Let $V = R[X]_{≤3}$ and $α ∈ R$. Define the linear image $ L : V → V$ given by $L(P(X)) = αP(X) + (X + 1)P'(X)$.
Proof that $L$ diagonalizable and determine the matrix $L$ with respect to a basis of eigenvectors.
I have found this matrix:
$$L=\begin{bmatrix}\alpha&1&0&0\\\ 0&1+\alpha&2&0\\0&0&2+\alpha&3\\0&0&0&3+\alpha\end{bmatrix}.$$ I used the standard basis {${1,x,x^2,x^3}$}
Then you know the eigenvalues are $\alpha, 1+\alpha, 2+\alpha$ and $3+\alpha$ with respectively the eigenspaces $(1,0,0,0),(0,1,0,0),(0,0,1,0),(0,0,0,1)$ and because every $d(\lambda)=m(\lambda)$ we know that $L$ is diagonalizable.
First is this correct? If so, How do I construct the matrix $L$ with respect to a basis of eigenvectors. Is it possible that this is just the matrix with on the diagonal the eigenvalues?
Let's try and find the eigenvectors of the representing matrix with respect to $\alpha$. We need to find the null space of $$ L-\alpha I= \begin{bmatrix} 0&1&0&0\\ 0&1&2&0\\ 0&0&2&3\\ 0&0&0&3 \end{bmatrix} $$ and we find $[1\ 0\ 0\ 0]^T$. This yields the polynomial $1$ as an eigenvector for $L$.
With respect to $1+\alpha$, we need the null space of $$ L-(1+\alpha) I= \begin{bmatrix} -1&1&0&0\\ 0&0&2&0\\ 0&0&1&3\\ 0&0&0&2 \end{bmatrix} $$ and we find $[1\ 1\ 0\ 0]^T$. This yields $1+x$ as an eigenvector for $L$.
You may find also the other eigenvectors. However, you don't need it. The matrix with respect to a basis of eigenvectors is $$ \begin{bmatrix} \alpha & 0 & 0 & 0 \\ 0 & 1+\alpha & 0 & 0 \\ 0 & 0 & 2+\alpha & 0 \\ 0 & 0 & 0 & 3+\alpha \end{bmatrix} $$ (or any permutation of the eigenvalues along the diagonal).