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Which of the following statements is/are $\textbf{NOT CORRECT}$?

  1. If $v1$ and $v2$ are linearly independent eigenvectors then they can correspond to the same eigenvalue.
  2. If $A$ is a nilpotent matrix, meaning that $A^k = 0$ for the least positive integer $k$, and if $k = 2$, then $A$ can have non-zero value as its eigenvalue.
  3. $\lambda $ is the eigenvalue of $A$ if and only if  $\lambda $ is the eigenvalue of $A^T$.
  4. If $\lambda $ is an eigenvalue of an invertible matrix $A$ then  $\lambda ^{-1}$ is an eigenvalue of $A^{-1}$.
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2 Answers

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Option B

if \( A \) is a nilpotent matrix with \( k = 2 \) (meaning \( A^2 = 0 \)), then \( A \) cannot have a non-zero eigenvalue. 

To understand why, let's suppose that \( A \) has a non-zero eigenvalue \( \lambda \). Then there exists a non-zero vector \( v \) such that \( Av = \lambda v \). 

Now, let's consider \( A^2v = A(Av) = A(\lambda v) = \lambda(Av) = \lambda(\lambda v) = \lambda^2v \).

Since \( A^2 = 0 \), we have \( \lambda^2v = 0 \). But since \( v \) is non-zero, this implies that \( \lambda^2 = 0 \). However, if \( \lambda^2 = 0 \), then \( \lambda = 0 \). Thus, any eigenvalue of \( A \) must be zero if \( A \) is nilpotent with \( k = 2 \).

3 votes
3 votes
  1. Distinct eigenvalues have LI eigenvectors but same eigenvalue can also have LI eigenvectors.

  2. $A^2 = 0$ then $A$ has only $0$ as its eigenvalue.

  3. True

  4. True
Answer:

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