Lecture 9 - Finishing Linear Functional Via Inner Products

Recall:

adjoint

The adjoint of T∈L(V,W) is the function T∗:W→V satisffying:
⟨Tv,w⟩=⟨v,T∗w⟩
for all v∈V,w∈W.

We said a few facts about T∗, namely:

Lemma

T∗ is linear

\begin{proof}
Given two vectors w1,w2∈W, we want to show that T∗(w1+w2)=T∗w1+T∗w2. But it's hard to start with the left hand side, so to prove it we have to introduce the inner product. We need a handy lemma:

Lemma

⟨v,u1⟩=⟨v,u2⟩ for all v∈V is equivalent to u1=u2.

As such, we just need to show that the inner product of the vectors against the two vectors above are equal. Let's do that. Let v∈V:

⟨v,T∗(w1+w2)⟩=⟨Tv,w1+w2⟩=⟨Tv,w1⟩+⟨Tv,w2⟩=⟨v,T∗w1⟩+⟨v,T∗w2⟩

Thus T∗(w1+w2)=T∗(w1)+T∗(w2) using Lecture 9 - Finishing Linear Functional Via Inner Products#^9c0ab3, so then T∗ is additive. For homogeneity, let λ∈F be arbitrary. Then:

⟨v,T∗(λw1)⟩=⟨Tv,λw1⟩=λ―⟨Tv,w1⟩=λ―⟨v,T∗w1⟩=⟨v,λT∗w1⟩

Thus, in a similar way, then λT∗(w1)=T∗(λw1), showing homogeneity.
\end{proof}
There's many other things we could prove, but we'll save you on time.

Properties of the adjoint

  • (S+T)∗=S∗+T∗
  • (λT)∗=λ―T∗
  • (T∗)∗=T
  • I∗=I
  • (ST)∗=T∗S∗

\begin{proof}
Let's prove (c) for fun. Let v∈V,w∈W. Looking at the inner product:

⟨w,(T∗)∗v⟩=⟨T∗w,v⟩=⟨v,T∗w⟩―=⟨Tv,w⟩―=⟨w,Tv⟩

Thus by uniqueness lemma, then T=(T∗)∗.

Another one, let's do (d). Consider where I∈L(V):

⟨v,I∗v1⟩=⟨Iv,v1⟩=⟨v,v1⟩=⟨v,Iv1⟩

So then I=I∗.
\end{proof}
Recall that the adjoint of the matrix was the conjugate of the transpose of M(T). See Lecture 8 - Linear Functionals#^a25838 for more info.

here we have:

We claim that T∗=φV−1∘T′∘φW, using the picture from above.

Theorem

T∗=φV−1∘T′∘φW.

We'll use the fact that ⟨v,T∗w⟩=⟨Tv,w⟩ for all v∈V and w∈W.

\begin{proof}

⟨v,T∗w⟩⏟⟨⋅,T∗w⟩=⟨Tv,w⟩⏟⟨⋅,w⟩φV(T∗w)v=φW(w)Tv=(φW(w)∘T)v

So then φV(T∗w)=φW(w)∘T. But this is the dual map on the RHS, which is:

φV(T∗w)=φW(w)∘T=T′(φW)T∗(w)=φV−1∘T′∘φW(w)

Notice that ∃φV−1 since all linear functionals are injective, mainly because these are finite-dimensions. As such, then the theorem is proved.
\end{proof}
Notice specifically that this is a way to show that T∗ is linear, since all φW,T′,φV are linear. Further, φV,φW have conjugate homogeneity, so that actually makes T∗ a fully linear transformation.

Matrix Representation of the Adjoint

Let's do the proof.

We'll use the orthonormal basis βV={e1,...,en} for V, and βW={f1,...,fm} for W. So then:

M(T∗,βW,βV)ij=⟨T∗(fj),ei⟩⏟⟨v,e1⟩e1+⋯+⟨v,en⟩enei=⟨Tei,fj⟩―=M(T,βV,βW)ji―

Thus M(T∗) is the conjugate transpose of M(T). A∗ is the conjugate transpose of A.

null and range of T∗

Note that (a,d) are the same thing, and similarly (b,c) as well. Further (a,c) are equivalent, so then we only really need to show one of them.

\begin{proof}
We prove (a). Suppose w∈null(T∗) so then T∗(w)=0→V. So then:

⟨v,T∗w⟩=0⟨Tv,w⟩=0

for all v∈V, so then we must have it that w∈(range(T))⊥, as otherwise the inner product is not 0.
\end{proof}