# CHAPTER 5: Convex Polytopes

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CHAPTER 5: Convex Polytopes. Anastasiya Yeremenko. Definitions. Convex polytopes - convex hulls of finite point sets in . Examples:. For example, let’s take a look at 3-dimensional polytopes , called permutahedrones - PowerPoint PPT Presentation

### Text of CHAPTER 5: Convex Polytopes

CHAPTER 5: Convex Polytopes

Anastasiya Yeremenko11Definitions2Introductory notes.2Examples:

3Example: 3-dimensional permutahedron

4

Lecture slides:Geometric DualityH-Polytopes and V-PolytopesFaces of a Convex Polytope

5A list of procedures and steps, or a lecture slide with media.5Duality 2DPoints (x,y) can be mapped in a one-to-one manner to lines (slope, intercept) in a different space.There are different ways to do this, called duality transforms.

6Duality 2D:One possible duality transform

7Lemma: incidence and order preserving 2DLet p be a point in the plane and let l be a non-vertical line in the plane. The duality transform * has the following properties: It is incidence preserving: pl if and only if l*p*It is order preserving: p lies above l if and only if l* lies above p*

8Lemma: incidence and order preserving 2D

(p*)* = p, (l*)*=lpl if and only if l*p*p lies above l if and only if l* lies above p*9Proof: (p*)* = p, (l*)* =l:

10Proof: pl if and only if l*p*11Proof: p lies above l if and only if l* lies above p*p lies above l if and only if l* lies above p*

12Definition:13Lemma (Duality preserves incidences)14Definition: Geometric Duality15Geometric meaning of duality:

16Geometric Duality17Geometric Duality, illustration d=2

18

19Lemma (Duality preserves incidences)20Proof of the Lemma21Definition: Dual Set22Example:

23Dual Polytope

The dual polytope. Let P be a convex polytope containing the origin in its interior. Then the dual set P* is also a polytope.

The dual of acubeis anoctahedron, shown here with vertices at the cube face centers.24Geometric Duality

25Geometric meaning of Dual Set:

26H-Polytopes and V-Polytopes27Definition: H and V-polytope

28Relative vocabulary list. 28Examples

29Tetrahedron

It has 6edgesand 4 vertices, 4 faces. 30Cube or Hexahedron

It has 12edgesand 8 vertices, 6 faces. 31Octahedron

It has 12edgesand 6 vertices, 8 faces. A regular octahedron is a Platonic solid composed of 8 equilateral triangles, four of which meet at each vertex.32Dodecahedron

It is composed of 12 regular pentagonal faces, with three meeting at each vertex. It has 20 vertices, 30 edges. Its dual polyhedron is the icosahedron. 33Icosahedron

In geometry, an icosahedron is a regular polyhedron with 20 identical equilateral triangular faces, 30 edges and 12 vertices. It has five triangular faces meeting at each vertex. 34H-polytopes and V-polytopes are equivalentA basic theorem about convex polytopes claims that from the mathematical point of view, H-polytopes and V-polytopes are equivalent. Although H-polytopes and V-polytopes are mathematically equivalent, there is an enormous difference between them from the computational point of view. That is, it matters a lot whether a convex polytope is given to us as a convex hull of a finite set or as an intersection of half-spaces.

35H and V PolytopesFor example, given a set of n points specifying a V-polytope, how do we find its representation as an H-polytope? It is not hard to come up with some algorithm, but the problem is to find an efficient algorithm that would allow one to handle large real-world problems.

36 Maximization of a given linear function over a given polytope. As another illustration of the computational difference between V-polytopes and H-polytopes, we consider the maximization of a given linear function over a given polytope. For V-polytopes it is a trivial problem, since it suffices to substitute all points of V into the given linear function and select the maximum of the resulting values. But maximizing a linear function over the intersection of a collection of half-spaces is the basic problem of linear programming, and it is certainly nontrivial.37Basic Example: Cubes

38Basic Example: Crosspolytopes

39Definition: Simplex

40Theorem: V and H-polytopes are equivalentProof: Each H-polytope is a V-polytope. Proof: Each V-polytope is an H-polytope.41Proof: Each H-polytope is a V-polytope.

42Proof: Each H-polytope is a V-polytope.

43Proof: Each V-polytope is a H-polytope. 44A face of a convex polytope P is defined as either P itself, or a subset of P of the form P h, where h is a hyperplane such that P is fully contained in one of the closed half-spaces determined by h.

Faces of a Convex Polytope

45FacesWe observe that each face of P is a convex polytope. This is because P is the intersection of finitely many half-spaces and h is the intersection of two half-spaces, so the face is an H-polyhedron, and it is bounded. If P is a polytope of dimension d, then its faces have dimensions -1, 0, 1,..., d, where -1 is, by definition, the dimension of the empty set. A face of dimension j is also called a j-face. 46Names of Faces for d dimensional polytope0-faces vertices 1-faces edges(d-2)-faces - ridges (d-1)-faces - facets

For example, the 3-dimensional cube has 28 faces in total: the empty face, 8 vertices, 12 edges, 6 facets, and the whole cube

47Extremal

48Proposition(proof next lesson)49Graphs of polytopes.Each 1-dimensional face, or edge, of a convex polytope has exactly two vertices. We can thus define the graph G(P) of a polytope P in the natural way: The vertices of the polytope are vertices of the graph, and two vertices are connected by an edge in the graph if they are vertices of the same edge of P. 50Example:Here is an example of a 3-dimensional polytope, the regular octahedron, with its graph.

Moreover, it can be shown that the graph is vertex 3-connected. A graph G is called vertex k-connected if |V(j)| > k+1 and deleting any at most k-1 vertices leaves G connected

51Theorem (Steinitz theorem).A finite graph is isomorphic to the graph of a 3-dimensional convex polytope if and only if it is planar and vertex 3-connected.

Note: Graphs of higher-dimensional polytopes probably have no nice description comparable to the 3-dimensional case, and it is likely that the problem of deciding whether a given graph is isomorphic to a graph of a 4-dimensional convex polytope is NP-hard. 52Examples

53Examples

54The face lattice.Let F(P) be the set of all faces of a (bounded) convex polytope P (including the empty face of dimension -1). We consider the partial ordering of F(P) by inclusion.

55 The face lattice can be a suitable representation of a convex polytope in a computer. Each j-face is connected by pointers to its (j-1)-faces and to the (j+1)-faces containing it.

56Definition:Simple and simplicial polytopesA polytope P is called simplicial if each of its facets is a simplex (this happens, in particular, if the vertices of P are in general position, but general position is not necessary). A d-dimensional polytope P is called simple if each of its vertices is contained in exactly d facets.

57Platonic solidsAmong the five Platonic solids, the tetrahedron, the octahedron, and the icosahedron are simplicial; and the tetrahedron, the cube, and the dodecahedron are simple.

58More examples:The dual of a simple polytope is simplicial, and vice versa. The dual of acubeis anoctahedron, shown here with vertices at the cube face centers.

59

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