If $u$ is an eigen vector of $\exp(A)$ then $u$ is an eigen vector (e.vector) of $A$.
Is it true for a $2 \times 2$ real-valued matrix $A$.
My try: $\exp(A)$ is invertible so all e.values (eigenvalues) are non zero so we can write $$\exp(A)=U(e^aI+N)U^{-1}$$ where $e^a$ is an e.value corresponding to the e.vector $u$. Now I can write $$\exp(A)=U(e^aI+N)U^{-1}=U(e^aI(I+e^{-a}N)U^{-1}$$
So, even if I write $$\log(e^aI)+\log(I+e^{-a}N)=\log(e^aI)-e^{-a}N$$
How will I manage $U$ and $U^{-1}$. Help me here.
Btw, for complex case the statement is not correct. We can get a contradiction here
Let $$A = \begin{bmatrix} 4\pi i & 0\\ 0 & 2\pi i\\ \end{bmatrix}.$$
Then $\exp(A) = Id$ and $v = \begin{bmatrix} 1\\ 1 \end{bmatrix}$ is an eigenvector of $\exp(A)$ but not of $A$.
Look here.