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​​​​​Suppose $\lambda$ is an eigenvalue of matrix $A$ and $x$ is the corresponding eigenvector. Let $x$ also be an eigenvector of the matrix $B=A-2 I$, where $I$ is the identity matrix. Then, the eigenvalue of $B$ corresponding to the eigenvector $x$ is equal to

  1. $\lambda$
  2. $\lambda+2$
  3. $2 \lambda$
  4. $\lambda-2$

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Important Rule :
If $x$ is an eigenvector of $A$ with eigenvalue $\lambda$, then $Ax = \lambda x$.

 For any matrix $B = f(A)$, the eigenvalue is $f(\lambda)$ while the eigenvector $x$ remains the same.

Given $B = A - 2I$. Multiplying by eigenvector $x$:
\[ Bx = (A - 2I)x \]
\[ Bx = Ax - 2Ix \]
Since $Ax = \lambda x$ and $Ix = x$:
\[ Bx = \lambda x - 2x \]
\[ Bx = (\lambda - 2)x \]
By the definition $Bx = \lambda_B x$, the eigenvalue of $B$ is $(\lambda - 2)$.

$\lambda - 2$ (Option D) is correct
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