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Gruber P. Convex and Discrete Geometry

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18 Theorems of Alex<strong>and</strong>rov, Minkowski <strong>and</strong> Lindelöf 301<br />

Remark. To Günter Ziegler [1046] we owe the following comment. The proof<br />

of the theorem of Asimow <strong>and</strong> Roth is via the rigidity matrix, which characterizes<br />

infinitesimal rigidity. Thus it shows that, in the simplicial case, the polytope actually<br />

is infinitesimally rigid, which implies rigidity, but is a stronger property in general.<br />

18 Theorems of Alex<strong>and</strong>rov, Minkowski <strong>and</strong> Lindelöf<br />

In convex geometry there are results of geometric interest, but not (yet?) of a systematic<br />

character. This does not exclude that such a result is useful as a tool or that there<br />

are related results. Of course, this may change over the years. In the nineteenth century<br />

Steiner’s formula for the volume of parallel bodies was an interesting curiosity,<br />

through the work of Minkowski it is now an essential part of the Brunn–Minkowski<br />

theory.<br />

In the following we present results of this type on convex polytopes due to<br />

Alex<strong>and</strong>rov [16], Minkowski [739] <strong>and</strong> Lindelöf [658]. Besides the geometric<br />

interest of these results, it is the methods of proof which contribute to their appeal.<br />

18.1 Alex<strong>and</strong>rov’s Uniqueness Theorem for <strong>Convex</strong> Polytopes<br />

Given two convex polytopes, what conditions ensure that one is a translate of the<br />

other? There are several such results in the literature, dealing with projections, sections<br />

or properties of faces.<br />

This section contains Alex<strong>and</strong>rov’s sufficient condition for the congruence of<br />

convex polytopes in E 3 , see [16]. The proof makes use of Cauchy’s combinatorial<br />

lemma.<br />

Alex<strong>and</strong>rov’s Uniqueness Theorem<br />

In the proof, unconventional terminology is used. A side of a (possibly improper)<br />

convex polygon or polytope is a vertex or an edge. If F <strong>and</strong> G are convex polygons,<br />

then by parallel sides we mean sides defined by support lines of F <strong>and</strong> G, respectively,<br />

with the same exterior normal vector. Let H = F + G. Then each edge of<br />

H is the sum of corresponding (unique, parallel) sides of F <strong>and</strong> G. We say that F<br />

can be embedded into G if F + t � G for a suitable vector t. These definitions may<br />

easily be extended to vertices, edges <strong>and</strong> facets, i.e. to faces of convex polytopes<br />

in E 3 . Alex<strong>and</strong>rov’s uniqueness theorem for convex polytopes in E 3 can now be<br />

stated as follows:<br />

Theorem 18.1. Let P, Q be proper convex polytopes in E 3 . Then the following statements<br />

are equivalent:<br />

(i) For each pair of parallel faces of P <strong>and</strong> Q, at least one of which is a facet,<br />

neither can be embedded in the other.<br />

(ii) P <strong>and</strong> Q coincide up to translation.

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