Find $k^{th}$ power of a square matrix

Question

I am trying to find the $A^{k}$, for all $k \geq 2$ of a matrix, \begin{pmatrix} a & b \\ 0 & 1 \end{pmatrix}

My approach:

$A^{2}=\begin{pmatrix} a^2 & ab+b \\ 0 & 1 \end{pmatrix}$

$A^{3}=\begin{pmatrix} a^3 & a^{2}b+ab+b \\ 0 & 1 \end{pmatrix}$

$A^{4}=\begin{pmatrix} a^4 & a^{3}b+a^{2}b+ab+b \\ 0 & 1 \end{pmatrix}$

$A^{5}=\begin{pmatrix} a^5 & a^{4}b+a^{3}b+a^{2}b+ab+b \\ 0 & 1 \end{pmatrix}$

Continuing this way, we obtain

$A^{k}=\begin{pmatrix} a^k & (a^{k-2}+a^{k-3}+a^{k-4}+.....+1)b \\ 0 & 1 \end{pmatrix}$

I am stuck here! I was wondering if you could give me some hints to move further. I appreciate your time.

Answer 1

Hint: Write $A=D+B$ here $D$ is diagonal. Use that $B^2=0$, $DB=aB$, $BD=B$.

Answer 2

Hint: Use Cayley–Hamilton: $A^2-(a+1)A+aI=0$.

Answer 3

To add on to lhf's hints, do you know induction? If so, try to find patterns in each of the 4 entries individually once you have corrected your examples.

Answer 4

Writing $A^n$ as $\begin{bmatrix}a^n & b_n\\ 0 & 1\end{bmatrix}$. Expanding $A^{n+1} = AA^n$ leads to a recurrence relation of the form: $$b_{n+1} = a b_n + b$$ Since $b_1 = b$, solving the recurrence relation will lead to $$b_n = (a^{n-1}+ a^{n-2} + \cdots + 1)b = \begin{cases} \frac{a^n-1}{a-1} b, & a \ne 1\\ nb, & a = 1\end{cases}$$

Answer 5

Not the best way, but you could also try diagonalisation. The caveat with diagonalisation is that for certain values of $a$ and $b$ (in particular, if $a = 1$ and $b \neq 0$), the matrix won't be diagonalisable. However, if we make the assumption that $a \neq 1$, then we should end the process with a perfectly valid expression for $A^n$ that will work for all $a \neq 1$, and by continuity, we can conclude that it works for $a = 1$ too (or take the formula, and prove by induction).

Also, I know you want hints, so I hid everything behind spoiler boxes.

The eigenvalues are $1$ and $a$, and we will assume they are different. We have,

$$A - I = \begin{pmatrix} a - 1 & b \\ 0 & 0 \end{pmatrix},$$

with eigenvector $(-b, a - 1)$. Also,

$$A - aI = \begin{pmatrix} 0 & b \\ 0 & 1 - a \end{pmatrix},$$

with eigenvector $(1, 0)$. So, let

$$P = \begin{pmatrix} 1 & -b \\ 0 & a - 1\end{pmatrix},$$

giving us

$$P^{-1} = \frac{1}{a - 1}\begin{pmatrix} a - 1 & b \\ 0 & 1\end{pmatrix}.$$

We should have

$$A = P\begin{pmatrix} a & 0 \\ 0 & 1\end{pmatrix}P^{-1},$$

so

$$\begin{align*} A^n &= P\begin{pmatrix} a^n & 0 \\ 0 & 1\end{pmatrix}P^{-1} \\ &= \frac{1}{a - 1}\begin{pmatrix} 1 & -b \\ 0 & a - 1\end{pmatrix}\begin{pmatrix} a^n & 0 \\ 0 & 1\end{pmatrix}\begin{pmatrix} a - 1 & b \\ 0 & 1\end{pmatrix} \\ &= \frac{1}{a - 1}\begin{pmatrix} 1 & -b \\ 0 & a - 1\end{pmatrix}\begin{pmatrix} a^{n+1} - a^n & ba^n \\ 0 & 1\end{pmatrix} \\ &= \frac{1}{a - 1}\begin{pmatrix} a^{n+1} - a^n & ba^n - b \\ 0 & a - 1\end{pmatrix} \\ &= \begin{pmatrix} a^n & b \frac{a^n - 1}{a - 1} \\ 0 & 1\end{pmatrix} \\ &= \begin{pmatrix} a^n & b(1 + a + a^2 + \ldots + a^{n-1}) \\ 0 & 1\end{pmatrix}.\end{align*}$$

That last formula must hold (at least) for $a \neq 1$, but due to the continuity of matrix powers, it must also hold at $a = 1$ too.

Answer 6

I'm partial to the SVD for this. The eigenvalues are $a$ and $1$ associated with eigenvectors $(1,0)$ and $(b,1-a)$ respectively.

So, we get

$$\begin{bmatrix} a & b \\ 0 & 1 \end{bmatrix}^n= \begin{bmatrix} 1 & b \\ 0 & 1-a \end{bmatrix} \begin{bmatrix} a^n & 0 \\ 0 & 1 \end{bmatrix} \begin{bmatrix} 1 & \frac{-b}{1-a} \\ 0 & \frac{1}{1-a} \end{bmatrix} = \begin{bmatrix} a^n & \frac{b(1-a^n)}{1-a} \\ 0 & 1 \end{bmatrix}$$