Given:
$M$ is an $n \times n$ matrix with $M^2 = 0$
$\alpha \in \mathbb{R} \setminus {0}$
Key property: Since $M^2 = 0$, all eigenvalues of $M$ are 0.
Step 1: Finding eigenvalues of $(M + \alpha I)$:
Let $\lambda$ be an eigenvalue of $M$ with eigenvector $v$: $$Mv = \lambda v = 0 \cdot v = 0$$
Then: $$(M + \alpha I)v = Mv + \alpha v = 0 + \alpha v = \alpha v$$
Therefore, $\alpha$ is an eigenvalue of $(M + \alpha I)$.
Since all eigenvalues of $M$ are 0, and $(M + \alpha I)$ shifts all eigenvalues by $\alpha$:
All eigenvalues of $(M + \alpha I)$ are $0 + \alpha = \alpha$
Step 2: Finding eigenvalues of $(M - \alpha I)$:
Similarly: $$(M - \alpha I)v = Mv - \alpha v = 0 - \alpha v = -\alpha v$$
Therefore, $-\alpha$ is an eigenvalue of $(M - \alpha I)$.
All eigenvalues of $(M - \alpha I)$ are $0 - \alpha = -\alpha$
Step 3: Finding eigenvalues of $(\alpha I - M)$:
$$(\alpha I - M)v = \alpha v - Mv = \alpha v - 0 = \alpha v$$
Therefore, $\alpha$ is an eigenvalue of $(\alpha I - M)$.
All eigenvalues of $(\alpha I - M)$ are $\alpha$
Step 4: Evaluating options:
(A) $(M + \alpha I)$ has eigenvalue $\alpha$, but $(M - \alpha I)$ has eigenvalue $-\alpha$, not $\alpha$
(B) $(M + \alpha I)$ has eigenvalue $\alpha$, and $(\alpha I - M)$ has eigenvalue $\alpha$
(C) $(M + \alpha I)$ has eigenvalue $\alpha$, not $-\alpha$
(D) $(M + \alpha I)$ has eigenvalue $\alpha$, not $-\alpha$
Answer: (B) $\alpha$ is the only eigenvalue of $(M + \alpha I)$ and $(\alpha I - M)$
For the matrix, $A = \begin{bmatrix} -4 & 0 \\ -1.6 & 4 \end{bmatrix}$, the eigenvalues ($\lambda$) and eigenvectors ($X$) respectively are: