Show that inner product is zero.

In summary: This is easily done by noting that they must be perpendicular to the linear combination of the eigenvectors associated with the other eigenvalue.
  • #1
perishingtardi
21
1
Let A be a Hermitian operator with n eigenkets: [itex]A|u_i\rangle = a_i |u_i\rangle[/itex] for i=1,2,...,n.

Suppose B is an operator that commutes with A. How could I show that
[tex]\langle u_i | B | u_j \rangle = 0 \qquad (a_i \neq a_j)?[/tex]

I have tried the following but not sure how to proceed:
[tex]AB - BA=0\\ \implies \langle u_i | AB | u_j \rangle - \langle u_i | BA | u_j \rangle = 0[/tex]
 
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  • #2
Is ##A## Hermitian or is it self-adjoint? If it is the latter then the result is immediate from what you wrote down because for any self-adjoint operator ##A##, if ##|u_i \rangle## is an eigenket of ##A## with eigenvalue ##a_i## then ##\langle u_i|## is an eigenbra of ##A## with the same eigenvalue i.e. ##\langle u_i|A = a_i\langle u_i |## so you would be left with ##(a_i -a_j) \left \langle u_i|B|u_j \right \rangle = 0##.
 
  • #3
Actually I think I got it:

[tex]a_i \langle u_i |B|u_j \rangle - \langle u_i |B| u_j \rangle a_j = 0[/tex] using the Hermiticity of A for the first term, and then since [itex]a_i \neq a_j[/itex] we get
[tex]\langle u_i |B| u_j \rangle = 0[/tex]
 
  • #4
This is a technical point and I don't know if it matters for your class however it should be noted that while ##\langle u_i |A = a_i \langle u_i |## is certainly true if ##A## is self-adjoint, it won't necessarily be true if ##A## is only Hermitian.
 
  • #5
WannabeNewton said:
Is ##A## Hermitian or is it self-adjoint? If it is the latter then the result is immediate from what you wrote down because for any self-adjoint operator ##A##, if ##|u_i \rangle## is an eigenket of ##A## with eigenvalue ##a_i## then ##\langle u_i|## is an eigenbra of ##A## with the same eigenvalue i.e. ##\langle u_i|A = a_i\langle u_i |## so you would be left with ##(a_i -a_j) \left \langle u_i|B|u_j \right \rangle = 0##.

Thanks for that - I think we both posted at the same time! My question is related to quantum mechanics. I think physicists use the words Hermitian and self-adjoint interchangeably. I know that pure mathematicians will distinguish them but it's not important for my area. Thanks!
 
  • #6
Alrighty then! Glad you got it worked out :)
 
  • #7
Just by using the Dirac bra-ket formalism (one of the most vicious inventions in the history of science) means that you're hiding a lot of mathematical beauty under the carpet. Let's proceed then and leave finesse aside and say that if A and B commute, then they have a common set of eigenvectors. Thus the ui's of A are the ui's of B, so that you need to prove that 2 eigenvectors pertaining to 2 different eigenvalues are orthogonal one on each other.
 

What is an inner product?

An inner product is a mathematical operation that takes two vectors and produces a scalar value. It is used to measure the angle between two vectors and to determine the length of a vector.

What does it mean for an inner product to be zero?

If the inner product of two vectors is zero, it means that the vectors are orthogonal, or perpendicular, to each other. This also means that the angle between the two vectors is 90 degrees.

Why is it important to show that an inner product is zero?

Showing that an inner product is zero can provide valuable information about the relationship between two vectors. It can also be used to prove certain properties or theorems related to vector spaces.

How do you show that an inner product is zero?

To show that an inner product is zero, you must first calculate the inner product using the given vectors. If the result is zero, then the inner product is zero. This can also be shown visually by demonstrating that the vectors are perpendicular to each other.

What are some real-world applications of inner products being zero?

Inner products being zero have many applications in physics, engineering, and data analysis. For example, in physics, the concept of work is related to the inner product of a force vector and a displacement vector, and if the inner product is zero, then no work is being done. In data analysis, inner products can be used to identify patterns and relationships between variables in a dataset.

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