Jump to content

Functional Analysis/Topological vector spaces

From Wikibooks, open books for an open world

25% developed  as of May 28, 2008 (May 28, 2008)

A vector space endowed by a topology that makes translations (i.e., x+y) and dilations (i.e., αx) continuous is called a topological vector space or TVS for short.

A subset E of a TVS is said to be:

  • bounded if for every neighborhood V of 0 there exist s>0 such that E⊂tV for every t>s
  • balanced if λE⊂E for every scalar λ with |λ|≤1
  • convex if λ1x+λ2y∈E for any x,y∈E and any λ1,λ2≥0 with λ1x+λ2y=1.

1 Corollary (s+t)E=sE+tE for any s,t>0 if and only if E is convex.
Proof: Supposing s+t=1 we obtain sx+ty∈E for all x,y∈E. Conversely, if E is convex,

ss+tx+ts+ty∈E, or sx+sy∈(s+t)E for any x,y∈E.

Since (s+t)E⊂sE+tE holds in general, the proof is complete.◻

Define f(λ,x)=λx for scalars λ, vectors x. If E is a balanced set, for any |λ|≤1, by continuity,

f(λ,E‾)⊂f(λ,E)‾⊂E‾.

Hence, the closure of a balanced set is again balanced. In the similar manner, if E is convex, for s,t>0

f((s+t),E‾)=f((s+t),E)‾=sE+tE‾,

meaning the closure of a convex set is again convex. Here the first equality holds since f(λ,⋅) is injective if λ≠0. Moreover, the interior of E, denoted by E∘, is also convex. Indeed, for λ1,λ2≥0 with λ1+λ2=1

λ1E∘+λ2E∘⊂E,

and since the left-hand side is open it is contained in E∘. Finally, a subspace of a TVS is a subset that is simultaneously a linear subspace and a topological subspace. Let ℳ be a subspace of a TVS. Then ℳ‾ is a topological subspace, and it is stable under scalar multiplication, as shown by the argument similar to the above. Let g(x,y)=x+y. If ℳ is a subspace of a TVS, by continuity and linearity,

g(ℳ‾,ℳ‾)⊂g(ℳ,ℳ)‾=ℳ‾.

Hence, ℳ‾ is a linear subspace. We conclude that the closure of a subspace is a subspace.

Let V be a neighborhood of 0. By continuity there exists a δ>0 and a neighborhood W of 0 such that:

f({λ;|λ|<δ},W)⊂V

It follows that the set {λ;|λ|<δ}W is a union of open sets, contained in V and is balanced. In other words, every TVS admits a local base consisting of balanced sets.

1 Theorem Let 𝒳 be a TVS, and E⊂𝒳. The following are equivalent.

  • (i) E is bounded.
  • (ii) Every countable subset of E is bounded.
  • (iii) for every balanced neighborhood V of 0 there exists a t>0 such that E⊂tV.

Proof: That (i) implies (ii) is clear. If (iii) is false, there exists a balanced neighborhood V such that E⊄nV for every n=1,2,.... That is, there is a unbounded sequence x1,x2,... in E. Finally, to show that (iii) implies (i), let U be a neighborhood of 0, and V be a balanced open set with 0∈V⊂U. Choose t so that E⊂tV, using the hypothesis. Then for any s>t, we have:

E⊂tV=stsV⊂sV⊂sU

◻

1 Corollary Every Cauchy sequence and every compact set in a TVS are bounded.
Proof: If the set is not bounded, it contains a sequence that is not Cauchy and does not have a convergent subsequence. ◻

1 Lemma Let f be a linear operator between TVSs. If f(V) is bounded for some neighborhood V of 0, then f is continuous.
◻

6 Theorem Let f be a linear functional on a TVS 𝒳.

  • (i) f has either closed or dense kernel.
  • (ii) f is continuous if and only if ker⁡f is closed.

Proof: To show (i), suppose the kernel of f is not closed. That means: there is a y which is in the closure of ker⁡f but f(y)≠0. For any x∈𝒳, x−f(x)f(y)y is in the kernel of f. This is to say, every element of 𝒳 is a linear combination of y and some other element in ker. Thus, ker⁡f is dense. (ii) If f is continuous, ker⁡f=f−1({0}) is closed. Conversely, suppose ker⁡f is closed. Since f is continuous when f is identically zero, suppose there is a point y with f(y)=1. Then there is a balanced neighborhood V of 0 such that y+V⊂(ker⁡f)c. It then follows that supV|f|<1. Indeed, suppose |f(x)|≥1. Then

y−xf(x)∈ker⁡(f)∩(y+V) if x∈V, which is a contradiction.

The continuity of f now follows from the lemma. ◻

6 Theorem Let 𝒳 be a TVS and ℳ⊂𝒳 its subspace. Suppose:

ℳ is dense ⟺ z∈𝒳∗=0 in ℳ implies z=0 in 𝒳.

(Note this is the conclusion of Corollary 2.something) Then every continuous linear function f on a subspace ℳ of 𝒳 extends to an element of 𝒳∗.
Proof: We essentially repeat the proof of Theorem 3.8. So, let ℳ be the kernel of f, which is closed, and we may assume ℳ≠𝒳. Thus, by hypothesis, we can find g∈𝒳∗ such that:g=0 in M, but g(p)≠0 for some point p outside M. By Lemma 1.6, g=λf for some scalar λ. Since both f and g do not vanish at p, λ=g(p)f(p)≠0. ◻

Lemma Let V0,V1,... be a sequence of subsets of a a linear space containing 0 such that Vn+1+Vn+1⊂Vn for every n≥0. If x∈Vn1+...+Vnk and 2−n1+...+2−nk≤2−m, then x∈Vm.
Proof: We shall prove the lemma by induction over k. The basic case k=1 holds since Vn⊂Vn+Vn for every n. Thus, assume that the lemma has been proven until k−1. First, suppose n1,...,nk are not all distinct. By permutation, we may then assume that n1=n2. It then follows:

x∈Vn1+Vn2+...+Vnk⊂Vn2−1+...+Vnk and 2−n1+...2−nk=2−(n2−1)+...+2−nk≤2m.

The inductive hypothesis now gives: x∈Vm. Next, suppose n1,...,nk are all distinct. Again by permutation, we may assume that n1<n2<...nk. Since no carry-over occurs then and m<n1, m+1<n2 and so:

2−n2+...+2−nk≤2−(m+1).

Hence, by inductive hypothesis, x∈Vn1+Vm+1⊂Vm. ◻

1 Theorem Let 𝒳 be a TVS.

  • (i) If 𝒳 is Hausdorff and has a countable local base, 𝒳 is metrizable with the metric d such that
d(x,y)=d(x+z,y+z) and d(λx,0)≤d(x,0) for every |λ|≤1
  • (ii) For every neighborhood V⊂𝒳 of 0, there is a continuous function g such that
g(0)=0, g=1 on Vc and g(x+y)≤g(x)+g(y) for any x,y.

Proof: To show (ii), let V0,V1,... be a sequence of neighborhoods of 0 satisfying the condition in the lemma and V=V0. Define g=1 on Vc and g(x)=inf⁡{2−n1+...+2−nk;x∈Vn1+...+Vnk} for every x∈V. To show the triangular inequality, we may assume that g(x) and g(y) are both <1, and thus suppose x∈Vn1+...+Vnk and y∈Vm1+...+Vmj. Then

x+y∈Vn1+...+Vnk+Vm1+...+Vmj

Thus, g(x+y)≤2−n1+...+2−nk+2−m1+...+2−mj. Taking inf over all such n1,...,nk we obtain:

g(x+y)≤g(x)+2−m1+...+2−mj

and do the same for the rest we conclude g(x+y)≤g(x)+g(y). This proves (ii) since g is continuous at 0 and it is then continuous everywhere by the triangular inequality. Now, to show (i), choose a sequence of balanced sets V0,V1,... that is a local base, satisfies the condition in the lemma and is such that V0=𝒳. As above, define f(x)=inf⁡{2−n1+...+2−nk;x∈Vn1+...+Vnk} for each x∈𝒳. For the same reason as before, the triangular inequality holds. Clearly, f(0)=0. If f(x)≤2−m, then there are n1,...,nk such that 2−n1+...+2−nk≤2−m and x∈Vn1+...+Vnk. Thus, x∈Vm by the lemma. In particular, if f(x)≤2−m for "every" m, then x=0 since 𝒳 is Hausdorff. Since Vn are balanced, if |λ|≤1,

λx∈Vn1+...+Vnk for every n1,...,nk with x∈Vn1+...+Vnk.

That means f(λx)≤f(x), and in particular f(x)=f(−(−x))≤f(−x)≤f(x). Defining d(x,y)=f(x−y) will complete the proof of (i). In fact, the properties of f we have collected shows the function d is a metric with the desired properties. The lemma then shows that given any m, {x;f(x)<δ}⊂Vm for some δ≤2m. That is, the sets {x;f(x)<δ} over δ>0 forms a local base for the original topology. ◻

The second property of d in (i) implies that open ball about the origin in terms of this d is balanced, and when 𝒳 has a countable local base consisting of convex sets it can be strengthened to:d(λx,y)≤λd(x,y), which implies open balls about the origin are convex. Indeed, if x,y∈Vn1+...+Vnk, and if λ1≥0 and λ2≥0 with λ1+λ2, then

λ1x+λ2y∈Vn1+...+Vnk

since the sum of convex sets is again convex. This is to say,

f(λ1x+λ2y)≤min⁡{f(x),f(y)}≤f(x)+f(y)2

and by iteration and continuity it can be shown that f(λx)≤λf(x) for every |λ|≤1.

Corollary For every neighborhood V of some point x, there is a neighborhood of x with W‾⊂V
Proof: Since we may assume that x=0, take W={x;g(x)<2−1}. ◻

Corollary If every finite set of a TVS 𝒳 is closed, 𝒳 is Hausdorff.
Proof: Let x,y be given. By the preceding corollary we find an open set V⊂V‾⊂{y}c containing x. ◻

A TVS with a local base consisting of convex sets is said to be locally convex. Since in this book we will never study non-Hausdorff locally convex spaces, we shall assume tacitly that every finite subset of every locally convex is closed, hence Hausdorff in view of Theorem something.

Lemma Let 𝒳 be locally convex. The convex hull of a bounded set is bounded.

Given a sequence pn of semi-norms, define:

d(x,y)=∑n=0∞2−npn(x−y)1+pn(x−y).

d then becomes a metric. In fact, Since (1+p(x)+p(y))p(x+y)≤(p(x)+p(y))(1+p(x+y)) for any seminorm p, d(x,y)≤d(x,z)+d(z,y).


References

[edit | edit source]