MHB MHBCalculate A^17: Powers of Matrices

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Hello MHB,
Calculate $$A^{17}$$ where
f3c5619c04a59ddc1718baa948968b1.png
.

Progress,
I have multiplicate without adding them together to see a pattern and I can se at $$A^{17}$$ on that matrice where it's 6's it will be $$6^{17}$$ and rest I can't se any pattern those riight side of the triangle, cause the left will be zero

Regards,
 
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Petrus said:
Hello MHB,
Calculate $$A^{17}$$ where
f3c5619c04a59ddc1718baa948968b1.png
.

Progress,
I have multiplicate without adding them together to see a pattern and I can se at $$A^{17}$$ on that matrice where it's 6's it will be $$6^{17}$$ and rest I can't se any pattern those riight side of the triangle, cause the left will be zero

Regards,

Cayley Hamilton theorem might be useful. Cayley
 
A little exploration shows:

If A = \left( \begin{array}{ccc}<br /> a &amp; 1 &amp; 0 \\<br /> 0 &amp; a &amp; 1 \\<br /> 0 &amp; 0 &amp; a \end{array} \right)

Then A^{17} = \left( \begin{array}{ccc}<br /> a^{17} &amp; 17a^{16} &amp; 8\cdot 17\cdot a^{15} \\<br /> 0 &amp; a^{17} &amp; 17a^{16} \\<br /> 0 &amp; 0 &amp; a^{17} \end{array} \right)

Upper triangular with only '1' off the diagonal? That HAS to be rather tractable.
 
In general, if we have a Jordan block $J(\lambda)$ of order $n$ we can express $$J(\lambda)=\begin{bmatrix} \lambda & 1 & 0 &\ldots & 0 & 0 & 0\\ 0 & \lambda & 1 &\ldots & 0&0&0 \\0 & 0 & \lambda &\ldots & 0&0&0 \\\vdots&&&&&&\vdots \\ 0 &0 & 0 &\ldots & \lambda & 1&0\\0 &0 &0 &\ldots &0&\lambda & 1\\0 & 0 &0&\ldots & 0&0&\lambda\end{bmatrix}=\lambda I+N$$ where $N$ is nilpotent of order $n$. As $(\lambda I_n)N=N(\lambda I_n)$, we can apply the binomial theorem $$J(\lambda)^m=(\lambda I+N)^m=(\lambda I)^{m}+\binom{m}{1}(\lambda I)^{m-1}N+\binom{m}{2}(\lambda I)^{m-2}N^2+\ldots\\=\lambda^mI+m\lambda^{m-1} N+\frac{m(m-1)}{2}\lambda^{m-2}N^2+\ldots$$ If $n=3$, $N$ is nilpotent of order $2$: $$N=\begin{bmatrix}{0}&{1}&{0}\\{0}&{0}&{1}\\{0}&{0}&{0}\end{bmatrix},N^2=\begin{bmatrix}{0}&{0}&{1}\\{0}&{0}&{0}\\{0}&{0}&{0}\end{bmatrix},N^3=0$$ $$J(\lambda)^m=\lambda^mI+m\lambda^{m-1} N+\frac{m(m-1)}{2}\lambda^{m-2}N^2$$ $$\begin{bmatrix}{\lambda}&{1}&{0}\\{0}&{\lambda}&{1}\\{0}&{0}&{\lambda}\end{bmatrix}^m=\lambda^m \begin{bmatrix}{1}&{0}&{0}\\{0}&{1}&{0}\\{0}&{0}&{1}\end{bmatrix}+m\lambda^{m-1}\begin{bmatrix}{0}&{1}&{0}\\{0}&{0}&{1}\\{0}&{0}&{0}\end{bmatrix}+\frac{m(m-1)}{2}\lambda^{m-2}\begin{bmatrix}{0}&{0}&{1}\\{0}&{0}&{0}\\{0}&{0}&{0}\end{bmatrix}$$ $$=\begin{bmatrix}{\lambda^m}&{m\lambda^{m-1}}&{\frac{m(m-1)}{2}}\lambda^{m-2}\\{0}&{\lambda^m}&{m\lambda^{m-1}}\\{0}&{0}&{\lambda^m}\end{bmatrix}$$
 
Thread 'How to define a vector field?'
Hello! In one book I saw that function ##V## of 3 variables ##V_x, V_y, V_z## (vector field in 3D) can be decomposed in a Taylor series without higher-order terms (partial derivative of second power and higher) at point ##(0,0,0)## such way: I think so: higher-order terms can be neglected because partial derivative of second power and higher are equal to 0. Is this true? And how to define vector field correctly for this case? (In the book I found nothing and my attempt was wrong...

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