Solution to a Matrix Quadratic Equation

In summary, a matrix quadratic equation is an extended form of a quadratic equation where the coefficients are matrices and x is a variable. The solution to a matrix quadratic equation is the value(s) of x that make the equation true, and it can have up to two solutions, which can be matrices. To solve a matrix quadratic equation, various methods such as factoring, completing the square, or using the quadratic formula can be used, with proper matrix operations. These equations have real-life applications in fields such as physics, engineering, and computer science, for modeling and solving problems involving motion, optimization, and 3D transformations.
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Euge
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Let ##A## be a complex nilpotent ##n\times n##-matrix. Show that there is a unique nilpotent solution to the quadratic equation ##X^2 + 2X = A## in ##M_n(\mathbb{C})##, and write the solution explicitly (that is, in terms of ##A##).
 
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[tex](X+E)^2=A+E[/tex]
[tex]X=(A+E)^{1/2}-E[/tex]
But I am not certain that any matrix has its "square root".
 
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To be clearer, the solution should be expressed as a polynomial in ##A##.
 
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We are given that [itex]A^k = 0[/itex] for some minimal [itex]0 < k \leq n[/itex]. So we need a polynomial [tex]
p(A) = \sum_{r=0}^{k-1} a_rA^r[/tex] such that [tex]
p(A)^2 = \sum_{r=0}^{k-1} A^r \left(\sum_{s=0}^{r} a_sa_{r-s}\right) = A + I.[/tex] Hence [tex]
X = (a_0 - 1)I + \frac{1}{2a_0}A + \dots[/tex] where [itex]a_0 = \pm 1[/itex]. That gives two solutions, so we need to show that only one is nilpotent; I suspect the one with [itex]a_0 = 1[/itex] since then [tex]
X^k = (\tfrac12 A + \dots)^k = \tfrac{1}{2^k} A^k + \dots = 0[/tex] whereas with [itex]a_0 = -1[/itex], [tex]
X^r = (-2I + \dots)^r = (-2)^rI + \dots[/tex] which does not appear to be zero for any [itex]r[/itex].
 
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  • #5
anuttarasammyak said:
[tex](X+E)^2=A+E[/tex]
[tex]X=(A+E)^{1/2}-E[/tex]
But I am not certain that any matrix has its "square root".
I think you can just take

\begin{align*}
X = \pm (I + A)^{1/2} - I
\end{align*}

and expand the ##(I + A)^{1/2}##. It convergences because ##A## is nilpotent.

Then you can use that the eigenvalues of ##-(I + A)^{1/2} - I## are non-zero implying it is not nilpotent. The nilpotent solution, for ##A^k=0##, is:

\begin{align*}
X & = \sum_{r=1}^{k-1} (-1)^{r-1} \dfrac{(2r)!}{(2r-1) (2^r r!)^2} A^r
\nonumber \\
& = \frac{A}{2} - \frac{A^2}{8} + \frac{A^3}{16} - \frac{5A^4}{128} + \cdots + (-1)^k \dfrac{(2k-2)!}{(2k-3) (2^{k-1} (k-1)!)^2} A^{k-1}
\end{align*}

You can check this. Say ##A^2=0##, so that ##X=a_0 I + a_1 A##, then:

\begin{align*}
(a_0 I + a_1 A)^2 + 2 (a_0 I + a_1 A) = A
\end{align*}
or
\begin{align*}
(a_0^2+2a_0) I + 2 a_1 (a_0 + 1) A = A
\end{align*}
so that
\begin{align*}
(a_0^2+2a_0) =0 , \quad 2 a_1 (a_0 + 1) = 1 .
\end{align*}
Implying ##a_0=-2 , a_1= -\frac{1}{2}## or ##a_0=0 , a_1= \frac{1}{2}##.

Say ##A^3=0##, so that ##X=a_0 I + a_1 A + a_2 A^2##, then:

\begin{align*}
(a_0 I + a_1 A + a_2 A^2)^2 + 2 (a_0 I + a_1 A + a_2 A^3) = A
\end{align*}
or
\begin{align*}
(a_0^2+2a_0) I + 2 a_1 (a_0 + 1) A + (a_1^2 + 2a_0 a_2 + 2 a_2) A^2 = A
\end{align*}
so that
\begin{align*}
(a_0^2+2a_0) =0 , \quad 2 a_1 (a_0 + 1) = 1 , \quad a_1^2 + 2a_0 a_2 + 2 a_2= 0 .
\end{align*}
Implying ##a_0=-2 , a_1= -\frac{1}{2} , a_2 = \frac{1}{8}## or ##a_0=0 , a_1= \frac{1}{2} , a_2 = -\frac{1}{8}##.

The conditions you get on ##a_0,a_1, \dots, a_{k-1}## are the same conditions you would get by plugging ##\alpha = \sum_{r=0}^\infty a_r x^r## into

\begin{align*}
\alpha^2 + 2 \alpha = x
\end{align*}

and considering terms of powers up to ##x^{k-1}## on the LHS. This is why the approach of plugging ##X=\sum_{r=0}^{k-1} a_r A^r## into ##X^2 + 2X = A## will give the same answer as expanding ##\pm (I + A)^{1/2} - I##.
 
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1. What is a solution to a matrix quadratic equation?

A solution to a matrix quadratic equation is a set of values that satisfies the equation when substituted into the variables. In matrix form, it is written as AX^2 + BX + C = 0, where A, B, and C are matrices, X is a variable matrix, and 0 is the zero matrix.

2. How do you solve a matrix quadratic equation?

To solve a matrix quadratic equation, you can use various methods such as factoring, completing the square, or using the quadratic formula. The method used will depend on the specific equation and the given matrices.

3. Can a matrix quadratic equation have multiple solutions?

Yes, a matrix quadratic equation can have multiple solutions. This is because matrices can have multiple values that satisfy the equation, unlike regular quadratic equations with only one solution.

4. What is the significance of solving a matrix quadratic equation?

Solving a matrix quadratic equation is important in various fields of science and mathematics, such as physics, engineering, and computer science. It allows us to find solutions to complex problems involving matrices and can help in making predictions and solving real-world problems.

5. Are there any special cases when solving a matrix quadratic equation?

Yes, there are special cases when solving a matrix quadratic equation. One example is when the determinant of the matrix A is equal to 0, which results in a singular matrix and makes the equation unsolvable. Another case is when the matrix equation has complex solutions, which can occur when the matrices involved have complex numbers.

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