Solution

ID: past-exam-of-the-year-1-of-the-computer-science-course-of-the-university-of-oxford/2016/discrete-mathematics-continuous-mathematics-and-probability/4/c/solution

The gradient vanishes when and . Subtracting these equations gives , so the unique critical point is , with .
The Hessian matrix is
It is indefinite, so the critical point is a saddle point. Explicitly, around that point the change is exactly : it is positive for and negative for . Thus arbitrarily close points have both larger and smaller values.

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