C)\mu(A\cup B\cup C) = \sum\mu(A) - \sum\mu(A\cap B) + \mu(A\cap B\cap C)

(sums over the obvious index sets).

(b) For Lebesgue measure, An=[n,+∞)↓∅A_n = [n, +\infty) \downarrow \varnothing, but λ(An)=∞↛0\lambda(A_n) = \infty \not\to 0.

(c) A point lies in an interval of length ε\varepsilon: λ({x})=0\lambda(\{x\}) = 0; countable subadditivity kills countable sets. Hence λ(Q∩[0, 1])=0\lambda(\Q \cap \intcc01) = 0 and, by additivity, λ([0, 1]∖Q)=1\lambda(\intcc01\setminus\Q) = 1: the irrationals carry all the length.

Exercise 9.3 ★★

Let μ,ν\mu, \nu be probability measures on B(R)\mathcal B(\R) with μ((−∞, t])=ν((−∞, t])\mu(\intoc{-\infty}t) = \nu(\intoc{-\infty}t) for all t∈Rt \in \R. Show μ=ν\mu = \nu. (This makes the distribution function F(t)=μ((−∞, t])F(t) = \mu(\intoc{-\infty}t) a complete invariant — the foundation of Chapter 22.)

Solution

Solution of Exercise 9.3.

The rays (−∞, t]\intoc{-\infty}t form a π\pi-system (the intersection of two is the smaller) generating B(R)\mathcal B(\R) (Exercise 9.1). The sets Pk=(−∞, k]P_k = \intoc{-\infty}k increase to R\R with μ(Pk)≤1<∞\mu(P_k) \leq 1 < \infty: Theorem 9.7 applies, and μ=ν\mu = \nu on B(R)\mathcal B(\R). Thus the distribution function determines the measure.

Exercise 9.4 ★★

(Borel–Cantelli, measure version) Let (An)(A_n) be measurable with ∑nμ(An)<∞\sum_n\mu(A_n) < \infty, and lim sup⁡An=⋂N⋃n≥NAn\limsup A_n = \bigcap_N\bigcup_{n\geq N}A_n (the points belonging to infinitely many AnA_n). Show μ(lim sup⁡An)=0\mu(\limsup A_n) = 0. Application: for almost every x∈[0, 1]x \in \intcc01, only finitely many nn satisfy ∣x−p/qn∣≤4−n\abs{x - p/q_n} \leq 4^{-n} for the nn-th rational p/qnp/q_n of an enumeration of Q∩[0, 1]\Q\cap\intcc01.

Solution

Solution of Exercise 9.4.

For every NN, lim sup⁡An⊆⋃n≥NAn\limsup A_n \subseteq \bigcup_{n \geq N}A_n, so μ(lim sup⁡An)≤∑n≥Nμ(An)\mu(\limsup A_n) \leq \sum_{n\geq N}\mu(A_n), the tail of a convergent series: let N→∞N \to \infty. Application: with An={x∈[0, 1]:∣x−rn∣≤4−n}A_n = \{x \in \intcc01 : \abs{x - r_n} \leq 4^{-n}\} (rnr_n the nn-th rational), λ(An)≤2⋅4−n\lambda(A_n) \leq 2\cdot4^{-n} is summable: λ(lim sup⁡An)=0\lambda(\limsup A_n) = 0, i.e. almost every xx belongs to only finitely many AnA_n. (Yet every xx is a limit of rationals: the point is the speed 4−n4^{-n}.)

Exercise 9.5 ★★

(Fat Cantor set) Repeat the Cantor construction on [0, 1]\intcc01, but at step nn remove from each of the 2n−12^{n-1} intervals a centered open interval of length 4−n4^{-n} only. Show that the resulting K=⋂KnK = \bigcap K_n is compact, has empty interior (no interval survives), and

λ(K)=1−∑n≥12n−14−n=12:\lambda(K) = 1 - \sum_{n\geq1}2^{n-1}4^{-n} = \tfrac12 :

a nowhere dense set of measure 12\frac12. Deduce a meagre subset of [0, 1]\intcc01 of full measure 11, and an open dense subset of measure <ε< \varepsilon.

Solution

Solution of Exercise 9.5.

K=⋂KnK = \bigcap K_n is an intersection of finite unions of closed intervals: compact. At stage nn there remain 2n2^n intervals of common length ℓn≤2−n\ell_n \leq 2^{-n} (each stage halves and shrinks); an interval I⊆KI \subseteq K would lie inside a single stage-nn interval for every nn, forcing ℓ(I)=0\ell(I) = 0: empty interior. The measure removed is ∑n≥12n−1⋅4−n=12∑n≥12−n=12\sum_{n\geq1}2^{n-1}\cdot 4^{-n} = \frac12\sum_{n\geq1}2^{-n} = \frac12, all removals being disjoint open intervals: λ(K)=12\lambda(K) = \frac12.

Variant: removing central intervals of length ε4−n\varepsilon 4^{-n} leaves a nowhere dense compact K(ε)K^{(\varepsilon)} of measure 1−ε21 - \frac\varepsilon2. Then ⋃mK(1/m)\bigcup_m K^{(1/m)} is meagre (countable union of nowhere dense sets) of measure ≥sup⁡m(1−12m)=1\geq \sup_m(1 - \frac1{2m}) = 1: a meagre set of full measure — and its complement in (0, 1)\intoo01 is a dense GδG_\delta of measure 00 (topologically fat, metrically null). The complement of K(ε)K^{(\varepsilon)} in (0, 1)\intoo01 is open, dense, of measure ε2<ε\frac\varepsilon2 < \varepsilon.

Exercise 9.6 ★★

Let μ\mu be a measure on B(R)\mathcal B(\R), invariant under translations, with c=μ((0, 1])<∞c = \mu(\intoc01) < \infty. Show μ=c λ\mu = c\,\lambda on B(R)\mathcal B(\R). (Compute μ\mu on dyadic intervals by dividing (0, 1]\intoc01 into 2n2^n translates, then invoke Theorem 9.7.)

Solution

Solution of Exercise 9.6.

Cutting (0, 1]\intoc01 into 2n2^n translates of (0, 2−n]\intoc0{2^{-n}}: c=2n μ((0, 2−n])c = 2^n\,\mu(\intoc0{2^{-n}}), so μ((0, 2−n])=c 2−n=c λ((0, 2−n])\mu(\intoc0{2^{-n}}) = c\,2^{-n} = c\,\lambda(\intoc0{2^{-n}}). By translation invariance and additivity, μ=cλ\mu = c\lambda on every interval (a, b]\intoc ab with b−ab - a a dyadic rational and any aa; a general (a, b]\intoc ab is an increasing union of such (bk↑bb_k \uparrow b dyadic steps from aa), and continuity from below extends the equality. The intervals (a, b]\intoc ab form a π\pi-system generating B(R)\mathcal B(\R), with (−k, k]↑R\intoc{-k}k \uparrow \R of finite measure (μ((−k, k])=2kc\mu(\intoc{-k}k) = 2kc): Theorem 9.7 gives μ=cλ\mu = c\lambda on B(R)\mathcal B(\R).

Exercise 9.7 ★★

(Approximation) Let A∈LA \in \mathcal L with λ(A)<∞\lambda(A) < \infty and ε>0\varepsilon > 0. Show there is a finite union of intervals BB with λ(A △ B)<ε\lambda(A\,\triangle\,B) < \varepsilon (△\triangle = symmetric difference). (Regularity: squeeze K⊆A⊆UK \subseteq A \subseteq U and use the structure of the open UU as a countable union of intervals, plus compactness of KK.)

Solution

Solution of Exercise 9.7.

By regularity (Theorem 9.13) choose K⊆A⊆UK \subseteq A \subseteq U with KK compact, UU open, λ(U∖K)<ε\lambda(U\setminus K) < \varepsilon (both approximations within ε/2\varepsilon/2, and λ(U∖K)=λ(U∖A)+λ(A∖K)\lambda(U \setminus K) = \lambda(U\setminus A) + \lambda(A \setminus K)). Write UU as a countable disjoint union of open intervals (In)(I_n) (the components of the open set); the compact KK is covered by finitely many, K⊆B=I1∪⋯∪IN⊆UK \subseteq B = I_1\cup\dots\cup I_N \subseteq U. Then A∖B⊆A∖K⊆U∖KA \setminus B \subseteq A\setminus K \subseteq U\setminus K and B∖A⊆U∖A⊆U∖KB \setminus A \subseteq U \setminus A \subseteq U\setminus K: λ(A △ B)≤2λ(U∖K)\lambda(A\,\triangle\,B) \leq 2\lambda(U\setminus K) — start from ε/2\varepsilon/2 to land below ε\varepsilon.

Exercise 9.8 ★★★

(Steinhaus) Let A∈LA \in \mathcal L with λ(A)>0\lambda(A) > 0. Show that A−A={x−y:x,y∈A}A - A = \{x - y : x, y \in A\} contains an interval around 00. (Reduce to λ(A)<∞\lambda(A) < \infty; by Exercise 9.7-style regularity, find an interval II with λ(A∩I)>34ℓ(I)\lambda(A \cap I) > \frac34\ell(I); then for ∣t∣<12ℓ(I)\abs t < \frac12\ell(I), the sets A∩IA\cap I and (A∩I)+t(A\cap I) + t both sit in an interval of length 32ℓ(I)\frac32\ell(I) and have total measure >32ℓ(I)> \frac32\ell(I): they must intersect.)

Solution

Solution of Exercise 9.8.

Replacing AA by A∩[−M,M]A \cap [-M, M] of positive measure (some MM works, by continuity from below), assume 0<λ(A)<∞0 < \lambda(A) < \infty. Take U⊇AU \supseteq A open with λ(U)<43λ(A)\lambda(U) < \frac43\lambda(A) and decompose U=⨆nInU = \bigsqcup_nI_n into disjoint open intervals: λ(A)=∑nλ(A∩In)\lambda(A) = \sum_n\lambda(A\cap I_n). If every nn had λ(A∩In)≤34ℓ(In)\lambda(A\cap I_n) \leq \frac34\ell(I_n), summing would give λ(A)≤34λ(U)<λ(A)\lambda(A) \leq \frac34\lambda(U) < \lambda(A): some interval II satisfies λ(A∩I)>34ℓ(I)\lambda(A\cap I) > \frac34\ell(I). Set B=A∩IB = A \cap I and let ∣t∣<12ℓ(I)\abs t < \frac12\ell(I): both BB and B+tB + t lie in the interval I∪(I+t)I \cup (I + t), of length <32ℓ(I)< \frac32\ell(I). If they were disjoint: λ(B)+λ(B+t)=2λ(B)>32ℓ(I)\lambda(B) + \lambda(B + t) = 2\lambda(B) > \frac32\ell(I) would exceed the containing interval’s measure — impossible. So B∩(B+t)≠∅B \cap (B + t) \neq \varnothing: some x∈Bx \in B writes x=y+tx = y + t with y∈By \in B, and t=x−y∈A−At = x - y \in A - A. Hence (−ℓ(I)2, ℓ(I)2)⊆A−A\intoo{-\frac{\ell(I)}2}{\frac{\ell(I)}2} \subseteq A - A.

Exercise 9.9 ★★★

Show that every A∈LA \in \mathcal L with λ(A)>0\lambda(A) > 0 contains a non-measurable subset. (Intersect AA with the translates V+qV + q of Vitali’s set: if all A∩(V+q)A \cap (V+q) were measurable, each would be null by the argument of Theorem 9.15 — Steinhaus (Exercise 9.8) helps: a measurable set of positive measure inside V+qV + q would give (V+q)−(V+q)⊇(V+q) - (V+q) \supseteq an interval, contradicting that this difference set meets Q\Q only at 00; conclude with subadditivity.)

Solution

Solution of Exercise 9.9.

The Vitali translates (V+q)q∈Q(V + q)_{q\in\Q} partition R\R (every real is equivalent to exactly one representative). Suppose all the sets Bq=A∩(V+q)B_q = A \cap (V + q) were measurable. Any two elements of V+qV + q differ by an irrational or zero (two distinct representatives are inequivalent), so Bq−BqB_q - B_q meets Q\Q only in {0}\{0\}: it contains no interval, and Steinhaus (Exercise 9.8) forces λ(Bq)=0\lambda(B_q) = 0. Then λ(A)≤∑qλ(Bq)=0\lambda(A) \leq \sum_{q}\lambda(B_q) = 0, contradicting λ(A)>0\lambda(A) > 0. So some Bq⊆AB_q \subseteq A is non-measurable.

Exercise 9.10 ★★

Show that A⊆RA \subseteq \R with λ∗(A)<∞\lambda^*(A) < \infty is Lebesgue-measurable iff for every ε>0\varepsilon > 0 there is an open U⊇AU \supseteq A with λ∗(U∖A)<ε\lambda^*(U \setminus A) < \varepsilon, iff there is a GδG_\delta set G⊇AG \supseteq A with λ∗(G∖A)=0\lambda^*(G\setminus A) = 0. (So Lebesgue sets are Borel sets modulo null sets.)

Solution

Solution of Exercise 9.10.

Measurable ⇒\Rightarrow ε\varepsilon-approximation: by outer regularity (Theorem 9.13) pick open U⊇AU \supseteq A with λ(U)≤λ(A)+ε\lambda(U) \leq \lambda(A) + \varepsilon; measurability allows the subtraction λ(U∖A)=λ(U)−λ(A)≤ε\lambda(U\setminus A) = \lambda(U) - \lambda(A) \leq \varepsilon. ε\varepsilon-version ⇒\Rightarrow GδG_\delta-version: take UnU_n with λ∗(Un∖A)<1n\lambda^*(U_n\setminus A) < \frac1n and G=⋂UnG = \bigcap U_n: a GδG_\delta with λ∗(G∖A)≤λ∗(Un∖A)→0\lambda^*(G\setminus A) \leq \lambda^*(U_n\setminus A) \to 0. GδG_\delta-version ⇒\Rightarrow measurable: G∖AG\setminus A is λ∗\lambda^*-null, hence measurable by completeness (Theorem 9.9), and A=G∖(G∖A)A = G \setminus (G\setminus A) is measurable (GG is Borel). So Lebesgue sets are exactly “Borel modulo null”.

Exercise 9.11 ★★

(Continuity along monotone limits, and its sharpness) (a) Show that for measurable sets, μ(lim inf⁡An)≤lim inf⁡μ(An)\mu(\liminf A_n) \leq \liminf\mu(A_n) (Fatou for sets), and that if μ(⋃An)<∞\mu\bigl(\bigcup A_n\bigr) < \infty, also lim sup⁡μ(An)≤μ(lim sup⁡An)\limsup\mu(A_n) \leq \mu(\limsup A_n). (b) Exhibit, for Lebesgue measure on R\R, a sequence with μ(An)=1\mu(A_n) = 1 for all nn yet μ(lim sup⁡An)=0\mu(\limsup A_n) = 0: the finiteness hypothesis in the second inequality is not decorative. (c) Deduce: if ∑μ(An)<∞\sum\mu(A_n) < \infty then μ(lim sup⁡An)=0\mu(\limsup A_n) = 0 (Borel–Cantelli again), and if the AnA_n increase or decrease (with μ(A1)<∞\mu(A_1) < \infty in the decreasing case), μ(lim⁡An)=lim⁡μ(An)\mu(\lim A_n) = \lim\mu(A_n).

Solution

Solution of Exercise 9.11.

(a) lim inf⁡An=⋃N⋂n≥NAn\liminf A_n = \bigcup_N\bigcap_{n\geq N}A_n is an increasing union of the sets BN=⋂n≥NAnB_N = \bigcap_{n\geq N}A_n, so μ(lim inf⁡An)=lim⁡Nμ(BN)\mu(\liminf A_n) = \lim_N\mu(B_N) (continuity from below); and μ(BN)≤inf⁡n≥Nμ(An)\mu(B_N) \leq \inf_{n \geq N}\mu(A_n), whose limit is lim inf⁡μ(An)\liminf\mu(A_n). For the lim sup⁡\limsup: apply the same to the complements inside the finite-measure ambient U=⋃AnU = \bigcup A_n — continuity from above on the decreasing CN=⋃n≥NAnC_N = \bigcup_{n\geq N}A_n requires μ(C1)≤μ(U)<∞\mu(C_1) \leq \mu(U) < \infty, and gives μ(lim sup⁡An)=lim⁡μ(CN)≥lim sup⁡μ(An)\mu(\limsup A_n) = \lim\mu(C_N) \geq \limsup\mu(A_n).

(b) The moving interval An=[n, n+1]A_n = \intcc n{n+1}: every point belongs to at most two of the AnA_n and to none eventually, so lim sup⁡An=∅\limsup A_n = \varnothing; yet μ(An)=1\mu(A_n) = 1. Thus lim sup⁡μ(An)=1>0=μ(lim sup⁡An)\limsup\mu(A_n) = 1 > 0 = \mu(\limsup A_n): without a finite-measure envelope, the second inequality of (a) fails — the mass escapes to infinity, where no fixed set can catch it.

(c) If ∑μ(An)<∞\sum\mu(A_n) < \infty: μ(CN)≤∑n≥Nμ(An)→0\mu(C_N) \leq \sum_{n\geq N}\mu(A_n) \to 0 and lim sup⁡An=⋂CN\limsup A_n = \bigcap C_N has measure ≤inf⁡μ(CN)=0\leq \inf\mu(C_N) = 0. Monotone cases: increasing is continuity from below; decreasing with μ(A1)<∞\mu(A_1) < \infty is continuity from above — both proved in Chapter 9’s basic properties; the counterexample An=[n, ∞)A_n = \intco n\infty (decreasing to ∅\varnothing with μ≡∞\mu \equiv \infty) shows the finiteness is again essential.

Exercise 9.12 ★★★

(Egorov’s theorem) Let μ(X)<∞\mu(X) < \infty and fn→ff_n \to f pointwise, all measurable (real-valued). For k,N≥1k, N \geq 1 set

Ek,N=⋂n≥N{x:∣fn(x)−f(x)∣≤1k}.E_{k,N} = \bigcap_{n \geq N}\Bigl\{x : \abs{f_n(x) - f(x)} \leq \tfrac1k\Bigr\} .

(a) Show that for fixed kk, Ek,N↗XE_{k,N} \nearrow X as N→∞N \to \infty, and deduce NkN_k with μ(X∖Ek,Nk)≤ε2−k\mu(X \setminus E_{k,N_k}) \leq \varepsilon2^{-k}. (b) Conclude Egorov’s theorem: for every ε>0\varepsilon > 0 there is a measurable AA with μ(X∖A)≤ε\mu(X\setminus A) \leq \varepsilon such that fn→ff_n \to f uniformly on AA — pointwise convergence is uniform convergence off an arbitrarily small set. (c) Show the theorem fails on (R,λ)(\R, \lambda): the moving bumps fn=1[n, n+1]f_n = \mathbf 1_{\intcc n{n+1}} converge pointwise to 00 but uniformly on no complement of a finite-measure set. Where did (a) use μ(X)<∞\mu(X) < \infty?

Solution

Solution of Exercise 9.12.

(a) The sets Ek,NE_{k,N} increase with NN (fewer constraints), and every xx eventually satisfies ∣fn(x)−f(x)∣≤1k\abs{f_n(x) - f(x)} \leq \frac1k for all n≥N(x)n \geq N(x) (pointwise convergence): ⋃NEk,N=X\bigcup_NE_{k,N} = X. Continuity from below: μ(Ek,N)→μ(X)<∞\mu(E_{k,N}) \to \mu(X) < \infty, so μ(X∖Ek,N)→0\mu(X\setminus E_{k,N}) \to 0; choose NkN_k accordingly.

(b) Let A=⋂kEk,NkA = \bigcap_kE_{k,N_k}: μ(X∖A)≤∑kε2−k=ε\mu(X\setminus A) \leq \sum_k\varepsilon2^{-k} = \varepsilon. On AA: for every kk, all n≥Nkn \geq N_k satisfy sup⁡A∣fn−f∣≤1k\sup_A\abs{f_n - f} \leq \frac1k — exactly uniform convergence on AA.

(c) For the moving bump, uniform convergence on AA requires AA to eventually avoid every [n, n+1]\intcc n{n+1} — more precisely sup⁡A∣fn∣<12\sup_A\abs{f_n} < \frac12 forces A∩[n, n+1]A \cap \intcc n{n+1} to be empty for large nn, so X∖AX \setminus A contains a tail ⋃n≥n0[n, n+1]\bigcup_{n\geq n_0}\intcc n{n+1}, of infinite measure. In (a), finiteness converted “Ek,N↗XE_{k,N}\nearrow X” into “the complements’ measures tend to 00”: continuity from above needs a finite start, and on infinite-measure spaces the escape to infinity is precisely what it cannot see.

9.6 Problem: the Cantor–Vitali staircase and a measurable set that is not Borel

The Cantor–Vitali staircase: constant on every gap of the Cantor set, yet climbing from 0 to 1 continuously. Its derivative vanishes almost everywhere — all the climbing happens on a null set.
The Cantor–Vitali staircase: constant on every gap of the Cantor set, yet climbing from 00 to 11 continuously. Its derivative vanishes almost everywhere — all the climbing happens on a null set.

Problem 9.1

Weekend problem — the devil’s staircase, and B(R)⊊L\mathcal B(\R) \subsetneq \mathcal L

We construct the Cantor–Vitali function (devil’s staircase), use it to transport measure pathologically, and conclude with a theorem that no soft argument gives: there exist Lebesgue-measurable sets that are not Borel. Notation: CC is the Cantor set, CnC_n its nn-th stage (2n2^n intervals of length 3−n3^{-n}), and every x∈Cx \in C has ternary digits x=∑2bn3−nx = \sum 2b_n3^{-n}, bn∈{0,1}b_n \in \{0,1\} (Exercise 6.10).

Part I — The staircase. Define c0(x)=xc_0(x) = x and cn+1c_{n+1} from cnc_n by

cn+1(x)={12 cn(3x)0≤x≤13,1213≤x≤23,12+12 cn(3x−2)23≤x≤1.c_{n+1}(x) = \begin{cases} \tfrac12\,c_n(3x) & 0 \leq x \leq \tfrac13,\\[2pt] \tfrac12 & \tfrac13 \leq x \leq \tfrac23,\\[2pt] \tfrac12 + \tfrac12\,c_n(3x - 2) & \tfrac23 \leq x \leq 1. \end{cases}
  1. Show that each cnc_n is continuous, nondecreasing, with cn(0)=0c_n(0) = 0, cn(1)=1c_n(1) = 1, and that ∥cn+1−cn∥∞≤12∥cn−cn−1∥∞\norm{c_{n+1} - c_n}_\infty \leq \tfrac12\norm{c_n - c_{n-1}}_\infty.
  2. Deduce that (cn)(c_n) converges uniformly to a continuous nondecreasing cc with c(0)=0c(0) = 0, c(1)=1c(1) = 1 (the Cantor–Vitali function), which satisfies the same self-similar relations as the cn+1c_{n+1} above.
  3. Show that cc is constant on each connected component of [0, 1]∖C\intcc01\setminus C, and that for x=∑n2bn3−n∈Cx = \sum_n 2b_n3^{-n} \in C, c(x)=∑nbn2−nc(x) = \sum_n b_n2^{-n}: the staircase reads Cantor digits in binary (Problem 6.1’s function gg, made monotone and global).
  4. Deduce that cc is differentiable, with c′=0c' = 0, at every point of [0, 1]∖C\intcc01\setminus C: c′=0c' = 0 λ\lambda-almost everywhere (Example 9.14). Conclude that the fundamental theorem of calculus fails for cc:

    c(1)−c(0)=1≠0=∫01c′(t)  ⁣dtc(1) - c(0) = 1 \neq 0 = \int_0^1 c'(t)\,\dd t

    (the integral being over the full-measure set where c′=0c' = 0; anticipating Chapter 10, null sets do not affect integrals). Which hypothesis of the C1\mathcal C^1 fundamental theorem is violated?

  5. Show that c(C)=[0, 1]c(C) = \intcc01: the null set CC is mapped onto a set of full measure.

Part II — The crooked homeomorphism. Let h(x)=c(x)+x2h(x) = \frac{c(x) + x}{2}.

  1. Show that h ⁣:[0, 1]→[0, 1]h \colon \intcc01 \to \intcc01 is a homeomorphism (strictly increasing, continuous, surjective).
  2. Show that λ(h([0, 1]∖C))=12\lambda\bigl(h(\intcc01\setminus C)\bigr) = \tfrac12: on each gap of length ℓ\ell, hh acts as an affine map of slope 12\tfrac12, and the gaps have total length 11.
  3. Deduce λ(h(C))=12\lambda\bigl(h(C)\bigr) = \tfrac12: the homeomorphic image of a null set can have positive measure. (Where does this contradict naive intuition about “size”?)

Part III — A measurable set that is not Borel.

  1. By Exercise 9.9, choose a non-measurable W⊆h(C)W \subseteq h(C). Show that Z=h−1(W)⊆CZ = h^{-1}(W) \subseteq C is Lebesgue-measurable. (It is a subset of a null set; completeness, Theorem 9.9.)
  2. Show that the preimage of a Borel set under a continuous map is Borel. (Good sets principle: {B:h−1(B)∈B}\{B : h^{-1}(B) \in \mathcal B\} is a σ\sigma-algebra containing the open sets — mind the direction of the map.)
  3. Conclude that ZZ is not Borel: if it were, W=(h−1)−1(Z)W = (h^{-1})^{-1}(Z) would be Borel (apply question 10 to the continuous h−1h^{-1}), hence measurable — contradiction. Therefore

     B(R)⊊L \boxed{\ \mathcal B(\R) \subsetneq \mathcal L\ }

    and completeness genuinely enlarges the Borel world.

  4. Exhibit a Lebesgue-measurable function gg and a continuous function φ\varphi such that g∘φg \circ \varphi is not Lebesgue-measurable: measurability, unlike continuity, does not compose. (Take g=1Zg = \mathbf 1_Z and φ=h−1\varphi = h^{-1}, anticipating the definition of measurable functions from Chapter 10: preimages of Borel sets are Lebesgue sets. Where must one be careful about which σ\sigma-algebra is used on the target?)

Part IV — Epilogue.

  1. Sort the following classes by strict inclusion and justify each strictness with an example from this chapter and its problem: countable sets; Borel null sets; Lebesgue null sets; Borel sets; Lebesgue sets; arbitrary sets.

Part V — The Cantor measure: mass on a null set. The staircase is the distribution function of a remarkable measure, which we now build with this chapter’s own tools.

  1. (Lebesgue–Stieltjes, existence) Let F ⁣:R→RF\colon\R\to\R be nondecreasing, continuous, bounded. On half-open intervals define ρ((a, b])=F(b)−F(a)\rho\bigl(\intoc ab\bigr) = F(b) - F(a) and, for A⊆RA \subseteq \R,

    μF∗(A)=inf⁡{∑k(F(bk)−F(ak)):A⊆⋃k(ak, bk]}.\mu_F^*(A) = \inf\Bigl\{\sum_k\bigl(F(b_k) - F(a_k)\bigr) : A \subseteq \bigcup_k\intoc{a_k}{b_k}\Bigr\} .

    Show that μF∗\mu_F^* is an outer measure and that μF∗((a, b])=F(b)−F(a)\mu_F^*\bigl(\intoc ab\bigr) = F(b) - F(a) (imitate the compactness argument of Theorem 9.12, enlarging each (ak, bk]\intoc{a_k}{b_k} to an open interval at FF-cost ≤ε2−k\leq \varepsilon2^{-k} — where is continuity of FF used?).

  2. Show that every Borel set is μF∗\mu_F^*-measurable in the Carathéodory sense (as in the Lebesgue case, it suffices to test half-lines; follow the proof of Theorem 9.9’s application), so that μF=μF∗\mu_F = \mu_F^* restricted to B(R)\mathcal B(\R) is a measure with μF((a, b])=F(b)−F(a)\mu_F(\intoc ab) = F(b) - F(a): the Lebesgue–Stieltjes measure of FF.
  3. Apply this to the staircase (F=cF = c extended by 00 on R−\R_- and 11 on [1, ∞)\intco1\infty): the Cantor measure μ\mu. Show μ(R)=1\mu(\R) = 1, that every gap of the Cantor set is μ\mu-null (cc is constant there), and conclude

    μ(C)=1,λ(C)=0:\mu(C) = 1, \qquad \lambda(C) = 0 :

    μ\mu and λ\lambda live on disjoint carriers (CC and its complement). Two measures in this position are called mutually singular, written μ⊥λ\mu \perp \lambda.

  4. Show that μ\mu has no atoms: μ({x})=0\mu(\{x\}) = 0 for every xx (continuity of cc). An atomless probability measure carried by a Lebesgue-null compact: compare with the only measures seen so far.
  5. (Coin tossing in disguise) For a word (ε1,…,εm)∈{0,1}m(\varepsilon_1, \dots, \varepsilon_m) \in \{0,1\}^m, let CεC_{\varepsilon} be the set of x∈Cx \in C whose ternary digits satisfy bi(x)=εib_i(x) = \varepsilon_i for i≤mi \leq m (one of the 2m2^m Cantor pieces of depth mm). Show μ(Cε)=2−m\mu(C_\varepsilon) = 2^{-m} (the staircase climbs 2−m2^{-m} across that piece: use Part I, question 3). The Cantor measure is the law of an infinite sequence of fair coin flips read in ternary — Chapter 22 will make this exact.
  6. Prove the self-similarity: for every Borel AA,

    μ(A)=12 μ(3A)+12 μ(3A−2),\mu(A) = \tfrac12\,\mu(3A) + \tfrac12\,\mu(3A - 2) ,

    where 3A−2={3x−2:x∈A}3A - 2 = \{3x - 2 : x \in A\} (check it on the generating intervals (a, b]\intoc ab via the self-similar relations of cc, then invoke uniqueness, Theorem 9.7).

  7. Show that the reflection s(x)=1−xs(x) = 1 - x preserves μ\mu: μ(s(A))=μ(A)\mu(s(A)) = \mu(A) (via c(1−x)=1−c(x)c(1 - x) = 1 - c(x), which follows from the symmetry of the construction — prove it).
  8. Compute the first two moments of μ\mu, i.e. of a random point XX with law μ\mu (the integrals may be handled as limits of sums over the depth-mm pieces, anticipating Chapter 10): symmetry gives ∫x  ⁣dμ=12\int x\,\dd\mu = \frac12, and self-similarity gives

    ∫x2  ⁣dμ=38,henceVar⁡(X)=18.\int x^2\,\dd\mu = \frac38, \qquad\text{hence}\qquad \operatorname{Var}(X) = \frac18 .

    Compare with the uniform law on [0, 1]\intcc01 (variance 112\frac1{12}): the Cantor mass, pushed to the edges, spreads more.

  9. Show that the (topological) support of μ\mu — the smallest closed set of full measure — is exactly CC.
  10. (Synthesis) The staircase cc is continuous and nondecreasing yet fails the fundamental theorem of calculus (Part I); the measure μc\mu_c is a probability, atomless, singular with respect to λ\lambda. Explain in a short paragraph how these are two faces of one phenomenon, and state the general moral: nondecreasing functions correspond to measures (F↔μFF \leftrightarrow \mu_F), differentiability a.e. corresponds to the “absolutely continuous part”, and cc is the standard witness that a continuous FF can carry no absolutely continuous part at all.
  11. (The sharp modulus of continuity) Let s=ln⁡2ln⁡3s = \frac{\ln 2}{\ln 3}. Show that cc is Hölder continuous of exponent ss:

    ∣c(x)−c(y)∣≤4 ∣x−y∣s(x,y∈[0, 1]),\abs{c(x) - c(y)} \leq 4\,\abs{x - y}^{s} \qquad (x, y \in \intcc01),

    and that no exponent t>st > s can work, even locally. Deduce the measure-theoretic form: for every xx and every r∈(0, 1]r \in \intoc01,

    μ([x−r, x+r])≤8 rs.\mu\bigl(\intcc{x - r}{x + r}\bigr) \leq 8\,r^{s} .

    (Compare a depth-mm triadic grid with the scale of ∣x−y∣\abs{x - y}; question 18 gives the climb across each piece. The exponent ss is the Hausdorff dimension of CC, as later courses will say.)

  12. (Self-similarity characterizes μ\mu) Prove the converse of question 19: if ν\nu is a probability measure on B(R)\mathcal B(\R) carried by [0, 1]\intcc01 and satisfying

    ν(A)=12 ν(3A)+12 ν(3A−2)(A∈B(R)),\nu(A) = \tfrac12\,\nu(3A) + \tfrac12\,\nu(3A - 2) \qquad (A \in \mathcal B(\R)),

    then ν=μ\nu = \mu. (Iterate the relation mm times to spread ν\nu over the 2m2^m depth-mm Cantor pieces, estimate ν((a, b])\nu(\intoc ab) against the count of pieces inside (a, b]\intoc ab, and let m→∞m \to \infty; finish with Theorem 9.7.)

Solution

Solution of Problem 9.1.

1. Induction. Continuity: the three formulas agree at the junctions (12cn(1)=12\frac12c_n(1) = \frac12 and 12+12cn(0)=12\frac12 + \frac12c_n(0) = \frac12); each piece is continuous. Monotonicity and the boundary values are inherited. For the contraction estimate: on [0,13][0,\frac13], ∣cn+1−cn∣(x)=12∣cn−cn−1∣(3x)≤12∥cn−cn−1∥∞\abs{c_{n+1} - c_n}(x) = \frac12\abs{c_n - c_{n-1}}(3x) \leq \frac12\norm{c_n - c_{n-1}}_\infty; on the middle third the difference is 00; on the right third, the same as the left.

2. ∥cn+1−cn∥∞≤2−n∥c1−c0∥∞\norm{c_{n+1} - c_n}_\infty \leq 2^{-n}\norm{c_1 - c_0}_\infty: the series of increments converges uniformly, so cn→cc_n \to c uniformly; cc is continuous, nondecreasing, c(0)=0c(0) = 0, c(1)=1c(1) = 1 (all preserved by uniform limits), and passing to the limit in the defining recursion shows cc itself satisfies the three self-similar identities.

3. By the middle identity, c≡12c \equiv \frac12 on [13, 23]\intcc{\frac13}{\frac23}, the first gap. Every gap of CC is the image of the first gap under a composition of the two affine contractions x↦x3x \mapsto \frac x3, x↦x+23x\mapsto\frac{x + 2}3; the identities transport constancy accordingly (with values the dyadic rationals). For the digit formula, take x=∑n2bn3−n∈Cx = \sum_n 2b_n3^{-n} \in C: if b1=0b_1 = 0 then x∈[0,13]x \in [0,\frac13] and c(x)=12c(3x)c(x) = \frac12c(3x) with 3x3x having digits (b2,b3,… )(b_2, b_3, \dots); if b1=1b_1 = 1 then x∈[23,1]x \in [\frac23, 1] and c(x)=12+12c(3x−2)c(x) = \frac12 + \frac12c(3x - 2), same shift. By induction, the first NN binary digits of c(x)c(x) are b1,…,bNb_1, \dots, b_N for every NN: c(x)=∑nbn2−nc(x) = \sum_nb_n2^{-n}.

4. Off CC, cc is locally constant: differentiable with derivative 00. Since λ(C)=0\lambda(C) = 0 (Example 9.14), c′=0c' = 0 almost everywhere. Yet c(1)−c(0)=1c(1) - c(0) = 1: the fundamental theorem in its C1\mathcal C^1 form requires cc to be differentiable everywhere with continuous (or at least integrable, plus absolute continuity — see Chapter 10) derivative; cc is not differentiable at points of CC, and more fundamentally cc fails absolute continuity: it climbs on a null set.

5. Given y=∑nβn2−n∈[0, 1]y = \sum_n\beta_n2^{-n} \in \intcc01 (βn∈{0,1}\beta_n \in \{0,1\}), the point x=∑n2βn3−n∈Cx = \sum_n2\beta_n3^{-n} \in C has c(x)=yc(x) = y by question 3: c(C)=[0, 1]c(C) = \intcc01, a set of measure 11 — the null set CC carries, through cc, the whole interval.

6. hh is continuous, and strictly increasing (xx is, cc is nondecreasing); h(0)=0h(0) = 0, h(1)=1h(1) = 1, so by the intermediate value theorem hh is a continuous bijection of [0, 1]\intcc01; a continuous bijection from a compact space to a Hausdorff one is a homeomorphism (Corollary 6.14).

7. On a gap (u,v)(u, v) (length ℓ\ell), cc is constant, so hh is affine with slope 12\frac12: h((u,v))h((u,v)) is an interval of length ℓ2\frac\ell2. The gaps are disjoint and hh is injective: the images are disjoint, of total measure 12∑ℓ=12(1−λ(C))=12\frac12\sum\ell = \frac12(1 - \lambda(C)) = \frac12.

8. h([0, 1])=[0, 1]h(\intcc01) = \intcc01 and h(C)h(C) is compact (continuous image), hence measurable, with

λ(h(C))=1−λ(h([0, 1]∖C))=1−12=12.\lambda\bigl(h(C)\bigr) = 1 - \lambda\bigl(h(\intcc01\setminus C)\bigr) = 1 - \tfrac12 = \tfrac12 .

A homeomorphism can inflate a null set to measure 12\frac12: “topological size” (category, dimension) and “measure” are transported by homeomorphisms very differently — only the former is a topological invariant.

9. Z=h−1(W)⊆h−1(h(C))=CZ = h^{-1}(W) \subseteq h^{-1}(h(C)) = C has λ∗(Z)≤λ(C)=0\lambda^*(Z) \leq \lambda(C) = 0: a null set, hence Lebesgue-measurable by completeness (Theorem 9.9).

10. Let φ\varphi be continuous and D={B:φ−1(B)∈B}\mathcal D = \{B : \varphi^{-1}(B) \in \mathcal B\}. Preimages commute with complements and countable unions, so D\mathcal D is a σ\sigma-algebra; it contains the open sets (continuity): D⊇B\mathcal D \supseteq \mathcal B — preimages of Borel sets under continuous maps are Borel.

11. If ZZ were Borel, apply question 10 to the continuous φ=h−1\varphi = h^{-1}: φ−1(Z)=h(Z)=W\varphi^{-1}(Z) = h(Z) = W would be Borel, hence Lebesgue-measurable — contradicting the choice of WW. So Z∈L∖BZ \in \mathcal L \setminus \mathcal B: Lebesgue’s σ\sigma-algebra strictly contains Borel’s.

12. g=1Zg = \mathbf 1_Z is Lebesgue-measurable (Z∈LZ \in \mathcal L) and φ=h−1\varphi = h^{-1} is continuous, but (g∘φ)−1({1})=φ−1(Z)=W(g\circ\varphi)^{-1}(\{1\}) = \varphi^{-1}(Z) = W is not measurable: g∘φg \circ \varphi is not Lebesgue-measurable. The care needed: “Lebesgue-measurable function” means preimages of Borel sets land in L\mathcal L; composing requires preimages of Lebesgue sets to be Lebesgue, which continuity does not grant (here φ−1(Z)∉L\varphi^{-1}(Z) \notin \mathcal L even though φ\varphi is a homeomorphism).

13. The chains, with witnesses for strictness:

{countable}⊊{Borel null}⊊{Lebesgue null}⊊L⊊P(R),{Borel null}⊊B⊊L.\{\text{countable}\} \subsetneq \{\text{Borel null}\} \subsetneq \{\text{Lebesgue null}\} \subsetneq \mathcal L \subsetneq \mathcal P(\R), \qquad \{\text{Borel null}\} \subsetneq \mathcal B \subsetneq \mathcal L .

Witnesses: CC is Borel, null, uncountable (first gap); ZZ is Lebesgue null but not Borel (second and, inside B⊊L\mathcal B \subsetneq \mathcal L, sixth); a fat Cantor set is Borel, nowhere dense, of positive measure (separating null sets from Borel sets); Vitali’s VV is not in L\mathcal L (last gap). Measure, topology and cardinality slice P(R)\mathcal P(\R) along genuinely different lines.

14. Outer measure: μF∗(∅)=0\mu_F^*(\varnothing) = 0 (cover by a vanishing interval), monotonicity is clear, and countable subadditivity follows by splicing ε2−k\varepsilon2^{-k}-optimal covers, exactly as for λ∗\lambda^*. The one-interval cover gives μF∗((a, b])≤F(b)−F(a)\mu_F^*(\intoc ab) \leq F(b) - F(a). Conversely let (a, b]⊆⋃k(ak, bk]\intoc ab \subseteq \bigcup_k\intoc{a_k}{b_k}. By continuity of FF, pick bk′>bkb_k' > b_k with F(bk′)≤F(bk)+ε2−kF(b_k') \leq F(b_k) + \varepsilon2^{-k}, and a′∈(a, b)a' \in \intoo ab with F(a′)≤F(a)+εF(a') \leq F(a) + \varepsilon. The compact [a′, b]\intcc{a'}b is covered by the open (ak, bk′)\intoo{a_k}{b_k'}: finitely many suffice, and the chaining argument of Theorem 9.12 (walk from a′a' to bb through overlapping intervals, telescoping FF-increments, monotonicity absorbing overlaps) yields F(b)−F(a′)≤∑k(F(bk′)−F(ak))≤∑k(F(bk)−F(ak))+εF(b) - F(a') \leq \sum_k(F(b_k') - F(a_k)) \leq \sum_k(F(b_k) - F(a_k)) + \varepsilon. Let ε→0\varepsilon \to 0: equality. (Continuity of FF is what allowed opening the intervals at arbitrarily small FF-cost.)

15. It suffices to prove each half-line Ht=(−∞, t]H_t = \intoc{-\infty}t Carathéodory-measurable, since the measurable sets form a σ\sigma-algebra (Theorem 9.9) and half-lines generate B\mathcal B. Given AA and an ε\varepsilon-optimal cover ((ak, bk])(\intoc{a_k}{b_k}) of AA: each interval splits as (ak, t∧bk]∪(t∨ak, bk]\intoc{a_k}{t\wedge b_k} \cup \intoc{t \vee a_k}{b_k} (one piece possibly empty), with FF-costs adding up exactly to F(bk)−F(ak)F(b_k) - F(a_k); the first pieces cover A∩HtA \cap H_t, the second A∖HtA \setminus H_t. Hence μF∗(A∩Ht)+μF∗(A∖Ht)≤μF∗(A)+ε\mu_F^*(A\cap H_t) + \mu_F^*(A\setminus H_t) \leq \mu_F^*(A) + \varepsilon, and the reverse inequality is subadditivity. Restricting the resulting measure to B\mathcal B: the Lebesgue–Stieltjes measure μF\mu_F.

16. μ(R)=lim⁡n(F(n)−F(−n))=1−0=1\mu(\R) = \lim_n(F(n) - F(-n)) = 1 - 0 = 1 (continuity of the measure along (−n, n]\intoc{-n}n). On a gap (u, v)\intoo uv of CC, cc is constant, so every half-open subinterval is μ\mu-null and so is the gap (countable union); outside [0, 1]\intcc01, cc is constant too. Hence μ(R∖C)=0\mu(\R\setminus C) = 0, μ(C)=1\mu(C) = 1, while λ(C)=0\lambda(C) = 0 (Example 9.14): each of μ,λ\mu, \lambda is carried by a set the other declares null — mutually singular.

17. μ({x})=lim⁡δ↓0μ((x−δ, x])=lim⁡(c(x)−c(x−δ))=0\mu(\{x\}) = \lim_{\delta\downarrow0} \mu(\intoc{x-\delta}x) = \lim(c(x) - c(x-\delta)) = 0 by continuity of cc: no atoms. So μ\mu is an atomless probability measure carried by a Lebesgue-null compact — neither diffuse-with-density like λ\lambda’s restrictions, nor atomic like counting measures: a third species.

18. The piece CεC_\varepsilon spans a ternary interval IεI_\varepsilon of length 3−m3^{-m}, and Part I question 3 shows that across IεI_\varepsilon the staircase climbs exactly 2−m2^{-m} (the first mm binary digits of cc are frozen to ε\varepsilon, the rest sweep everything). Hence μ(Cε)=μ(Iε)=c(right end)−c(left end)=2−m\mu(C_\varepsilon) = \mu(I_\varepsilon) = c(\text{right end}) - c(\text{left end}) = 2^{-m}: depth-mm digit cylinders all have mass 2−m2^{-m}, the law of mm fair coins.

19. The right-hand side defines the Borel measure ν=12 (x↦x3)∗μ+12 (x↦x+23)∗μ\nu = \frac12\,(x \mapsto \tfrac x3)_*\mu + \frac12\,(x \mapsto \tfrac{x+2}3)_*\mu evaluated at AA — probability measure. Pointwise, with cc globally extended, one checks case by case (x≤0x \leq 0; the three thirds; x≥1x \geq 1) the identity

c(x)=12 c(3x)+12 c(3x−2),c(x) = \tfrac12\,c(3x) + \tfrac12\,c(3x - 2),

e.g. on [1/3, 2/3]\intcc{1/3}{2/3}: 12⋅1+12⋅0=12=c(x)\frac12\cdot1 + \frac12\cdot0 = \frac12 = c(x). Evaluating ν\nu on (a, b]\intoc ab therefore gives c(b)−c(a)=μ((a, b])c(b) - c(a) = \mu(\intoc ab), and two finite measures agreeing on the π\pi-system of half-open intervals coincide on B\mathcal B (Theorem 9.7): ν=μ\nu = \mu.

20. By induction on nn: c0(1−x)=1−c0(x)c_0(1-x) = 1 - c_0(x), and if cnc_n has the symmetry, then for x∈[0, 1/3]x \in \intcc0{1/3}: cn+1(1−x)=12+12cn(3(1−x)−2)=12+12cn(1−3x)=12+12(1−cn(3x))=1−cn+1(x)c_{n+1}(1 - x) = \frac12 + \frac12c_n(3(1-x) - 2) = \frac12 + \frac12c_n(1 - 3x) = \frac12 + \frac12(1 - c_n(3x)) = 1 - c_{n+1}(x); the middle third mirrors around 12\frac12; the right third is the left case reflected. In the limit c(1−x)=1−c(x)c(1-x) = 1 - c(x). Pushforward: (s∗μ)((a, b])=μ([1−b, 1−a))=c(1−a)−c(1−b)(s_*\mu)(\intoc ab) = \mu(\intco{1-b}{1-a}) = c(1-a) - c(1-b) (μ\mu atomless, question 17, so boundary conventions cost nothing) =(1−c(a))−(1−c(b))=μ((a, b])= (1 - c(a)) - (1 - c(b)) = \mu(\intoc ab): s∗μ=μs_*\mu = \mu by uniqueness.

21. Let X∼μX \sim \mu (integrals of continuous functions against μ\mu exist as limits of Riemann-type sums over the depth-mm pieces, each of mass 2−m2^{-m}, with sampling error ≤osc⁡≤∥f′∥∞3−m\leq \operatorname{osc} \leq \norm{f'}_\infty3^{-m}; Chapter 10 will systematize this). Symmetry: 1−X∼X1 - X \sim X, so EX=12\E X = \frac12. Self-similarity: XX has the law of Y3\frac Y3 with probability 12\frac12 and of Y+23\frac{Y+2}3 with probability 12\frac12, Y∼μY \sim \mu, so

EX2=12 EY29+12 EY2+4EY+49=2EX2+618,\E X^2 = \frac12\,\frac{\E Y^2}9 + \frac12\, \frac{\E Y^2 + 4\E Y + 4}{9} = \frac{2\E X^2 + 6}{18},

whence EX2=38\E X^2 = \frac38 and Var⁡X=38−14=18\operatorname{Var}X = \frac38 - \frac14 = \frac18. The uniform law has variance 112<18\frac1{12} < \frac18: Cantor mass hugs the endpoints.

22. CC is closed and μ(C)=1\mu(C) = 1. If an open II meets CC at xx, the depth-mm pieces containing xx shrink to xx, so some Iε⊆II_\varepsilon \subseteq I and μ(I)≥2−m>0\mu(I) \geq 2^{-m} > 0: no smaller closed set can carry μ\mu. Points off CC have gap neighborhoods of μ\mu-measure 00. Hence supp⁡μ=C\operatorname{supp}\mu = C exactly.

23. One phenomenon, two dialects. Part I says the growth of cc is invisible to its derivative: c′=0c' = 0 a.e., all the climbing concentrated on the null set CC. Part V says the associated measure μc\mu_c puts all its mass on that same null set: μc⊥λ\mu_c \perp \lambda, so no density f≥0f \geq 0 can satisfy μc(A)=∫Af  ⁣dλ\mu_c(A) = \int_Af\,\dd\lambda — a density forces vanishing on λ\lambda-null sets. The dictionary: nondecreasing bounded F↔F \leftrightarrow finite measure μF\mu_F (questions 14–15); FF an integral of its derivative ↔\leftrightarrow μF\mu_F has a density (the “absolutely continuous” case); and in general F′F', which exists a.e. for monotone FF (Lebesgue’s differentiation theorem, beyond this chapter), recovers only the density part. The staircase is the extreme: continuous, with derivative 00 a.e. — its measure is purely singular, and the fundamental theorem of calculus, far from failing by accident, fails by the exact amount μc(R)=1\mu_c(\R) = 1 of singular mass.

24. Fix x<yx < y in [0, 1]\intcc01 and choose m≥0m \geq 0 with 3−(m+1)<y−x≤3−m3^{-(m+1)} < y - x \leq 3^{-m}. Across any triadic interval [k3−m, (k+1)3−m]\intcc{k3^{-m}}{(k+1)3^{-m}} the staircase climbs at most 2−m2^{-m}: such an interval is either one of the 2m2^m pieces of CmC_m, where the climb is exactly 2−m2^{-m} (question 18), or it is contained in the closure of a single gap of some stage ≤m\leq m, where cc is constant. Since y−x≤3−my - x \leq 3^{-m}, the interval [x, y]\intcc xy meets at most two consecutive depth-mm triadic intervals, so

c(y)−c(x)≤2⋅2−m=2(3−m)s<2(3(y−x))s=4 (y−x)s,c(y) - c(x) \leq 2\cdot2^{-m} = 2\bigl(3^{-m}\bigr)^{s} < 2\bigl(3(y - x)\bigr)^{s} = 4\,(y - x)^{s},

using 3s=23^{s} = 2 and 3−m<3(y−x)3^{-m} < 3(y - x). Optimality: the endpoints u<vu < v of a depth-mm Cantor piece satisfy v−u=3−mv - u = 3^{-m} and c(v)−c(u)=2−m=(v−u)sc(v) - c(u) = 2^{-m} = (v - u)^{s}; a Hölder bound ∣c(v)−c(u)∣≤K(v−u)t\abs{c(v) - c(u)} \leq K(v - u)^{t} with t>st > s would force K≥2−m3mt=(3t/2)m→∞K \geq 2^{-m}3^{mt} = (3^{t}/2)^{m} \to \infty (since 3t>3s=23^{t} > 3^{s} = 2), and every subinterval of [0, 1]\intcc01 contains such pieces, so the failure is local as well. Measure form: μ([x−r, x+r])≤c(x+r)−c(x−r)≤4(2r)s=4⋅2srs≤8rs\mu\bigl(\intcc{x-r}{x+r}\bigr) \leq c(x + r) - c(x - r) \leq 4(2r)^{s} = 4\cdot2^{s}r^{s} \leq 8r^{s} (values of cc extended to R\R as in question 16; μ\mu has no atoms, question 17).

25. Write S0(x)=x3S_0(x) = \frac x3 and S1(x)=x+23S_1(x) = \frac{x+2}3; the hypothesis says ν=12(S0)∗ν+12(S1)∗ν\nu = \frac12(S_0)_*\nu + \frac12(S_1)_*\nu. Iterating mm times,

ν=2−m∑w∈{0,1}m(Sw)∗ν,Sw=Sw1∘⋯∘Swm.\nu = 2^{-m}\sum_{w \in \{0,1\}^m}(S_w)_*\nu, \qquad S_w = S_{w_1}\circ\dots\circ S_{w_m}.

Since ν\nu is carried by [0, 1]\intcc01 and Sw([0, 1])=IwS_w(\intcc01) = I_w, the depth-mm Cantor piece indexed by ww, each (Sw)∗ν(S_w)_*\nu is a probability measure carried by IwI_w; the 2m2^m pieces are pairwise disjoint closed intervals of length 3−m3^{-m}. Fix (a, b]\intoc ab and let NmN_m be the number of pieces Iw⊆(a, b]I_w \subseteq \intoc ab. A piece meeting (a, b]\intoc ab without being contained in it must contain aa or bb, and a point lies in at most one piece, so

2−mNm≤ν((a, b])≤2−mNm+2⋅2−m.2^{-m}N_m \leq \nu(\intoc ab) \leq 2^{-m}N_m + 2\cdot2^{-m}.

The same double inequality holds for μ\mu (question 19 gives the identical iteration), with the same count NmN_m. Hence ∣ν((a, b])−μ((a, b])∣≤2−m+1→0\abs{\nu(\intoc ab) - \mu(\intoc ab)} \leq 2^{-m+1} \to 0: ν\nu and μ\mu agree on the π\pi-system of half-open intervals, and both are probability measures, so Theorem 9.7 gives ν=μ\nu = \mu. The staircase measure is thus the fixed point of the two-map averaging scheme — the measure-level statement of the self-similarity of CC.

Terms defined in this chapter

See all 395 terms in the glossary