Diagonalizing Matrix A: Eigenvalues, Eigenvectors, Matrix P & D

In summary, the conversation is discussing how to find the eigenvalues and corresponding eigenvectors of a given matrix A, as well as finding the matrix P that diagonalizes A. There is confusion about finding the diagonal matrix D and the orthogonal matrix P. The correct eigenvectors are v1 = [0, -1, 1] and v2 = [0, 1, 0].
  • #1
xicor
37
0

Homework Statement



[tex]
A=\left[\begin{array}{ccc}1 & 0 & 0\\ 0 & 1 & -1\\ 0 & 0 & 2\end{array}
[/tex]

a) Find the eigenvalues and corresponding eigenvectors of matrix A.
b)Find the matrix P that diagonalizes A.
c)Find the diagonal matrix D suh that A = PDP-1, and verify the equality.
d) Find the orthogonal matrix P that diagonalizes A.
e) Compute A4

Homework Equations



A = PDP-1,
AP = DP
A-I[tex]\lambda[/tex] = 0

The Attempt at a Solution



First I started by finding the eigenvalues values where [tex]\lambda[/tex]=1 multipity two, 2. After this I tried finding the eigenvectors that form P and got v1=[0,-1,1] from [tex]\lambda[/tex]=2 , and {v2, v3} = {[0, 1, 0], [0, 0, 1]}. From this I constructed the P matrix and got [tex]
P=\left[\begin{array}{ccc}0 & 0 & 0\\ -1 & 1 & 0\\ 1 & 0 & 1\end{array}
[/tex] and [tex]
D=\left[\begin{array}{ccc}2 & 0 & 0\\ 0 & 1 & 0\\ 0 & 0 & 1\end{array}
[/tex] and this is where I get confused. The P matrix doesn't work in the form AP = PD and you can't find the inverse of P since the top row is all zeros. Once I figure this out, parts d and e should be straight-forward. Can someone point me to where I'm making a mistake here please. Thanks to everybody who helps.
 
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  • #2
[itex]v_3 = [0, 0, 1][/itex] is not an eigenvector corresponding to [itex]\lambda = 1[/itex]. Just perform the multiplication to see that [itex]A v_3 \neq v_3[/itex].
 
  • #3
Show us how you found the eigenvectors because only one actually is correct.
 
  • #4
vela said:
Show us how you found the eigenvectors because only one actually is correct.

Both [itex]v_1[/itex] and [itex]v_2[/itex] are correct, actually.
 
  • #5
jbunniii said:
Both [itex]v_1[/itex] and [itex]v_2[/itex] are correct, actually.
Apparently, I can't add. :)
 
  • #6
Alright, then there is something I'm possibly missing about eigenvectors. The first eigenvector was found by plugging [tex]\lambda[/tex] = 2 into the (A - I[tex]\lambda[/tex]) matrix producing [tex]
\begin{bmatrix}-1 & 0 & 0 \\ 0 & -1 & -1 \\ 0 & 0 & 0\end{bmatrix}
[/tex] which gives the equations x1 = 0 and x2 = -x3 and constructing the vector from x3 gives x3[0, -1, 1] where the first eigenvector v1 = [0, -1, 1]. I then used the other eigenvalue [tex]\lambda[/tex] = 1 and found the matrix [tex]
\begin{bmatrix}0 & 0 & 0 \\ 0 & 0 & -1 \\ 0 & 0 & 1\end{bmatrix}
[/tex] and the way I'm interpreting the book's reasoning for dealing with these matrixes, the eigenvectors that form would be x2[0, 1, 0] + x3[0, 0, 1] which are also the eigenvectors. Clearly there is something different I need to do when dealing with this kind of matrix.
 
  • #7
The matrix you got for the eigenvalue equal to 1 gives you the equation x3=0. It doesn't tell you anything about the other components. Do you see what the other eigenvector should be now?
 

1. What is the purpose of diagonalizing a matrix?

Diagonalizing a matrix is a process used to simplify the calculations involving matrices. It transforms a matrix into a diagonal matrix, which makes it easier to perform operations such as multiplication and finding powers.

2. What are eigenvalues and eigenvectors?

Eigenvalues are scalar values that represent how a linear transformation changes the magnitude of a vector. Eigenvectors are the corresponding vectors that are only scaled by the eigenvalues, without changing their direction.

3. How do you find the eigenvalues and eigenvectors of a matrix?

To find the eigenvalues and eigenvectors of a matrix, you need to solve the characteristic equation (det(A-λI)=0), where A is the original matrix and λ is the eigenvalue. The eigenvectors can then be found by plugging in the eigenvalues into the equation (A-λI)v=0 and solving for v.

4. What is the significance of matrix P and D in diagonalizing a matrix?

Matrix P is the matrix of eigenvectors, and matrix D is the diagonal matrix of eigenvalues. The product of P and D gives the diagonalized form of the original matrix A. This is significant because it simplifies the calculations involving A, making it easier to analyze and perform operations on.

5. Can any matrix be diagonalized?

Not all matrices can be diagonalized. A matrix can only be diagonalized if it has n linearly independent eigenvectors, where n is the size of the matrix. If a matrix does not have n linearly independent eigenvectors, it is considered to be defective and cannot be diagonalized.

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