Vector Space, Lecture Notes - Mathematics - 3, Study notes of Mathematics

duality of Lspaces first bite

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2. Lpand `p
2.1. Duality of Lp-spaces: first bite. An important task in this Chapter will be that of characterizing the duals of
Lp-spaces for 1 p < . The theorem is easier to state than to prove: the dual of Lp“is” Lq, where p1+q1= 1
(and q=in the case p= 1). The Section B course included proofs of this duality for `p-spaces and for L2(which is a
Hilbert space).
Theorem 2.1. Let 1p , let qbe the conjugate index and let (Ω,F)be a (σ-finite) measure space. There is a
linear isometric embedding Uq:LqL
pgiven by
(Uq(y))(x) = hx, yi=Z
x(t)y(t)dµ(t).
Proof. By older’s inequality the integral defining (Uq(y))(x) exists and we have
|(Uq(y))(x)|≤kykqkxkp.
Since linearity of Uq(y) is trivial we thus have Uq(y)L
pwith
kUq(y)k kykq, .
The operator Uq(which is also patently linear) is thus of norm at most 1; we need to show it is isometric. So let yLq
be an element with kykq= 1. Initially assume that 1 <p<, set x=|y|q/psign yand observe that
kxkp= 1 ; (Uq(y))(x) = Zxy dµ=Z|y|q/p|y|dµ=Z|y|qdµ= 1.
We deduce that kUq(y)k= 1 as required.
If p=we simply set x= sign yand have
kxk= 1 ; (U1(y))(x) = Zxy dµ=Z|y|dµ=kyk1= 1.
Finally, in the case p= 1, need to be a little more careful, since σ-finiteness comes into the argument. Let yLbe
an element with kyk= 1. For any r < 1 the set [|y| r] is non null and by σ-finiteness, we can choose a set AF
with A[|y| r], and 0 < µ(A)<. We now set
x= (µ(A))1sign y1A,
and have
xL1,kxk1= 1,(U(y))(x) = (µ(A))1ZA
|y|dµr.
The difficult part of our duality proofs will involve proving that Uqis surjective and we defer this to a later section.
Let us note that (except in the finite-dimensional case) U1is never a surjection from L1onto L
. We shall show, in due
course, that Uqis surjective in all other cases.
Notice, in passing, the use of the angle-brackets notation ,·i for the duality between Lpand Lq. We shall use the
same notation in the context of the familiar duality between `pand `q, putting
hx, yi=
X
n=1
x(n)y(n).
2.2. Disjointness in Lp.Another theme in this chapter is going to be the question: to what extent is Lp(0,1) “like” `p?
We know that when p= 2 these spaces are isometrically isomorphic. What happens when p6= 2? We start by observing
that there is at least some similarity between Lpand `p.
Definition 2.2. If xis a scalar-valued function on some set Γ we define the support of xto be
supp x={γΓ : x(γ)6= 0}.
We say that two functions xand yare disjointly supported, or just disjoint, if supp xsupp y=.When we are thinking
of elements of Lpwe say that xand yare disjoint if µ(supp xsupp y) = 0, or equivalently xy = 0 a.e.
Proposition 2.3. Let 1p < and let (xk)kNbe a disjoint sequence of non-zero vectors in Lp(µ). Then
kX
kN
xkkp= X
kN
kxkkp
p!1/p
.
The closed linear span X=sph{xk:kN}i is isometrically isomorphic to `pand is complemented in Lp(µ)by a
projection Pof norm 1.
16
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  1. Lp and `p

2.1. Duality of Lp-spaces: first bite. An important task in this Chapter will be that of characterizing the duals of Lp-spaces for 1 ≤ p < ∞. The theorem is easier to state than to prove: the dual of Lp “is” Lq , where p−^1 + q−^1 = 1 (and q = ∞ in the case p = 1). The Section B course included proofs of this duality for `p-spaces and for L 2 (which is a Hilbert space).

Theorem 2.1. Let 1 ≤ p ≤ ∞, let q be the conjugate index and let (Ω, F , μ) be a (σ-finite) measure space. There is a linear isometric embedding Uq : Lq → L∗ p given by

(Uq (y))(x) = 〈x, y〉 =

Ω

x(t)y(t) dμ(t).

Proof. By H¨older’s inequality the integral defining (Uq (y))(x) exists and we have

|(Uq (y))(x)| ≤ ‖y‖q ‖x‖p.

Since linearity of Uq (y) is trivial we thus have Uq (y) ∈ L∗ p with

‖Uq (y)‖ ≤ ‖y‖q ,.

The operator Uq (which is also patently linear) is thus of norm at most 1; we need to show it is isometric. So let y ∈ Lq be an element with ‖y‖q = 1. Initially assume that 1 < p < ∞, set x = |y|q/psign y and observe that

‖x‖p = 1 ; (Uq (y))(x) =

xy dμ =

|y|q/p|y| dμ =

|y|q^ dμ = 1.

We deduce that ‖Uq (y)‖ = 1 as required. If p = ∞ we simply set x = sign y and have

‖x‖∞ = 1 ; (U 1 (y))(x) =

xy dμ =

|y| dμ = ‖y‖ 1 = 1.

Finally, in the case p = 1, need to be a little more careful, since σ-finiteness comes into the argument. Let y ∈ L∞ be an element with ‖y‖∞ = 1. For any r < 1 the set [|y| ≥ r] is non null and by σ-finiteness, we can choose a set A ∈ F with A ⊆ [|y| ≥ r], and 0 < μ(A) < ∞. We now set

x = (μ(A))−^1 sign y (^1) A,

and have

x ∈ L 1 , ‖x‖ 1 = 1, (U∞(y))(x) = (μ(A))−^1

A

|y| dμ ≥ r.



The difficult part of our duality proofs will involve proving that Uq is surjective and we defer this to a later section. Let us note that (except in the finite-dimensional case) U 1 is never a surjection from L 1 onto L∗∞. We shall show, in due course, that Uq is surjective in all other cases. Notice, in passing, the use of the angle-brackets notation 〈·, ·〉 for the duality between Lp and Lq. We shall use the same notation in the context of the familiar duality between p andq , putting

〈x, y〉 =

∑^ ∞

n=

x(n)y(n).

2.2. Disjointness in Lp. Another theme in this chapter is going to be the question: to what extent is Lp(0, 1) “like” p? We know that when p = 2 these spaces are isometrically isomorphic. What happens when p 6 = 2? We start by observing that there is at least some similarity between Lp andp.

Definition 2.2. If x is a scalar-valued function on some set Γ we define the support of x to be

supp x = {γ ∈ Γ : x(γ) 6 = 0}.

We say that two functions x and y are disjointly supported, or just disjoint, if supp x ∩ supp y = ∅. When we are thinking of elements of Lp we say that x and y are disjoint if μ(supp x ∩ supp y) = 0, or equivalently xy = 0 a.e.

Proposition 2.3. Let 1 ≤ p < ∞ and let (xk)k∈N be a disjoint sequence of non-zero vectors in Lp(μ). Then

k∈N

xk‖p =

k∈N

‖xk‖pp

) 1 /p .

The closed linear span X = sp〈{xk : k ∈ N}〉 is isometrically isomorphic to `p and is complemented in Lp(μ) by a projection P of norm 1.

16

17

Proof. We observe that for disjointly supported vectors

|

k

xk|p^ =

k

|xk|p.

Hence

∑^ n

k=

xk‖pp =

∑^ n

k=

xk

p dμ

∫ (^) ∑n

k=

|xk|pdμ by disjointness

∑^ n

k=

|xk|pdμ =

∑^ n

k=

‖xk‖pp.

Replacing xk with the normalized vector ˆxk = ‖xk‖− p 1 xk, we may assume that ‖xk‖p = 1. There is a unique linear mapping T : c 00 → p satisfying t(ek) = xk, and the identity we have just established shows that T is isometric. Hence T extends to an isometry fromp to the closed linear span X of the xk’s. Finally, we have to define a projection P onto X. For each k let yk = x∗ k = |xk|p/q^ sign xk,

where q is the conjugate index. It is easy to check that yk ∈ Lq with ‖yk‖q = 1, that the sequence (yk) is disjoint and that 〈yk, xl〉 = δk,l. We note that, for any z ∈ `p ∑

k

|〈z, yk〉|p^ =

k

〈zk, yk〉p, where zk = zsign yk,

k

‖zk‖pp‖yk‖pq =

k

‖zk‖pp = ‖

k

zk‖pp ≤ ‖z‖pp,

by disjointness. Hence we may well-define P (z) =

k

〈yk, z〉xk

getting our required projection of norm 1.