Normalization Constant for Gaussian

In summary, to find the normalization constant N for the Gaussian wave packet, the integral of the wave function squared must equal 1. By performing substitutions and solving for N, it can be determined that N = (1/(Kx_0√π))^1/2, without the inclusion of x_0 in the final answer.
  • #1
atomicpedals
209
7

Homework Statement



Find the normalization constant N for the Gaussian wave packet
[tex]\psi (x) = N e^{-(x-x_{0})^{2}/2 K^{2}}[/tex]

Homework Equations


[tex]1 = \int |\psi (x)|^{2} dx[/tex]

The Attempt at a Solution


[tex]1 = \int |\psi (x)|^{2} dx = N^{2} \int e^{-(x-x_{0})^{2}/K^{2}} dx[/tex]
Substitute [itex]y=(x-x_{0})[/itex]
[tex]N^{2} \int e^{-y^{2}/K^{2}} dy[/tex]
Substitute again [itex]z = y/|K|[/itex]
[tex]N^{2} \int e^{-z^{2}} dz = N^{2} x_{0} K \sqrt{\pi}[/tex]
[tex]N= ( \frac{1}{K x_{0} \sqrt{\pi}})^{1/2}[/tex]
Where my question lies is with the [itex]x_{0}[/itex] in N. Should that be there?
 
Last edited:
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  • #2
Actually... that first substitution may be flawed.
 
  • #3
Ok, I think I see where I went wrong. The [itex]x_{0}[/itex] doesn't belong in the final answer.
 
  • #4
yes, you've figured it out.

P.S. on this line, on the left hand side, there should be K since you have changed dy for dz:
[tex]N^{2} \int e^{-z^{2}} dz = N^{2} x_{0} K \sqrt{\pi}[/tex]
But after that you've remembered the K, so I guess you just forgot to type the K here, but you understand the right answer.
 
  • #5
Yeah, I forgot about the K, so what I should end up with is:
[tex]N^{2} K \int e^{-z^{2}} dz = N^{2} K \sqrt{\pi}[/tex]
 
  • #6
yep, looks right to me :)
 

1. What is the normalization constant for a Gaussian distribution?

The normalization constant for a Gaussian distribution is a value that ensures the total area under the curve of the distribution is equal to 1. This constant is also known as the standard deviation or the variance of the distribution.

2. Why is the normalization constant important in Gaussian distributions?

The normalization constant is important in Gaussian distributions because it allows us to calculate the probabilities of different events occurring within the distribution. Without this constant, the probabilities calculated would not accurately represent the true probabilities.

3. How is the normalization constant calculated?

The normalization constant is calculated by taking the inverse of the square root of 2π, which is the denominator in the formula for the Gaussian distribution. This value is then multiplied by the standard deviation of the distribution.

4. Can the normalization constant be different for different Gaussian distributions?

Yes, the normalization constant can be different for different Gaussian distributions. This is because the standard deviation, which is a component of the normalization constant, can vary for each distribution.

5. How does the normalization constant affect the shape of a Gaussian distribution?

The normalization constant does not affect the shape of a Gaussian distribution. This constant only ensures that the total area under the curve of the distribution is equal to 1, regardless of the standard deviation or mean of the distribution.

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