How do I plot this probability density over time?

In summary: This is what will give you the time dependence.In summary, the conversation discusses the need to plot representative snapshots of a wave function, but the exponential factor cancels out when squared. It is determined that the wave function is not an eigenstate of the Hamiltonian and must evolve in time. To plot different instances in time, the wave function needs to be projected onto the energy eigenstates to determine its expression. The conversation also touches on the concept of pure and mixed states, and the need to compute the Hamiltonian to determine if a wave function is an eigenstate.
  • #1
baouba
41
0
Here's the question: http://imgur.com/N60qRmw

I normalized the wave function and got A = sqrt(315/8L^9)

but how would I plot representative snapshots if the exponential factor will cancel when I square it? It's not a mixed state so it shouldn't depend on time as far as I can tell. Should I use a Fourier series? I'm just at a loss as to how to plot different instances in time if the complex term should cancel out when taking the square modulus. I feel like I might not have a complete understanding of the wave function or pure/mixed states. Could someone help clear this up?

Thank you
 
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  • #2
That wavefunction is not an eigenstate of the Hamiltonian, so it must evolve in time. You will need to project that wavefunction onto the wavefunctions for the energy eigenstates to determine an expression for ##\psi(x,t)##.
 
  • #3
fzero said:
That wavefunction is not an eigenstate of the Hamiltonian, so it must evolve in time. You will need to project that wavefunction onto the wavefunctions for the energy eigenstates to determine an expression for ##\psi(x,t)##.

How can you tell if a given wave function isn't an eigenstate of the hamiltonian? I just don't get how if |Ψn(x, y)|^2 = |Anψn(x)e^-iEnt/h-bar|^22 and Ψ is a pure state, how doesn't the exponential factor cancel out in 1 = ∫ |Ψn(x, y)|2 dx ?
 
  • #4
baouba said:
How can you tell if a given wave function isn't an eigenstate of the hamiltonian?

The most direct way would be to just compute ##\hat{H} \psi##. If the result is not ##\lambda \psi##, where ##\lambda## is a constant, then ##\psi## is not an eigenfunction of the Hamiltonian.

I just don't get how if |Ψn(x, y)|^2 = |Anψn(x)e^-iEnt/h-bar|^22 and Ψ is a pure state, how doesn't the exponential factor cancel out in 1 = ∫ |Ψn(x, y)|2 dx ?

The time-dependent wavefunction ##\psi(x,t)## will be a linear combination of the energy eigenstates. When you compute ##|\psi(x,t)|^2##, you will find cross-terms where the exponents do not cancel.
 

1. How do I plot a probability density over time using a graphing tool?

To plot a probability density over time, you will need to use a graphing tool that allows you to plot a line or curve on a graph. Popular graphing tools include Excel, Python's Matplotlib, and R's ggplot2. These tools have built-in functions for plotting probability density functions, making it easy to visualize your data.

2. What data do I need to plot a probability density over time?

To plot a probability density over time, you will need a set of data points that represent the probability at different points in time. This data can be obtained through experiments, simulations, or other data-gathering methods. The more data points you have, the more accurate your plot will be.

3. How do I interpret the plot of a probability density over time?

The plot of a probability density over time shows how the probability of a particular event changes over time. The y-axis represents the probability, while the x-axis represents time. The shape of the curve or line on the graph can provide insights into the trend and variability of the probability over time.

4. Can I use a bar graph to plot a probability density over time?

No, a bar graph is not suitable for plotting a probability density over time. This is because a bar graph represents discrete data, while a probability density function is continuous. Therefore, a line or curve graph is more appropriate for visualizing the changing probability over time.

5. How can I compare multiple probability density plots over time?

To compare multiple probability density plots over time, you can plot them on the same graph and use different colors or line styles to differentiate between them. This will allow you to see how the probability changes over time for different events or scenarios. You can also use statistical measures such as mean and standard deviation to compare the plots and determine which one has a higher or lower probability over time.

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