Convex position

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In discrete and computational geometry, a set of points in the Euclidean plane or a higher-dimensional Euclidean space is said to be in convex position or convex independent if none of the points can be represented as a convex combination of the others. [1] A finite set of points is in convex position if all of the points are vertices of their convex hull. [1] More generally, a family of convex sets is said to be in convex position if they are pairwise disjoint and none of them is contained in the convex hull of the others. [2]

An assumption of convex position can make certain computational problems easier to solve. For instance, the traveling salesman problem, NP-hard for arbitrary sets of points in the plane, is trivial for points in convex position: the optimal tour is the convex hull. [3] Similarly, the minimum-weight triangulation of planar point sets is NP-hard for arbitrary point sets, [4] but solvable in polynomial time by dynamic programming for points in convex position. [5]

The Erdős–Szekeres theorem guarantees that every set of points in general position (no three in a line) in two or more dimensions has at least a logarithmic number of points in convex position. [6] If points are chosen uniformly at random in a unit square, the probability that they are in convex position is [7]

The McMullen problem asks for the maximum number such that every set of points in general position in a -dimensional projective space has a projective transformation to a set in convex position. Known bounds are . [8]

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Point set triangulation

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K-set (geometry)

In discrete geometry, a k-set of a finite point set S in the Euclidean plane is a subset of k elements of S that can be strictly separated from the remaining points by a line. More generally, in Euclidean space of higher dimensions, a k-set of a finite point set is a subset of k elements that can be separated from the remaining points by a hyperplane. In particular, when k = n/2, the line or hyperplane that separates a k-set from the rest of S is a halving line or halving plane.

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Integral polytope

In geometry and polyhedral combinatorics, an integral polytope is a convex polytope whose vertices all have integer Cartesian coordinates. That is, it is a polytope that equals the convex hull of its integer points. Integral polytopes may also be called convex lattice polytopes or Z-polytopes. The special cases of two- and three-dimensional integral polytopes may be called polygons or polyhedra instead of polytopes, respectively.

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The McMullen problem is an open problem in discrete geometry named after Peter McMullen.

Topological graph

In mathematics, a topological graph is a representation of a graph in the plane, where the vertices of the graph are represented by distinct points and the edges by Jordan arcs joining the corresponding pairs of points. The points representing the vertices of a graph and the arcs representing its edges are called the vertices and the edges of the topological graph. It is usually assumed that any two edges of a topological graph cross a finite number of times, no edge passes through a vertex different from its endpoints, and no two edges touch each other (without crossing). A topological graph is also called a drawing of a graph.

Flip graph

A flip graph is a graph whose vertices are combinatorial or geometric objects, and whose edges link two of these objects when they can be obtained from one another by an elementary operation called a flip. Flip graphs are special cases of geometric graphs.

Penny graph

In geometric graph theory, a penny graph is a contact graph of unit circles. That is, it is an undirected graph whose vertices can be represented by unit circles, with no two of these circles crossing each other, and with two adjacent vertices if and only if they are represented by tangent circles. More simply, they are the graphs formed by arranging pennies in a non-overlapping way on a flat surface, making a vertex for each penny, and making an edge for each two pennies that touch.

References

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  2. Tóth, Géza; Valtr, Pavel (2005), "The Erdős-Szekeres theorem: upper bounds and related results", Combinatorial and computational geometry, Math. Sci. Res. Inst. Publ., 52, Cambridge: Cambridge Univ. Press, pp. 557–568, MR   2178339
  3. Deĭneko, Vladimir G.; Hoffmann, Michael; Okamoto, Yoshio; Woeginger, Gerhard J. (2006), "The traveling salesman problem with few inner points", Operations Research Letters, 34 (1): 106–110, doi:10.1016/j.orl.2005.01.002, MR   2186082
  4. Mulzer, Wolfgang; Rote, Günter (2008), "Minimum-weight triangulation is NP-hard", Journal of the ACM , 55 (2), Article A11, arXiv: cs.CG/0601002 , doi:10.1145/1346330.1346336
  5. Klincsek, G. T. (1980), "Minimal triangulations of polygonal domains", Annals of Discrete Mathematics, 9: 121–123, doi:10.1016/s0167-5060(08)70044-x
  6. Erdős, Paul; Szekeres, George (1935), "A combinatorial problem in geometry", Compositio Mathematica, 2: 463–470
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  8. Forge, David; Las Vergnas, Michel; Schuchert, Peter (2001), "10 points in dimension 4 not projectively equivalent to the vertices of a convex polytope", Combinatorial geometries (Luminy, 1999), European Journal of Combinatorics , 22 (5): 705–708, doi:10.1006/eujc.2000.0490, MR   1845494