
Cristian M. answered 08/07/20
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Given what we already know about the eigenvector {2, 2}, let's augment that eigenvector against A-1I:
[ -2 2 2 ]
[ -2 2 2 ]
Putting this system into reduced row-echelon form gets us:
[ 1 -1 -1 ]
[ 0 0 0 ]
This means that x - y = -1, and that y is a free variable. We can re-express this as x = y - 1, and y is a free variable. Here, we can pick different values of y (since y is free to vary), and this should produce a linearly independent eigenvector. Picking y = 0 shows that x = -1 and y = 0, or {-1, 0}.
The first eigenvector {2, 2} is free to take on any scalar multiple, so there should be a c1{2, 2} term in the answer. The next part of the answer will feature {2, 2}, but multiplied by t. Failure to include that t would produce a result that demonstrates linear dependence. The new eigenvector {-1, 0} does not need to be multiplied by anything else, although it should be multiplied from the outside by an arbitrary c2.
And of course, our eigenvalues are both 1.
D.) C1et[2]+C2et([-1]+t [2])
[2] [0] [2]