Sakurai 2.17 - More elegant solution help?

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It is a generalization of the integration by parts argument that leads to integration of the Gaussian. In summary, the conversation discusses finding a solution for the one-dimensional simple harmonic oscillator using the position and momentum representations. The solution involves computing the Fourier transform and using Wick's theorem to simplify the process. This is considered a more elegant solution compared to the previous approach.
  • #1
Domnu
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Problem

Show for the one-dimensional simple harmonic oscillator

[tex]\langle 0 | e^{ikx} | 0 \rangle = \exp{[-k^2 \langle 0 | x^2 | 0 \rangle / 2]} [/tex]

where [tex]x[/tex] is the position operator (here, [tex]k[/tex] is a number, not an operator, with dimensions 1/length).

My Solution

Well, I already know how to do this problem, but my solution isn't as clean. I was searching for a more elegant solution. Here's the outline to my solution:

1. We know that [tex]e^{ikx}|p'\rangle = |p' + \hbar k\rangle[/tex] (pretty simple to prove).
2. We can show that
[tex]\langle 0 |e^{ikx}| 0 \rangle = \int dp' \langle 0|p' \rangle \langle p'-\hbar k | 0 \rangle[/tex]​
by putting everything in the momentum basis.
3. We then just need to find the harmonic oscillator's ground state in the momentum representation, which is just a Fourier transform of the ground state in the position representation.
4. Substitute into the thing got in #2 and compute away, leading to the equality. (and this works, after expanding everything)

As we can see, computing the Fourier transform in step 3 and computing everything in step 4 takes some time, and isn't exactly the "winning" solution.:smile: So would someone help me find or post a more elegant solution?
 
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  • #2
I don't know if this is more elegant or not, but ...

1) Expand in powers of k.
2) Note that expectation value of odd powers of x is zero, because the ground-state wave function is an even function of x.
3) Prove that

[tex]\langle x^{2n}\rangle = (2n{-}1)!\,\langle x^2\rangle^n.[/tex]

Useful identify for the proof:

[tex]\int_{-\infty}^{+\infty}dx\;x^{2n}e^{-cx^2}=\left(-{d\over dc}\right)^{\!n}\int_{-\infty}^{+\infty}dx\;e^{-cx^2}.[/tex]

4) Resum the series.
 
  • #3
Wow... number three seems to be pretty useful! This was actually my initial first approach... I found a really neat analog to the Catalan numbers, but wasn't able to complete it. I'll go and try out this approach. Thanks a lot for the help :smile:
 
  • #4
In quantum field theory #3 is known as Wick's theorem.
 

1. What is Sakurai 2.17 and why is it important in the scientific community?

Sakurai 2.17 refers to a specific equation in quantum mechanics, named after the Japanese physicist Jun Sakurai. It is important because it provides an elegant solution to the problem of calculating the energy levels of bound states in a quantum system.

2. How does Sakurai 2.17 differ from other equations in quantum mechanics?

Sakurai 2.17 is unique in its simplicity and effectiveness in solving the energy level problem. It is also notable for its elegant mathematical form, which is why it is often referred to as the "elegant solution."

3. What are the applications of Sakurai 2.17 in scientific research?

Sakurai 2.17 has been widely used in various fields of physics, including atomic and molecular physics, nuclear physics, and solid-state physics. It has also been applied in the study of quantum systems in chemistry and materials science.

4. How does understanding Sakurai 2.17 contribute to our understanding of quantum mechanics?

By understanding Sakurai 2.17, scientists gain a deeper understanding of the principles and concepts of quantum mechanics. It also allows for more accurate calculations and predictions of the behavior of quantum systems, leading to advancements in various fields of science and technology.

5. Are there any limitations or criticisms of Sakurai 2.17?

While Sakurai 2.17 is a powerful and widely used equation, it is not without its limitations. Some researchers have criticized its assumptions and applicability to certain complex systems. Additionally, it may not accurately predict the behavior of systems with strong interactions or in extreme conditions.

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