Finite difference Hamiltonian

In summary, the conversation discusses solving a 1D Hamiltonian on the interval [0,L] using the standard approach of discretizing the interval and using finite difference formulas. This method assumes that the wave-function goes to zero outside the interval, but the speaker is wondering if there is a way to enforce a non-zero value on the boundaries. The suggestion is to include the areas outside of [0,L] in the discretization.
  • #1
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Suppose I am given some 1D Hamiltonian:

H = ħ2/2m d2/dx2 + V(x) (1)

Which I want to solve on the interval [0,L]. I think most of you are familiar with the standard approach of discretizing the interval [0,L] in N pieces and using the finite difference formulas for V and the second derivative in (1), which can then be formulated as a matrix equation, which may be diagonalized for the eigenvector and eigenvalues.
Now for all this to work one has to assume that the wave-function goes to zero outside the interval [0,L], which follows if one makes the effort of writing up the finite difference expressions. My question is: Is there a way to enforce another boundary condition with this method? I am solving a problem, where it would be beneficial to enforce the wave function to take a non-zero value on the boundaries of the interval [0,L]. Is this possible with the standard finite difference method or should I look at more advanced methods?
 
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  • #2
you just have to include the areas outside of the [itex] [0,L][/itex] in the discretization, the wave function will fall off to 0 depending on the structure of the potential.
 

1. What is a finite difference Hamiltonian?

A finite difference Hamiltonian is a numerical method used to solve differential equations in quantum mechanics. It discretizes the continuous Hamiltonian operator into a matrix of finite differences, allowing for easier computation of the time evolution of a quantum system.

2. How does the finite difference Hamiltonian differ from other methods?

The finite difference Hamiltonian differs from other methods, such as the finite element method, by using a grid-based approach instead of a continuous approximation. This makes it more suitable for systems with discrete energy levels, such as quantum systems.

3. What are the advantages of using a finite difference Hamiltonian?

The advantages of using a finite difference Hamiltonian include its simplicity, efficiency, and accuracy. It is also well-suited for problems with complex geometries and boundary conditions, and can handle non-linear and time-dependent systems.

4. Are there any limitations to using a finite difference Hamiltonian?

One limitation of the finite difference Hamiltonian is that it can only handle systems with a finite number of energy levels. It also requires a fine grid resolution to accurately represent the system, which can be computationally expensive.

5. How is a finite difference Hamiltonian used in practice?

In practice, a finite difference Hamiltonian is used to solve differential equations in quantum mechanics by discretizing the Hamiltonian operator and then solving the resulting matrix equation using numerical methods. It is commonly used in computational chemistry, quantum mechanics, and other fields that involve solving differential equations.

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