Noperthedron

3 Rupert pairs

Write \(\pi \colon \operatorname{\mathbb {R}}^3 \to \operatorname{\mathbb {R}}^2\) for the projection \((x_0, x_1, x_2) \mapsto (x_0, x_1)\) onto the screen.

Definition 7
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A convex polyhedron with vertex set \(V\) is Rupert if there are rotations \(R_i, R_o \in SO(3)\) and an offset \(o \in \operatorname{\mathbb {R}}^2\) such that

\[ o + \pi (R_i \mathsf{Co}(V)) \subseteq \operatorname {int} \pi (R_o \mathsf{Co}(V)). \]
Definition 8
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The main statement: there is a finite set \(V \subseteq \operatorname{\mathbb {R}}^3\) whose convex hull has nonempty interior and which is not Rupert.

3.1 Rupert sets

Theorem 9 Rupert Polyhedron iff Rupert Set
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The convex polyhedron with vertex set \(V\) is Rupert if and only if the convex hull of \(V\) is a Rupert set, i.e. there is a pose (two rotations and an offset) under which the closure of the inner shadow lies in the interior of the outer shadow.

Proof ▶

The convex hull of a finite set is compact, so its shadow is closed.

Theorem 10
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Let \(S \subseteq \operatorname{\mathbb {R}}^3\) be point-symmetric and convex. If a pose with offset \(o\) passes \(S\) through itself, then so does the same pose with offset \(0\).

Proof ▶

Write \(K\) for the closure of the inner shadow and \(L\) for the interior of the outer shadow; both are point-symmetric and \(L\) is convex. From \(o + K \subseteq L\) and symmetry, \(-o + K = -(o + K) \subseteq L\). Every \(k \in K\) is the midpoint of \(o + k \in L\) and \(-o + k \in L\), so \(k \in L\) by convexity.

3.2 Shadows and the separation criterion

From now on \(\operatorname{\mathbf{P}}\) denotes the Noperthedron (Definition 2).

Definition 11
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The shadow of a \(3 \times 3\) matrix \(R\) is \(\mathrm{Sh}(R) = \pi (R\, \operatorname{\mathbf{P}})\). A pair of matrices \((R_o, R_i)\) is a Rupert pair if \(\overline{\mathrm{Sh}(R_i)} \subseteq \operatorname {int} \mathrm{Sh}(R_o)\).

Lemma 12
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If \(\operatorname{\mathbf{P}}\) is Rupert, then there is a Rupert pair \((R_o, R_i)\) with \(R_o, R_i \in SO(3)\).

Proof ▶

Combine Theorem 9 and Theorem 10; \(\operatorname{\mathbf{P}}\) is point-symmetric (Lemma 5) and convex.

For \(w = (w_0, w_1) \in \operatorname{\mathbb {R}}^2\) write \(\langle w, x \rangle = w_0 x_0 + w_1 x_1\) for \(x \in \operatorname{\mathbb {R}}^3\) (only the screen coordinates enter).

Theorem 13 Separation criterion
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Let \(S\) be a vertex of \(\operatorname{\mathbf{P}}\) and \(w \ne 0\). If

\[ \langle w, R_o T \rangle \le \langle w, R_i S \rangle \]

for every vertex \(T\) of \(\operatorname{\mathbf{P}}\), then \((R_o, R_i)\) is not a Rupert pair.

Proof ▶

The outer shadow is the convex hull of the points \(\pi (R_o T)\), so it lies in the closed half-plane \(\{ z : \langle w, z \rangle \le \langle w, R_i S \rangle \} \). The point \(\pi (R_i S)\) of the inner shadow lies on the boundary line of this half-plane, so it is not an interior point of the outer shadow.

Only a non-strict inequality is needed, so poses in which the two shadows touch need no special treatment.