A rigid motion of $\mathbb {R^{n}}$ is a map
$M = T ◦ R : \mathbb {R^{n}} \to \mathbb {R^{n}}$
where $ \mathbb {R^{n}} \to \mathbb {R^{n}} $ is linear and satisfies $|R(v)| = |v| \space \space \space \space \space \space ∀v \in \mathbb {R^{n}}$
And T : $ \mathbb {R^{n}} \to \mathbb {R^{n}} $ is translation, i.e. there exists $ w \in \mathbb {R^{n}}$ such that $T (v) = v + w$ $\space \space \space \space \space∀v \in \mathbb {R^{n}} $
Argue that the function R is represented by a matrix $ R(v) = A(v)$ where A is n x n and satisfies $ A^T A = I $
Im not really familiar with rotational mappings but in Dynamical Systems we used rotational and translation matrices to move solutions around.
How do i argue that a rotational map is the same thing as a rotation matrix?
Let $R$ be the map and $e_1,e_2,\dots,e_n$ be the standard basis. We have that $\langle R(e_j),R(e_j)\rangle=1$ for all $j$.
We also have $\sqrt{2}=||e_i+e_j||=||R(e_i+e_j)||=\sqrt{R(e_i+e_j),R(e_i+e_j)\rangle}=\sqrt{\langle R(e_i),R(e_i)\rangle +\langle R(e_j),R(e_j)\rangle +2\langle R(e_i),R(e_j)\rangle}$.
This implies that $\langle e_i, e_j\rangle=0$ if $i\neq j$ and $1$ if $i=j$.
Now notice that the element $i,j$ of the matrix $R^tR$ is equal to $\langle e_i,e_j\rangle$, so we are good to go.