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INCIDENCE GEOMETRIES CHAPTER 4.

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1 INCIDENCE GEOMETRIES CHAPTER 4

2 Contents Pappus and Desarguers Theorem Existence and Countnig
Motivation Incidence Geometries Incidence Geometry Constructions Residuals, Truncations - Sections, Shadow Spaces Incidence Structures and Combinatorial Configurations Substructures, Symmetry and Duality Haar Graphs and Cyclic Configurations Algebraic Structures Euclidean Plane, Affine Plane, Projective Plane Point Configurations, Line Arrangements and Polarity Pappus and Desarguers Theorem Existence and Countnig Coordinatization Combinatorial Configurations on Surfaces Generalized Polygons Cages and Combinatorial Configurations A Case Study – The Gray Graph Another Case Study - Tennis Doubles

3 1. Motivation

4 Motivation When Slovenia joined the European Union it obtained 7 seats in the Parliament of the European Union. In 2004 the first elections to the European Parliament in Slovenia were held. There were 13 political parties (7 parliamentary parties: 1, 2, 3, 4, 5, 6, 7, and 6 non-parliamentary parties: A, B, C, D, E, F) competing for these seats. TV Slovenia decided to cover the campain by hosting political parties in 6 TV shows: a,b,c,d,e,f. TV asked mathematicians to help them select the guests in a fair way.

5 Motivation With a little help from mathematicians TV came up with the following schedule. a b c d e f A B C D E F 1 2 3 4 6 7 5

6 Example – TV coverage of EU parliamentary elections in Slovenia
TV Shows Parties a A 1 4 5 b B 2 6 c C 3 d D 7 e E f F

7 Model We can model the above schedule as follows:
Let P = {1,2,3,4,5,6,7,A,B,C,D,E,F} Let L = {a,b,c,d,e,f} Let I ½ P £ L such that (p,L) 2 I if and only if political party p appears in the show L. I = {(A,a), (1,a), (4,a), (5,a), ... }

8 Incidence structure An incidence structure C is a triple
C = (P,L,I) where P is the set of points, L is the set of blocks or lines I  P  L is an incidence relation. Elements from I are called flags.

9 Levi Graph The bipartite incidence graph G(C) with black vertices P, white vertices L and edges I is known as the Levi graph of the structure C.

10 Levi graph for the Election structure
On the left there is the Levi graph for the incidence structure of the media coverage of the European Union Parliament elections in Slovenia. Each parliamentary party appears twice and each non-parliamentary party appears once. (check valence!) 1 4 5 B e D C c 2 d E b 6 3 7 F f

11 Menger graph Given an incidence structure C = (P,L,I) we say that two points p and q are collinear, if there is a line L that contains both of them. Menger graph M(C). Vertices P p ~ q if and only if p and q are collinear.

12 Menger Graph from Levi Graph
There is a simple procedure for computing M from L. Take the pure graph power L(2). It is obtained from L by taking the same vertex set and making two vertices adjacent in L(2) if and only if they are at distance two in L. Since L is bipartite L(2). has (at least) two components. The one defined on the black vertices (corresponding to points of the incidence structure) is Menger graph M. The other one is called dual Menger graph.

13 Menger graph for the Election structure
1 On the left there is the Menger graph for the incidence structure of the media coverage of the European Union Parliament elections in Slovenia. 4 5 B C D 2 E 6 3 F 7

14 Configuration Graph The configuration graph K is the complement of the Menger graph. The dual configuration graph is the complement of the dual Menger graph.

15 Dual Configuration graph for the Election structure
On the left there is the dual configuration graph for the incidence structure of the media coverage of the European Union Parliament elections in Slovenia. f e c d a b

16 Dual Configuration graph for the Election structure
The Hamilton path abcdef in the dual configuration graph guarantees that no political party appears in two consecutive TV shows. f e c d a b

17 Examples 1. Each graph G = (V,E) is an incidence structure: P = V, L = E, (x,e) 2 I if and only if x is an endvertex of e. 2. Any family of sets F µ P(X) is an incidence structure. P = X, L = F, I = 2. 3. A line arrangement L = {l1, l2, ..., ln} consisting of a finite number of n distinct lines in the Euclidean plane E2 defines an incidence structure. Let V denote the set of points from E2 that are contained in at least two lines from L. Then: P = V, L = L and I is the point-line incidence in E2.

18 Exercises 1 N1. Draw the Levi graph of the incidence structure defined by the complete bipartite graph K3,3. N2. Draw the Levi graph of the incidence structure defined by the power set P({a,b,c}). N3. Determine the Levi graph of the incidence structure, defined by an arrangement of three lines forming a triangle in E2. N4 Determine the Levi graph of the line arrangement on the left.

19 2. Incidence Geometry

20 Incidence geometry An incidence geometry (G,c) of rank k is a graph G with a proper vertrex coloring c, where k colors are used. Sometimes we denote the geometry by (G,~,T,c). Here c:V(G) ! T is the coloring and |T| = k is the number of colors, also known as the rank of G. The relation ~ is called the incidence. T is the set of types. Note that only objects of different types may be incident.

21 Examples 1. Each incidence structure is a rank 2 geometry. (Actualy, look at its Levi graph.) 2. Each 3 dimensional polyhedron is a rank 3 geometry. There are three types of objects: vertices, edges and faces with obvious geometric incidence. 3. Each (abstract) simplicial complex is an incidence geometry. Incidence is defined by inclusion of simplices. 4. Any complete multipartite graph is a geometry. Take for instance K2,2,2, K2,2,2,2, K2,2, ..., 2. The vertex coloring defining the geometry in each case is obvious.

22 Pasini Geometry Pasini defines incidence geometry (that we call Pasini geometry) in a more restrictive way. For k=1, the graph must contain at least two vertices: |V(G)|>1. For k>1: G has to be connected, For each x  V(G) the (k-1)-colored graph (Gx,c), called residuum, induced on the neigbors of x is a Pasini geometry of rank (k-1).

23 Incidence geometries of rank 2
Incidence geometries of rank 2 are simply bipartite graphs with a given black and white vertex coloring. Rank 2 Pasini geometries are in addition connected and the valence of each vertex is at least 2: d(G) >1.

24 Example of Rank 2 Geometry
Graph H on the left is known as the Heawood graph. H is connected H is trivalent: d(H) = D(H) = 3. H is bipartite. H is a Pasini geometry.

25 Another View The geometry of the Heawood graph H has another interpretation. Rank = 2. There are two types of objects in Euclidean plane, say, points and curves. There are 7 points, 7 curves, 3 points on a curve, 3 curves through a point. The corresponding Levi graph is H!

26 In other words ... The Heawood graph (with a given black and white coloring) is the same thing as the Fano plane (73), the smallest finite projective plane. Any incidence geometry can be interpeted in terms of abstract points, lines. If we want to distinguish the geometry (interpretation) from the associated graph we refer to the latter as the Levi graph of the corresponding geometry.

27 Simplest Rank 2 Pasini Geometries
Cycle (Levi Graph) “Simplest” geometries of rank 2 in the sense of Pasini are even cycles. For instance the Levi graph C6 corresponds to the triangle. Triangle (Geometry)

28 Rank 3 Incidence geometries of rank 3 are exactly 3-colored graphs.
Pasini geometries of rank 3 are much more restricted. Currently we are interested in those geometries whose residua are even cycles. Such geometries correspond to Eulerian surface triangulations with a given vertex 3-coloring.

29 Flag System as Geometries
Any flag system  µ V £ E £ F defines a rank 3 geometry on X = V t E t F. There are three types of elements and two distinct elements of X are incicent if and only if they belong to the same flag of .

30 Self-avoiding maps Recall that a map is self-avoiding if and only if neither the skeleton of the map nor the skeleton of its dual has a loop.

31 Self-avoiding maps as Geometries of rank 4
Consider a generalized flag system  µ V £ E £ F £ P that defines a rank 4 geometry on X = V t E t F t P. There are four types of elements and two distinct elements of X are incident if and only if they belong to the same flag of . We may take any self-avoiding map M and the four involutions 0,1,2 and 3 and define a geometry as above.

32 Exercises 2 N1. Prove that the Petrie dual of a self-avoiding map is self-avoiding. N2. Prove that any operation Du,Tr,Me,Su1, ... of a self-avoiding map is self-avoiding. N3. Prove that BS of any map is self-avoiding. N4. Show that any self-avoiding map may be considered as a geometry of rank 4 (add the fourth involution).

33 Homework 2 H1 Describe the rank 4 geometry of the projective planar map on the left.

34 3. Incidence Geometry Constructions

35 Geometries from Groups
Let G be a group and let {G1,G2,...,Gk} be a family of subgroups of G. Form the cosets xGt, t 2 {1,2, ..., k}. An incidence geometry of rank k is obtained as follows: Elements of type t 2 {1,2,...,k} are the cosets xGt. Two cosets are incident: xGt ~ yGs if and only if xGt Å yGs ¹ ;.

36 Q – The Quaternion Units
1 -1 i -i j -j k -k

37 Geometry from Quaternions
Example: Q = {+1,-1,+i,-i,+j,-j,+k,-k}. Gi = {+1,-1,+i,-i}, Gj = {+1,-1,+j,-j}, Gk ={+1,-1,+k,-k}.

38 Quaternions - Continiuation
j,k The Levi graph is an octahedron. Labels on the left: i = {+1,-1,+i,-i} j,k = {+j,-j,+k,-k}, etc. k j i i,j i,k

39 Quaternions– Examle of Rank 4 Geometry.
j,k Levi graph was an octahedron. Notation: i = {+1,-1,+i,-i} j,k = {+j,-j,+k,-k}, etc. If we add the sugroup G0 = {+1,-1}, four more cosets are obtained: Additional notation: 1 = {+1,-1},i’={+i,-i}, etc. k’ j’ k 1 j i i’ i,k i,j

40 Reye’s Configuration Reye’s configuration of points, lines and planes in 3-dimensional projective space consists of = 12 points (3 at infinity) = 16 lines 6 + 6 = 12 planes. P=12 L=16 S=12 - 4 6 3

41 Theodor Reye Theodor Reye (1838 - 1919), German Geometer.
Known for his book Geometrie der Lage (1866 and 1868). Published his famous configuration in 1878. Posed “the problem of configurations.”

42 Centers of Similitude We are interested in tangents common to two circles in the plane. The two intersections are called the centers of similitudes of the two circles. The blue center is called the internal, the red one is the external center. If the radii are the same, the external center is at infinity.

43 Reye’s Configuration -Revisited
Reye’s configuration can be obtained from centers of similitudes of four spheres in three space (see Hilbert ...) Each plane contains a complete quadrangle. There are C(4,2) = 2 4 3/2 = 12 points.

44 Exercises 3-1 N1. Consider the geometry defined by Z3 and Z5 in Z15. Draw its Levi graph. N2. Draw the Levi graph of the geometry defined by all non-trivial subgroups of the symmetric group S3. N3. Draw the Levi graph of the geometry defined by all non-trivial subgroups of the group Z23.

45 Exercises 3-2 N4. Let there be three circles in a plane giving rise to 3 internal and 3 external centers of similitude. Prove that the three external centers of similitude are colinear.

46 4. Residuals, Truncations - Sections, Shadow Spaces

47 Residual geometry Each incidence geometry
G =(G, ~, T,c) (G,~) a simple graph c, proper vertex coloring, T collection of colors. c: V(G) ! T Each element x 2 V(G) determines a residual geometry Gx. defined by an induced graph defined on the neighborhood of x in G. G Gx x

48 Flags and Residuals In an incidence geometry G a clique on m vertices (complete subgraph) is called a flag of rank m. Residuum can be definied for each flag F ½ V(G). G(F) = Å{G(x) = Gx |x 2 F}.

49 Chambers and Walls A maximal flag (flag of rank |T|} is called a chamber. A flag of rank |T|-1 is called a wall. To each geometry G we can associate the chamber graph: Vertices: chambers Two chambers are adjacent if and only if they share a common wall. (See Egon Shulte, ..., Tits systems)

50 The 4-Dimensional Cube Q4.
0010 0001 0000 0100 1000

51 Hypercube The graph with one vertex for each n-digit binary sequence and an edge joining vertices that correspond to sequences that differ in just one position is called an n-dimensional cube or hypercube. v = 2n e = n 2n-1

52 4-dimensional Cube. 0110 0010 0111 1110 0011 1010 1011 1111 0001 1101 1001 0000 0100 1100 1000

53 4-dimensional Cube and a Famous Painting by Salvador Dali
Salvador Dali (1904 – 1998) produced, in 1954, the Crucifixion (Metropolitan Museum of Art, New York) in which the cross is a 3-dimensional net of a 4-dimensional hypercube.

54 4-dimensional Cube and a Famous Painting by Salvador Dali
Salvador Dali (1904 – 1998) produced in 1954, the Crucifixion (Metropolitan Museum of Art, New York) in which the cross is a 3-dimensional net of a 4-dimensional hypercube.

55 The Geometry of Q4. Vertices (Q0) of Q4: 16 Edges (Q1)of Q4: 32
Squares (Q2) of Q4: 24 Cubes (Q3) of Q4: 8 Total: 80 The Levi graph of Q4 has 80 vertices and is colored with 4 colors.

56 Residual geometries of Q4.
V E S Q3. G(V) - 4 6 G(E) 2 3 G(S) G(Q3) 8 12

57 Truncations or Sections
Given a geometry G = (V,~,T,c) and a subset of types J µ T, define a J-section G/J of G as the geometry H = (U,~,J,c), where U = {v 2 V| c(v) 2 J} and H is the induced subgraph of G.

58 Quaternions– Example of Rank 4 Geometry - Section
j j,k i,k i,j 1 i’ k’ j’ j,k k j i i,j i,k Rank 3 section Rank 4 geometry

59 Shadow Spaces Given a geometry G = (V,~,T,c) and J µ T we may define an incidence structure Spa(G,J) whose points are J-flags and the blocks are composed of those sets of J-flags that belong to the residual geometry G(F) for some flag F from the original geometry G.

60 Shadow Spaces - An Example
4 3 Let us denote the types I = {g,r,b}. Let J = {r,b}. There are three J-flags: 26, 45 and 56. The set system for the shadow space: {{45},{26},{45,56},{26,56}}. For J = {g,b} we get three flags: {16,14,34} The set system for the shadow space: {{16},{34},{14,16},{14,34}} 5 6 1 2

61 Shadow spaces of Maps For maps as rank 3 geometries the notion of shadow spaces gives rise to an interesting interpretation. There are three types of objects {v,e,f}. Hence, there are 7 types of shadow spaces: {v} - primal: id {e} - medial: Me {f} - dual: Du {v,e} - truncation: Tr {v,f} - Me Me {e,f} - leapfrog: Le {v,e,f}- Co

62 Shadows - Example 4 5 c E h g 6 d C i D b 3 e f B a 2 1 A
Our map is a prism. All flags (structured by type): ;, 1,2,3,4,5,6 a,b,c,d,e,f,g,h,i A,B,C,D,E 1a,1d,1e,2a,2b,2f,3e,3f,3i,4c,4d,4h,5b,5c,5g,6g,6h,6i 1A,1B,1C,2A,2B,2D,3B,3C,3D,4A,4C,4E,5A,5D,5E,6C,6D,6E aA,aB,bA,bD,cA,cE,dA,dC,eB,eC,fB,fD,gD,gE,hC,hE,iC,iD 1aA,1aB,1dA,1dC,1eB,1eC,2aA,2aB,2bA,2bD,2fB,2fD,3eB,3eC,3fB,3fD,3iC,3iD,4cA,3cE,4dA,4dC,4hC,4hE,5bA,5bD,5cA,5cE,5gD,5gE,6gD,6gE,6hC,6hE,6iC,8iD 4 5 c E h g 6 d C i D b 3 e f B a 2 1 A

63 Shadows - Example - Primal
Our map is a prism. T ={v,e,f}: J = {v} J-flags: 1, 2, 3, 4, 5, 6 Sets: 12, 13, 14, 23, 25, 36, 45, 46, 56, 123, 456, 1245, 1346, 2356. 4 5 c E h g 6 d C i D b 3 e f B a 2 1 A

64 Shadows - Example - Dual
Our map is a prism. T = {v,e,f}: J = {f} Flags: A,B,C,D,E Sets: AB, AC, AD, AE, BC, BD, CD, CE, DE, ABC, ABD, BCD, CDE, ACE, ADE. 4 5 c E h g 6 d C i D b 3 e f B a 2 1 A

65 Shadows - Example - Medial
Our map is a prism. T = {v,e,f}: J = {e} Flags: a,b,c,d,e,f,g,h,i Sets: ae,ab,ad,af,bc,bf,bg,cd,cg,ch,de,dh,ef,ei,fi,gh,gi,hi, aef, bfgi, dehi, abcd,cgh. 4 5 c E h g 6 d C i D b 3 e f B a 2 1 A

66 Shadows - Example - Truncation
Our map is a prism. T = {v,e,f}: J = {v,e} Flags: 1a,1d,1e,2a,2b,2f,3e,3f,3i,4c,4d,4h,5b,5c,5g,6g,6h,6i Sets: 1a,1d,1e,2a,2b,2f,3e,3f,3i,4c,4d,4h,5b,5c,5g,6g,6h,6i ... 4 5 c E h g 6 d C i D b 3 e f B a 2 1 A

67 Posets Let (P,·) be a poset. We assume that we add two special (called trivial) elements, 0, and 1, such that for each x 2 P, we have 0 · x · 1.

68 Ranked Posets Note that a ranked poset (P,·) of rank n has the property that there exists a rank function r:P ! {-1,0,1,...,n}, r(0) = -1, r(1) = n and if y covers x then r(y) = r(x) +1. If we are given a poset (P, ·) with a rank function r, then such a poset defines a natural incidence geometry. V(G) = P. x ~ y if and only if x < y. c(x) := r(x). Vertex color is just the rank.

69 Intervals in Posets Let (P,·) be a poset.
Then I(x,z) = {y| x · y · z} is called the interval between x and z. Note that I(x,z) is empty if and only if x £ z. I(x,z) is also a ranked poset with 0 and 1.

70 Connected Posets. A ranked poset (P,·) wih 0 and 1 is called connected, if either rank(P) = 1 or for any two non-trivial elements x and y there exists a sequence x = z0, z1, ..., zm = y, such that there is a path avoiding 0 and 1 in the Levi graph from x to y and the rank function is changed by § 1 at each step of the path.

71 Abstract Polytopes Peter McMullen and Egon Schulte define abstract polytopes as special ranked posets. Their definition is equivalent to the following: (P,·) is a ranked poset with 0 and 1 (minimal and maximal element) For any two elements x and z, such that r(z) = r(x)+2, x < z there exist exactly two elements y1, y2 such that x < y1 < z, x < y2 < z. Each section is connected. Note that abstract poytopes are a special case of posets but they form also a generalization of the convex polytopes.

72 Convex vs abstract polytopes
To each convex polytope we may associate an abstract polytope. For instance, the tetrahedron: 4 vertices: v1, v2, v3, v4. 6 edges: e1, e2, ..., e6, 4 faces: t1,t2,t3, t4 1 e1 = v1v2, e2 = v1v3, e3 = v1v4, e4 = v2v3, e5 = v2v4, e6 = v3v4. t4 = v1v2v3, t1 = v2v3v4, t3 = v1v2v4, t2 = v1v3v4.

73 The Poset In the Hasse diagram we have the following local picture: 1

74 Diagram geometries For any incidence geometry G(V,~,T,c) we usually study for each pair i,j 2 T the section (truncation) of rank two: G/(i,j). We deliberatly make distinction between G/(i,j) and its dual G(j,i). Sometimes each connected component of G/(i,j) has the same structure. This is indicated by a diagram. A diagram in an edge-labeled graph on the vertex set T, where the lables indicate the structure of each section.

75 String diagram geometries
The edge between i an j is omitted if and only if G/(i,j) is a generalized digon. This means that each connected component is a complete bipartite graph. G is called a string diagram geometry if the corresponding diagram has a shape of a path (or union of paths). Example: Each abstract polytope is a string diagram geometry.

76 The Grassmann graph Let G(V,~,T,c) be an incidence geometry and let i 2 T be a type. Then we define the Grassmann graph G(i) to on the vertex set V(i) = {v 2 V| c(v) = i} and two vertices u and v are adjacent in G(i) if an only if for each j  i there exists an w 2 V(j) such that u ~ w and w ~ v (in the original geometry.) Example: For instance, in the case of rank two geometries, the Grassmann graphs are exactly the Menger graph and the dual Menger graph.

77 Exercises 4-1 N1. Our map is a prism. I = {v,e,f}: 4 5 c E h g 6 d C i
For each set of type J = {v,f} J = {e,f} J = {v,e,f} determine the shadow space. 4 5 c E h g 6 d C i D b 3 e f B a 2 1 A

78 Exercises 4-2 N2. Repeat the analysis of previous two slides for the simplex K5. N3. Repeat the analysis of the previous two slides for the generalized octahedron K2,2,2,2.

79 Exercises 4-3 N4: Determine all residual geometries of Reye’s configuration N5: Determine all residual geometries of Q4. N6: Determine all residual geometries of the Platonic solids. N7: Determine the Levi graph of the geometry for the group Z2 £ Z2 £ Z2, with three cyclic subgroups, generated by 100, 010, 001, respectively.

80 Exercises 4-4 N18: Determine the posets and Levi graphs of each of the polytopes on the left. Solution for the haxagonal pyramid: 7 vertices: v0, v1, v2, ..., v6. 12 edges: e1, e2, ..., e6, f1, f2, ..., f6 7 faces: h,t1,t2,t3,.., t6 1 e1 = v1v2, e2 = v2v3, e3 = v3v4, e4 = v4v5, e5 = v5v6, e6 = v6v1, f1 = v1v0, f2 = v2v0,f3 = v3v0, f4 = v4v0, f5=v5v0, f6 = v6v0. h = v1v2v3v4v5v6, t1 = v1v2v0, t2 = v2v3v0, t3 = v3v4v0, t4 = v4v5v0, t5 = v5v6v0, t6 = v6v1v0,

81 5. Incidence Structures

82 Incidence structure An incidence structure C is a triple
C = (P,L,I) where P is the set of points, L is the set of blocks or lines I  P  L is an incidence relation. Elements from I are called flags. The bipartite incidence graph G(C) with black vertices P, white vertices L and edges I is known as the Levi graph of the structure C.

83 (Combinatorial) Configuration
A (vr,bk) configuration is an incidence structure C = (P,L,I) of points and lines, such that v = |P| b = |L| Each point lies on r lines. Each line contains k points. Two lines intersect in at most one point. Warning: Levi graph is semiregular of girth  6

84 Symmetric configurations
A (vr,bk) configuration is symmetric, if v = b (this is equivalent to r = k). A (vk,vk) configuration is usually denoted by (vk).

85 Small Configurations Triangle, the only (32) configuration.
Pasch configuration (62,43) and its dual Perfect Quadrangle (43,62) have the same Levi graph.

86 6. Substructures, Symmetry and Duality

87 Substructures An incidence structure C’ = (P’, L’,I’) is a substructure of an incidence structure C = (P, L,I), C’ µ C, if P’ µ P, L’ µ L and I’ µ I.

88 Duality Each incidence structure C = (P,L,I) gives rise to a dual structure Cd = (L,P,Id) with the role of points and lines reversed and keeping the incidence. The structures C and Cd share the same Levi graph with the roles of black and white vertices reversed.

89 Self-Duality and Automorphisms
If C is isomorphic to its dual Cd , it is said that C is selfdual, the corresponding isomorphism is called a (combinatorial) duality. A duality of order 2 is called (combinatorial) polarity. An isomorphism mapping C to itself is called an automorphism or (combinatorial) collinearity.

90 Automorphisms and Antiautomorphisms
Automorphisms of the incidence structure C form a grup that is called the group of automorphisms and is denoted by Aut0C. If automorphisms and dualities (antiautomorphisms) are considered together as permutations, acting on the disjoint union P  L, we obtain the extended group of automorphism Aut C. Warning: If C is disconnected there may be mixed automorphisms.

91 Graphs and Configurations
The Levi graph of a configuration is bipartite and carries complete information about the configuration. Assume that C is connected. The extended group of automorphisms AutC coincides with the group of automorphisms of the Levi graph L ignoring the vertex coloring, while Aut0C stabilises both colors.

92 Examples 1. Each graph G = (V,E) is an incidence structure: P = V, L = E, (x,e) 2 I if and only if x is an endvertex of e. 2. Any family of sets F µ P(X) is an incidence structure. P = X, L = F, I = 2. 3. A line arrangement L = {l1, l2, ..., ln} consisting of a finite number of n distinct lines in the Euclidean plane E2 defines an incidence structure. Let V denote the set of points from E2 that are contained in at least two lines from L. Then: P = V, L = L and I is the point-line incidence in E2.

93 Exercises 6 N1: Draw the Levi graph of the incidence structure defined by the complete bipartite graph K3,3. N2: Draw the Levi graph of the incidence structure defined by the powerset P({a,b,c}). N3: Determine the Levi graph of the incidence structure, defined by an arrangemnet of three lines forming a triangle in E2.

94 7. Haar Graphs and Cyclic Configurations

95 Haar graph of a natural number
Let us write n in binary: n = bk-12k-1 + bk-2 2k b12 + b0 where B(n) = (bk-1, bk-2, ..., b1, b0), bk-1= 1are binary digits of n. Graph H(n) = H(k; n), called the Haar graph of the natural number n, has vertex set ui, vi, i=0,1,...,k-1. Vertex ui is adjacent to vi+j, if and only if bj = 1 (arithmetic is mod k).

96 Remark When defininig H(n) we assumed that k is the number of binary digits of n. In general, for H(k;n) one can take k to be greater than the number of binary digits. In such a case a different graph is obtained!

97 Example Determine H(37). Binary digits: B(37) = {1,0,0,1,0,1} k = 6.
H(37) = H(6;37) is depicted on the left!

98 Dipoles qn The dipole qn has two vertices, joined by n parallel edges. If we want to distinguish the two vertices, we call one black, the other one white. On the left we see q5. Each dipole is a bipartite graph. Therefore each of its covering graphs is a bipartite graph. In particular q3 is a cubic graph also known as the theta graph q.

99 Cyclic covers over a dipole
Each Haar graph is a cyclic cover over a dipole. One can use the following recipe: H(37) is determined by a natural number 37, or, equivalently by a binary sequence:( ). The length is k=6, therefore the group Z6. The indices are written below: ( ) ( ) The “1”s appear in positions: 0, 3 in 5. These numbers are used as voltages for H(37). 3 5 Z6

100 Connected Haar graphs Graph G is connected if there is a path between any two of its vertices. There exist disconnected Haar graphs, for instance H(10). Define n to be connected, if the corresponding Haar graph H(n) is connected. Disconnected numbers: 2,4,8,10,16,32,34,36,40,42,64...

101 The Mark Watkins Graph The cubic Haar graph H( ) has an interesting property is the smallest connected number that is cyclically equivalent to no odd number. Recall that two sets S,T µ Zn are cyclically equivalent if there exists a 2 Zn* and b 2 Zn such that S = aT + b (mod n).

102 Girth of Connected Haar graphs
K2 is the only connected 1-valent Haar graph. Even cycles C2n are connected 2-valent Haar graphs. Theorem: Let H be a connected Haar graph of valence d > 2. Then either girth(H) = 4 or girth(H) = 6.

103 Cyclic Configurations
A symmetric (vr) configuration determined by its first column s of the configuration table where each additional column is obtained from s by addition (mod m) is called a cyclic configuration Cyc(m;s). The left figure depicts a cyclic Fano configuration Cyc(7;1,2,4) = Cyc(7;0,1,3). a b c d e f g k 1 2 3 4 5 6 k+1 k+3

104 Connection to Haar graphs
Theorem: A symmetric configuration (vr), r ¸ 1 is cyclic, if and only if its Levi graph is a Haar graph with girth ¹ 4. Corollary: Each cyclic configuration is point- and line-transitive and combinatorially self-dual. Corollary: Each cyclic configuration (vr), r > 2 contains a triangle. Question: Does there exist a cyclic configuration that is not combinatorially self-polar?

105 Problem Study cyclic configurations with respect to flag orbits.
Example: On the left we see the smallest 0-symmetric graph Haar(261) on 18 vertices. It is the Levi graph of the cyclic (93) configuration having 3 flag orbits.

106 Exercises 7-1 The graph on the left is the so-called Heawood graph H. Prove: N1: H is bipartite N2: H is a Haar graph. (Find n!) N3: Determine H as a cyclic cover over q3.. N4: Prove that H has no cycle of length < 6. N5: Prove that H is the smallest cubic graph of girth 6. N6: Find a hexagonal torus embedding of H . N7: Determine the dual of the embedded H.

107 Exercises 7-2 N8: Prove that each 2m is a disconnected number.
N9: Show that the Möbius-Kantor graph G(8,3) is a Haar graph of some number. Which number is that? N10: (*) Determine all generalized Petersen graphs that are Haar graphs of some natural number. N11: Show that some Haar graphs are circulants. N12: Show that some Haar graphs are non-circulants.

108 Exercises 7-3 N13: Prove that each Haar graph is vertex transitive.
N14: Prove that each Haar graph is a Cayley graph for a dihedral group. N15: Prove that there exist bipartite Cayley graphs of dihedral groups that are not Haar graphs (such as the graph on the left).

109 Exercises 7-4 N16: The numbers n and m are cyclically equivalent, if the binary string of the first number can be cyclically transformed to the binary string of the second number. This means that the string can be cyclically permuted, mirrored or multiplied by a number relatively prime with the string length. N17: The numbers n and m are Haar equivalent, if their Haar graphs are isomorphic: H(n) = H(m). N18: Prove that cyclic equivalence implies Haar equivalence. N19: Determine all numbers that are cyclically equivalent to 69. N20: Use a computer to show that and are Haar equivalent, but are not cyclically equivalent.

110 Exercises 7-5 N21: Show that each Haar graph of an odd number H(2n+1) is hamiltonian and therefore connected.

111 Homework 7 Use Vega to explore the edge-orbits of cyclic Haar graphs.
H1. Find an example of a cubic Haar graph that has 1,2, or 3 edge orbits. H2. Find an example of a quartic Haar graph that has 1, 2, 3, or 4 edge orbits. Study the graphs with 2 edge orbits.

112 8. Algebraic Structures

113 Real Numbers R. Let us review the structure of the set of real numbers (real line) R. In particular, consider addition + and multiplication £. (R,+) forms an abelian group. (R,£) does not form a group. Why? (R,+,£) forms a (commutative) field.

114 Real Numbers R. - Exercises
N43: Write down the axioms for a group, abelian group, a ring and a field. N44: What algebraic structure is associated with the integers (Z,+,£)? N45: Draw a line and represent the numbers R. Mark 0, 1, 2, -1, ½, p.

115 A Skew Field K A skew field is a set K endowed with two constants 0 and 1, two unary operations -: K ! K, ‘: K ! K, and with two binary operations: +: K £ K ! K, ­: K £ K ! K, satisfying the following axioms: (x + y) + z = x + (y +z) [associativity] x + 0 = 0 + x = x [neutral element] x + (-x) = 0 [inverse] x + y = y + x [commutativity] (x ­ y) ­ z = x ­ (y ­ z). [associativity] (x ­ 1) = (1 ­ x) = x [unit] (x ­ x’) = (x’ ­ x) = 1, for x ¹ 0. [inverse] (x + y) ­ z = x ­ z + y ­ z. [left distributivity] x ­ (y + z) = x ­ y + y ­ z. [right distributivity] A (commutative) field satisfies also: x ­ y = y ­ x.

116 Examples of fields and skew fields
Reals R Rational numbers Q Complex numbers C Quaterions H (non-commutative!! Will consider briefly later!) Residues mod prime p: Fp Residues mod prime power q = pk: Fq (more complicated, need irreducible poynomials!!Will consider briefly later!)

117 Complex numbers C a = a + bi 2 C a* = a – bi b = c + di 2 C
ab = (ac –bd) + (bc + ad)i b ¹ 0, a/b = [(ac + bd) + (bc – ad)i]/[c2 + d2] a-1 = (a –bi)/(a2 + b2)

118 Quaternions H. Quaternions form a non-commutative field. General form:
q = x + y i + z j + w k., x,y,z,w 2 R. i 2 = j 2 = k 2 =-1. q = x + y i + z j + w k. q’ = x’ + y’ i + z’ j + w’ k. q + q’ = (x + x’) + (y + y’) i + (z + z’) j + (w + w’) k. How to define q .q’ ? i.j = k, j.k = i, k.i = j, j.i = -k, k.j = -i, i.k = -j. q.q’ = (x + y i + z j + w k)(x’ + y’ i + z’ j + w’ k)

119 Quaternions H. - Exercises
N46: There is only one way to complete the definition of multiplication and respect distributivity! N47: Represent quaternions by complex matrices (matrix addition and matrix multiplication)! Hint: q = [a b; -b* a*]. (We are using Matlab notation). a b -b* a*

120 Residues mod n: Zn. Two views: Zn = {0,1,..,n-1} Define ~ on Z:
x ~ y $ x = y + cn Zn = Z/~ (Zn,+) is an abelian group, namely a cyclic group. Here + is taken mod n!!!

121 Example (Z6, +). + 1 2 3 4 5

122 Example (Z6, £). 1 2 3 4 5

123 Example (Z6\{0}, £). £ 1 2 3 4 5 It is not a group!!!
For p prime, (Zp\{0}, £) forms a group: (Zp, +,£) = Fp. 1 2 3 4 5

124 Vector space V over a field K
+: V £ V ! V (vector addition) .: K £ V ! V (scalar multiple) (V,+) abelian group (l + m)x = l x + m x 1.x = x (l m).x = l(m x) l.(x +y) = l.x + l.y

125 9. Euclidean Plane, Affine Plane, Projective Plane

126 Euclidean plane E2 and real plane R2
R2 = {(x,y)| x,y 2 R} R2 is a vector space over R. The elements of R2 are ordered pairs of reals. (x,y) + (x’,y’) = (x+x’,y+y’) l(x,y) = (l x,l y) We may visualize R2 as an Euclidean plane (with the origin O).

127 Subspaces One-dimensional (vector) subspaces are lines through the origin. (y = ax) One-dimensional affine subspaces are lines. (y = ax + b) y = ax + b y = ax o

128 Three important results
Thm1: Through any pair of distinct points passes exactly one affine line. Thm2: Through any point P there is exactly one affine line l’ that is parallel to a given affine line l. Thm3: There are at least three points not on the same affine line. Note: parallel = not intersecting or identical!

129 Affine Plane Axioms: A1: Through any pair of distinct points passes exactly one line. A2: Through any point P there is exactly one line l’ that is parallel to a given line l. A3: There are at least three points not on the same line. Note: parallel = not intersecting or identical!

130 Examples Each affine plane is an incidence structure C = (P,L,I) of points and lines. Let K be a field, then K2 has a structure of an affine plane. K = Fp. Determine the number of points and lines in the affine plane A2(p) = Fp2.

131 Parallel Lines Parallel lines l || m define an equivalence relation on the set of lines. l || l l || m ) m || l l || m, m || n ) l || n.

132 A pencil of parallel lines
An equivalence class of parallel lines is called a pencil of parallel lines. Thm. Each pencil of parallel lines defines an equivalence relation on the set of lines.

133 Ideal points and Ideal line
Each pencil of parallel lines defines a new point, called an ideal point (or a point at inifinity.) New point is incident with each line of the pencil. In addition we add a new ideal line (or line at infinity)

134 Extended Plane Let A be an arbitrary affine plane. The incidence structure obtained from A by adding ideal points and ideal lines is called the extended plane and is denoted by P(A). Theorem. Let C be an extended plane obtained from any affine plane. The following holds: T1. For any two distinct points P and Q there exists a unique line l connecting them. T2. For any two distinct lines l and m there exists a unique point P in their intersection. T3. There exist at least four points P,Q,R,S such that no three of them are colinear.

135 Projective Plane Axioms for the Projective Plane. Let C be an incidence structure of points and lines that satisfies the following axioms: P1. For any two distinct points P and Q there exists a unique line l connecting them. P2. For any two distinct lines l and m there exists a unique point P in their intersesction. P3. There exist at least four points P,Q,R,S such that no three of them are colinear.

136 Linear Transformations
In a vector space the important mappings are linear transformations: L(l x + m y) = l L(x) + m L(y). L-1 exists. L can be represented by a nonsingular square matrix.

137 Semi Linear Transformations
A semi linear transformation is more general: L(lx + m y) = f(l) L(x) + f(m) L(y). L-1 exists, f: K ! K is an automorphism of K.

138 Affine Transformations
In an affine plane the important mappings are affine transformations (=affinities). An affine transformation maps sets of collinear points to collinear points. Each affine transformation is of the form A(x) + c, where A is a semilinear transformation.

139 Projective plane from R3
Consider the incidence structure defined by 1-dimensional and 2-dimensional subspaces of R3 where the incidence is defined by inclusion. Call 1-dimensional subspaces points and 2-dimensional subspaces lines.

140 Homogeneous Coordinates
Let (a,b,c) ¹ (0,0,0) be a point in R3. There is exactly one line through the origin passing through (a,b,c). Hence a projective point can be represented by (a,b,c). However, for any l ¹ 0 the same projective point can be represented by (l a, l b, l c). That is why (a,b,c) are called homogeneous coordinates.

141 Unit sphere model Take a unit sphere in R3.
Let pairs of antipodal points be projective points. Let big circles be projective lines. Prove that this system is a model for a projective plane.

142 Stereographic Projection
There is a homeomorphic mapping of a sphere without the north pole N to the Euclidean plane R2. It is called a stereographic projection. Take the unit sphere x2 + y2 + z2 = 1 and the plane z = 0. The mapping p: T0(x0,y0,z0) a T1(x1,y1) is shown on the left. N T0 T1

143 Stereographic Projection
The mapping p: T0(x0,y0,z0) a T1(x1,y1) is shown on the left. r1 = r0/(1-z0) x1 = x0/(1-z0) y1 = y0/(1-z0) N T0 T1

144 Example Take the Dodecahedron and a random point N on a sphere.
Stereographic projection is depicted below. A better strategy is to take N to be a face center.

145 Example A better strategy is to take N to be a face center as shown on the left.

146 Exercises 9-1 N1. Conditions 1. and 2. are true for any incidence structure. (Prove it!) N2: Prove condition 3 for affine planes and find a counter-example for general incidence structure. N3. Prove that this structure satisfies all three axioms for the projective plane. N4: Prove that in R, Q, Fp, (p- prime) there are no nontrivial automorphisms.

147 Exercises 9-2 N5: Prove that z a z* (conjugate) is an automorphism of C. N6: Go to the library or the internet and find a reference to the group of authomorphisms of the complex numbers C and the quaternions H. N7: Determine the size of the group of automorphisms of Fq, for q = pk, a power of a prime.

148 10. Point Configurations, Line Arrangements, Polarity

149 Point Configuration A point configuration in R2 is a collection of points affinely spanning R2. In other words: not all points are collinear.

150 Line Arrangement A line arrangement is a partitioning of the plane R2 into connected regions (cells, edges, and vertices) induced by a finite set of lines.

151 Area of a Triangle Area of the green trapezoid: In the same way:
A12= (1/2)(y2 +y1) (x2 – x1) In the same way: A23= (1/2)(y2 +y3) (x3 – x2) A13= (1/2)(y3 +y1) (x3 – x1) Area of the triangle: T = A12 + A23 – A13. P2(x2,y2) y2 y1 P1(x1,y1) y3 P3(x3,y3) O x1 x2 x3

152 Area of a Triangle P2(x2,y2) y2 y1 P1(x1,y1) y3 P3(x3,y3) O x1 x2 x3

153 Triple of Collinear Points
P2(x2,y2) y2 y1 P1(x1,y1) y3 P3(x3,y3) O x1 x2 x3 The points P1(x1,y1), P2(x2,y2), P3(x3,y3), are collinear if and only if T = 0.

154 Point Configurations – Line Arrangements
Each point configuration S gives rise to a line arrangement A(S). The lines are determined by all pairs of points. Another line arrangement A3(S) is determined by triples of collinear points.

155 Polarity with Respect to a Circle
Let us consider the extended plane and a circle K in it. There is a mapping from points to lines (and vice versa). p: p a P. p – polar P – pole N53: Determine the polar of an ideal point and the pole of the ideal line. P p P p P

156 Polarity with respect to the unit circle
Given P(a,b) the equation of the polar is p: y = (-a/b)x + (1/b) p: by + ax = 1 In general: p: y(b-q) + x(a-p) = p(a-p) + q(b-q) + r2. Given p: y = kx + n P(a,b) a = -k/n b = 1/n a = p-kr2/(kp + n – q) b = q+ r2/(kp + n –q)

157 Natural Parameters p,q,r
For a given point configuration S the center of the circle(p,q) is determined as the barycenter of S while the radius is given as the average distance from the center.

158 Polarity in General A general polarity is defined with respect to a conic section (ellipse, hyperbola, or parabola).

159 Polar Duality of Vectors and Central Planes in R3.
A polar duality is a mapping associating a vector v 2 R3 with an oriented central plane having v as its normal vector and vice versa.

160 A Standard Affine Polar-Duality
A standard affine polar duality is a mapping between non-vertical lines and points of R2 associating the non-vertical line y = ax + b with the point (a,-b) and vice versa.

161 Polar Duality of Points and Lines in the Affine Space.
General rule: Take a polar-duality of vectors and central planes and consider the intersetion with some affine plane in R3 .

162 Homogeneous Coordinates
Take the affine plane z = 1. A point with Euclidean coordinates (x,y) can be assigned the homogeneous coordinates (x,y,1). Ideal points get homogeneous coordinates (x,y,0). (z0x0,z0y0,z0) (x0,y0,1) (x0,y0)

163 Equation of a plane through the origin
Recall general plane: ax + by + cz = d. Equation of a plane through the origin: ax + by + cz = 0- Another meaning: (x,y,z) homogeneous coordinates of a projective point [a,b,c] homogeneous coordinates of a projective line.

164 Point on a Line Let (a,b,c) be homogeneous coordinates of a point P and let [A,B,C] be homogeneous coordinates of a line p. Then P lies on p if and only if aA + bB + cC = 0. Let P(a,b,c) and P’(a’,b’,c’). The equation of a line through P Æ P’. is defined by the cross product [A,B,C] = (a,b,c) £ (a’,b’,c’). Similarly we get the intersection of two lines.

165 Example Polarity of a point configuration consisting of the points of a 10 £ 10 grid. Parameters of the circle are determined automatically.

166 Star Polygons (n/k). By (n/k) we denote star polygons.
Note that each of them defines an incidence structure. in which the points are the vertices and intersections while the lines are the edges of a polygon. 3/1 4/1 5/1 5/2 6/1 6/2 7/1 7/2 7/3

167 Fano Plane 1 We obtain the Fano plane from F23. There are obviously 7 (non-zero) points: Any pair of points defines a unique line that contians exactly one additional point.

168 Exercises 10-1 A polarity maps a point configuration to a line arrangement and vice versa. N1:Take an equilateral triangle ABC with sides a,b,c. Find a polarity, such that a a A, b a B and c a C. N2: Determine the polar figure of point configuration determined by the vertices of a regular n-gon with respect to its inscribed circle.

169 Exercises 10-2 N3: Determine the number of points and lines of the incidence structure defined by the star polygon 5/2. N4(*): Determine the number of points and lines of the incidence structure determined by the star polygon n/k.

170 11. Pappus and Desargues Theorem

171 Pappus Theorem C Let A, B, C be three collinear points and let A', B' , C' be another triple of collinear points. Let A'' be the intersection of (BC') and (B'C), B'' the intersection (A,C') and (A'C), C'' the intersetion of (AB') and (A'B). Then the points A'', B'' and C'' are collinear. B A A'' B'' C'' A' B' C'

172 Desargues Theorem B'' B' Let ABC and A'B'C' be two triangles. Let A'' be the intersection of BC and B'C', let B'' be the intersection of AC and A'C' and C'' be the intersection of AB and A'B'. The lines AA',BB' and CC' intersect in a common point O if and only if A'', B'' and C'' are collinear. A' C'' A O B C C' A''

173 Ternary ring coordinatization.
[b] Ternary operation, desrcibed in geometric terms. Properties: (a) x*0*b = 0*x*b=b (b)x*1*0 = 1 * x * 0 = x (c) Given x,y,a, there is a unique b such that y = x*a*b (d) Given x,x’,y,y’ with x ¹ x’ there is a unique ordered pair (a,b) such that y = x*a*b and y’=x’*a*b. (e) Given a,a’,b,b’ with a ¹ a’, there is a unique x such that x*a*b=x*a’*b’. [0,a*b*c] [b] [0,c] [0,b] [1,b] [0,0] [1,0] [a,0]

174 Pappian and Desarguesian Projective Planes
Thm. A projective plane is desarguesian if and only if the ternary ring is a field or a sqew-field. Thm. A projective plane is pappian if an only if the ternary ring is a field.

175 Non-Desarguesian Projective Plane
F.R.Multon (1902) Points: points in the real projective plane. Lines: y = mx+n, m· 0. y = mx + n, x¸(-n/m), m¸0 y = (m/2)x + n), m¸0,y·0. Line at infinity contains points [m].

176 Exercises 11 N1(*): Prove the Pappus theorem in the Euclidean plane.
N2(*): Prove the Desargues theorem in the Eucliudean plane.

177 12. Existence and Counting of Combinatorial Configurations

178 Lineal Configurations
In order to emphasise configurations as partial linear spaces we call them lineal configurations (= digon – free configurations).

179 Existence of Lineal Configurations
Proposition: For each lineal (vr,bk) configuration (r ¸ k) the following is true: v.r = b.k b ¸ v ¸ 1 + r(k – 1) Corollary: For symmetric (vk) configurations the following lower bound is obtained: v ¸ 1 + k(k-1) = 1 –k + k2 In particular: For k = 3 we have v ¸ 7, For k = 4 we have v ¸ 13, For k = 5 we have v ¸ 21.

180 Lower Bounds (Adapted from Grünbaum)
r\k 3 4 5 6 7 (73) (123,94) (203,125) (263,136) (353,157) (94,123) (134) (204,165) ?(304,206)? ?(494,,287)? (125,203) (165,204) (215) (305,256) ?(425,307)? (136,263) ?(206,304)? (256,305) (316) X(496,427)X (157,353) ?(287,494)? ?(307,425)? X(427,496)X X(437)X

181 Blocking Set A set of points B of an incidence structure is called a blocking set, if each line L contains two points x and y, such that: x 2 B and (x,L) 2 I, y Ï B and (y,L) 2 I.

182 Notation

183 Counting (v3) Configurations

184 Counting Triangle-Free (v3) Configurations

185 13. Coordinatization

186 Coordinatization m11 m12 ... m1n m21 m22 m2n m31 m32 m3n
Reconstruct an incidence structure from a matrix M: Columns are homogeneous coordinates in some field or sqew-field F. <ijk> = det (Mi Mj Mk) ijk form a line if and only if <ijk> = 0. m11 m12 ... m1n m21 m22 m2n m31 m32 m3n

187 Fano plane (73). We can reconstruct (73) from the matrix M.
Columns are homogeneous coordinates in F2. <ijk> = det (Mi Mj Mk) ijk form a line if and only if <ijk> = 0. 1

188 Menger Graph on Torus On the left there is a hexagonal embedding of the Heawood graph in the torus. (Heawood = Levi graph of Fano) Its dual is a triangular embedding of K7 in S2.

189 Menger Graph on Torus Menger graph (of Fano) is K7 and has a triangular embedding in torus. (Consider only red vertices). Later we show how to generalize this construction.

190 Möbius-Kantor Configuration – Revisited
Möbius-Kantor configuration is the only (83) configuration. Its Levi graph is the generalized Petersen graph G(8,3). The configuration has no geometric realization with (real) points and lines in the Euclidean plane.

191 Affine plane of order 3 2 1 3 4 5 6 7 8 9 (94,123) configuration is the affine plane of order 3. It contains the Pappus configuration. It contains also the Möbius-Kantor configuration.

192 Complex Coordinatization of (94,123)

193 A Z3 coordinatization of (134) = PG(2,3)

194 A Z3 coordinatization of (123, 94)
By removing one point from the projective plane we get the affine plane. (Its dual is (94,123))

195 Dual coordinates and dual lines

196 Möbius-Kantor Configuration – Revisited
Möbius-Kantor configuration is coordinatizable over the complex field and over F3. Something is wrong here. I expected that one can change -1 ! 2  ! 2 in the top matrix, and get the desired coordinatization. But columns 1 and 4 become identical. -1 1 a -1 1 a

197 Complex Coordinatization of (83)
By removing one point (and 4 incident lines) we get (83) from (94,124).

198 Exercises 13 N1: Determine the homogeneous coordinates of the 9 lines from the previous problem. N2: Write a computer program that will find the matrix for the polar. N3:Show that by deleting any column of the matrix for (94,123) a coordinatization of (83) is obtained. N4: Given the Levi graph G(8,3) of (83), determine the Levi graph of (94,123).

199 14. Combinatorial Configurations on Surfaces

200 Menger graph of Möbius-Kantor Configuration
Menger graph of this configuration is depleated K8: DK8 = K8 – 4K2 Vertices represent configuration points while triangles represent lines.

201 Möbius-Kantor Graph in Double Torus
The Möbius-Kantor graph is embedded in the double torus such that: The embedding is octagonal. The map is regular.

202 Möbius-Kantor Graph in Double Torus
This embedding of the Möbius-Kantor graph gives rise to an embedding of the Menger graph DK8 in the same surface with 8 triangles and 6 quadrilaterals. By adding 4 missing edges we get an embedding of K8 in the double torus with all triangles, except for two quadrilaterals.

203 The Dual The dual graph is S[2](K4).
Let G be any graph. Recall that S(G) is the subdivision graph. S[k](G) is obtained from S(G) by multiplying the original vertices of G k times.

204 Pappus configuration Pappus (93) configuration can be represented in the plane by exhibiting homogeneous coordinates for each point (a,b,c). Each line can be described in a similar way: [p,q,r] where the incidence is given by ap+bq+cr=0. This can be considered as an example of an orthogonal representation of (Levi) graphs where u~v implies r(u) ^ r(v).

205 Pappus Graph on Torus Collection of hexagons: {10, 17, 18, 13, 12, 11}
{8, 15, 16, 17, 10, 9} {7,12, 13, 14, 15, 8} {4, 11, 12, 7, 6, 5} {3,4, 5, 16, 15, 14} {2, 9, 10, 11, 4, 3} {1, 2, 3, 14, 13, 18} {1, 18, 17, 16, 5, 6} {1, 6, 7, 8, 9, 2} Euler formula: = 0 g = 1

206 Three (93) Configurations

207 Three (93) Configurations
They are all combinatorially self-polar. Pappus (red) Cyclic (green) Non-cyclic (yellow?).

208 Three (93) Configurations
List of faces: {5, 11, 14, 7, 15, 16, 12, 6} {4, 10, 18, 17, 11, 5} {3, 9, 17, 18, 12, 16, 8, 13, 10, 4} {2, 8, 16, 15, 9, 3} {1, 2, 3, 4, 5, 6} {1, 6, 12, 18, 10, 13, 14, 11, 17, 9, 15, 7} {1, 7, 14, 13, 8, 2} Euler formula: V = 18, E = 27, F = 7 = -2 = 2 - 2g. g = 2

209 Three (93) Configurations
List of faces: {10, 16, 15, 11, 17, 18} {8, 18, 17, 9, 14, 13} {7, 15, 16, 12, 13, 14} {4, 5, 6, 12, 16, 10} {3, 9, 17, 11, 5, 4} {2, 3, 4, 10, 18, 8} {1, 2, 8, 13, 12, 6} {1, 6, 5, 11, 15, 7} {1, 7, 14, 9, 3, 2} g = 1.

210 Menger and Levi - Pappus

211 Menger and Levi – Non-Cyclic

212 Menger and Levi - Cyclic

213 Again - Shaken (coordinates slightly perturbed)

214 Menger and Its Complement of G(10,3)

215 Genus of G(10,3) is 2. List of faces: {6, 7, 17, 20, 13, 16}
{5, 6, 16, 19, 12, 15} {4, 5, 15, 18, 11, 14} {3, 13, 20, 10, 9, 8, 7, 6, 5, 4} {2, 3, 4, 14, 17, 7, 8, 18, 15, 12} {1, 2, 12, 19, 9, 10} {1, 10, 20, 17, 14, 11} {1, 11, 18, 8, 9, 19, 16, 13, 3, 2} Euler formula: V - E + F = 2 - 2g. = -2 = 2 - 2g. g = 2.

216 Clebsch hexagon

217 Clebsch hexagon – revisited

218 Clebsch graph

219 Hypercube Q4

220 Clebsch graph – revisited
Connection to hypercube?

221 Exercises 14 N1: Show that each (93) configuration is combinatorially self-polar. N2: Determine the groups of automorphisms and extended automorphisms. N3: Show that the genus of two configurations is 1 while the genus of the third one is 2. Make models! N4: Determine the three Menger graphs and their duals on the minimal surfaces. N5: Prove that the complements of the three Menger graphs are respectively C9, C6 [ C3, 3C3.

222 15. Generalized Polygons

223 Generalized Polygons A generalized polygon is a bipartite graph of diameter d and girth 2d. (From Godsil and Royle) Any Km,n is a generalized 2-gon.

224 Near-Pencil N(n) is a near-pencil (or degenerate projective plane) with n+1 points and n+1 lines with the incidence shown on the left. N(4)

225 Projective Space PG(3,q)
Let V = Fq4 be the four-dimensional vector space over the field of order q and let PG(3,q) be the corresponding projective space. There are (q4 – 1)/(q-1) = (q + 1)(q2 + 1) projective points in PG(3,q).

226 The Matrix H The matrix H 2 Fq4 £ Fq4 is defined below.

227 Totally Isotropic Subspace S of V.
A subspace S ½ V is totally isotropic if uT H v = 0 for all u,v 2 S. Each one-dimensional subspace S is totally isotropic: uT H u = 0. A two-dimensional subspace S, spanned by u and v: S = span{u,v} is totally isotropic if and only if uT H v = 0.

228 u?. For u ¹ 0 define u? = {v 2 V| uT H v = 0}.
Note that u? is a 3-dimensional subspace of V, containing u, that is orthogonal to HTu. In order to count the number of totally isotropic 2-dimensional subspaces of V, we proceed as follows: There are q4 – 1 non-zero vectors u 2 V. There are q3-q vectors v 2 u? – span{u}. Hence there are (q4 – 1)(q3 – q) pairs of vectors. Each 2-dimensional subspace is spanned by (q2-1)(q2-q) pairs, hence the number of totally isotropic 2-dimensional subspaces of V is given by: (q4 – 1)(q3 – q)/[(q2 –1)(q2 – q)] = (q2 + 1)(q + 1).

229 W(q) W(q) is the incidence structure of all totally isotropic points and totally isotropic lines in PG(3,q). It is a ((q2 + 1)(q + 1)q+1) configuration.

230 Generalized Quadrangle
p A generalized quadrangle is a partial linear space satisfying the following two conditions: Given any line L and a point p not on L there is a unique point p’ on L such that p and p’ are collinear. There are non-collinear points and non-concurrent lines. L p’

231 Tutte’s 8-Cage In 1947 Tutte gave a construction of the only 8-cage on 30 vertices.

232 Tutte’s 8-Cage – Construction (I)
Take S(Q3). There are 6 pairs of antipodal new vertices of valence 2. These 6 pairs are naturally grouped into 3 quadruples – a quadruple represents a 1-factor.

233 Tutte’s 8-Cage – Construction (II)
The tree on the left has 6 pairs of leaves and these 6 pairs are naturally grouped into 3 quadruples.

234 Tutte’s 8-Cage – Construction (III)
By gluing appropriately the leaves of the tree on the left to the midpoints of the edges of the cube on the right one obtains Tutte’s 8-Cage. Cubic graph Bipartite graph Girth 8 Diameter 4.

235 Question Q. If we subdivide the edges of K4 we may attach the tree on the left to it in such a way that we avoid quadrangles. What graph is produced in ths way?

236 Similar Question Same for the S(K2,2,2) and the tree. First layer antipodal edges, second layer main squares of the octahedron. Truncate vertices of valence 4. (What about S(Q4)?)

237 4-dimensional Cube Q4. 0000 1000 0010 0100 0001 1100 1110 0110 0111 0011 1001 1101 1111 1011 1010

238 W(2) and Q4. W(2) can be modelled on the vector space F24 (represented as hypercube). What are totally isotropic points (lines throug the origin) and lines (planes through the origin)? 0000 1000 0010 0100 0001 1100 1110 0110 0111 0011 1001 1101 1111 1011 1010

239 W(2) W(2) is a (153) configuration. Its Levi graph is Tutte’s 8-cage.
W(2) admits geometric realization that is known as the Cremona-Richmond Configuration.

240 Cremona Richmond Configuration
Cremona Richmond Configuration can be drawn by exhibiting pentagonal cyclic symmetry. It is the smallest triangle-free (v3) configuration.

241 Cremona-Richmond Configuration in Space
Take the following points related to tetrahedon. 4 vertices 6 midpoins of the edges. 4 centers of trinangles 1 center of the tetrahedon The following lines: 4 x 3 = 12 triangle hights 3 lines connecting antipodal midpoints of edges and the center The resulting structure is the Cremona-Richmond configuration.

242 Exercises 15-1 N1: Prove that in PG(n,q) there are (qn+1 – 1)(qn+1 – q) ... (qn + 1 – qp)/ [(qp+1 – 1)(qp+1- q) ... (qp+1 – qp)] projective subspaces of dimension p.

243 Exercises 15-2 N2: Study properties of W(3). By definition it is a (404) triangle-free configuration. What is its symmetry group? N3: Find one of its drawings. N4: Prove that the Levi graph of W(3) is semi-symmetric (= regular, edge-transitive but not vertex-transitive).

244 16. Cages and Configurations

245 The Balaban 10-cage The Balaban 10-cage is presented on the left. This is one of the three smallest cubic graphs of girth 10. It has 70 vertices, a symmetry is clearly visible. The cage has a Hamilton cycle. For instance one of its LCF codes is given here: [-9, -25, -19, 29, 13, 35, -13, -29, 19, 25, 9, -29, 29, 17, 33, 21, 9, -13, -31, -9, 25, 17, 9, -31, 27, -9, 17, -19, -29, 27, -17, -9, -29, 33, -25, 25, -21, 17, -17, 29, 35, -29, 17, -17, 21, -25, 25, -33, 29, 9, 17, -27, 29, 19, -17, 9, -27, 31, -9, -17, -25, 9, 31, 13, -9, -21, -33, -17, -29, 29]

246 The other two 10-cages Besides the Balaban cage there are two more 10-cages. The more symmetric one is drawn here. LCF: [(-29, -19, -13, 13, 21, -27, 27, 33, -13, 13, 19, -21, -33, 29)5]

247 The third 10-cage The third 10-cage is the least symmetric. LCF:
[9, 25, 31, -17, 17, 33, 9, -29, -15, -9, 9, 25, -25, 29, 17, -9, 9, -27, 35, -9, 9, -17, 21, 27, -29, -9, -25, 13, 19, -9, -33, -17, 19, -31, 27, 11, -25, 29, -33, 13, -13, 21, -29, -21, 25, 9, -11, -19, 29, 9, -27, -19, -13, -35, -9, 9, 17, 25, -9, 9, 27, -27, -21, 15, -9, 29, -29, 33, -9, -25].

248 10-cages All 10-cages are hamiltonian (see their LCF description).
Respective automorphism group orders: 80, 120, 24. Reference: T.Pisanski, M. Boben, D. Marušič, A. Orbanič, A. Graovec: The 10-cages and derived Configurations, Discrete Math. 275 (2003),

249 17. A Case Study – The Gray Graph

250 The Gray Graph G The smallest known cubic edge- but not vertex-transitive graph has 54 vertices and is known as the Gray graph. It is denoted by G. Since its girth is 8, it is the Levi graph of two dual, smallest, triangle-free, point-, line- and flag-transitive, non-self-dual (273)-configurations.

251 The Gray Configuration
Cyclic drawings of two dual Gray configurations. These drawings show the problem of a straight-line realizations of configurations. They both contain false incidences.

252 Gray Configuration Revisited
There is a much better drawing of the Gray configuration available. Using this drawing it becomes clear that the Menger graph M of the Gray configuration is isomorphic to K3  K3  K3 .

253 Menger and Dual Menger Graph
The representation of the configuration in the previous slide determines the choice between the Gray configuration (and Menger graph M = K33) and the dual Gray configuration and the dual Menger graph D.

254 The genus of a graph Let g(G) denote the genus of the graph G. This parameter denotes the least integer k, such that G admits an embedding into an orientable surface of genus k.

255 The Genus of K3  K3  K3 Several years ago it was shown that the genus of g(K3  K3  K3 ) = 7. The genus embedding was constructed by Mohar, Pisanski, Škoviera and White. It is depicted in the figure. b a c c' b' a' c+

256 The Genus Embedding The genus embedding has some very nice features.
It contains a bipartite dual. If we color the faces in two colors all 27 triangles get a single color. This means that points of the Gray configurations correspond to vertices while the lines correspond to the triangles.

257 The Gray Graph admits an embedding into a surface of genus 7
If we keep the original vertices and introduce the centers of triangles as new vertices with an old vertex v adjacent to a new vertex t if and only if v lies on the boundary of the triangle t, the resulting graph is the Gray graph. Hence the Gray graph fits onto the same surface!

258 The Gray Graph admits an embedding into a surface of genus 7
If we keep the original vertices and introduce the centers of triangles as new vertices with an old vertex v adjacent to a new vertex t if and only if v lies on the boundary of the triangle t, the resulting graph is the Gray graph. Hence the Gray graph fits onto the same surface!

259 The lower bound The upper bound for genus is 7. The lower bound 7 follows from the following: Proposition: Let L be the Levi graph and let M be the Menger graph of some (v3) configuration C, then g(M)  g(L). Proof: Start with the genus embedding of L. By the reverse process depicted in the figure one can obtain the embedding of M in the same surface.

260 The dual Menger graph D There is just one unfinished case to consider. Namely, the dual Menger graph D can also be embedded into the surface of genus 7. It turns out that this graph is quite interesting. It is a Cayley graph of the semidirect product Z3 ⋉ Z9. It can be described as a Z9-covering graph over the base graph in the next slide.

261 The Voltage Graph The Dual Menger graph is the Z9 covering graph over the voltage graph on the left. It can be viewed as the Cayley graph for the following presentation. +4 +1 -1 -2 +2 -4

262 The Holt Graph The 4-valent Holt graph H is a spanning subgraph of on 27 vertices is the smallest 1/2-arc transitive graph. This means it is vertex- and edge- but not arc-transitive. It is depicted in the figure on the left.

263 The Holt Graph - again The 4-valent Holt graph H is an induced subgraph of the graph D. It is obtained from D by removing a suitable 2-factor composed of three 9-cycles. H is a Z9-covering graph over the green voltage graph on the left [with the 3 red loops removed.] +2 -4 -1 +4 +1 +2 +1 +4 -2

264 Some Presentations for Z3 ⋉ Z9
Both H and D are Cayley graphs for the same group Z3 ⋉ Z9. Z3 ⋉ Z9 = <a, b | a9 = b3 = 1, b-1ab = a2> D = <x, y, z | x9 = y9 = z9 = 1, y-1xy = x2, y-1zy = z2, x-1yx = y2, x-1zx = z2, z-1xz = x2, z-1yz = y2> H is obtained from D by omitting any single generator x,y,or z.

265 The Final Problems What is the genus of D? What is the genus of H? The genus of Z3 ⋉ Z9 is known. It is g(Z3 ⋉ Z9) = 4. On the other hand we proved that D admits an embedding into the surface of genus 7. Hence 4  g(D)  7 4  g(H)  7 In the first case one should improve the lower bound, in the second, the upper bound should be improved.

266 18. Another Case Study - Tennis Doubles

267 Story This problem was posed by an undergraduate student, Jure Kališnik, a tennis doubles fan, during the lectures on configurations that were held in Ljubljana in 2002.

268 Tennis Club Problem There are n players in a Tennis Club TC. The club owns two tennis courts. Occasionaly the club organizes a Tennis Doubles tournament with m rounds on both courts (altogether 2m games) along the following rules: TC1. Each player plays k games. TC2. During the tournamet each player meets any other player on a court at most once. TC3. No player may appear in the same round in both courts.

269 The Model We may model the tournament schedule by a configuration table. The table has 4 rows and 2m columns. The first m columns correspond to the games played on court A while the second m columns correspond to the games played on court B. Each column has distinct marks. Each pair of marks appears in the same column at most once. Each mark appears k times. 8m = nk The first m columns are permuted arbitrarily. The second m columns are premuted in such a way that Ci Å Ci+m = ;, for i = 1..m.

270 The Model and Configurations
We may model the schedule as a (nk,2m4) configuration. Clearly k = 8m/n. For k · 4 we use the inequality: n ¸ 2m ¸ 1 + 4(k - 1) may obtain smallest cases: k = 1, n = 8, m = 1 (81, 24) k = 2, n = 12, m = 3 (122, 64) k = 3, n = 16, m = 6 (163,124) k = 4, n = 14, m = 7 (144,144)

271 The Model and Configurations
Again, k = 8m/n. For k > 4, we use the inequality: 2m ¸ n ¸ 1 + 3k. may obtain smallest cases: k = 5, n = 16, m = 10 (165, 204) k = 6, n = 20, m = 15 (206, 304) k = 7, n = 24, m = 21 (247, 424) k = 8, n = 25, m = 25 (258, 504) k = 9, n = 32, m = 36 (329, 724)

272 Tennis Court A 1 2 - 3 4 9 10 11 12 6 16 7 17 14 19 13 5 8 18 20

273 Tennis Court B 5 6 - 7 8 13 14 15 16 17 18 19 20 3 10 9 1 12 11 4

274 Chapter 4. Statistics Page
Number of slides:276 Number of sections:18 Number of exercises:70 Number of homeworks:3


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