Proving Hermitian if it has real eigenvalues

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Discussion Overview

The discussion revolves around the conditions under which an operator with real eigenvalues can be proven to be Hermitian. Participants explore the implications of diagonalizability, the role of eigenvectors, and the definitions of Hermitian operators in relation to different bases and inner products.

Discussion Character

  • Debate/contested
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • One participant questions how to prove an operator is Hermitian if it has real eigenvalues and a complete basis of eigenvectors.
  • Another participant asserts that the claim is not true even for 2x2 matrices with real entries, suggesting confusion with spectral properties.
  • A later reply discusses that while a diagonal matrix with real eigenvalues is Hermitian, a diagonalizable matrix with real eigenvalues is not necessarily Hermitian.
  • Participants discuss the implications of coordinate transformations on the symmetry of matrices and the necessity of specifying an orthogonal basis for rigorous proofs.
  • One participant emphasizes that the adjoint of an operator is defined with respect to an inner product, which can vary based on the basis used.
  • Examples are provided to illustrate that a matrix can be diagonalizable with real eigenvalues but still not be Hermitian.
  • There is a suggestion that if eigenvectors are orthonormal, proving the operator is Hermitian may be straightforward.

Areas of Agreement / Disagreement

Participants express disagreement on the initial claim regarding Hermitian operators and real eigenvalues. Multiple competing views remain regarding the conditions under which an operator can be considered Hermitian, particularly in relation to the basis and inner product used.

Contextual Notes

Limitations include the dependence on the definitions of Hermitian operators and inner products, as well as the unresolved nature of the relationship between diagonalizability and Hermitian properties.

maddogtheman
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If you had an operator A-hat whose eigenvectors form a complete basis for the Hilbert space has only real eigenvalue how would you prove that is was Hermitian?
 
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You wouldn't. That's not even true when restricted to 2x2 matrices whose entries are all real!

(And please don't post the same thing multiple times. We don't tolerate it on this forum)
 
Hurkyl said:
You wouldn't. That's not even true when restricted to 2x2 matrices whose entries are all real!

(And please don't post the same thing multiple times. We don't tolerate it on this forum)

Could it be you confused the problem with some claim about spectrum? If 2x2 matrix is diagonalizable with real eigenvalues, isn't it quite Hermitian then? And isn't eigenvectors forming a complete basis the same thing as diagonalizability?
 
jostpuur said:
If 2x2 matrix is diagonalizable with real eigenvalues, isn't it quite Hermitian then?
A diagonal matrix with real eigenvalues is Hermitian. But not necessarily if the matrix is merely diagonalizable with real eigenvalues. Why should (PDP^{-1})^* = PDP^{-1}?
 
I see... so symmetry of a matrix isn't always conserved in coordinate transformations. It would have fixed the problem, if maddogtheman had mentioned his basis to be orthogonal?
 
I assumed the basis to be orthogonal but I think it makes for a rigorous proof.
 
doesn't make*
 
The problem is that T\mapsto T^{\dagger} does not commute with all linear coordinate transformations, so actually we never should speak about a linear mapping being Hermitian. A simple fact, which I had never thought about before. Instead, we should speak about linear mapping being Hermitian with respect to some basis (or with respect to a certain kind of collection of different basis).

Examine

<br /> (\psi_i | (T-T^{\dagger})\psi_j)<br />

with orthogonal eigenvectors \psi_k, which satisfy T\psi_k = \lambda_k \psi_k.

(edit: I first wrote complicated instructions, and then edited them simpler)
 
Last edited:
For example, if

<br /> T = \left(\begin{array}{cc} 1 &amp; 2 \\ 0 &amp; 3 \\ \end{array}\right)<br />

then the vectors

<br /> u_1 = \left(\begin{array}{c} 1 \\ 0 \\ \end{array}\right),\quad u_2 = \left(\begin{array}{c} 1 \\ 1 \\ \end{array}\right)<br />

are the eigenvectors with eigenvalues \lambda_1 = 1 and \lambda_2 = 3. So the matrix is diagonalizable with real eigenvalues, but it is not Hermitian since T \neq T^{\dagger}.

Lols. :blushing:

But if we define a new inner product (u_i|u_j)=\delta_{ij}, and a new conjugate mapping T\mapsto T^{\dagger} by (\psi|T^{\dagger}\phi)=(T\psi|\phi) with the new inner product, then T becomes Hermitian.
 
  • #10
jostpuur said:
The problem is that T\mapsto T^{\dagger} does not commute with all linear coordinate transformations, so actually we never should speak about a linear mapping being Hermitian. A simple fact, which I had never thought about before. Instead, we should speak about linear mapping being Hermitian with respect to some basis (or with respect to a certain kind of collection of different basis).

This is because the adjoint of an operator is only defined with respect to an inner product. Specifically, it is the operator A^\dagger such that (u,Av) = (A^\dagger u,v) for all vectors u and v. In terms of matrices, as long as we write the coefficients in an orthonormal basis, this just amounts to taking the conjugate transpose. And this will also be true in any other orthonormal basis, where the other orthonormal bases are precisely the ones which can be reached by a unitary transformation (with which the adjoint operation does commute).

As for the OP, it depends on whether the eigenvectors are orthonormal. If so, then the answer should be easy based on what I just said.
 

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