031 Review Part 3, Problem 5

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Find a formula for    by diagonalizing the matrix.


Foundations:  
Recall:
1. To diagonalize a matrix, you need to know the eigenvalues of the matrix.
2. Diagonalization Theorem
An    matrix    is diagonalizable if and only if    has    linearly independent eigenvectors.
In fact,    with    a diagonal matrix, if and only if the columns of    are    linearly
independent eigenvectors of    In this case, the diagonal entries of    are eigenvalues of    that
correspond, respectively , to the eigenvectors in  Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle P.}


Solution:

Step 1:  
To diagonalize this matrix, we need to find the eigenvalues and a basis for each eigenspace.
First, we find the eigenvalues of    by solving  
       
Therefore, setting
Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle (\lambda +2)(\lambda +3)=0,}  
we find that the eigenvalues of    are    and  
Step 2:  
Now, we find a basis for each eigenspace by solving  Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle (A-\lambda I){\vec {x}}={\vec {0}}}   for each eigenvalue  
For the eigenvalue  Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle \lambda =-2,}   we have

       

We see that    is a free variable. So, a basis for the eigenspace corresponding to    is
Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle {\bigg \{}{\begin{bmatrix}2\\1\\\end{bmatrix}}{\bigg \}}.}
Step 3:  
For the eigenvalue  Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle \lambda =-3,}   we have

       Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle {\begin{array}{rcl}\displaystyle {A+3I}&=&\displaystyle {{\begin{bmatrix}1&-6\\2&-6\end{bmatrix}}-{\begin{bmatrix}3&0\\0&3\end{bmatrix}}}\\&&\\&=&\displaystyle {\begin{bmatrix}4&-6\\2&-3\end{bmatrix}}\\&&\\&\sim &\displaystyle {{\begin{bmatrix}1&{\frac {-3}{2}}\\0&0\end{bmatrix}}.}\end{array}}}

We see that    is a free variable. So, a basis for the eigenspace corresponding to    is
Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle {\bigg \{}{\begin{bmatrix}{\frac {3}{2}}\\1\\\end{bmatrix}}{\bigg \}}.}
Step 4:  
To diagonalize our matrix, we use the information from the steps above.

Using the Diagonalization Theorem, we have  Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle A=PDP^{-1}}   where

Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle D={\begin{bmatrix}-2&0\\0&-3\end{bmatrix}},P={\begin{bmatrix}2&{\frac {3}{2}}\\1&1\end{bmatrix}}.}
Step 5:  
Notice that

       


Final Answer:  
       Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. Server problem."): {\displaystyle {\begin{bmatrix}2(-2)^{k+1}+3(-3)^{k}&6(-2)^{k}+-6(-3)^{k}\\(-2)^{k+1}+2(-3)^{k}&3(-2)^{k}+(-4)(-3)^{k}\end{bmatrix}}}       

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