How can diagonal matrices help solve eigenvalue problems?

In summary, the conversation discusses how to compute e^{At} for an nxn matrix A with distinct eigenvalues. It is shown that, if A is diagonalizable, one can compute e^{At} by only computing the diagonal entries after diagonalizing. It is also proven that (sI-A)L(e^{At}) = Identity and the pattern for 2x2 case is shown.
  • #1
soulflyfgm
28
0
hi, can some one give me any hints how to solve this problem? thank you


i tried to type it here but it dint come up so i uploaded http://tinypic.com/view.php?pic=2hgtqoz&s=3" with the problem.

Thank you so much


Recall that for an nxn matrix A with distinct eigenvalues [tex]\lambda[/tex] [tex]_{F}[/ktex], k=1,2,...,n


e^{At} = \sum^{n}_{k=1} Z_{k}e^{\lambda_{k}t}

By taking the Laplace Transform of both sides (or otherwise) show that
\sum^{n}_{k=1}Z_{k}= I_{n}

Where I_{n} is the nxn identity matrix
 
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  • #2
Although stated in a very horrible way, what is asked here boils down to show that, if A is diagonalizable, one can compute [itex]e^{At}[/itex] by only computing the diagonal entries after diagonalizing. Keep in mind that [itex]\mathcal{L}(e^{At}) = (sI - A)^{-1}[/itex].

So once you have the diagonal form employ the inverse laplace transformation.

I am sure that you can do it, so think about it for a while...
 
  • #3
okay maybe i read it totally wrong but if you know that

[tex] e^{At} = \sum^{n}_{k=1} Z_{k}e^{\lambda_{k}t} [/tex]

for all t then use it fot t=0 and get

[tex] I = e^{0} = e^{A0} = \sum^{n}_{k=1} Z_{k}e^{\lambda_{k}0} = \sum^{n}_{k=1} Z_{k}[/tex]

and you are done?
 
  • #4
The sum works with a general form of the following
[tex]
\left[ {\begin{array}{*{20}c}
1 & 0 \\
0 & 0 \\
\end{array}} \right] + \left[ {\begin{array}{*{20}c}
0 & 0 \\
0 & 1 \\
\end{array}} \right] = I
[/tex]

So it is directly related with the diagonal form... Thus you can also prove for non-zero t
 
  • #5
ok i have proven this so far
(SI-A)L(e^(At)) = Identity...but i do not how to prove that this is equal to [tex]\sum^{n}_{k=1}Z_{k}[/tex]

Any hints? thank you so much
 
  • #6
OK, but that one tells you nothing, how about this? Let A is a diagonal matrix, then for 2x2 case,

[tex]
e^{At}= e^{\left[ {\begin{array}{*{20}c}
\alpha & 0 \\
0 & \beta \\
\end{array}} \right]t} = \left[ {\begin{array}{*{20}c}
e^{\alpha t} & 0 \\
0 & e^{\beta t} \\
\end{array}} \right] = \left[ {\begin{array}{*{20}c}
1 & 0 \\
0 & 0 \\
\end{array}} \right]e^{\alpha t} + \left[ {\begin{array}{*{20}c}
0 & 0 \\
0 & 1 \\
\end{array}} \right]e^{\beta t}
[/tex]
And, then from the previous post,
[tex]

\left[ {\begin{array}{*{20}c}
1 & 0 \\
0 & 0 \\
\end{array}} \right] + \left[ {\begin{array}{*{20}c}
0 & 0 \\
0 & 1 \\
\end{array}} \right] = I

[/tex]

Can you see the pattern now?
 

1. What are eigenvalues and how are they related to Laplace?

Eigenvalues are a set of special numbers that represent the scaling factor of a vector when multiplied by a particular matrix. They are related to Laplace because the eigenvalues of a Laplace matrix correspond to the frequencies of oscillations in a physical system.

2. How are eigenvalues and eigenvectors calculated?

Eigenvalues and eigenvectors are calculated using the characteristic equation of a matrix. This equation involves taking the determinant of the matrix and solving for the values that make the determinant equal to zero.

3. What is the significance of eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are important in many fields, including physics, engineering, and computer science. They provide insights into the behavior and stability of systems and are used in a variety of applications, such as image processing and data compression.

4. How are eigenvalues and eigenvectors used in differential equations?

Eigenvalues and eigenvectors are used to solve systems of linear differential equations. By converting a system of differential equations into a matrix form, the eigenvalues and eigenvectors can be used to find the general solution of the system.

5. Can eigenvalues and eigenvectors be complex numbers?

Yes, eigenvalues and eigenvectors can be complex numbers. This is especially common in quantum mechanics, where the eigenvalues represent the possible energies of a system and can have both real and imaginary components.

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