Variational principle convergence

In summary, the variational principle is not only used to find the ground state energy of a system, but also to find higher order states. It does so by minimizing the energy of a wavefunction while also requiring it to be orthogonal to previous wavefunctions. This approach is similar to using matrix techniques like the Roothan equations or Rayleigh-Schrodinger perturbation theory to find all states at once.
  • #1
Manchot
473
4
A text I am reading has used the variational principle not only to find the ground state of a system, but also to find some higher order states. (Specifically, it was used to derive the Roothaan equations, which are ultimately related to the LCAO method of orbital calculations.) I don't see how this could be valid.

For finding the ground state energy of a system, it is obvious why minimizing the expected value of the Hamiltonian gets the best approximation to the ground state. But in what sense does the variational principle converge to the right result? I thought at first that it might minimize the variance of Hamiltonian in the trial wavefunction, but I do not believe that this is the case. So, does anyone know exactly in what precise sense the variational principle finds the "best" solutions to the eigenvalue problem?
 
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  • #2
Manchot said:
For finding the ground state energy of a system, it is obvious why minimizing the expected value of the Hamiltonian gets the best approximation to the ground state. But in what sense does the variational principle converge to the right result? I thought at first that it might minimize the variance of Hamiltonian in the trial wavefunction, but I do not believe that this is the case. So, does anyone know exactly in what precise sense the variational principle finds the "best" solutions to the eigenvalue problem?

The higher order (excited) states are local minima of the Hamiltonian, while the ground state are the global minima. If your initial guess is sufficiently close to the excited state then it will converge to the excited one.
Or you can modify the functional (the Hamiltonian) such that the excited states are also grobal minima.

There is a lot of literature on this subject, you can start with http://portal.acm.org/citation.cfm?id=587202
 
  • #3
The way I see how to Variational principle works in the Roothan equation, or in Raylieigh-Schrodinger perturbation theory, etc in order to find both gound and excited states (at least in 1-particle Hamiltonians) is this:

We agree that the variational principle makes sense that one could find the ground state wavefunction by minimizing the energy, right? I submit the strategy, without proof, that I could then start again minimizing the energy of a wavefunction, while also requiring that this new wavefunction is orthogonal to the ground state wavefunction. This will give me the first excited state. I can then find a third wavefunction through minimization by requiring that it be orthogonal to the first two, etc, until I build up an approximation to the entire spectrum.

Using a matrix technique, like the Roothan equations or Rayleigh-Schrodinger, is sort of like doing that procedure to find all of the states all at once. The eigenvalues from the Matrix equation all correspond with orthogonal wavefunctions.
 

Related to Variational principle convergence

What is the variational principle?

The variational principle is a mathematical principle that states that the actual state of a physical system is the one that minimizes a certain functional.

What is variational principle convergence?

Variational principle convergence refers to the process of finding the solution to a physical system by minimizing the functional using the variational principle.

How is the variational principle used in physics?

The variational principle is used in physics to find the equations of motion for a system by minimizing the action functional, which is a measure of the system's energy.

What are the benefits of using the variational principle?

Using the variational principle can simplify the process of finding the equations of motion for a physical system, as it allows for the use of powerful mathematical techniques such as the Euler-Lagrange equations.

What are some applications of the variational principle in science and engineering?

The variational principle has a wide range of applications in various fields such as classical mechanics, quantum mechanics, electromagnetism, and engineering. It is commonly used in the study of fluid dynamics, optimization problems, and in the design of efficient algorithms.

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