Number of eigenvectors for Hermitian matrices

In summary, the conversation discusses a theorem in quantum mechanics stating that a Hermitian matrix of dimensionality n will always have n independent eigenvectors/eigenvalues. The goal is to prove this statement, which requires showing that a polynomial associated with the matrix can be factored into distinct linear factors. However, there may be degeneracy in the roots of the polynomial, as shown through counter-examples. The conversation concludes with the acknowledgement that more research is needed to fully understand the context of the theorem.
  • #1
haisydinh
24
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Hello,

I am currently trying to study the mathematics of quantum mechanics. Today I cam across the theorem that says that a Hermitian matrix of dimensionality ##n## will always have ##n## independent eigenvectors/eigenvalues. And my goal is to prove this. I haven't taken any linear algebra classes so my knowledge in this field is quite limited.

Now, I have realized that if I were to prove this statement, I would basically have to show that there is a polynomial associated with the matrix and that this polynomial can be factored into a product of distinct linear factors. Mathematically, if I let ##M## to be the Hermitian matrix, ##I## be the identity matrix, and ##\lambda## be the placeholder for the eigenvalues, then I have to show that the following is true for all ##n##:

##det(M-I\lambda) = (\lambda - \lambda_1)(\lambda - \lambda_2)...(\lambda - \lambda_n)## (where ##\lambda_i## are independent eigenvalues)

Here, I’m just stuck. I really don’t know how to tackle this at all. If someone could help me out on this problem, it would be really great. Or if you guys can point me to some sort of literature, that would also be good for me. Thank you very much in advance! :)
 
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  • #2
[itex] det(M-I\lambda)=0 \Rightarrow (\lambda-\lambda_1)(\lambda-\lambda_2)(\lambda-\lambda_3)...(\lambda-\lambda_n)=0 [/itex]
This is an algebraic equation of degree n, which according to the fundamental theorem of algebra, has n roots. But these roots need not be distinct. Any number of them may be equal and so there may be degeneracy.
 
  • #3
Shyan said:
[itex] det(M-I\lambda)=0 \Rightarrow (\lambda-\lambda_1)(\lambda-\lambda_2)(\lambda-\lambda_3)...(\lambda-\lambda_n)=0 [/itex]
This is an algebraic equation of degree n, which according to the fundamental theorem of algebra, has n roots. But these roots need not be distinct. Any number of them may be equal and so there may be degeneracy.

Hi, thanks for replying.

However, the theorem says that "the polynomial associated with a Hermitian matrix always has ##n## distinct roots". In other words, this is a special property of a Hermitian matrix. I can easily prove this with a ##2×2##- Hermitian matrix or a ##3×3##-Hermitian matrix, however I want to find a generalized proof to show that this is true for all ##n##.

Thanks.
 
  • #4
I don't know what you did but that's wrong!
A [itex] 2\times 2 [/itex] Hermitian matrix is of the form [itex] \left( \begin{array}{lr} a \ \ \ \ \ \ c+id \\ c-id \ \ \ \ \ \ b \end{array} \right) [/itex]. This matrix has two eigenvalues and these two become equal when [itex] a-b=\pm 2 i \sqrt{c^2+d^2} [/itex]. So I'm showing you an infinite number of counter-examples to that statement.
 
  • #5
Shyan said:
I don't know what you did but that's wrong!
A [itex] 2\times 2 [/itex] Hermitian matrix is of the form [itex] \left( \begin{array}{lr} a \ \ \ \ \ \ c+id \\ c-id \ \ \ \ \ \ b \end{array} \right) [/itex]. This matrix has two eigenvalues and these two become equal when [itex] a-b=\pm 2 i \sqrt{c^2+d^2} [/itex]. So I'm showing you an infinite number of counter-examples to that statement.

Maybe I should be more clear with my question. Let's say that ##M = \begin{pmatrix} a & c+id \\ c-id & b \end{pmatrix}## is our Hermitian matrix, then the polynomial is:

##det(M - I\lambda) = det\begin{pmatrix} a-\lambda & c+id \\ c-id & b-\lambda \end{pmatrix}##

## = \lambda^2 + (a+b)\lambda + (ab-c^2-d^2) = 0##

The discriminant is thus ##(a+b)^2 - 4(ab-c^2-d^2) = a^2-2ab+b^2+4(c^2+d^2)=(a-b)^2+4(c^2+d^2)## which is obviously positive (unless all ##a, b, c, d = 0## which is uninteresting). Therefore the polynomial has 2 distinct roots for ##\lambda##. Now, the proof for ##3×3##-matrix is more complicated, but will give the same result. So my question is how do we prove this statement for all ##n##?

Thank you!
 
  • #6
haisydinh said:
The discriminant is thus (a+b)2−4(abc2−d2)=a2−2ab+b2+4(c2+d2)=(ab)2+4(c2+d2)(a+b)^2 - 4(ab-c^2-d^2) = a^2-2ab+b^2+4(c^2+d^2)=(a-b)^2+4(c^2+d^2) which is obviously positive (unless all a,b,c,d=0a, b, c, d = 0 which is uninteresting)
This part is wrong. If you set the discriminant equal to zero, you'll get the equation I mentioned in my previous post! Which means its is possible for the discriminant to be zero without a,b,c and d all be zero!

EDIT: Because a and b are real, that equation can only be true when c and d are zero which means a=b. So the only [itex] 2\times 2 [/itex] matrix with degenerate eigenvalues is the identity matrix. For higher dimensions, there may be more!
 
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  • #7
Shyan said:
This part is wrong. If you set the discriminant equal to zero, you'll get the equation I mentioned in my previous post! Which means its is possible for the discriminant to be zero without a,b,c and d all be zero!

EDIT: Because a and b are real, that equation can only be true when c and d are zero which means a=b. So the only [itex] 2\times 2 [/itex] matrix with degenerate eigenvalues is the identity matrix. For higher dimensions, there may be more!

Yes, you are absolutely right! How silly of me! Thanks for pointing that out!

Well, it's clear that my proof is wrong here. But the problem still remains though. Maybe it's more relevant to physics rather than to mathematics. Maybe in quantum mechanics, they are talking about a different type of Hermitian matrices that disallow ##a## and ##b## to be the same. In any case, I would have to look more into the context of the physics situation, rather than generalizing it to all Hermitian matrices.

Thanks again!
 

FAQ: Number of eigenvectors for Hermitian matrices

What is the significance of the number of eigenvectors for Hermitian matrices?

The number of eigenvectors for Hermitian matrices is important because it determines the dimension of the corresponding eigenspace. This, in turn, provides information about the geometric and algebraic properties of the matrix, such as its rank and diagonalizability.

How many eigenvectors can a Hermitian matrix have?

A Hermitian matrix can have as many eigenvectors as its dimension. This means that for an n x n Hermitian matrix, there can be a maximum of n linearly independent eigenvectors.

Can a Hermitian matrix have repeated eigenvectors?

No, a Hermitian matrix cannot have repeated eigenvectors. This is because eigenvectors corresponding to distinct eigenvalues are always linearly independent, and a Hermitian matrix has distinct eigenvalues.

How does the number of eigenvectors affect the diagonalizability of a Hermitian matrix?

The number of eigenvectors is directly related to the diagonalizability of a Hermitian matrix. If the number of eigenvectors is equal to the dimension of the matrix, then the matrix is diagonalizable. However, if the number of eigenvectors is less than the dimension, then the matrix is not diagonalizable.

Can the number of eigenvectors change if the matrix is transformed?

No, the number of eigenvectors for a Hermitian matrix remains the same regardless of any transformations applied to the matrix. However, the eigenvectors themselves may change as they are dependent on the specific values of the matrix's entries.

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