Show eigenvalues are real and positive (too easy?)

In summary, the eigenvalues of J2 = Jx2 + Jy2 + Jz2 are real and non-negative because the individual matrices Jx, Jy, and Jz are Hermitian and their sum, J, is also Hermitian. Additionally, the product of two Hermitian matrices is also Hermitian, so J2 is Hermitian as well. This guarantees that the eigenvalues of J2 are real and non-negative.
  • #1
ognik
643
2
I'm given that the matrices Jx, Jy, Jz are Hermitian (they are angular momentum components). Show the eigenvalues of J2 = Jx2 + Jy2 + Jz2 are real and non-negative.

My proof seems too easy, I'd appreciate improvements to it:
i) The eigenvalues of an Hermitian matrix are real
ii) The square of any real number is \(\displaystyle \geq\) 0
Therefore the eigenvalues of each of Jx, Jy, Jz are real and their squares are non-negative, therefore the eigenvalues of J2 are also real and non-negative.

Its just too easy, is there a more formal approach?
 
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  • #2
Hi ognik,

Everything you've said is correct, but you haven't stated a key fact that really proves the "therefore" portion of your argument.

As you've said, the eigenvalues of \(\displaystyle J_{i}\), \(\displaystyle i=x,y,z\) are real, but you haven't mentioned how you know the sum of the square of these numbers is actually an eigenvalue of \(\displaystyle J^2.\)

Also, even if the eigenvalues of individual operators are nonnegative, that does not imply the operator given by their sum has nonnegative eigenvalues. For example, take the \(\displaystyle 2\times 2\) matrices

\(\displaystyle A=
\begin{bmatrix}
1 & 0\\
4 & 1
\end{bmatrix}\)

and

\(\displaystyle B =
\begin{bmatrix}
1 & 4\\
0 & 1
\end{bmatrix}
\)

The eigenvalues of both of these matrices are positive, but the eigenvalues of their sum \(\displaystyle A+B\) are \(\displaystyle \lambda = -2,6.\)

This example further demonstrates that, in general, the eigenvalues of \(\displaystyle A+B\) are not simply the sum of the individual eigenvalues of \(\displaystyle A\) and \(\displaystyle B\).

All that being said, you really only need to add one statement to your argument to make it complete. Try to think it over and see what you can come up with. Let me know if anything is unclear/not quite right. Good luck!
 
Last edited:
  • #3
Fair enough, so switching tack slightly,
Ji with i=x,y,z are all Hermitian. The sum of Hermitian matrices is also Hermitian. J=Jx + Jy + Jz, so J is also Hermitian, therefore the eigenvalues of J are real.
Then J2 = J.J so the square of real eigenvalues makes the eigenvalues of J2 real and non-negative.

Also from (AB)\(\displaystyle \dagger\) = B\(\displaystyle \dagger\)A\(\displaystyle \dagger\), ie the product of 2 hermitian matrices is also hermitian, therefore J2 is hermitian... Have I got close yet?
 

FAQ: Show eigenvalues are real and positive (too easy?)

What does it mean for eigenvalues to be real and positive?

Eigenvalues are values that are associated with a square matrix. When eigenvalues are real and positive, it means that the matrix is symmetric and all of its eigenvalues are positive numbers. This is important because it allows us to easily solve for the eigenvalues and eigenvectors of the matrix.

How do I show that eigenvalues are real and positive?

To show that eigenvalues are real and positive, you can use the properties of symmetric matrices. First, you can show that the matrix is symmetric by proving that it is equal to its transpose. Then, you can use the properties of symmetric matrices to show that all of the eigenvalues are positive. This can be done by finding the determinant of the matrix and showing that it is positive.

Why is it important for eigenvalues to be real and positive?

Having real and positive eigenvalues allows us to easily solve for the eigenvalues and eigenvectors of a matrix. This is important because eigenvalues and eigenvectors are used in many applications, such as in solving differential equations, finding the stability of a system, and in data analysis.

Can eigenvalues be complex numbers?

Yes, eigenvalues can be complex numbers. However, when dealing with real matrices, the eigenvalues will always come in complex conjugate pairs. This means that if one eigenvalue is a + bi, the other eigenvalue will be a - bi. In order to have real eigenvalues, the matrix must be symmetric.

What is the relationship between eigenvalues and diagonalization?

Diagonalization is the process of transforming a matrix into a diagonal matrix using its eigenvalues and eigenvectors. The eigenvalues of a matrix are the diagonal entries of the resulting diagonal matrix. Additionally, the eigenvectors of the matrix are used to form the diagonalizing matrix. Therefore, the eigenvalues play a crucial role in the process of diagonalization.

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