031 Review Part 3, Problem 1

(a) Is the matrix  $A={\begin{bmatrix}3&1\\0&3\end{bmatrix}}$  diagonalizable? If so, explain why and diagonalize it. If not, explain why not.

(b) Is the matrix  $A={\begin{bmatrix}2&0&-2\\1&3&2\\0&0&3\end{bmatrix}}$  diagonalizable? If so, explain why and diagonalize it. If not, explain why not.

Foundations:
Recall:
1. The eigenvalues of a triangular matrix are the entries on the diagonal.
2. By the Diagonalization Theorem, an  $n\times n$  matrix  $A$  is diagonalizable
if and only if  $A$  has  $n$  linearly independent eigenvectors.

Solution:

(a)

Step 1:
To answer this question, we examine the eigenvalues and eigenvectors of  $A.$
Since  $A$  is a triangular matrix, the eigenvalues are the entries on the diagonal.
Hence, the only eigenvalue of  $A$  is  $3.$

Step 2:
Now, we find a basis for the eigenspace corresponding to  $3$  by solving  $(A-3I){\vec {x}}={\vec {0}}.$
We have
${\begin{array}{rcl}\displaystyle {A-3I}&=&\displaystyle {{\begin{bmatrix}3&1\\0&3\end{bmatrix}}-{\begin{bmatrix}3&0\\0&3\end{bmatrix}}}\\&&\\&=&\displaystyle {{\begin{bmatrix}0&1\\0&0\end{bmatrix}}.}\end{array}}$
Solving this system, we see  $x_{1}$  is a free variable and  $x_{2}=0.$
Therefore, a basis for this eigenspace is
${\bigg \{}{\begin{bmatrix}1\\0\end{bmatrix}}{\bigg \}}.$

Step 3:
Now, we know that  $A$  only has one linearly independent eigenvector.
By the Diagonalization Theorem,  $A$  must have  $2$  linearly independent eigenvectors to be diagonalizable.
Hence,  $A$  is not diagonalizable.

(b)

Step 1:

Step 2:

Final Answer:
(a)     $A$  is not diagonalizable.
(b)

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