Variational method approximation for half-space linear potential

In summary, the conversation discussed a test question where the student was asked to use the variational method to approximate the ground state potential. The student was confused about the correct integrals and whether to assume a negative or positive alpha value. The conversation ended with the suggestion to take the derivative and set it to zero to find the minimum energy.
  • #1
mjordan2nd
177
1

Homework Statement



This was a test question I just had, and I'm fairly certain I got it wrong. I'm confused as to what I did wrong, though. We were told that our potential was infinite when x<0, and Cx where x>0. We were asked to approximate the ground state potential using the variational method with a test function [tex]xe^{- \alpha x}[/tex].

Homework Equations



The variational method states that

[tex]\frac{\langle \psi \mid \hat{H} \mid \Psi \rangle}{\langle \psi \mid \Psi \rangle} \ge E_0.[/tex]


The Attempt at a Solution



I calculate

[tex] \langle \psi \mid \hat{H} \mid \Psi \rangle = \frac{3\hbar^2}{8m} + \frac{c}{4 \alpha^3}.[/tex]

and

[tex]\langle \psi \mid \Psi \rangle = \frac{1}{4 \alpha^3}.[/tex]

In total this gives me

[tex]\frac{\langle \psi \mid \hat{H} \mid \Psi \rangle}{\langle \psi \mid \Psi \rangle} = \frac{3 \hbar^2 \alpha^3}{2m} + c.[/tex]

Now assuming I had gotten this far correctly, I was a little confused where to go from here. Presumable I need to minimize this with respect to alpha. However, this would mean that alpha will be negative and unbounded, correct? Or do I need to assume that alpha is greater than 0. In that case, wouldn't the minimum energy just be c? This seems wrong to me. Any advice would be appreciated.
 
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  • #2
Those should all be the same bras and kets up there. Can't go back and edit for some reason.
 
  • #3
I believe that your integrals were a little off.

I find that the integrals should be

hbar^2/(8m*alpha), 3/(8*alpha^4), (4*alpha^3)^(-1)

After you simplify those, your next step is always to take the derivative with respect to alpha and set to zero. You were right to be alarmed by an unbounded, negative energy. That should not occur.
 

Related to Variational method approximation for half-space linear potential

1. What is the variational method approximation for half-space linear potential?

The variational method approximation for half-space linear potential is a mathematical technique used to approximate the solution to a linear potential problem in a half-space. It involves finding an approximate solution that minimizes the energy functional of the system.

2. How does the variational method approximation differ from other methods for solving linear potential problems?

The variational method approximation differs from other methods, such as the finite difference method or the finite element method, in that it does not require discretization of the problem domain. Instead, it finds an approximate solution by minimizing the energy functional, which can result in a more accurate and efficient solution.

3. What are the advantages of using the variational method approximation for half-space linear potential?

The variational method approximation has several advantages, including its ability to handle complex geometries and boundary conditions, its high accuracy, and its ability to handle both linear and nonlinear problems. It also does not require a large number of computational resources, making it a cost-effective option.

4. What are the limitations of the variational method approximation for half-space linear potential?

One limitation of the variational method approximation is that it can only provide an approximate solution, which may not be as accurate as the exact solution. It also requires some prior knowledge of the problem to determine the appropriate energy functional, which may be challenging for complex problems.

5. In what fields is the variational method approximation commonly used?

The variational method approximation is commonly used in various fields such as physics, engineering, and materials science. It is particularly useful for solving problems involving potential flow, heat transfer, and stress analysis, among others. It has also found applications in quantum mechanics and statistical mechanics.

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