Uncertainty of a Gaussian wavepacket

In summary, a Gaussian wavepacket is a type of wave function that represents the probability distribution of a particle in quantum mechanics. It is characterized by its central peak and its rate of spreading, which is determined by the uncertainty principle. The uncertainty of a Gaussian wavepacket refers to the inherent uncertainty in the position and momentum of the particle, which increases as the wavepacket spreads over time. This uncertainty is a fundamental property of quantum mechanics and is essential for the understanding of the behavior of particles on a microscopic level.
  • #1
Isaac0427
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Hi,

I know that a Gaussian wavepacket has minimum uncertainty. The issue is, some sources are telling me that σxσp=ħ and others are telling me that σxσp=ħ/2. I am really confused. I think the latter is correct due to what I have been taught about the uncertainty principle, but then I don't understand what sources like the following are telling me:
http://oer.physics.manchester.ac.uk/QM/Notes/jsmath/Notesse39.html (see equation 10.17)

However, my own math (to my understanding) gives me a result similar to the link above. Working this out on my own, this is how I understand it:
A normalized Gaussian, where ##\left<x\right>=0## with a standard deviation ##\sigma_x## is
$$\psi (x) = \frac{1}{\sigma_x \sqrt{\pi}}e^{-x^2/2\sigma_x^2}$$
It's Fourier transform is
$$\tilde{\psi} (k) = \frac{\sigma_x}{\sqrt{\pi}}e^{-k^2\sigma_x^2/2}=\frac{1}{\sigma_k\sqrt{\pi}}e^{-k^2/2\sigma_k^2}$$
where the uncertainty in k is
$$\sigma_k=\frac{1}{\sigma_x}$$

This seems to yield
$$\sigma_x\sigma_k=1$$
or
$$\sigma_x\sigma_p=\hbar$$
Since the Gaussian minimizes uncertainty, the uncertainty principle would thus be
$$\sigma_x\sigma_p\geq \hbar$$
as the linked article suggests. To my knowledge, however, the uncertainty principle is
$$\sigma_x\sigma_p\geq\frac{\hbar}{2}$$
What is going on here?
 
Last edited:
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  • #2
Isaac0427 said:
I think the latter is correct
True
Isaac0427 said:
but then I don't understand what sources like the following are telling me:
http://oer.physics.manchester.ac.uk/QM/Notes/jsmath/Notesse39.html (see equation 10.17)
Equation 10.13 is correct, but 10.17 cannot be (they contradict!). I don't think that site is very reliable and accurate. I spotted other typos there too. May be try doing the math instead of trusting it.
 
  • #3
Stavros Kiri said:
May be try doing the math instead of trusting it.
Right-- I edited that into the original post. Could you tell me what I did wrong there?
 
  • #4
Looking back at the link, I think I found the mistake. Equation 10.21 is the key and is correct (yields Δp = ħ/σ√2), but equations 10.17 and 10.22 are both wrong (typo).

Do you still want me to check your Fourier transform method?
 
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  • #5
Stavros Kiri said:
Do you still want me to check your Fourier tranforms?
If you could, as I still don't know what I did wrong there.
 
  • #6
Ok. I think that although the original gaussian is correct and normalized, the Fourier transform isn't normalized. When you normalize it you should get the same form as the original (just x and k switched, I think) and the correct result ...
 
  • #7
Stavros Kiri said:
Ok. I think that although the original gaussian is correct and normalized, the Fourier transform isn't normalized. When you normalize it you should get the same form as the original (just x and k switched, I think) and the correct result ...
What would the correct result be (i.e. the correct transform)?
 
  • #8
Isaac0427 said:
A normalized Gaussian, where ##\left<x\right>=0## with a standard deviation ##\sigma_x## is
$$\psi (x) = \frac{1}{\sigma_x \sqrt{\pi}}e^{-x^2/2\sigma_x^2}$$
It's Fourier transform is
Just switch x and k. Just noticed you have it there:
Isaac0427 said:
It's Fourier transform is
$$\tilde{\psi} (k) = \frac{\sigma_x}{\sqrt{\pi}}e^{-k^2\sigma_x^2/2}=\frac{1}{\sigma_k\sqrt{\pi}}e^{-k^2/2\sigma_k^2}$$

But the first part of this last double equation seems to be wrong. How did you get it? Is that equation normalized? The second part is.
 
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  • #9
Hang on. I am fixing the quotes.
 
  • #10
Isaac0427 said:
A normalized Gaussian, where ##\left<x\right>=0## with a standard deviation ##\sigma_x## is
$$\psi (x) = \frac{1}{\sigma_x \sqrt{\pi}}e^{-x^2/2\sigma_x^2}$$
It's Fourier transform is
$$\tilde{\psi} (k) = \frac{\sigma_x}{\sqrt{\pi}}e^{-k^2\sigma_x^2/2}=\frac{1}{\sigma_k\sqrt{\pi}}e^{-k^2/2\sigma_k^2}$$
 
  • #11
All fixed. Just see and reply to #8 above.
 

1. What is a Gaussian wavepacket?

A Gaussian wavepacket is a type of wave function commonly used to describe the position and momentum of a quantum particle. It is a mathematical function that represents the probability distribution of finding the particle at different positions and momenta.

2. How is uncertainty related to a Gaussian wavepacket?

Uncertainty in quantum mechanics refers to the limitations in simultaneously measuring the position and momentum of a particle. In a Gaussian wavepacket, the uncertainty is related to the spread of the wavepacket. The more spread out the wavepacket is, the greater the uncertainty in the particle's position and momentum.

3. How is the uncertainty of a Gaussian wavepacket calculated?

The uncertainty of a Gaussian wavepacket can be calculated using the Heisenberg uncertainty principle, which states that the product of the uncertainties in position and momentum is equal to or greater than a constant value. In the case of a Gaussian wavepacket, this constant is equal to the width of the wavepacket.

4. Can the uncertainty of a Gaussian wavepacket be reduced?

No, the uncertainty of a Gaussian wavepacket cannot be reduced beyond the limitations set by the Heisenberg uncertainty principle. This is a fundamental principle of quantum mechanics and is not affected by any external factors.

5. What are some practical applications of the uncertainty of a Gaussian wavepacket?

The uncertainty of a Gaussian wavepacket is used in various applications, such as in quantum computing, where precise control of particles is required. It is also used in time-resolved spectroscopy, which studies the dynamics of chemical reactions and other processes. Additionally, it is used in medical imaging techniques, such as MRI, to provide detailed images of the body's internal structures.

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