C⁢[0,1]: the Faber-Schauder basis, the Riesz representation theorem, and the Borel σ-algebra

Jordan Bell
July 24, 2015

1 Introduction

In this note I work out some results about the space of continuous functions [0,1]→ℝ. In some cases these are instances of general results about continuous functions on compact Hausdorff spaces or compact metrizable spaces.

2 C⁢(K)

Let K be a compact topological space (not necessarily Hausdorff) and let C⁢(K) be the collection of continuous functions K→ℝ. With the norm

∥f∥=supt∈K⁡|f⁢(t)|,f∈C⁢(K),

this is a real Banach algebra, with unity 1:K→ℝ defined by 1⁢(t)=1 for all t∈K.11 1 Charalambos D. Aliprantis and Kim C. Border, Infinite Dimensional Analysis: A Hitchhiker’s Guide, third ed., p. 124, Lemma 3.97. Generally, if X is a compact metrizable space and Y is a separable metrizable space then C⁢(X,Y) is separable.22 2 Charalambos D. Aliprantis and Kim C. Border, Infinite Dimensional Analysis: A Hitchhiker’s Guide, third ed., p. 125, Lemma 3.99. Thus, when K is a compact metrizable space, C⁢(K) is a separable unital Banach algebra.

3 Schauder bases

If X is a real normed space, a Schauder basis for X is a sequence (hk) in X such that for each x∈X there is a unique sequence of real numbers (ck⁢(x)) such that ∑k=1nck⁢(x)⁢hk→x. A sequence (hk) in X is called a basic sequence if it is a Schauder basis for the closure of its linear span.33 3 Because Schauder bases are not as familiar objects as orthonormal bases (Hilbert space bases) or vector space bases (Hamel bases), it is worth explicitly checking their properties to make ourselves familiar with how they work.

If (hk) is a Schauder basis, then ck⁢(0)=0 for all k. Suppose that for some real numbers a1,…,an we have ∑k=1nak⁢hk=0. Then ak=ck⁢(0)=0 for 1≤k≤n, which means that the set {h1,…,hn} is linearly independent. Therefore a Schauder basis is linearly independent. It is immediate that the linear span of a Schauder basis is a dense linear subspace of X. The following shows that a normed space with a Schauder basis is separable.44 4 In particular, a Banach space with a Schauder basis is separable. There is a celebrated counterexample found by Per Enflo of a separable Banach space for which there does not exist a Schauder basis.

Lemma 1.

If (hk) is a Schauder basis for a normed space X then

{∑k=1nak⁢hk:n≥1,a1,…,an∈ℚ}

is dense in X.

Proof.

Let x∈X and let ϵ>0. There is some n for which

∥∑k=1nck⁢(x)⁢hk-x∥≤ϵ.

For each 1≤k≤n, let ak∈ℚ satisfy |ak-ck⁢(x)|≤ϵn⁢∥hk∥. Then

∥∑k=1nak⁢hk-x∥ ≤∥∑k=1n(ak-ck⁢(x))⁢hk∥+ϵ
≤∑k=1n|ak-ck⁢(x)|⁢∥hk∥+ϵ
≤2⁢ϵ,

which proves the claim. ∎

For each k we define hk*:X→ℝ by hk*⁢(x)=ck⁢(x). For x,y∈X, ∑k=1nhk*⁢(x)⁢hk→x and ∑k=1nhk*⁢(y)⁢hk→y, so ∑k=1n(hk*⁢(x)+hk*⁢(y))⁢hk→x+y and therefore hk*⁢(x+y)=hk*⁢(x)+hk*⁢(y), and for α∈ℝ, ∑k=1nα⁢hk*⁢(x)⁢hk→α⁢x and therefore hk*⁢(α⁢x)=α⁢hk*⁢(x). This shows that hk*:X→ℝ is linear. It is apparent that hk*⁢(hj)=δj,k.

We define Pn:X→X by

Pn⁢x=∑k=1nhk*⁢(x)⁢hk,

and it is immediate that Pn is linear and that for each x∈X, Pn⁢x→x as n→∞. It is also immediate that Pn is a finite-rank operator: Pn⁢(X) is a finite-dimensional linear subspace of X. For m,n≥1,

Pn⁢Pm⁢x =Pn⁢∑k=1mhk*⁢(x)⁢hk
=∑k=1mhk*⁢(x)⁢Pn⁢hk
=∑k=1mhk*⁢(x)⁢∑j=1nhj*⁢(hk)⁢hj
=∑k=1mhk*⁢(x)⁢∑j=1nδj,k⁢hj
=Pmin⁡(m,n)⁢x,

showing that

Pn⁢Pm=Pmin⁡(m,n).

In particular, Pn2=Pn, namely, Pn is a projection operator. We prove that when X is a Banach space, Pn is continuous.55 5 N. L. Carothers, A Short Course in Banach Space Theory, p. 26, Theorem 3.1. We indicate explicitly in the proof when we use that X is a Banach space rather than merely a normed space.

Theorem 2.

If X is a Banach space and (hn) is a Schauder basis for X, then each Pn is continuous, and supn≥1⁡∥Pn∥<∞. Furthermore, each hk* is continuous.

Proof.

For x∈X, Pn⁢x→x, so ∥Pn⁢x∥→∥x∥, which implies that supn≥1⁡∥Pn⁢x∥<∞. It thus makes sense to define

p⁢(x)=supn≥1⁡∥Pn⁢x∥.

It is immediate that p⁢(α⁢x)=|α|⁢p⁢(x) and that p⁢(x+y)≤p⁢(x)+p⁢(y). If p⁢(x)=0, then Pn⁢x=0 for all n, which implies that x=0. Therefore p is a norm on X.

For n≥1 and x∈X,

∥Pn⁢x∥≤p⁢(x),

showing that Pn:(X,p)→(X,∥⋅∥) is a bounded linear operator with operator norm ≤1. Suppose that (xk) is a Cauchy sequence in the norm p. Then we have for each n that Pn⁢xk is a Cauchy sequence in the norm ∥⋅∥, and because (X,∥⋅∥) is a Banach space, there is some yn∈X such that Pn⁢xk→yn in the norm ∥⋅∥ as k→∞. For ϵ>0 there is some kϵ such that when j,k≥kϵ, p⁢(xj-xk)≤ϵ, and thus for k≥kϵ and for any n,

∥Pn⁢xk-yn∥=limj→∞⁡∥Pn⁢xk-Pn⁢xj∥≤lim supj→∞⁡p⁢(xk-xj)≤ϵ. (1)

Now, for any m,n and any k,

∥yn-ym∥≤∥yn-Pn⁢xk∥+∥Pn⁢xk-xk∥+∥Pm⁢xk-xk∥+∥Pm⁢xk-ym∥,

so using the above, for k≥kϵ,

∥yn-ym∥≤2⁢ϵ+∥Pn⁢xk-xk∥+∥Pm⁢xk-xk∥.

Because Pn⁢xk→xk as n→∞, there is some nϵ such that ∥Pn⁢xk-xk∥≤ϵ when n≥nϵ, and in this case for n,m≥nϵ,

∥yn-ym∥≤4⁢ϵ,

which shows that yn is a Cauchy sequence in the norm ∥⋅∥, and because (X,∥⋅∥) is a Banach space there is some y∈X such that yn→y in the norm ∥⋅∥.

For any n,m, the restriction of the linear map Pn:X→X to the finite-dimensional linear subspace Pm⁢(X) is continuous in the norm ∥⋅∥, thus

Pn⁢ym =Pn⁢(limk→∞⁡Pm⁢xk)
=limk→∞⁡Pn⁢Pm⁢xk
=limk→∞⁡Pmin⁡(m,n)⁢xk
=ymin⁡(m,n).

Using this, we find by induction that for each n,

yn=∑k=1nhk*⁢(yk)⁢hk,

and because yn→y in the norm ∥⋅∥ as n→∞ and (hk) is a Schauder basis, this implies that hk*⁢(y)=hk*⁢(yk) for all k, and thus Pn⁢y=yn. Therefore

p⁢(xk-y)=supn≥1⁡∥Pn⁢(xk-y)∥=supn≥1⁡∥Pn⁢xk-yn∥.

For ϵ>0 and k≥kϵ, by (1) we have ∥Pn⁢xk-yn∥≤ϵ and therefore p⁢(xk-y)≤ϵ, which shows that xk→y in the norm p as k→∞. Thus, (X,p) is a Banach space.

The identity map idX:X→X is a linear isomorphism, and for x∈X,

∥idX⁢x∥=∥x∥=limn→∞⁡∥Pn⁢x∥≤p⁢(x),

showing that idX is continuous (X,p)→(X,∥⋅∥). Because (X,p) and (X,∥⋅∥) are Banach spaces and idX is a continuous linear isomorphism, by the open mapping theorem66 6 Walter Rudin, Functional Analysis, second ed., p. 49, Corollary 2.12c. there is some a>0 such that

∥x∥=∥idX∥≥a⁢p⁢(x),x∈X.

Then

∥Pn⁢x∥≤p⁢(x)≤1a⁢∥x∥,

which means that Pn:(X,∥⋅∥)→(X,∥⋅∥) is a bounded linear operator with operator norm ≤1a. ∎

Each Pn is a bounded linear operator on X, and for each x∈X, Pn⁢x→x, which means that Pn→idX in the strong operator topology. The fact that the functions hk*:X→ℝ are linear and continuous means that they belong to the dual space X*.

In Theorem 2, if supn≥1⁡∥Pn∥=1, we call the Schauder basis (xk) monotone.

The following theorem gives sufficient and necessary conditions under which a sequence in a Banach space X is a basic sequence.77 7 Joseph Diestel, Sequences and Series in Banach Spaces, p. 36, Chapter V, Theorem 1. Thus if a sequence satisfies this condition and its linear span is dense in X space, then it is a Schauder basis.

Theorem 3.

Suppose that X is a Banach space and that (xk) is a sequence of nonzero elements of X. There is some K such that for any sequence of real numbers (ak) and any n<N,

∥∑k=1nak⁢xk∥≤K⁢∥∑k=1Nak⁢xk∥ (2)

if and only if (xk) is a basic sequence.

Proof.

It is apparent that K≥1. Let S be the linear span of (xk), and let Sn be the linear span of {x1,…,xn}. For n<N,

|an|⁢∥xn∥≤∥∑k=1n-1ak⁢xk∥+∥∑k=1nak⁢xk∥≤2⁢K⁢∥∑k=1Nak⁢xk∥. (3)

Thus if ∑k=1Nak⁢xk=0 then using the above with aN+1=0, for 1≤n≤N we get an=0, showing that (xk) is linearly independent. Because (xk) is linearly independent, it makes sense to define a linear map Qn:S→Sn by

Qn⁢xk={xkk≤n0k>n.

For x=∑k=1Nak⁢xk∈S, if n<N then by (2), ∥Qn⁢x∥≤K⁢∥x∥, and if n≥N then Qn⁢x=x. Thus for each n, Qn:S→Sn is a bounded linear operator with operator norm ≤K, and because X is a Banach space and S¯n=Sn, there is a unique bounded linear operator Pn:S¯→Sn whose restriction to S is equal to Qn, which satisfies ∥Pn∥=∥Qn∥≤K.88 8 Gert K. Pedersen, Analysis Now, revised printing, p. 47, Proposition 2.1.11. For s∈S, Qn⁢Qm⁢s=Qmin⁡(m,n)⁢s, and for x∈S¯, there is a sequence sk∈S that tends to x, thus

Pn⁢Pm⁢x=limk→∞⁡Pn⁢Pm⁢sk=limk→∞⁡Pmin⁡(m,n)⁢sk=Pmin⁡(m,n)⁢x. (4)

For x∈S¯ and ϵ>0, there is some s∈S with ∥s-x∥≤ϵ. Then there are some a1,…,am∈ℝ for which s=∑i=1mai⁢xi, and for n>m,

∥x-Pn⁢x∥ ≤∥x-s∥+∥s-Pn⁢s∥+∥Pn⁢s-Pn⁢x∥
=∥x-s∥+∥Pn⁢s-Pn⁢x∥
≤ϵ+K⁢∥s-x∥
≤(K+1)⁢ϵ,

showing that Pn⁢x→x. It follows from this and (4) that for each x∈S¯ there is a sequence of real numbers (ck) such that ∑k=1nck⁢xk→x. If (bk) is another such sequence, let ak=ck-bk, and then we obtain from (3) that ak=0 for each k. Therefore, (ck) is the unique sequence of real numbers such that ∑k=1nck⁢xk→x, which establishes that (xk) is a Schauder basis for S¯. ∎

4 Haar system and Faber-Schauder system

For k≥0, for 1≤i≤2k, and for n=2k+i, write

Δn=Δki=(i-12k,i2k),

and we write Δ1=Δ00=(0,1).99 9 We are partly following the presentation in B. S. Kashin and A. A. Saakyan, Orthogonal Series, p. 61, Chapter III. Thus

Δ1=Δ00=(0,1),Δ2=Δ01=(0,1),Δ3=Δ11=(0,12),Δ4=Δ12=(12,1).

If (a,b)⊂[0,1], let (a,b)-=(a,a+b2) and (a,b)+=(a+b2,b). Thus

Δn-=(Δki)-=(i-12k,2⁢i-12k+1)=(2⁢i-22k+1,2⁢i-12k+1)=Δk+12⁢i-1

and

Δn+=(Δki)+=(2⁢i-12k+1,i2k)=(2⁢i-12k+1,2⁢i2k+1)=Δk+12⁢i.
Lemma 4.

If n≥m then either Δn⊂Δm or Δn∩Δm=∅.

Proof.

Let n=2k+i and m=2l+j, with k≥l. Then

Δlj=(j-12l,j2l)=(2k-l⁢(j-1)2k,2k-l⁢j2k).

There are three cases: (i) i≤2k-l⁢(j-1), (ii) 2k-l⁢(j-1)<i≤2k-l⁢j, (iii) i>2k-l⁢j. In the first case, Δki∩Δlj=∅, i.e. Δn∩Δm=∅. In the second case, i-1≥2k-l⁢(j-1) and i≤2k-l, so Δki⊂Δlj, i.e. Δn⊂Δm. In the third case, i-1≥2k-l⁢j so Δki∩Δlj=∅, i.e. Δn∩Δm=∅. ∎

We define χ1=1, and for k≥0, 1≤i≤2k, and n=2k+i, we define

χn⁢(t)={1t∈Δn-=(2⁢i-22k+1,2⁢i-12k+1)-1t∈Δn+=(2⁢i-12k+1,2⁢i2k+1)0otherwise.

For example,

χ2⁢(t)={1t∈(0,12)-1t∈(12,1)0otherwise

and

χ3⁢(t)={1t∈(0,14)-1t∈(14,12)0otherwise

and

χ4⁢(t)={1t∈(12,34)-1t∈(34,1)0otherwise.

We call (χn) the Haar system. It is a fact that (χn) is a monotone Schauder basis for the Banach space L1⁢[0,1] with the norm ∥f∥L1=∫01|f⁢(t)|⁢𝑑t.1010 10 Joram Lindenstrauss and Lior Tzafriri, Classical Banach Spaces I and II, p. 3.

Now we define ϕ1=1 and for n>1 we define ϕn:[0,1]→ℝ by

ϕn⁢(t)=∫0tχn-1⁢(u)⁢𝑑u.

Each ϕn belongs to C⁢[0,1], and we call (ϕn) the Faber-Schauder system. For example,

ϕ2⁢(t)=∫0tχ1⁢(u)⁢𝑑u=t,

and

ϕ3⁢(t)={∫0t1⁢𝑑ut∈[0,12]∫01/21⁢𝑑u+∫1/2t-1⁢d⁢ut∈[12,1]={tt∈[0,12]-t+1t∈[12,1]

and

ϕ4⁢(t)={∫0t1⁢𝑑ut∈[0,14]∫01/41⁢𝑑u+∫1/4t-1⁢d⁢ut∈[14,12]0t∈[12,1]={tt∈[0,14]-t+12t∈[14,12]0t∈[12,1]

and

ϕ5⁢(t)={0t∈[0,12]∫1/2t1⁢𝑑ut∈[12,34]∫1/23/41⁢𝑑u+∫3/4t-1⁢d⁢ut∈[34,1]={0t∈[0,12]t-12t∈[12,34]-t+1t∈[34,1].

Generally for k≥0, for 1≤i≤2k, and for n=2k+i,

ϕn+1⁢(t)={t-i-12kt∈Δn-=(i-12k,2⁢i-12k+1)-t+i2kt∈Δn+=(2⁢i-12k+1,i2k)0otherwise.

We remark that

∥ϕn+1∥=2⁢i-12k+1-i-12k=2-k-1.

5 Riesz representation theorem

Let (X,𝔐) be a measurable space. A signed measure is a function μ:𝔐→[-∞,∞] such that (i) μ⁢(∅)=0, (ii) μ assumes at most one of the values -∞,∞, and (iii) if (Ej) is a sequence of disjoint elements of 𝔐 then μ⁢(⋃Ej)=∑μ⁢(Ej). A finite signed measure is a signed measure whose image is contained in ℝ. We denote by ca⁢(𝔐) the collection of all finite signed measures on 𝔐. For μ,λ∈ca⁢(𝔐) and for c∈ℝ, define

(μ+λ)⁢(E)=μ⁢(E)+λ⁢(E),(c⁢μ)⁢(E)=c⁢μ⁢(E)

for E∈𝔐, and we check that with addition and scalar multiplication thus defined ca⁢(𝔐) is a real vector space. A positive measure is a signed measure whose imaged is contained in [0,∞]. For μ,λ∈ca⁢(𝔐), we write

μ≥λ

if μ-λ is a positive measure; in any case μ-λ∈ca⁢(𝔐). We check that ≤ is a partial order on ca⁢(𝔐) with which ca⁢(𝔐) is an ordered vector space. Finally, a probability measure is a positive measure satisfying μ⁢(X)=1, which in particular belongs to ca⁢(𝔐).

For E∈𝔐, a partition of E is a countable subset {Ei} of 𝔐 whose members are pairwise disjoint. For μ∈ca⁢(𝔐) and E∈𝔐 we define

|μ|(E)=sup{∑i=1∞|μ(Ei)|:{Ei} is a partition of E}.

It is immediate that |μ⁢(E)|≤|μ|⁢(E). It is proved that |μ| is a finite positive measure on 𝔐, called the total variation measure of μ.1111 11 Walter Rudin, Real and Complex Analysis, third ed., pp. 117–118, Theorem 6.2 and Theorem 6.4. For μ∈ca⁢(𝔐), define

μ+=12⁢(|μ|+μ),μ-=12⁢(|μ|-μ).

Because |μ| is a finite positive measure and |μ⁢(E)|≤|μ⁢(E)|, μ+ and μ- are finite positive measures, called the positive and negative variations of μ. Then μ=μ+-μ-, called the Jordan decomposition of μ.

For μ∈ca⁢(𝔐), define

∥μ∥=|μ|⁢(X)=μ+⁢(X)+μ-⁢(X).

One checks that ∥⋅∥ is a norm on ca⁢(𝔐).

For a compact Hausdorff space K and for f,g∈C⁢(K), write g≥f when (g-f)⁢(t)≥0 for all t∈K. A positive linear functional is a linear map ϕ:C⁢(K)→ℝ such that ϕ⁢(f)≥0 when f≥0. In this case, because ∥f∥⋅1+f≥0,

∥f∥⁢ϕ⁢(1)+ϕ⁢(f)=ϕ⁢(∥f∥⋅1+f)≥0

i.e. -ϕ⁢(f)≤ϕ⁢(1)⁢∥f∥, and because ∥f∥⋅1-f≥0,

∥f∥⁢ϕ⁢(1)-ϕ⁢(f)=ϕ⁢(∥f∥⋅1-f)≥0,

i.e. ϕ⁢(f)≤ϕ⁢(1)⁢∥f∥, showing because ∥1∥=1 that the operator norm of ϕ is ∥ϕ∥=ϕ⁢(1), and in particular that ϕ∈C⁢(K)*.

For normed spaces (V,∥⋅∥V) and (W,∥⋅∥W), an isometric isomorphism from V to W is a linear isomorphism T:V→W satisfying ∥T⁢v∥W=∥v∥V for all v∈V. The simplest version of the Riesz representation theorem is for compact metrizable spaces, for which we do not need to speak about regular Borel measures or continuous functions vanishing at infinity.1212 12 Walter Rudin, Real and Complex Analysis, third ed., p. 130, Theorem 6.19.

Theorem 5 (Riesz representation theorem for compact metrizable spaces).

Let K be a compact metrizable space and define Λ:ca⁢(ℬK)→C⁢(K)* by

Λ⁢(μ)⁢(f)=∫Kf⁢𝑑μ,μ∈ca⁢(ℬK),f∈C⁢(K).

Λ is an isometric isomorphism, and is order preserving: if μ≥0 then Λ⁢(μ)∈C⁢(K)* is a positive linear functional, and thus if μ≥λ then Λ⁢(μ)≥Λ⁢(λ).

6 The Borel σ-algebra of C⁢[0,1]

Let I=[0,1], with the relative topology inherited from ℝ, with which I is a compact metric space. For t1,…,tn∈I, we define πt1,…,tn:C⁢(I)→ℝn by

πt1,…,tn⁢(x)=(x⁢(t1),…,x⁢(tn)),x∈C⁢(I),

which is continuous.

For a set X and a collection of functions ft:X→ℝ, the coarsest σ-algebra on X such that each ft is measurable X→ℝ, where ℝ has the Borel σ-algebra, is called the σ-algebra generated by {ft:t∈I}, and is denoted by σ⁢({ft:t∈I}). We show that the Borel σ-algebra of C⁢(I) is equal to the σ-algebra generated by the family of projection maps C⁢(I)→ℝ.1313 13 K. R. Parthasarathy, Probability Measures on Metric Spaces, p. 212, Theorem 2.1.

Theorem 6.

Let 𝒜 be the σ-algebra generated by the family {πt:t∈[0,1]}. Then ℬC⁢[0,1]=𝒜.

Proof.

Because C⁢(I) is a separable metric space it is second-countable, and so if U is an open subset of C⁢(I) then U is equal to the union of countably many open balls. Each open ball is equal to the union of countably many closed balls: B⁢(x,r)=⋃B⁢(x,r-1/n)¯. Therefore each open subset of C⁢(I) is equal to the union of countably many closed balls, and to prove that ℬC⁢(I)⊂𝒜 it suffices to prove that all closed balls belong to 𝒜. To this end, let q1,q2,… be an enumeration of [0,1]∩ℚ, let x∈C⁢(I), and let r>0. Suppose that |y⁢(qn)-x⁢(qn)|≤r for all n, and take t∈[0,1]. Then there is a subsequence qan of qn that tends to t, and because y-x:[0,1]→ℝ is continuous, |y⁢(qan)-x⁢(qan)|→|y⁢(t)-x⁢(t)|, and then because for each n we have |y⁢(qan)-x⁢(qan)|≤r it follows that |y⁢(t)-x⁢(t)|≤r. This establishes

{y∈C⁢(I):∥y-x∥≤r}=⋂n=1∞{y∈C⁢(I):|y⁢(qn)-x⁢(qn)|≤r}.

But

{y∈C⁢(I):|y⁢(qn)-x⁢(qn)|≤r}=πqn-1⁢([πqn⁢(x)-r,πqn⁢(x)+r]),

which belongs to 𝒜. Thus B⁢(x,r)¯ is a countable intersection of elements of 𝒜 and so belongs to 𝒜, which shows that ℬC⁢(I)⊂𝒜.

On the other hand, for each t∈I the map πt:C⁢(I)→ℝ is continuous and hence is measurable ℬC⁢(I)→ℬℝ.1414 14 Charalambos D. Aliprantis and Kim C. Border, Infinite Dimensional Analysis: A Hitchhiker’s Guide, third ed., p. 140, Corollary 4.26. Therefore 𝒜⊂ℬC⁢(I). ∎

7 Relatively compact subsets of C⁢[0,1]

If (M,d) is a metric space, a subset A of M is called totally bounded if for each ϵ>0 there are finitely many points x1,…,xn∈M such that for any point x∈M there is some i for which d⁢(x,xi)<ϵ. It is immediate that a compact metric space is totally bounded, and the Heine-Borel theorem states that a metric space is compact if and only if it is complete and totally bounded.1515 15 Charalambos D. Aliprantis and Kim C. Border, Infinite Dimensional Analysis: A Hitchhiker’s Guide, third ed., p. 86, Theorem 3.28. On the other hand, one checks that if (M,d) is a metric space and A is a totally bounded subset of M, then the closure A¯ is a totally bounded subset of M. Thus, if A is a totally bounded subset of a complete metric space (M,d), then the closure A¯ is itself a complete metric space (because (M,d) is a complete metric space), and because A¯ is complete and totally bounded, by the Heine-Borel theorem it is compact.

If X is a topological space and ℱ is a subset of C⁢(X), we say that ℱ is equicontinuous at x∈X if for each ϵ>0 there is a neighborhood Ux,ϵ of x such that |f⁢(x)-f⁢(y)|<ϵ for all f∈ℱ and for all y∈Ux,ϵ, and we call ℱ equicontinuous if it is equicontinuous at each x∈X. We call ℱ pointwise bounded if for each x∈X, {f⁢(x):f∈ℱ} is a bounded subset of ℝ. The Arzelà-Ascoli theorem states that for a compact Hausdorff space X and for ℱ⊂C⁢(X), ℱ is equicontinuous and pointwise bounded if and only if ℱ is totally bounded.1616 16 Gerald B. Folland, Real Analysis: Modern Techniques and Their Applications, second ed., p. 137, Theorem 4.43. Then the closure ℱ¯ is totally bounded and is itself a complete metric space, and hence is a compact metric space. That is, for a compact Hausdorff space X, ℱ is equicontinuous and pointwise bounded if and only if ℱ is relatively compact in C⁢(X).

For x∈C⁢[0,1] and δ>0, define

ωx⁢(δ)=sups,t∈I,|s-t|≤δ⁡|x⁢(s)-x⁢(t)|.

For x∈C⁢[0,1] because x:I→ℝ is continuous and I is compact, x is uniformly continuous on I. Thus for ϵ>0 there is some δϵ>0 such that when |s-t|≤δϵ, |x⁢(s)-x⁢(t)|≤ϵ, hence if δ≤δϵ then ωx⁢(δ)≤ϵ, i.e. ωx⁢(δ)→0 as δ→0. We give sufficient and necessary conditions for a subset of C⁢[0,1] to be relatively compact.

Lemma 7.

Let A⊂C⁢[0,1]. A is relatively compact if and only if

supx∈A⁡|x⁢(0)|<∞ (5)

and

limδ↓0⁡supx∈A⁡ωx⁢(δ)=0. (6)
Proof.

For t∈I and for r>0, let

Br⁢(t)={s∈I:|s-t|<r},

which is an open neighborhood of t. The Arzelà-Ascoli theorem tells us that A is relatively compact if and only if A is equicontinuous and pointwise bounded. If A is relatively compact, then being pointwise bounded yields (5). Let ϵ>0. Because A is equicontinuous, for each t∈I there is some δt>0 such that for all x∈A and for all s∈Bδt⁢(t) we have |x⁢(s)-x⁢(t)|<ϵ/2. Then because I is compact, there are t1,…,tn∈I such that I=⋃i=1nBδti⁢(ti). Let δϵ>0 be the Lebesgue number for this open cover: for each t∈I there is some i for which Bδϵ⁢(t)⊂Bδti⁢(ti). For 0<δ≤δϵ, for x∈A, and for |s-t|≤δ/2, there is some i for which Bδ⁢(t)⊂Bδti⁢(ti), so s,t∈Bδti⁢(ti), which means that |x⁢(s)-x⁢(ti)|<ϵ/2 and |x⁢(t)-x⁢(ti)|<ϵ/2, and thus |x⁢(s)-x⁢(t)|≤|x⁢(s)-x⁢(ti)|+|x⁢(ti)-x⁢(t)|<ϵ. Therefore ωδ/2⁢(x)≤ϵ, and this is true for all x∈A which proves (6).

Suppose now that (5) and (6) are true. By (6), there is some m≥1 such that supx∈A⁡ωx⁢(1/m)≤1, and therefore for x∈A, ∥x∥≤|x⁢(0)|+m. With (5) this yields supx∈A⁡∥x∥<∞, whence A is pointwise bounded. Let t∈I and let ϵ>0. By (6) there is some δ>0 such that supx∈A⁡ωx⁢(δ)<ϵ. Thus for x∈A and for |s-t|≤δ, |x⁢(s)-x⁢(t)|<ϵ, which shows that A is equicontinuous at t. This is true for all t∈I, so A is equicontinuous and by the Arzelà-Ascoli theorem we get that A is relatively compact in C⁢[0,1]. ∎

8 Continuously differentiable functions

Let f:[0,1]→ℝ be a function. We say that f is differentiable at t∈[0,1] if there is some f′⁢(t)∈ℝ such that1717 17 cf. Nicolas Bourbaki, Elements of Mathematics. Functions of a Real Variable: Elementary Theory, p. 3, Chapter I, §1, no. 1, Definition 1.

lims→t,s∈[0,1]∖{t}⁡f⁢(s)-f⁢(t)s-t=f′⁢(t).

If f is differentiable at each t∈[0,1], we say that f is differentiable on [0,1] and define f′:[0,1]→ℝ by t↦f′⁢(t). We define C1⁢[0,1] to be the collection of those f:[0,1]→ℝ such that f is differentiable on [0,1] and f′:[0,1]→ℝ is continuous. C1⁢[0,1] is contained in C⁢[0,1], and it turns out that C1⁢[0,1] is a Borel set in C⁢[0,1].1818 18 Alexander S. Kechris, Classical Descriptive Set Theory, p. 70, §11.B, Example 2. On the other hand, the collection differentiable functions [0,1]→ℝ, which is a subset of C⁢[0,1], is not a Borel set in C⁢[0,1].1919 19 S. M. Srivastava, A Course on Borel Sets, p. 139, Proposition 4.2.7.