Hermitian conjugation identity

In summary, the equation for self-adjoint operators is a sum over 1,2,3, where the summation convention is used. The equation for Hermitian operators is the same, but with the conjugate transpose.
  • #1
Dyatlov
25
1

Homework Statement


##(\hat A \times \hat B)^*=-\hat B^* \times \hat A^*##
Note that ##*## signifies the dagger symbol.

Homework Equations


##(\hat A \times \hat B)=-(\hat B \times \hat A)+ \epsilon_{ijk} [a_j,b_k]##

The Attempt at a Solution


Using as example ##R## and ##P## operators:
##(\hat R \times \hat P)^*_i=-(\hat P \times \hat R)^*_i+ \epsilon_{ijk} [Y,P_z]##
##(\hat R \times \hat P)^*_i=-(\hat P \times \hat R)^*_i##
##(\hat R \times \hat P)^*=-\hat P^* \times \hat R^*##
 
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  • #2
Dyatlov said:

Homework Statement


##(\hat A \times \hat B)^*=-\hat B^* \times \hat A^*##
Note that ##*## signifies the dagger symbol.
Start instead from a component-wise definition:
$$(A \times B)_i ~=~ \epsilon_{ijk} A_j B_k $$ (where the usual summation convention applies to repeated indices).
 
  • #3
Since ##\epsilon_{ijk}## is antisymmetric then we have
##\epsilon_{ijk}A_jB_k=A_jB_k-A_kB_j##
##A_jB_k-A_kB_j=-(B_jA_k-B_kA_j)##
##(A \times B)_i=-(B \times A)_i##
Since A and B are Hermitian the same equlity holds for their self-adjoint counterparts.
 
Last edited:
  • #4
Dyatlov said:
Since ##\epsilon_{ijk}## is antisymmetric then we have
##\epsilon_{ijk}A_jB_k=A_jB_k-A_kB_j##
That equation does not make sense. On the LHS, ##i## is a free index, but ##j,k## are dummy summation indices. However, on your RHS both ##j## and ##k## are free indices, and there's no ##i## at all. Both left and right hand sides of such an equation must have exactly the same free indices.

The LHS uses a version of the summation convention. It is short for $$\sum_{j,k} \epsilon_{ijk}A_jB_k $$
##A_jB_k-A_kB_j=-(B_jA_k-B_kA_j)##
This is wrong if ##B_j## and ##A_k## don't commute (which is presumably the case here, since the problem statement didn't specify commutativity). So you can't blithely interchange ##A## and ##B## like that.

##(A \times B)_i=-(B \times A)_i##
Since A and B are Hermitian
Your original problem statement doesn't say that ##A,B## are Hermitian.

the same equality holds for their self-adjoint counterparts.
But that doesn't solve the problem as stated.

Start with this: $$\left( \sum_{j,k} \epsilon_{ijk}A_jB_k \right)^\dagger ~=~ \dots\,? \dots $$ Hint: for arbitrary operators ##X,Y##, what is ##(XY)^\dagger## ?
 
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  • #5
Thanks for the replies.
The title mentions that I am solving the identity for Hermitian operators.
I know that ##\epsilon_{ijk}A_jB_k## is a sum over j and k, with ##j,k=1,2,3##.
##(\epsilon_{ijk}A_jB_k)^\dagger=(\epsilon_{ijk}B^\dagger_kA^\dagger_j)=-(B^\dagger \times A^\dagger)_i##
Therefore:
##(A \times B)^\dagger_i=-(B^\dagger \times A^\dagger)_i##
 
  • #6
Dyatlov said:
The title mentions that I am solving the identity for Hermitian operators.
No it doesn't -- it mentions "Hermitian conjugation", which is an operation which can be performed on any operator.

Anyway, I take it you're now happy with the solution.
 
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  • #7
Bad wording I guess then.
Thanks for the help, anyway!
 

What is the Hermitian conjugation identity?

The Hermitian conjugation identity is a mathematical concept that relates to the properties of Hermitian matrices. It states that the Hermitian conjugate of the product of two matrices is equal to the product of their individual Hermitian conjugates, with the order of the matrices reversed.

What is a Hermitian matrix?

A Hermitian matrix is a square matrix with complex entries that is equal to its own transpose conjugate. This means that the entries of the matrix remain the same when you take the complex conjugate and transpose of the matrix.

What is the difference between Hermitian conjugation and transpose conjugation?

Hermitian conjugation involves taking the complex conjugate and then transposing a matrix, while transpose conjugation involves only transposing a matrix. In other words, Hermitian conjugation involves taking the transpose of the complex conjugate of a matrix, while transpose conjugation only involves taking the transpose of a matrix.

Why is the Hermitian conjugation identity important?

The Hermitian conjugation identity is important because it allows us to manipulate and simplify complex matrices in mathematical equations. It also has applications in quantum mechanics and signal processing, where Hermitian matrices are commonly used to represent physical systems.

What are some properties of Hermitian matrices?

Some properties of Hermitian matrices include having real eigenvalues and orthogonal eigenvectors, being diagonalizable, and being equal to their own adjoint (Hermitian conjugate). They also have a unique decomposition known as the spectral theorem, which states that any Hermitian matrix can be written as a combination of its eigenvalues and eigenvectors.

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