Let $A$ be an $n \times n$ matrix, and $u, v$ be eigenvectors corresponding to an eigenvalue $\lambda$ of $ A$ (that is, $Au = \lambda u$ and $Av = \lambda v$). Is it true that $u + v$ is an eigenvector corresponding to the eigenvalue $\lambda$.
I know that an eigenvector can't be the $0$ vector, but an eigenvalue can be $0$, it just means the matrix $A$ is not invertible.
By definition $ Au = \lambda u$, where $u \ne 0$, and $Av = \lambda v$, where $v \ne 0$. So, $$Au + Av = \lambda u + \lambda v \implies A(u + v) = \lambda (u + v)$$
where $u + v \ne 0$?
I feel like I'm missing something because my solution was too straightforward.
Best Answer
Well, the set of all eigenvectors of an eigenvalue forms a subspace.
I.e. if u,v $\in Eig(A,\lambda)$ then $a_1 u$+$a_2v\in Eig(A,\lambda)$:
For $Av=\lambda v$ and $Au=\lambda u$ we have:
$A(a_1u+a_2v)=a_1Au+a_2Av=a_1\lambda u+a_2\lambda v=\lambda(a_1u+a_2v)$
Note: $0$ is not an eigenvector. So the set above is only a space if we add $0$ to the space.