where \( \alpha \) is any non-zero real number, then the value of \( x \) is __________ (in integer).
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If a vector is an eigenvector of a matrix, then multiplying the matrix by that vector must result in a scalar multiple of the same vector. Use this property to derive unknowns like eigenvalues or entries of the matrix.
\[
v =
\begin{bmatrix}
2\alpha \\
\alpha
\end{bmatrix}
= \alpha
\begin{bmatrix}
2 \\
1
\end{bmatrix}
\]
Since an eigenvector is defined up to a scalar multiple, we may ignore \( \alpha \) and take
\[
v =
\begin{bmatrix}
2 \\
1
\end{bmatrix}
\]
Step 2: Use the eigenvector property.
If \( v \) is an eigenvector of matrix \( A \), then
\[
A v = \lambda v
\]
Given
\[
A =
\begin{bmatrix}
1 & 1 \\
-4 & x
\end{bmatrix}
\]
Compute \( A v \):