We consider the
linear mapping
-
given by the matrix
-

The question whether this mapping has
eigenvalues,
leads to the question whether there exists some
,
such that the equation
-

has a nontrivial solution
.
For a given
, this is a linear problem and can be solved with the elimination algorithm. However, the question whether there exist eigenvalues at all, leads, due to the variable "eigenvalue parameter“
, to a nonlinear problem. The system of equations above is
-
For
,
we get
,
but the null vector is not an eigenvector. Hence, suppose that
.
Both equations combined yield the condition
-

hence
.
But in
, the number
does not have a
square root,
therefore there is no solution, and that means that
has no eigenvalues and no
eigenvectors.
Now we consider the matrix
as a real matrix, and look at the corresponding mapping
-
The same computations as above lead to the condition
,
and within the real numbers, we have the two solutions
-
For both values, we have now to find the eigenvectors. First, we consider the case
,
which yields the linear system
-

We write this as
-

and as
-

This system can be solved easily, the solution space has dimension one, and
-

is a basic solution.
For
,
we do the same steps, and the vector
-

is a basic solution. Thus over
, the numbers
and
are eigenvalues, and the corresponding
eigenspaces
are
-