Adjoint of a linear operator

In summary: Using finite-dimensionality, we can decompose v into T(u) and T*(u) where T*(u) is the same as T*T(u). Since T is normal, we have that T*T(u) and T*(u) have the same image.
  • #1
kingwinner
1,270
0
Q) Let V be an inner product space and T:V->V a linear operator. Prove that if T is normal, then T and T* have the same image. (i.e. imT=imT*)

My Attempt:
<T(v),T(v)>
=<T*T(v),v>
=<TT*(v),v>
=<T*(v),T*(v)>

=>||T(v)|| = || T*(v)||

But this doesn't seem to help...

Thanks!
 
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  • #2
You are trying to prove two sets (Im(T) and Im(T*)) are the same. Start by assuming v is in Im(T). Then there exist u such that v= T(u). You want to show that v= T*(w) for some w in V.
 
  • #3
HallsofIvy said:
You are trying to prove two sets (Im(T) and Im(T*)) are the same. Start by assuming v is in Im(T). Then there exist u such that v= T(u). You want to show that v= T*(w) for some w in V.
I understand the definitions, but I have no idea how to prove this.
Can you give me more hints, please?:smile:
 
  • #4
My attempt:
v=T(u) for some u E V
=> T*(v)=T*T(u)
=> T*(v)=TT*(u) since T is normal

And now I am stuck, how can I prove that v=T*(w) for some w E V?
 
  • #5
This seems false unless you're given some other condition on V. Is it finite-dimensional or complete? If so, then from your observation that ||Tv||=||T*v|| we can conclude immediately that kerT=kerT*; on the other hand, it's easy to see that the orthogonal complement of imT* is kerT (i.e. [itex](\text{im} T^*)^{\perp} = \ker T[/itex]). Now use finite-dimensionality to place things together (in case of completeness, use direct sum decompositions).
 
  • #6
We are assuming finite-dimensional vector space.

v=T(u) for some u E V
=> T*(v)=T*T(u)
=> T*(v)=TT*(u) since T is normal
I have no idea how to proceed from here...

How is it possible to prove without using [itex](\text{im} T^*)^{\perp} = \ker T[/itex]?
 
  • #7
Why don't you want to use it?
 

1. What is the adjoint of a linear operator?

The adjoint of a linear operator is a mathematical concept that is closely related to the transpose of a matrix. It is a linear transformation that operates on the dual space of the original linear operator, and it represents the complex conjugate of the transpose of the linear operator.

2. How is the adjoint of a linear operator calculated?

The adjoint of a linear operator is calculated by taking the transpose of the matrix representing the linear operator and then taking the complex conjugate of each entry in the matrix. This results in a new matrix that represents the adjoint of the original linear operator.

3. What are the properties of the adjoint of a linear operator?

The adjoint of a linear operator has several important properties, including linearity, self-adjointness, and the fact that it is its own inverse. It also preserves the inner product between vectors, and it is closely related to the eigenvalues and eigenvectors of the original linear operator.

4. What is the significance of the adjoint of a linear operator in mathematics?

The adjoint of a linear operator has many applications in mathematics, particularly in the fields of linear algebra, functional analysis, and operator theory. It is used to analyze the properties of linear operators, and it plays a crucial role in solving systems of equations and studying the behavior of dynamical systems.

5. Can the adjoint of a linear operator be calculated for any type of linear operator?

Yes, the adjoint of a linear operator can be calculated for any type of linear operator, including matrices, differential operators, and integral operators. However, the method of calculation may vary depending on the specific type of linear operator and the space it operates on.

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