Why Doesn't the Hermitian Calculation Use Complex Conjugates?

In summary, the formula provided in the conversation is for proving Heisenberg's Uncertainty Relations. However, the right-hand side of the formula should be modified to include the adjoint operators of \Delta \hat{A} and \Delta \hat{B}. This is because the operators are Hermitian, meaning they equal their adjoint and have real eigenvalues.
  • #1
maverick6664
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Reading back in my book, Greiner's "QM :an introduction" I found a formula I don't understand.

Let [tex]\alpha[/tex] be a real number, [tex]\Delta \hat{A}, \Delta \hat{B}[/tex] be Hermitian operators. Now I have

[tex]\int (\alpha \Delta \hat{A} - i \Delta \hat{B})^* \psi^* (\alpha \Delta \hat{A} - i \Delta \hat{B}) \psi dx
= \int \psi^* (\alpha \Delta \hat{A} + i \Delta \hat{B}) ( \alpha \Delta \hat{A} - i \Delta \hat{B}) \psi dx[/tex]

This leads to an expected result to prove Heisenberg's Uncertainty Relations, but I think the right-hand side of this formula should be

[tex]\int \psi^* (\alpha \Delta \hat{A}^* + i \Delta \hat{B}^*) (\alpha \Delta \hat{A} - i \Delta \hat{B}) \psi dx[/tex]

I should be wrong, but I don't know why. Operators [tex]\Delta \hat{A}, \Delta \hat{B}[/tex] can be complex... (or are they always real?) So will anyone tell me how or why it's correct?

Thanks in advance!
 
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  • #2
Since the operators are Hermitian, you know that:

[tex]\Delta \hat{A}^* = \Delta \hat{A}[/tex]

[tex]\Delta \hat{B}^* = \Delta \hat{B}[/tex]
 
  • #3
Just a note for clarity. A Hermitian operator is one that equals its adjoint:
[tex]\hat{A} = \hat{A}^{\dagger}[/tex]

This implies that the eigenvalues of a Hermitian operator are real (and of course that their mean values are also real). But the operator can certainly be complex and still be Hermitian.
 

FAQ: Why Doesn't the Hermitian Calculation Use Complex Conjugates?

1. What is a Hermitian matrix?

A Hermitian matrix is a complex square matrix that is equal to its own conjugate transpose. In other words, the matrix is equal to its own reflection over the main diagonal.

2. What is the importance of Hermitian matrices in calculations?

Hermitian matrices have several important properties, such as being real and symmetric, having all eigenvalues that are real numbers, and having orthogonal eigenvectors. These properties make them useful in many mathematical and scientific applications, particularly in quantum mechanics and signal processing.

3. How do you calculate the conjugate transpose of a Hermitian matrix?

To calculate the conjugate transpose of a Hermitian matrix, you simply take the transpose of the matrix and then take the complex conjugate of each element within the matrix.

4. How do you determine if a matrix is Hermitian?

A matrix is Hermitian if it is equal to its own conjugate transpose. This can be determined by checking if the matrix is equal to its own reflection over the main diagonal. Another way to check is to see if all the eigenvalues are real numbers and if the eigenvectors are orthogonal.

5. Can a non-square matrix be Hermitian?

No, a non-square matrix cannot be Hermitian. Hermitian matrices must be square in order to have a transpose and a conjugate transpose that are equal.

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