Zero as an element of an eigenvector

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The discussion focuses on the conditions under which zero can appear as an element of an eigenvector. It highlights that if zero is the last element of the eigenvector, the matrix can be partitioned, leading to two key equations: Ax = λx and v^T x = 0. The last column of the original matrix does not influence these equations, suggesting that certain matrix properties might allow for zero in the eigenvector. Participants inquire about methods to ascertain the presence of zero in eigenvectors without explicit calculation. Overall, the conversation emphasizes the relationship between matrix structure and eigenvector characteristics.
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Quick question on eigenvectors;

Are there any general properties of a matrix that guarantee that a zero will or will not appear as an element in an eigenvector?

Thank you!
 
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Suppose the zero is the last element of the eigenvector. Then you can partition the matrix and write
##\begin{bmatrix} A & u \\ v^T & s \end{bmatrix}\begin{bmatrix} x \\ 0 \end{bmatrix} = \lambda
\begin{bmatrix} x \\ 0 \end{bmatrix}## where ##u## and ##v## are vectors and ##s## is a single matrix element.

Multiplying out you get the two equations ##Ax = \lambda x## and ##v^t x = 0##. Interestingly, the last column of the original matrix doesn't appear in those equations.
 
Thank you for your reply!

Is there a way to determine from the matrix whether a zero will appear without calculating the eigenvector explicitly?
 
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