Can Someone Please Explain Hermitian Conjugates To Me?

In summary: The domain of x^2 is the whole space and the domain of p^2 is just the subspace spanned by the real and imaginary parts of x. But in this case, we can still write the equality$$x^2+a^2p^2=(x+iap)(x-iap)+ia[x,p],$$ because the domain of x^2 includes both the domain of p^2 (the real part plus the imaginary part) and the whole space, and the domain of p^2 includes only the real part of x. In other words, the domains of x^2 and p^2 are the same, and we can use the same notation to write the equality.
  • #1
Bowenwww
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Can Someone Please Explain Hermitian Conjugates To Me!?

I'm working on some problems about the Hermitian of a Harmonic Oscillator - I keep coming across the Hermitian written in a form with A[dagger]A and similar things - when I've looked in textbooks and online I find it explained using Bra-ket notation, which I also struggle to understand.

Can someone please help me - I've got a lot of problems to do and I don't want to be sat here all night trying to figure this one thing out.

TIA

Xx
 
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  • #2


I think you should be more specific on what you are getting confused with. Are you confused with the notation or the concept of a Hermitian conjugate? Otherwise, I would suggest you read some intro QM texts like Griffiths.
 
  • #3


What you need to know to be able to use the concept is that the adjoint of A, denoted by ##A^*## or ##A^\dagger##, is the unique linear operator such that
$$\langle x,Ay\rangle=\langle A^*x,y\rangle$$ for all x,y in the Hilbert space. A more complete answer would explain how we can be sure that there's exactly one such operator, but that part is kind of hard. It requires you to understand the Riesz representation theorem for Hilbert spaces. It's not super hard, but it's hard enough that you won't be able to fully understand it tonight.
 
  • #4


The Hermitian conjugate of a matrix is very easy. You just need to take the complex conjugate of each entry and then transpose the matrix. The Hermitian conjugate of an operator is somewhat more difficult.

Since you mention [itex]A^\dagger A[/itex], it makes me think of positive(-definite) operators. Every positive operator can indeed be written in that form, but that's far from trivial.
 
  • #5


Its more expressing the hamiltonian of a quantum harmonic oscillator in terms of a variable - i.e

showing that:

H = p^2/2m + 1/2mw^2x^2

can be expressed as

(hbar)(w) [adagger*a + 1/2]

Where a = sqrt(mw/2hbar)x + i*sqrt(1/2mwhbar)p

where x and p are the position and momentum operators
 
  • #6


Doesn't the solution to that appear in all the introductory books? If you're trying to follow a proof and is stuck on a detail, you should ask about that detail (preferably with a link to the page at google books).

Edit: One thing you will need to know is that the adjoint operation ##A\mapsto A^*## is conjugate linear in the sense that for all complex numbers c and all linear operators A, we have ##(cA)^*=c^*A^*##. In particular, for any two self-adjoint A and B, we have $$(A+iB)^*=A^*+(iB)^*=A^*-iB^*=A-iB.$$
 
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  • #7


Fredrik;3768278[... said:
. In particular, for any two self-adjoint A and B, we have $$(A+iB)^*=A^*+(iB)^*=A^*-iB^*=A-iB.$$

This of course is valid only for bounded operators.
 
  • #8


Is it? I didn't even know that. I just checked the notes I've made on the adjoint operation, and they end right as I've started to explain the definition of the adjoint operation for unbounded operators, with a comment to myself that I need to check if it satisfies identities like that.

Anyway, physics books completely ignore this issue. I would guess that many of the authors don't know this. The solution I have seen definitely requires the readers to treat x-ip as the adjoint of x+ip.
 
  • #9


See it for yourself, the x and p are self-adjoint on individual non-equal domains in L^2 (R) and are only essentially self-adjoint on the intersection of their domains. Hence one should use operatorial inclusion instead of operatorial equality when using a and a^dagger. This finesse is indeed almost everywhere neglected and one uses the = sign in a quite abusive way.
 
  • #10


OK, I think I see what you mean. We have
$$\langle (A+iB)^*x,y\rangle=\langle (A^*-iB^*)x,y\rangle$$ for all x,y such that this equality and the calculation that proves it make sense. But we can't conclude that ##(A+iB)^*=A^*-iB^*##, because these operators may have different domains. When A and B are self-adjoint, this is not a problem.

In a calculation like
$$x^2+a^2p^2=(x+iap)(x-iap)+ia[x,p],$$ there's some abuse of notation going on, because the domains of ##x^2## and ##p^2## are smaller than the domains of x and p.
 

Related to Can Someone Please Explain Hermitian Conjugates To Me?

1. What is a Hermitian conjugate?

A Hermitian conjugate is a mathematical operation that involves taking the complex conjugate of a matrix or vector and then transposing it. This operation is commonly used in quantum mechanics and linear algebra to determine the adjoint of a matrix or to calculate inner products.

2. How is a Hermitian conjugate different from a regular conjugate?

A regular conjugate only involves taking the complex conjugate of a number, while a Hermitian conjugate involves both taking the complex conjugate and transposing a matrix or vector. In other words, a Hermitian conjugate is a more complex operation that involves both the complex conjugate and a transpose.

3. What is the significance of Hermitian conjugates in quantum mechanics?

In quantum mechanics, Hermitian conjugates are used to determine the adjoint of an operator, which is important in calculating the expectation value of a physical quantity. Additionally, Hermitian operators have real eigenvalues, which correspond to observable quantities in quantum mechanics.

4. Can you provide an example of how to calculate a Hermitian conjugate?

Sure, let's say we have a matrix A = [ 1 + 2i 3 - 4i ; 5 + 6i 7 + 8i ]. To calculate the Hermitian conjugate of this matrix, we first take the complex conjugate of each element, which gives us A* = [ 1 - 2i 3 + 4i ; 5 - 6i 7 - 8i ]. Then, we transpose this matrix, giving us the final Hermitian conjugate A† = [1 - 2i 5 - 6i ; 3 + 4i 7 + 8i].

5. How are Hermitian conjugates related to inner products?

Hermitian conjugates play a crucial role in calculating inner products, which are used to determine the similarity between two vectors or matrices. The inner product of two vectors is equal to the product of the first vector, the Hermitian conjugate of the second vector, and the transpose of the first vector. In other words, the inner product is equal to v†w, where v and w are vectors.

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