2

I've just started learning matrices and I've been shown how to perform row operations, how to find an inverse matrix, how to find eigenvectors from a given matrix, reduced-echelon form, basis, dim(M), rank(M), etc. However, I've just come across this question:

The vector e is an eigenvector of the square matrix G. Show that:
$i.$ e is an eigenvector of G + kI, where k is a scalar and I is an identity matrix.
$ii.$ e is an eigenvector of G$^2$

I know that applying the general rule $Ax = \lambda x \implies (A-\lambda I)x = 0$ will somehow help me here. But without being given any matrix to work with I'm not sure what sort of result I'm meant to achieve, or how I'm supposed to "prove" the two statements.

How should this be done?

Ozzy
  • 385

1 Answers1

2

Just use the definition of Eigenvectors, let's say $\lambda$ is the eigenvalue, so that $Ge=\lambda e$ $$(G+k I) \cdot e= G e + k I e = \lambda e + k e = (\lambda +k ) e$$ for the second $$G^2 e = G G e = G (G e) = G \lambda e= \lambda G e = \lambda^2 e$$