Past exam of the continuous optimisation course of the University of Oxford / 2025 / 3 / c

For $\mu >0$, the logarithmic barrier objective isThe domain of a function $D$ is a nonempty convex set by the same concavity argument as in part (a), with strict inequalities. Differentiating twice on $D$ givesHere ${\nabla }^{2}f⪰0$ by convexity, $-{\nabla }^2{c}_i⪰0$ by concavity, and each outer product is a positive semidefinite matrix. Hence ${\nabla }^2{f}_{\mu }⪰0$, proving convexity on $D$.

The domain qualification matters: the displayed real-valued logarithm expression is not defined on all of ${\mathbb{R}}^n$. The precise whole-space version is the extended-real convex function equal to $f_{\mu }$ on $D$ and $+\infty$ outside $D$.