Correct Setup for Finite Difference to Calculate Quantum Tunneling

In summary, the correct setup for finite difference methods to calculate quantum tunneling involves discretizing the Schrödinger equation on a grid to approximate derivatives. This requires defining an appropriate potential energy profile and ensuring that boundary conditions are correctly applied to capture the tunneling behavior. The grid spacing must be fine enough to accurately resolve the wavefunction, and sufficient points must be included to observe the tunneling effect effectively. Proper normalization of the wavefunction and careful handling of numerical stability are also essential for reliable results.
  • #1
Tertius
58
10
Homework Statement
I am discretizing the Schrodinger equation and solving for a quantum tunneling probability
Relevant Equations
Schrodinger equation
I thought I solved the problem in answering my own post a few days ago, but the tunneling probability vs. energy trend is clearly wrong. I've remade the post because I have totally changed my approach and need a better understanding of the boundary setup.

Overall description: a plane wave approaches a barrier, tunnels, and a plane wave exits. I am doing a full 1D simulation so I can eventually use non-standard potentials, but I'm starting with a square potential.

Setup of Solution:
$$-\frac{\hbar^{2}}{2m} \frac{d^{2}}{dx^{2}} \psi(x) +V(x)\psi(x)=E\psi(x)$$
$$H=-\frac{\hbar^{2}}{2m}+V(x)$$
The tri-diagonal matrix setup after applying finite derivates is ##\frac{h^2}{2ma^2}+V_i## for diagonals and ##\frac{-h^2}{2ma^2}## for the off-diagonals.

I have not included any boundary conditions explicitly. The standard setup for this problem is $$H\psi=E\psi$$ where H is the Hamiltonian and E are the energy eigenvalues. I don't need to compute the eigenvalues, however because this is an unbounded system. The energy eigenvalue for this system should be the kinetic energy of the incoming particle. This allows me to set it up as $$(H-IE)\psi=b$$ The vector b is used for the right side as an empty vector. ##I## is the identity matrix.

When the vector ##b## is actually all 0, the solution is always trivial. I have to include a very small, non-zero value somewhere in this vector for it to produce a solution that looks like the attached picture. However, when I recompute for different energies, the tunneling probablity changes in a weird, oscillatory way as shown in the other attached graph.

Question:
What is wrong with the assumptions of this setup? Do I need to include boundaries specifically, even though the solutions are plane waves?

1717544970862.png


1717545086366.png
 
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  • #2
Tertius said:
Overall description: a plane wave approaches a barrier, tunnels, and a plane wave exits. I am doing a full 1D simulation so I can eventually use non-standard potentials, but I'm starting with a square potential.
A plane wave cannot "approach" a barrier. A plane wave is a solution that covers all space. Do you mean a wave packet?

(Note: I know that when dealing with scattering, the incoming state is taken as a plane wave, but that is in the limit ##t \rightarrow \infty##, which is not suitable for a numerical simulation.)

Tertius said:
Setup of Solution:
$$-\frac{\hbar^{2}}{2m} \frac{d^{2}}{dx^{2}} \psi(x) +V(x)\psi(x)=E\psi(x)$$
$$H=-\frac{\hbar^{2}}{2m}+V(x)$$
The term ##\frac{d^{2}}{dx^{2}}## is missing here.

Tertius said:
The tri-diagonal matrix setup after applying finite derivates is ##\frac{h^2}{2ma^2}+V_i## for diagonals and ##\frac{-h^2}{2ma^2}## for the off-diagonals.
The kinetic term on the diagonal is off by a factor of 2.

Tertius said:
The standard setup for this problem is $$H\psi=E\psi$$ where H is the Hamiltonian and E are the energy eigenvalues.
Depends what you are after. The time-dependent Schrödinger equation might be more appropriate.

Tertius said:
I don't need to compute the eigenvalues, however because this is an unbounded system. The energy eigenvalue for this system should be the kinetic energy of the incoming particle.
If you solve the time-independent Schrödinger equation as above, with the potential as part of the Hamiltonian, you will get energy eigenstates that are not free-particle eigenstates, hence the energy won't correspond to the kinetic energy.

Tertius said:
However, when I recompute for different energies, the tunneling probablity changes in a weird, oscillatory way as shown in the other attached graph.
How do you calculate that probability?

Question:
What is wrong with the assumptions of this setup? Do I need to include boundaries specifically, even though the solutions are plane waves?
[/QUOTE]
Again, the solutions are not plane waves. AS set up, the problem assumes hard walls at the extremities of the grid, so the eigenfunctions should go to zero at both ends. You can solve the full eigenvalue problem ##H\psi=E\ps## and get the corresponding discrete set of eigenstates.
 
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  • #3
DrClaude said:
A plane wave cannot "approach" a barrier. A plane wave is a solution that covers all space. Do you mean a wave packet?

(Note: I know that when dealing with scattering, the incoming state is taken as a plane wave, but that is in the limit ##t \rightarrow \infty##, which is not suitable for a numerical simulation.)


The term ##\frac{d^{2}}{dx^{2}}## is missing here.


The kinetic term on the diagonal is off by a factor of 2.


Depends what you are after. The time-dependent Schrödinger equation might be more appropriate.


If you solve the time-independent Schrödinger equation as above, with the potential as part of the Hamiltonian, you will get energy eigenstates that are not free-particle eigenstates, hence the energy won't correspond to the kinetic energy.


How do you calculate that probability?

Question:
What is wrong with the assumptions of this setup? Do I need to include boundaries specifically, even though the solutions are plane waves?
Again, the solutions are not plane waves. AS set up, the problem assumes hard walls at the extremities of the grid, so the eigenfunctions should go to zero at both ends. You can solve the full eigenvalue problem ##H\psi=E\ps## and get the corresponding discrete set of eigenstates.
[/QUOTE]


Thanks for the response.

Ok so trying to use plane waves in a numerical simulation necessitates a boundary, which means they aren't plane waves. So, the current setup was really just solving the equation between two boundaries with a potential in the middle. And it would require solving for the eigensystem and the eigenstates may not match the kinetic energy of the incoming particle.

I am open to changing my approach, my intention is to just have accurate numerical estimates of tunneling probabilities so I can eventually use non-standard potentials. I am reading through https://www.reed.edu/physics/faculty/wheeler/documents/Quantum Mechanics/Miscellaneous Essays/Gaussian Wavepackets.pdf

and I have a Gaussian wave packet simulation built, and it appears more robust.

I suppose my question now is, how to compute the tunneling probability from numerical results. Do I simply compute ##\psi^* \psi## at the front and back of the barrier (and take the ratio)? Basically I would just compute that value at each point in time in the simulation and see where is it maximal.
 
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FAQ: Correct Setup for Finite Difference to Calculate Quantum Tunneling

What is the finite difference method in the context of quantum tunneling?

The finite difference method is a numerical technique used to approximate solutions to differential equations by discretizing the equations on a grid. In the context of quantum tunneling, it involves dividing the potential energy landscape into a finite number of points and approximating the wave function and its derivatives using finite differences. This allows for the calculation of tunneling probabilities by solving the time-independent Schrödinger equation across the potential barrier.

How do I choose the grid spacing for the finite difference method?

The grid spacing, or the distance between adjacent points in the discretized grid, should be small enough to capture the relevant features of the potential energy landscape and the wave function. A common approach is to perform a convergence study, where you calculate the tunneling probability using different grid spacings and identify the point at which further refinement yields negligible changes in the results. Typically, grid spacings on the order of 0.1 to 0.01 times the de Broglie wavelength of the particle are a good starting point.

What boundary conditions should I use for quantum tunneling calculations?

For quantum tunneling problems, the boundary conditions typically involve setting the wave function to zero at the boundaries of the potential barrier if it is an infinite barrier scenario. For finite barriers, the wave function should be continuous, and its derivative should also be continuous at the boundaries. Additionally, the wave function should approach a plane wave form at large distances from the barrier, reflecting the incoming and outgoing states of the particle.

How can I ensure the stability and accuracy of my finite difference scheme?

To ensure stability and accuracy in your finite difference scheme, you should use an appropriate time-stepping method if you are solving the time-dependent Schrödinger equation. For the time-independent case, ensure that the finite difference approximation is consistent with the physical problem being solved. You can also implement techniques like adaptive mesh refinement, where grid spacing is adjusted dynamically based on the behavior of the wave function, and validate your results against known analytical solutions or other numerical methods.

What software tools are commonly used for finite difference calculations in quantum mechanics?

Several software tools and programming languages are commonly used for finite difference calculations in quantum mechanics, including MATLAB, Python (with libraries such as NumPy and SciPy), and C++. These platforms provide robust numerical libraries and visualization tools that facilitate the implementation of finite difference methods. Additionally, specialized quantum mechanics simulation software, such as Quantum Development Kit (QDK) or Quantum Toolbox in Python (QuTiP), can also be utilized for more complex quantum systems.

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