Generalized eigenvectors and differential equations

In summary, we have a 3x3 matrix A such that A\mathbf{v_1}=\mathbf{v_1}+\mathbf{v_2}, A\mathbf{v_2}=\mathbf{v_2}+\mathbf{v_3}, A\mathbf{v_3}=\mathbf{v_3} where \mathbf{v_3} \neq \mathbb{0}. Using another 3x3 matrix S, we can find the general solution of \dot{\mathbf{x}}=A\mathbf{x} as SBS^{-1}\mathbf{x}. To find the general solution of \dot{\math
  • #1
drawar
132
0
Let [itex]A[/itex] be an 3x3 matrix such that [itex]A\mathbf{v_1}=\mathbf{v_1}+\mathbf{v_2}, A\mathbf{v_2}=\mathbf{v_2}+\mathbf{v_3}, A\mathbf{v_3}=\mathbf{v_3}[/itex] where [itex]\mathbf{v_3} \neq \mathbb{0}[/itex]. Let [itex]B=S^{-1}AS[/itex] where [itex]S[/itex] is another 3x3 matrix.
(i) Find the general solution of [itex]\dot{\mathbf{x}}=B\mathbf{x}[/itex].
(ii) Show that 1 is the only eigenvalue of [itex]B[/itex].

It's clear that [itex]\mathbf{v_3},\mathbf{v_2}[/itex] and [itex]\mathbf{v_1}[/itex] form a chain of generalized eigenvectors associated with [itex]\lambda=1[/itex] and hence are linearly independent. From this I can find the general solution of [itex]\dot{\mathbf{x}}=A\mathbf{x}=SBS^{-1}\mathbf{x}[/itex] but how can I proceed from here to find the general solution of [itex]\dot{\mathbf{x}}=B\mathbf{x}[/itex]?
Any help is much appreciated, thank you!
 
Physics news on Phys.org
  • #2
You have ##A = S B S^{-1}##.

If ##x## is a solution of ##\dot x = Bx##, let ##x = S^{-1} y##.

Then ##\dot y = Ay##.
 
  • #3
That's brilliant, thanks!
 

FAQ: Generalized eigenvectors and differential equations

1. What are generalized eigenvectors and how are they related to differential equations?

Generalized eigenvectors are a generalization of the concept of eigenvectors in linear algebra. They are a type of vector that corresponds to a specific eigenvalue of a matrix, but may not satisfy the usual definition of an eigenvector. In the context of differential equations, generalized eigenvectors are used to find solutions to systems of linear differential equations.

2. How are generalized eigenvectors computed?

Generalized eigenvectors can be computed using the Jordan canonical form of a matrix. This involves finding the eigenvalues and eigenvectors of a matrix, and then using those to construct a Jordan matrix. The generalized eigenvectors can then be found by solving a system of equations involving the Jordan matrix.

3. What is the importance of generalized eigenvectors in solving differential equations?

Generalized eigenvectors are important in solving differential equations because they allow us to find solutions to systems of linear differential equations that cannot be solved using traditional methods. They also help us to understand the behavior of solutions near critical points.

4. Can generalized eigenvectors be complex numbers?

Yes, generalized eigenvectors can be complex numbers. In fact, complex numbers are often used in the computation of generalized eigenvectors and in the solutions to differential equations. This is because complex numbers have both real and imaginary components, which can help to represent a wider range of solutions.

5. Are there any real-world applications of generalized eigenvectors and differential equations?

Yes, there are many real-world applications of generalized eigenvectors and differential equations. Some examples include modeling population growth, analyzing the stability of electrical circuits, and understanding the behavior of chemical reactions. They can also be used in fields such as economics, physics, and engineering to model and solve various systems.

Similar threads

Back
Top