Exploring Hermitian Matrix Properties in Quantum Mechanics

In summary: Alternatively, we can interpret your results, where we still need to apply a square root somehow, which you've left out.So yes, the identity matrix has only eigenvalue 1.But since we had $\lambda^2$ in the equation instead of $\lambda$, that means that $\lambda^2 = 1$.Ok, I see it.
  • #1
bugatti79
794
1
Hi Folks,

I am looking at Shankars Principles of Quantum Mechanics.

For Hermitian Matrices M^1, M^2, M^3, M^4 that obey

[tex]M^iM^j+M^jM^i=2 \delta^{ij}I[/tex], i,j=1...4

Show that eigenvalues of M^i are [tex]\pm1[/tex]
Hint: Go to eigenbasis of M^i and use equation i=j. Not sure how to start this?
Should I consider a 2*2 Hermitian Matrix such as [tex]\begin{bmatrix}1 & -i\\ -i& 1\end{bmatrix}[/tex] and evaluate the LHS?
 
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  • #2
bugatti79 said:
Hi Folks,

I am looking at Shankars Principles of Quantum Mechanics.

For Hermitian Matrices M^1, M^2, M^3, M^4 that obey

[tex]M^iM^j+M^jM^i=2 \delta^{ij}I[/tex], i,j=1...4

Show that eigenvalues of M^i are [tex]\pm1[/tex]
Hint: Go to eigenbasis of M^i and use equation i=j. Not sure how to start this?
Should I consider a 2*2 Hermitian Matrix such as [tex]\begin{bmatrix}1 & -i\\ -i& 1\end{bmatrix}[/tex] and evaluate the LHS?

Hi bugatti!

Let's set $i=j$, then we get:
$$(M^i)^2 = I$$

If we have $M^i v = \lambda v$ then it follows that $(M^i)^2 v = \lambda^2 v$ and also that $(M^i)^2 v= I v = v$.
For which values of $\lambda$ would these equations be satisfied?
 
  • #3
I like Serena said:
Hi bugatti!

Let's set $i=j$, then we get:
$$(M^i)^2 = I$$

If we have $M^i v = \lambda v$ then it follows that $(M^i)^2 v = \lambda^2 v$ and also that $(M^i)^2 v= I v = v$.
For which values of $\lambda$ would these equations be satisfied?
We would then have $$I v= \lambda^2 v$$
How do we work out the eigenvalues if we don't know the value of M..?
To me, the eigenbasis are determined by first finding the eigenvalues and eigenvectors. Not sure what he means by " going to the eigenbasis of M"!
 
Last edited:
  • #4
bugatti79 said:
We would then have $$I v= \lambda^2 v$$
How do we work out the eigenvalues if we don't know the value of M..?
To me, the eigenbasis are determined by first finding the eigenvalues and eigenvectors. Not sure what he means by " going to the eigenbasis of M"!

I don't understand either what is intended with: "going to the eigenbasis of M".
However, picking $i=j$ yields the eigenvalues directly using $I v= \lambda^2 v$.
 
  • #5
I like Serena said:
I don't understand either what is intended with: "going to the eigenbasis of M".
However, picking $i=j$ yields the eigenvalues directly using $I v= \lambda^2 v$.

But i calculate [tex]\lambda[/tex] to be the square root of the identity matrix which is the identity matrix to which its eigenvalues [tex]\lambda_1=\lambda_2=1[/tex] from the characteristic polynomial [tex]x^2-2x+1[/tex].
i don't see where [tex]\pm 1[/tex] comes from
 
  • #6
bugatti79 said:
But i calculate [tex]\lambda[/tex] to be the square root of the identity matrix which is the identity matrix to which its eigenvalues [tex]\lambda_1=\lambda_2=1[/tex] from the characteristic polynomial [tex]x^2-2x+1[/tex].
i don't see where [tex]\pm 1[/tex] comes from

Those are the eigenvalues of the identity matrix, but that's not what that equation is for.
What we have, is:
$$v = \lambda^2 v$$
where $v$ is a non-zero vector (an eigenvector of $M^i$).
This can only be true if $\lambda^2 = 1$.
What do you get if you solve this?Alternatively, we can interpret your results, where we still need to apply a square root somehow, which you've left out.
So yes, the identity matrix has only eigenvalue 1.
But since we had $\lambda^2$ in the equation instead of $\lambda$, that means that $\lambda^2 = 1$.
 
  • #7
Ok, I see it.
Thank you!
 

1. What is a Hermitian Matrix?

A Hermitian Matrix is a square matrix that is equal to its own conjugate transpose. In other words, the matrix is equal to its own complex conjugate when reflected along the main diagonal.

2. What makes a Hermitian Matrix special?

Hermitian Matrices have several unique properties that make them useful in mathematics and science. They have real eigenvalues, orthogonal eigenvectors, and are used in quantum mechanics to represent observable physical quantities.

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

To determine if a matrix is Hermitian, you must check if it is equal to its own conjugate transpose. This can be done by taking the complex conjugate of each element in the matrix and then transposing it. If the resulting matrix is equal to the original matrix, then it is Hermitian.

4. What is the difference between a Hermitian Matrix and a symmetric matrix?

A Hermitian Matrix is a type of symmetric matrix, but with the additional condition that it must be equal to its own conjugate transpose. A symmetric matrix only needs to be equal to its own transpose, without the complex conjugate.

5. In what fields of science is the Hermitian Matrix problem commonly used?

The Hermitian Matrix problem is commonly used in fields such as physics, engineering, and computer science. It is particularly useful in quantum mechanics, signal processing, and optimization problems.

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