# Linear Algebra/Characteristic Equation

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The matrix definition of an eigen value is very useful since it allows us to find eigen values for a given matrix using the following theorem:

$\lambda$ is an eigen value of $A$ iff $det(A-\lambda I_{n}v)=0.$ Proof:

If $Av=\lambda v$ then

$\Rightarrow Av=\lambda I_{n}v$ $\Rightarrow Av-\lambda I_{n}v=0$ $\Rightarrow (A-\lambda I_{n})v=0$ but since $v$ is non-zero we know that $(A-\lambda I_{n})$ is singular, ie it's determinant is zero so an eigen value of A will satisfy the equation

$det(A-\lambda I_{n}v)=0.$ which is known as the characteristic equation. (haven't proved the converse, but this is not required when calculating eigenvalues).

In the case $A$ is a $2x2$ matrix, this equation leads to the characteristic polynomial :

$det({\begin{bmatrix}a_{11}&a_{12}\\a_{21}&a_{22}\end{bmatrix}}-\lambda {\begin{bmatrix}1&0\\0&1\end{bmatrix}})=0$ $\Rightarrow det({\begin{bmatrix}a_{11}&a_{12}\\a_{21}&a_{22}\end{bmatrix}}-{\begin{bmatrix}\lambda &0\\0&\lambda \end{bmatrix}})=0$ $\Rightarrow det{\begin{bmatrix}a_{11}-\lambda &a_{12}\\a_{21}&a_{22}-\lambda \end{bmatrix}}=0$ $\Rightarrow (a_{11}-\lambda )(a_{22}-\lambda )-a_{21}a_{12}=0$ $\Rightarrow \lambda ^{2}-(a_{11}+a_{22})\lambda +a_{11}a_{22}-a_{12}a_{21}=0$ This is simply a quadratic equation and the roots of this are the eigen values of $A$ In order to find the corresponding eigen vectors, we simply solve the equation $Av=\lambda v$ which will be two simultaneous equations. There will in fact be infinitely many solutions to this equation since any scalar multiple of an eigen vector is also an eigen vector.