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

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Homework Help Overview

The discussion revolves around the diagonalization of a matrix A, specifically focusing on finding its eigenvalues and corresponding eigenvectors, constructing the matrix P that diagonalizes A, and verifying the relationship A = PDP-1. The subject area is linear algebra, particularly eigenvalues and eigenvectors.

Discussion Character

  • Exploratory, Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • The original poster attempts to find eigenvalues and eigenvectors, noting confusion regarding the construction of matrix P and its validity in the equation AP = PD. Some participants question the correctness of the identified eigenvectors and suggest reviewing the calculations for accuracy.

Discussion Status

Participants are actively engaging in clarifying the eigenvector calculations and addressing potential errors in the original poster's approach. There is a recognition of differing interpretations regarding the eigenvectors, and some guidance has been offered to reconsider the calculations based on the eigenvalue equations.

Contextual Notes

There is a mention of confusion regarding the eigenvector corresponding to the eigenvalue of 1 and the implications of the matrix structure affecting the identification of valid eigenvectors. The original poster also notes a challenge with the top row of matrix P being all zeros, complicating the inversion process.

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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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[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].
 
Show us how you found the eigenvectors because only one actually is correct.
 
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.
 
jbunniii said:
Both [itex]v_1[/itex] and [itex]v_2[/itex] are correct, actually.
Apparently, I can't add. :)
 
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.
 
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?
 

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