Proving Properties of Adjoint Operators in Functional Analysis

In summary: To deduce that if T is an isometry, then T has closed range, we can use the fact that for any bounded operator T, the range of T is closed if and only if T^*T is invertible.By part 3, we know that T^*T = I. Since T is an isometry, it is bounded and its adjoint T^* is also bounded. Therefore, T^*T is a bounded operator and thus invertible. Hence, the range of T is closed. \square6) To deduce that if T is an isometry, then TT^* is the projection onto the range of T, we can use the fact that for any bounded operator T,
  • #1
Oxymoron
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Im having some difficulties proving some basic properties of the adjoint operator. I want to prove the following things:

1) There exists a unique map [itex]T^*:K\rightarrow H[/itex]
2) That [itex]T^*[/itex] is bounded and linear.
3) That [itex]T:H\rightarrow K[/itex] is isometric if and only if [itex]T^*T = I[/itex].
4) Deduce that if [itex]T[/itex] is an isometry, then [itex]T[/itex] has closed range.
5) If [itex]S \in B(K,H)[/itex], then [itex](TS)^* = S^*T^*[/itex], and that [itex]T^*^* = T[/itex].
6) Deduce that if [itex]T[/itex] is an isometry, then [itex]TT^*[/itex] is the projection onto the range of [itex]T[/itex].

Note that [itex]H,K[/itex] are Hilbert Spaces.

There are quite a few questions, and I am hoping that by proving each one I will get a much better understanding of these adjoint operators. Now I think I have made a fairly good start with these proofs, so I'd like someone to check them please.

We'll begin with the first one.
 
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  • #2
I want to prove that there exists a unique mapping [itex]T^*:K\rightarrow H[/itex] such that

[tex]\langle Th,k \rangle = \langle h, T^*k \rangle \quad \forall \, h \in H, \, k\in K[/tex]

For each [itex]k \in K[/itex], the mapping [itex]h \rightarrow \langle Th, k\rangle_K[/itex] is in [itex]H^*[/itex]. Hence by Riesz's theorem, there exists a unique [itex]z \in H[/itex] such that

[tex]\langle Th,k \rangle_K = \langle h,z \rangle_H \quad \forall \, h \in H[/tex].

Therefore there exists a unique map [itex]T^*: K \rightarrow H[/itex] such that

[tex]\langle Th, k\rangle_K = \langle h,T^*k\rangle_H \quad \forall \, h \in H, \, k \in K [/tex].

Therefore there exists a unique [itex]T^*[/itex]. [itex]\square[/itex]
 
  • #3
2a) To see that [itex]T^*[/itex] is linear, take [itex]k_1, k_2 \in K[/itex] and [itex]\lambda \in \mathbb{F}[/itex], then for any [itex]h \in H[/itex] we have

[tex]\langle Th,k_1+\lambda k_2 \rangle_K &=& \langle Th,k_1\rangle_K + \overline{\lambda}\langle Th, k_2 \rangle_K \\
&=& \langle h,T^*k_1\rangle_K + \overline{\lambda}\langle h,T^*k_2\rangle_K \\
&=& \langle h, T^*k_1 + \lambda T^*k_2\rangle_K
[/tex]

Hence

[tex]T^*(k_1+\lambda k_2) = T^*(k_1) + \lambda T^*(k_2)[/tex]

[itex]T^*[/itex] is linear. [itex]\square[/itex]
 
  • #4
2b) To prove that [itex]T^*[/itex] is bounded note first that

[tex]\|T^*k\|^2 = \langle T^* k, T^*k \rangle_K = \langle T(T^*k), k \rangle \leq \|T(T^*k)\|\|k\| \leq \|T\|\|T^*k\|\|k\| \quad \forall \, k \in K [/tex]

Now suppose that [itex]\|T^*k\| > 0[/itex]. Then dividing the above by [itex]\|T^*k\|[/itex] we have

[tex]\|T^*k\| \leq \|T\|\|k\| \quad \forall \, k \in K[/tex]

Note that this is trivial if [itex]\|T^*k\| = 0[/itex].

Therefore [itex]T^*[/itex] is bounded. [itex]\square[/itex]
 
  • #5
Im not sure how to begin part 3 and 4 so I'll skip it for now.

5) Now I am not sure if what I have done here proves anything?

[tex]\langle T^*^* h,k \rangle = \langle x, T^* y\rangle = \overline{\langle T^*y, x\rangle} = \overline{\langle y, Tx \rangle} = \langle Tx,y \rangle [/tex]

Does this prove that [itex]T^*^* = T[/itex]?

[tex]\langle (TS)^*x,y \rangle = \langle y, (TS)x \rangle = \langle T^*x, Sy \rangle = \langle S^*T^*x,y \rangle [/tex]

And does this prove that [itex](TS)^* = S^*T^*[/itex]?
 
  • #6
3) We have to prove the following if and only if statement:

[tex]\|Th\| = \|h\| \Leftrightarrow T^*T = I[/tex]

[tex](\Leftarrow)[/tex]

Suppose [itex]T^*T = I[/itex] is true, then

[tex]\|Th\|^2 = \langle Th,Th \rangle = \langle h,T^*Th \rangle = \langle h,h \rangle = \|h\|^2[/tex]

Hence [itex]\|Th\| = \|h\|[/tex] after taking square roots of both sides.

[tex](\Rightarrow)[/tex]

Suppose [itex]\|Th\| = \|h\|[/itex] is true, then we have

[tex]\|Th\|^2 = \|h\|[/tex]

That is

[tex]\langle Th,Th \rangle = \langle h,h \rangle[/tex]

This implies that

[tex]\langle h,T^*Th \rangle = \langle h,h \rangle[/tex]

Which implies that

[tex]T^*T = I[/tex]

Therefore [itex]\|Th\| = \|h\| \Leftrightarrow T^*T = I[/itex]. [itex]\square[/tex]
 
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1. What is functional analysis?

Functional analysis is a branch of mathematics that deals with the study of vector spaces and linear transformations between them. It also involves the study of various mathematical concepts such as norms, inner products, and linear functionals.

2. What are some real-life applications of functional analysis?

Functional analysis has various applications in fields such as physics, engineering, economics, and computer science. Some examples include quantum mechanics, signal processing, optimization problems, and image reconstruction.

3. What are functional analysis problems?

Functional analysis problems are mathematical problems that involve solving equations or systems of equations in a vector space using the tools and concepts of functional analysis. These problems typically involve finding solutions that satisfy certain conditions or constraints.

4. What are some common techniques used in functional analysis problem-solving?

Some common techniques used in functional analysis problem-solving include Banach's fixed point theorem, Hahn-Banach theorem, and the method of Lagrange multipliers. Other techniques may include spectral theory, convex analysis, and operator theory.

5. How can functional analysis problems benefit society?

Functional analysis problems can benefit society by providing tools and methods for solving complex real-world problems, such as those in economics, engineering, and physics. By understanding and applying the principles of functional analysis, we can develop more efficient and effective solutions to these problems, ultimately improving our quality of life.

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