Eigenvalue Problem and the Calculus of Variations

In summary, the solution to the eigenvalue problem of ##B u = \lambda A u## can be found by finding stationary values of ##(Bu,u)## subject to ##(Au,u)=1##, where ##(g,f) = \int fg##. This can be done by using the method of Lagrange multipliers, in which the trial function ##u## is represented as a linear combination of known functions ##w_i## with a constraint on the coefficients ##\alpha_i##. This leads to the eigenvalue problem ##Bu=\lambda u##. However, this representation only works for finite-dimensional spaces. If working in infinite-dimensional spaces, other methods must be used.
  • #1
member 428835
Hi PF!

Given ##B u = \lambda A u## where ##A,B## are linear operators (matrices) and ##u## a function (vector) to be operated on with eigenvalue ##\lambda##, I read that the solution to this eigenvalue problem is equivalent to finding stationary values of ##(Bu,u)## subject to ##(Au,u)=1##, where ##(g,f) = \int fg##.

Can someone explain this to me, or point me in the right direction? I don't see how the two relate.
 
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  • #2
Did you try applying the method of Lagrange multipliers to the stationary value problem?
 
  • #3
Orodruin said:
Did you try applying the method of Lagrange multipliers to the stationary value problem?
Could you elaborate? I've seen something like this done before I think, where ##u = \sum_i \alpha_i w_i## where ##\alpha## is a constant and ##w## is a known trial function. By construction ##(w_i,w_j)=\delta_{ij}##. Then evidently we choose ##\alpha## to minimize ##(Bu,u)## (why?) under the constraint ##\sum \alpha_i^2=1##, and hence we arrive at the eigenvalue problem ##Bu=\lambda u##.
 
  • #4
joshmccraney said:
Hi PF!

Given ##B u = \lambda A u## where ##A,B## are linear operators (matrices) .

Note that Linear Operator and Matrix coincide only in finite-dimensional spaces. There is no such representation in infinite -dim spaces.
 
  • #6
StoneTemplePython said:
If you're still trying to tackle the problem of finding eigenvalues of ##B^{-1}A## or ##A^{-1}B## --you posted about this a few months back as I recall, then you may want to check out this thread:

https://www.physicsforums.com/threads/eigenvalues-of-the-product-of-two-matrices.588101
Yes, I definitely did ask about this a while ago. I ended up taking someone's advice on here (don't recall who it was) and used a build in function that worked great (errors were mine but shockingly also the paper's).
 

What is the eigenvalue problem?

The eigenvalue problem is a mathematical problem that involves finding the values of a given linear operator that satisfy a particular equation. These values are known as eigenvalues and are often used in physics and engineering to model systems and solve differential equations.

What is the calculus of variations?

The calculus of variations is a branch of mathematics that deals with finding the optimal value of a functional. It involves finding the function that minimizes or maximizes a given integral. This branch of mathematics has applications in physics, economics, and engineering.

How are eigenvalue problems and the calculus of variations related?

Eigenvalue problems and the calculus of variations are closely related in that both involve finding the extreme values of a mathematical function. In the case of eigenvalue problems, the function is a linear operator, while in the calculus of variations, the function is an integral. Both involve finding the function that makes the expression stationary.

What are some real-world applications of eigenvalue problems and the calculus of variations?

Eigenvalue problems and the calculus of variations have applications in a variety of fields, including physics, engineering, economics, and computer science. They can be used to model and solve problems in quantum mechanics, structural engineering, optimal control, and image processing, to name a few.

What are some techniques used to solve eigenvalue problems and the calculus of variations?

There are several techniques used to solve eigenvalue problems and the calculus of variations, including the Rayleigh-Ritz method, the variational method, and the Euler-Lagrange equation. These methods involve using different mathematical techniques, such as optimization and functional analysis, to find the optimal solutions for these problems.

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