A semiconvex function with constant on an open convex subset of Euclidean space is twice differentiable outside a null set, and wherever it is twice differentiable its Hessian is bounded below by .
We work in the setting of Product Measures and Lebesgue Measure on ℝⁿ: Standing Notation and Background, whose notation is fixed for every dimension and is used here with a natural number satisfying : the real numbers and finite index sets, the Euclidean norm , dot product, distance , notion of openness and closed balls , the Lebesgue measure , the notion of a null subset, the constant with , and the conventions on Lipschitz maps are as fixed there. Write for the set of symmetric real matrices, for the identity matrix, for the scalar multiple of a real matrix, and for the positive semidefinite ordering on ; the matrix below belongs to because all of its off-diagonal entries vanish.
Let be open and convex, let with , and let be semiconvex on with constant . Twice differentiability at a point and the Hessian are as fixed there. Then the following hold.
1. (Twice differentiability almost everywhere) The set of those at which is not twice differentiable is null.
2. (Lower bound on the Hessian) At every at which is twice differentiable one has
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