Prove Eigenvalues of an (operator)^2 are real and positive

In summary, according to the postulate of quantum mechanics, every dynamical observable is represented by a linear Hermitian operator. Therefore, if A is an observable associated with the operator A, then the eigenvalues of A^2 are real and positive. This can be proven by using the fact that A is Hermitian, which means that A^2 will also be Hermitian and will have real and positive eigenvalues.
  • #1
safekhan
6
0
Q: Using Dirac notation, show that if A is an observable associated with the operator A then the eigenvalues of A^2 are real and positive.

Ans: I know how to prove hermitian operators eigenvalues are real:
A ket(n) = an ket(n)
bra(n) A ket(n) = an bra(n) ket(n) = an
[bra(n) A ket(n)]* = an* bra(n) ket(n) = an*
[bra(n) A(dager) ket(n)] =[bra(n) A ket(n)] = an*
therefore, an*=an

But, I don't know how to treat an operator^2 and start this question.
 
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  • #2
safekhan said:
Q: Using Dirac notation, show that if A is an observable associated with the operator A then the eigenvalues of A^2 are real and positive.

Ans: I know how to prove hermitian operators eigenvalues are real:
A ket(n) = an ket(n)
bra(n) A ket(n) = an bra(n) ket(n) = an
[bra(n) A ket(n)]* = an* bra(n) ket(n) = an*
[bra(n) A(dager) ket(n)] =[bra(n) A ket(n)] = an*
therefore, an*=an

But, I don't know how to treat an operator^2 and start this question.
What is the relation between an observable and Hermetian operators?

Can you think of a way to rewrite the operator in the expression ##\hat{A}^2 | n \rangle##?
 
  • #3
Relationship: it's a postulate of QM that every dynamical observable is represented by a linear hermitian operator.

A*A ket(n) = ? but not sure what will be on the right hand side
 
  • #4
safekhan said:
Relationship: it's a postulate of QM that every dynamical observable is represented by a linear hermitian operator.
Correct.

safekhan said:
A*A ket(n) = ? but not sure what will be on the right hand side
Yes, which you can write as
$$
\hat{A}^2 | n \rangle = \hat{A} \left( \hat{A} | n \rangle \right)
$$
What can you say about the contents of the parenthesis?
 
  • #5
it equals =an ket(n)
than A(an ket(n)) = an A ket(n) = an (an ket (n))= an^2 ket(n)

is that correct way to do it?
 
  • #6
safekhan said:
it equals =an ket(n)
than A(an ket(n)) = an A ket(n) = an (an ket (n))= an^2 ket(n)

is that correct way to do it?
Yes. Now you can use the fact that A is Hermitian to complete the answer to the problem.
 
  • #7
Thanks
So for hermitian A= A(dager), but would u write (A^2)* = A*A* = A*(an* ket(n)) ...
 
  • #8
safekhan said:
Thanks
So for hermitian A= A(dager), but would u write (A^2)* = A*A* = A*(an* ket(n)) ...
No, that's not what I meant. You should use the proof you gave in the OP (I don't think you need the put the proof itself in the answer, but rather use what the proof says about Hermetian operators).
 
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1. What are eigenvalues and why are they important?

Eigenvalues are the values that satisfy the equation Av = λv, where A is a square matrix and v is a non-zero vector. They represent the scaling factor by which a vector is stretched or compressed when multiplied by a matrix. Eigenvalues are important because they help us understand the behavior of linear systems and are used in various fields such as physics, engineering, and computer graphics.

2. How do you prove that eigenvalues of an operator squared are real and positive?

To prove that the eigenvalues of an operator squared are real and positive, we can use the properties of eigenvalues and the fact that the operator is self-adjoint. First, we can show that the eigenvalues of the squared operator are real by using the fact that the eigenvalues of a self-adjoint operator are real. Then, we can use the definition of eigenvalues to show that they must be positive since the squared operator will always produce a positive result when multiplied by a non-zero vector.

3. Can you provide an example of an operator with real and positive eigenvalues?

One example of an operator with real and positive eigenvalues is the identity matrix. The eigenvalues of the identity matrix are all equal to 1, which is a real and positive number.

4. Are there any exceptions to the rule that the eigenvalues of an operator squared are real and positive?

Yes, there are some exceptions to this rule. In some cases, the eigenvalues of an operator squared may be complex numbers. This can occur when the operator is not self-adjoint or when the matrix is not square.

5. How is the concept of eigenvalues related to the concept of eigenvectors?

Eigenvalues and eigenvectors are closely related as they both represent the behavior of a linear system when multiplied by a matrix. Eigenvectors are the vectors that do not change direction when multiplied by a matrix, while eigenvalues represent the scaling factor by which the eigenvector is stretched or compressed. Together, they help us understand the behavior of a system when it is subjected to linear transformations.

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