I know how to find out the the minimal polynomial for a given matrix. But I am stuck to do the reverse process. For example how to find out a $3\times3$ matrix, whose minimal polynomial is $x^2$.
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6Companion matrices? – Angina Seng Dec 09 '17 at 13:29
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@LordSharktheUnknown Yes, that hits the nail on the head. – Peter Dec 09 '17 at 13:30
2 Answers
For a general monic polynomial $p(x)=a_0+a_1x+a_2x^2+\cdots +a_{n-1}x^{n-1}+x^n$ there is the so called companion matrix which looks like this
$$ C_p:=\begin{pmatrix} 0&-a_0 \\ I & -\mathfrak a \end{pmatrix} $$
where $I$ is the $(n-1)\times (n-1)$ identity matrix and $\mathfrak a=(a_1,...,a_{n-1})^\top$. $C_p$ is of dimensions $n\times n$ and has the characteristic and minimal polynomial equal to $p$.
Example. Let's take your example $p(x)=x^2$. We write this polynomial in the form
$$p(x)=x^2=0+0\cdot x+1\cdot x^2.$$
We have $a_0=0$ and $\mathfrak a=(0)^\top$. Because $n=2$, this will give us a $2\times 2$ companion matrix
$$C_p=\begin{pmatrix}0&0\\1&0\end{pmatrix}.$$
We can boost this onto a $3\times 3$ matrix by adding a zero line and a zero column:
$$C_p^{3\times 3}=\begin{pmatrix}0&0&\color{lightgray}0\\1&0&\color{lightgray}0\\\color{lightgray}0&\color{lightgray}0&\color{lightgray}0\end{pmatrix}.$$
The charcteristic polynomial will be $-x^3$, but it is not hard to see that the minimal polynomial is still $x^2$ as $[C_p^{3\times 3}]^2=0$.
Fun fact
From what I learned in my lectures on numerical mathematics, we have much better (faster, more stable, ...) algorithms for computing eigenvalues of matrices than for computing roots of polynomials directly. Therefore, in order to compute the roots of a polynomial $p$, we instead create the matrix $C_p$ and use our eigenvalue finding algorithms for these. These eigenvalues are exactly the roots of $p$.
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These eigenvalues are exactly the roots of $p$ well not exactly but they are more accurate. – percusse Dec 10 '17 at 00:47
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Numerically they are also prone to errors. Companion matrices often are also ill-conditioned with respect to eigenvalue but still way better than handling polynomials.There are many alternatives such as Fiedler matrices that are actively researched: One of the google hits : https://blogs.mathworks.com/cleve/2013/12/23/fiedler-companion-matrix/ – percusse Dec 10 '17 at 11:59
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Let's say the matrix you are looking for is $A$. Then, by definition, $p(x)=x^2$ is the smallest monic polynomial such that $p(A) = 0$ . So you need to find a matrix which fullfills this equation.
This will be a good candidate for example:
\begin{align}
A =
\begin{pmatrix}
0 & 0 & 1 \\
0 & 0 & 0 \\
0 & 0 & 0
\end{pmatrix}
\end{align}
You can check that indeed $p(A) = A^2 = 0$ . No polynomial $q(x)$ of smaller degree can have $q(A) = 0$, since it yould have to be of degree $1$ .
$$
q(x) = q_1 x + q_0 ~~~~~ \text{with}~~~~~ q_1 \neq 0
$$
However
$$
q(A) = q_1 A + q_0 =
\begin{pmatrix}
q_0 & 0 & q_1 \\
0 & q_0 & 0 \\
0 & 0 & q_0
\end{pmatrix}
\neq 0
$$
So $x^2$ is indeed the minimal polynomial of $A$ .
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