Why is T* the definition of an adjoint operator in functional analysis?

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How about you?In summary, we discussed the definition of the adjoint T* and its relationship to the adjugate matrix. We also explored the use of an orthonormal basis to understand the components of T* and how it relates to the standard inner product in different inner product spaces.
  • #1
jy02927731
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if T: H -> H' such <T x , y > = <x , T* y >

i want to ask , why SHOULD T* be the defination http://en.wikipedia.org/wiki/Adjugate_matrix#Definition"


PLZ help , i did think about this Question more than ONE week , that's why i register
 
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  • #2
Are you asking why the adjoint T* is equal to the "adjugate" Adj T defined on that page? It isn't. The Wikipedia page says that Adj T=T-1det T, so So T*=Adj T would imply T*T=(Adj T)T=T-1T det T=I det T for all invertible matrices. This isn't true. It holds when T is a member of SU(n), but not in general. As a counterexample, consider

[tex]T=\begin{pmatrix}0 & 1\\ 1 & 0\end{pmatrix}[/tex]

We have T*=T=T-1, but det T=-1. So T*T = I ≠ -I = I det T.
 
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  • #3
THX , fredrick
sorry for found a wrong defination, and i just found again , i sure that this is the defination of my book http://en.wikipedia.org/wiki/Conjugate_transpose" .


if <T x , y > = <x , T* y > , why SHOULD T* be the defination http://en.wikipedia.org/wiki/Conjugate_transpose"
 
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  • #4
The standard inner product on the space of n×1 matrices is defined by

[tex]\langle x,y\rangle=x^*y[/tex]

where x* is the complex conjugate of the transpose of x. This is the physicist's convention. Mathematicians usually want their inner products to be linear in the first variable instead of the second. For all matrices M, define M* to be the conjugate transpose of M (the matrix obtained by taking the transpose of M and replacing each component by its complex conjugate). Note that M**=M. If T is an n×n matrix, and x is n×1, then Tx is n×1 and (Tx)* is 1×n. You should be able to use the definition of matrix multiplication to prove that (Tx)*=x*T*. Let us know if you're not.

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

This is the explanation of the equalities:

1. Definition of the inner product.
2. Associativity of matrix multiplication.
3. The easy to prove result (T*x)*=x*T**=x*T.
4. Definition of the inner product.
 
  • #5
If T is defined as a linear operator, not a matrix, we have to define its matrix of components using a basis. It's convenient to use an orthonormal basis. Then the component on row i, column j of that matrix is

[tex](Te_j)_i=\langle e_i,Te_j\rangle[/tex]

(See this post if you don't know why). Let's call that matrix A. We need to show that if T* is the adjoint, defined using the inner product as in your posts, then its matrix of components, let's call it B, is the conjugate transpose of A.

[tex]A_{ij}=(Te_j)_i=\langle e_i,Te_j\rangle=\langle T^*e_i,e_j\rangle=\langle e_j,T^*e_i\rangle^*=((T^*e_i)_j)^*=(B_{ji})^*[/tex]

Edit: You said T:H→H'. My reply is for the case H'=H. If H' is a different inner product space, we have to use two bases, one for each space:

[tex]A_{ij}=(Te_j)_i=\langle f_i,Te_j\rangle=\cdots[/tex]
 
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  • #6
Fredrik,than you very much.
U explain it very clear.
Are u also student .
 
  • #7
You're welcome. I'm not a student, but I am studying. Right now I'm studying functional analysis, trying to understand the mathematics of quantum mechanics.
 

FAQ: Why is T* the definition of an adjoint operator in functional analysis?

Why is the adjoint operator important in mathematics?

The adjoint operator is important in mathematics because it allows for the study of linear transformations between vector spaces. It helps to understand the properties of a linear transformation and its relationship with its dual space. This is particularly useful in applications such as quantum mechanics and signal processing.

How is the adjoint operator related to the inverse of a linear transformation?

The adjoint operator is closely related to the inverse of a linear transformation. In fact, if a linear transformation has an inverse, then its adjoint operator is equal to the inverse of the original transformation. This relationship can be used to solve systems of linear equations and find the inverse of a linear transformation.

What is the difference between an adjoint operator and an adjoint matrix?

An adjoint operator is a linear transformation between vector spaces, while an adjoint matrix is a matrix representation of the adjoint operator with respect to a given basis. In other words, the adjoint matrix is a way to represent the adjoint operator in terms of matrices, which can be useful for calculations and applications.

How is the adjoint operator related to the inner product?

The adjoint operator is closely related to the inner product in that it preserves the inner product between two vectors. In other words, if we apply the adjoint operator to two vectors and then take their inner product, it will be the same as taking the inner product of the original vectors. This property is important in many applications, such as in quantum mechanics and functional analysis.

Can the adjoint operator be extended to infinite-dimensional vector spaces?

Yes, the adjoint operator can be extended to infinite-dimensional vector spaces. In fact, the concept of the adjoint operator is particularly useful in studying infinite-dimensional spaces, as it allows for the analysis of operators on function spaces, for example. This extension is important in many areas of mathematics, including functional analysis and differential equations.

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