The derivative of
with respect to
is
.
Also, the derivative of
with respect to
is
.
For a critical point at
, we require that
. Using the above two equations, this gives us the following system to solve for
and
:

.
Equation 2 tells us that
.
Substituting this value for
into equation 1 tells us that
. Therefore, we have that
.
This critical point is a saddle point. To show this, we solve for the second derivatives
,
and
.
First,
.
Therefore,
.
Second,
.
Therefore,

Third,
.
Therefore,
.
We can classify the critical points by looking at the formula,

If
then the critical point is a saddle point. If
then we look to the sign of
. If
then we have a local minimum and if
then we have a local maximum. For our problem,

Therefore since
the critical point is a saddle point.
Advanced:
Using the second partial derivatives of a function
we can define a general Hessian matrix as

which for our specific example is
.
The eigenvalues of this matrix are given by the solving the formula
for
.
That is,
.
Solving gives us the answer
.
Because one eigenvalue is positive and one eigenvalue is negative, we conclude that the Hessian matrix is indefinite, and thus the point
is a saddle point.