Documentation

LeanPool.NandakumarRamanaRao.NRR.Geometry.ConvexBody.SupportFunctionContinuity

NRR.Geometry.ConvexBody — continuity of the support function #

This module proves that the support function u ↦ h_K(u) of a ConvexBody K is (globally Lipschitz, hence) continuous in the direction variable. This is the analytic prerequisite for width, Cauchy perimeter, and all later integration over the unit circle / sphere.

Contents #

Design notes #

The proof follows the preferred Lipschitz route: subadditivity of the support function plus the radius bound h_K(u) ≤ R‖u‖ give h_K(u) - h_K(v) ≤ h_K(u - v) ≤ R‖u - v‖, and symmetrically, so the map is R-Lipschitz. This is more robust than a compact-maximum-with-parameters argument and yields the strongest downstream API.

Existence of a radius bound. Every convex body is bounded, so there is R ≥ 0 with ‖x‖ ≤ R for all x ∈ K.

Lipschitz estimate. If every point of K has norm at most R, the support function is R-Lipschitz: |h_K(u) - h_K(v)| ≤ R · ‖u - v‖.

theorem NRR.Geometry.ConvexBody.supportFunction_lipschitzWith {E : Type u_1} [NormedAddCommGroup E] [InnerProductSpace ℝ E] (K : ConvexBody E) {R : ℝ} (hRnn : 0 ≤ R) (hR : ∀ x ∈ K.carrier, ‖x‖ ≤ R) :

Bundled Lipschitz. The support function is R.toNNReal-Lipschitz when K ⊆ closedBall 0 R.

Full-space continuity of the support function in the direction variable.

Continuity at a point.

Continuity on a set.

Uniform continuity on a subset. The global Lipschitz bound gives uniform continuity on every subset of the ambient inner product space.

Continuity on the unit sphere, an immediate corollary of full-space continuity.