Let $B_c= \left\{(1,0,0,0),(0,1,0,0),(0,0,1,0),(0,0,0,1)\right\}$, $T:\mathbb{R}^4\rightarrow \mathbb{R}^4$ a linear operator such that \begin{equation} \det\left[T-I\lambda\right]_{B_{c}}=(2-\lambda)^4\qquad \text{and}\qquad T((0,0,0,1)) = (1,0,0,1)\end{equation} Is T diagonalizable?
I've tried to use the following reasoning: Since the algebraic multiplicity of the eigenvalue $2$ is $4$, we know that $T$ is diagonalizable if (and only if) the dimension of the eigenspace associated with the eigenvalue $2$ is $4$. But we also know that there's a vector in $\mathbb{R}^4$ that don't belong to $S_{2}$ (because $(0,0,0,1)$ is not an eigenvector). Can I use this argument to show that $T$ is not diagonalizable? Thanks in advance
from https://en.wikipedia.org/wiki/Minimal_polynomial_(linear_algebra)
I like to say that a matrix diagonalizes as some $P^{-1}AP = D$ if and only if the minimal polynomial is squarefree. They phrase that as "factors...into distinct linear factors"
If the minimal polynomial really were $\lambda - 2,$ we would have $A-2I = 0,$ so that $A=2I,$ and everything would be an eigenvector. Since they give a vector that is not an eigenvector, that does it. The minimal polynomial is not linear, it is one of $(\lambda-2)^2$ or $(\lambda-2)^3$ or $(\lambda-2)^4.$ Note that i am using the reverse order polynomial $\det(\lambda I - A).$ Oh, and $A$ is the square matrix defined by $T$