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Gruber P. Convex and Discrete Geometry

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74 <strong>Convex</strong> Bodies<br />

where r(·) is a suitable positive semi-definite quadratic form on H.<br />

(ii)⇒(i) Let x = o, f (o) = 0, u,v,H, r, ′′ , g be as before. By assumption,<br />

(9) g(y) = r(y) + o(�y� 2 ) as y → o, y ∈ H,<br />

where r(y) = y T By,fory ∈ H, is a positive semi-definite quadratic form on H.<br />

Lemma 5.1 shows that f is differentiable at o, that is<br />

(10) f (z) = a · z + o(�z�) as z → o, z ∈ D,<br />

where a is a suitable vector in E d . Note that<br />

(11) y = � z + f (z)v � ′′ = z ′′ + f (z)v ′′ .<br />

Propositions (9)–(11) yield the following:<br />

<strong>and</strong> then<br />

f (z) = � y + g(y)u � · v = y · v + g(y) u · v<br />

= z ′′ · v + f (z)v ′′ · v + g � z ′′ + f (z)v ′′� u · v,<br />

f (z)(1 − v ′′ · v) = z ′′ · v + r � z ′′ + f (z)v ′′� u · v + o � �z ′′ + f (z)v ′′ � 2� u · v<br />

= z ′′ · v + � z ′′T Bz ′′ + z ′′T Bv ′′ 2 f (z) + v ′′T Bv ′′ f (z) 2� u · v + o(�z� 2 )<br />

= z ′′ · v + � z ′′T Bz ′′ + z ′′T Bv ′′ 2 a · z + v ′′T Bv ′′ (a · z) 2� u · v + o(�z� 2 )<br />

= b · z + q(z) + o(�z� 2 ) as z → o, z ∈ D.<br />

Here b <strong>and</strong> q are a suitable vector in E d <strong>and</strong> a quadratic form on E d . Since f is<br />

convex, this can hold only if q is positive semi-definite. ⊓⊔<br />

Using Lemma 5.2 <strong>and</strong> Alex<strong>and</strong>rov’s Theorem 2.9 for convex functions, we obtain<br />

Alex<strong>and</strong>rov’s theorem on second-order differentiability of convex bodies:<br />

Theorem 5.4. Let C ∈ Cp. Then bd C is almost everywhere twice differentiable.<br />

Proof. bd C can be covered by finitely many relative interiors of its lower sides with<br />

respect to suitable Cartesian coordinate systems. To the corresponding convex functions,<br />

apply Alex<strong>and</strong>rov’s theorem 2.9 <strong>and</strong> Lemma 5.2, noting that a set on the relative<br />

interior of a lower side of bd C has (d − 1)-dimensional Hausdorff measure<br />

0 if its orthogonal projection into a hyperplane has (d − 1)-dimensional Hausdorff<br />

measure 0. (A convex function on an open set is locally Lipschitz.) ⊓⊔<br />

5.2 Extreme Points<br />

Extreme points of convex bodies play an important role in convex analysis, convex<br />

geometry <strong>and</strong> functional analysis, for example in the context of the Krein–Milman<br />

theorem <strong>and</strong> Choquet theory. A refinement of the notion of extreme point is that of<br />

exposed point. Using this notion, Straszewicz [973] proved a result of Krein–Milman<br />

type.

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