MHB Shelby's question at Yahoo Answers (Finding P with P^{-1}AP=D)

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The discussion centers on solving a linear algebra problem involving a specific 3x3 matrix A. The characteristic polynomial is computed as χ(λ) = (-λ + 2)(λ + 1)², leading to eigenvalues of λ = 2 (simple) and λ = -1 (double). Corresponding eigenvectors are found, with a basis for the eigenspace of λ = 2 being B₂ = {(1, 1, 1)} and for λ = -1 being B₋₁ = {(-1, 1, 0), (-1, 0, 1)}. Finally, the diagonal matrix D and the invertible matrix P are provided, confirming that D = P⁻¹AP holds true. This analysis effectively demonstrates the process of diagonalization for the given matrix A.
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Here is the question:

Let A be the real 3x3-matrix A =
0 1 1
1 0 1
1 1 0

(a) Compute the characteristic polynomial of A.
(b) Compute the eigenvalues of A.
(c) Compute the corresponding eigenvectors.
(d) Give a diagonal matrix D and an invertible matrix P such that D = (P^-1)AP.

Here is a link to the question:

Eigenvalues and eigenvectors question? - Yahoo! Answers

I have posted a link there to this topic so the OP can find my response.
 
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Hello Shelby,

$(a)$ Using the transformations $R_2\to R_2-R_1$, $R_3\to R_3-R_1$ and $C_1\to C_1+C_2+C_3$ we get the characteistic polynomial: $$\begin{aligned}
\chi(\lambda)&=\begin{vmatrix}{-\lambda}&{\;\;1}&{\;\;1}\\{\;\;1}&{-\lambda}&{\;\;1}\\{\;\;1}&{\;\;1}&{-\lambda}\end{vmatrix}\\&=\begin{vmatrix}{-\lambda}&{\;\;1}&{\;\;1}\\{\;\;1+\lambda}&{-\lambda}-1&{\;\;0}\\{\;\;1+\lambda}&{\;\;0}&{-\lambda-1}\end{vmatrix}\\&=\begin{vmatrix}{-\lambda+2}&{\;\;1}&{\;\;1}\\{\;\;0}&{-\lambda}-1&{\;\;0}\\{\;\;0}&{\;\;0}&{-\lambda-1}\end{vmatrix}\\&=(-\lambda+2)(\lambda+1)^2
\end{aligned}$$ $(b)$ Eigenvalues: $(-\lambda+2)(\lambda+1)^2=0$, so we get $\lambda=2$ (simple) and $\lambda=-1$ (double).
$(c)$ The eigenvectors are: $$\ker (A-2I)\equiv \left \{ \begin{matrix}-2x_1+x_2+x_3=0\\x_1-2x_2+x_3=0\\x_1+x_2-2x_3=0\end{matrix}\right. $$ As $\lambda=2$ is simple, $\dim(\ker(A-2I))=1$ and easily we find a basis of this eigenspace: $B_2=\{(1,1,1)\}$. On the other hand: $$\ker (A+I)\equiv \left \{ \begin{matrix}x_1+x_2+x_3=0\\x_1+x_2+x_3=0\\x_1+x_2+x_3=0\end{matrix}\right.$$ Now, $\dim(\ker(A+I))=3-\mbox{rank }(A+I)=3-1=2$ and easily we find a basis of this eigenspace: $B_{-1}=\{(-1,1,0),(-1,0,1)\}$.

$(d)$ As a consequence of $(c)$:
$$D=\begin{bmatrix}{2}&{\;\;0}&{\;\;0}\\{0}&{-1}&{\;\;0}\\{0}&{\;\;0}&{-1}\end{bmatrix}\;,\quad P=\begin{bmatrix}{1}&{-1}&{-1}\\{1}&{\;\;1}&{\;\;0}\\{1}&{\;\;0}&{\;\;1} \end{bmatrix}$$ We can verify the result proving that $AP=PD$ (which implies $P^{-1}AP=D$).
 
Here is a little puzzle from the book 100 Geometric Games by Pierre Berloquin. The side of a small square is one meter long and the side of a larger square one and a half meters long. One vertex of the large square is at the center of the small square. The side of the large square cuts two sides of the small square into one- third parts and two-thirds parts. What is the area where the squares overlap?

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