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Mria Markoov Graph definition Degree, in, out degree, oriented graph. Complete, regular, bipartite graph. Graph representation, connectivity, adjacency. Isomorphism of graphs. Paths, cycles, trials. Random


  1. Mária Markošová

  2.  Graph – definition  Degree, in, out degree, oriented graph.  Complete, regular, bipartite graph….  Graph representation, connectivity, adjacency.  Isomorphism of graphs.  Paths, cycles, trials.  Random graph.  Graph evolution.

  3. Definition: A graph G consists of vertex set V(G) and edge set E(G) and edges are defined by vertices pairs. loop supgraph multiple edge Oriented graph: if edges have orientation. Sim imple g graph: graph without loops and multiple edges, no edge orientation.

  4. w b Vertex d degree y e c a z d x Degree of a vertex x. k(x) is a number of edges incident with the vertex x . w b y a e c Oriented graph x d z   k in x In degree of vertex x, : Number of edges leading to the vertex x .   k out x Out degree of vertex x, : Number of edges leading out of vertex x.         k x k x k x in out

  5. Example. k(x)= 5         x k x k x k x in out    k x ? in    k x ? out

  6. Oriented graphs: G(V,E), where V is a set of vertices, E is a set of ordered pairs e=(u,v), u, v are endpoints of edge and their order is fixed. Simple graphs: without oriented edges, no loops, no multiple edges: in what follows we shall deal with such graphs, if not given otherwise. Lemma: Unoriented graph has even number of vertices with odd degree.

  7. Complete graph is a simple undirected graph in which every pair of distinct vertices is connected by a unique edge. K Complete graph of N vertices is denoted as N K K 4 K 12 7    N   N N 1     E  The number of edges in the complete graph: 2 2   K What is the degree of each node in ? N

  8. Regular graph is a graph where each vertex has the same number of neighbors, that means each vertex has the same degree. What about the complete graph? Is the complete graph also a regular graph?

  9. What is the complementary Complementary graphs K graph of ? 12 Are there a graphs, which have the same complementary graphs? Comlementary graphs mapped on each other create comple lete g graph, , in which each vertex is connected to each other vertex.

  10. Bipartite g graph Graphs, in which V(G) (vertex set) is the union of the two disjoint independent sets (no edges between nodes in the set). What type of the graph is also a bipartite graph? people jobs Find an example. women men authors papers Find another examples at home.

  11. Tree g graph: Undirected graph in which two vertices are connected exactly by one simple path. Is the tree on fig a bipartite graph? Every tree is a bipartite graph.

  12. Spannin ing tree: Spanning tree of the connected undirected graph G is a tree composed of all vertices and some edges of the graph G . A spanning tree of a connected graph G can also be defined as a maximal set of edges of G that contains no cycle, or as a minimal set of edges that connect all vertices.

  13. Graph representation Loopless graph: Graph without loops, multiple edges are allowed a b c d e w x y z w w 1 1 0 0 0 W   b 0 1 1 0 y   e c x 1 0 1 1 0 x 1 0 2 0 a   z   y 0 1 1 1 1 y 1 2 0 1 d x    z 0 0 0 0 1 z 0 0 1 0   A(G) adjacency matrix- number of edges between M(G) incidence matrix- defined endpoints One, if vertex is the endpoint of an edge, zero if not

  14. w b y e c a z d x w x y z W  0 1 1 0    Every adjacency matrix is symetric A(G)= x 1 0 2 0   (no oriented graphs).   y 1 2 0 1 The degree of vertex x is a sum of    entries of row x in both A(G) and z 0 0 1 0   M(G). a b c d e w 1 1 0 0 0         k x 1 2 1 1 1 3 x 1 0 1 1 0 M(G)= y 0 1 1 1 1 z 0 0 0 0 1

  15. Isomorphic ic graphs Two graphs G and H are isomorphic, if we are able to map one to the another (e.g. to find a bijection f: V(G) V(H), and if uv is from E(G) then f(u)f(v) is from E(H)) H G Adjacency matrix of G is the same as of H if we reorder the vertices

  16. Self complementary graphs Definition: A graph is self complementary if it is isomorphic to its complement. b 1 a 5 c 2 e 4 d 3

  17. Isomorfism has 1.reflexive, 2.symetric and 3. transitive property: 1. Each graph is isomorphic to itself.       f : V G V H 1 2. If is an isomorphism from G to H, then is an f isomorphism from H to G.           f : V F V G g : V G V H 3. Suppose that , and are f  g isomorphisms then composition is isomorphism from F to G. Isomorphic graphs have isomorphic complements. Sometimes it is easier to test the complements to decide, whether two graphs are isomorfic or not.

  18. Are they isomorphic? 1 1 a a 6 6 b b e e 5 5 2 2 f f d d c c 4 4 3 3 1 a 6 b Complementary e graphs 5 2 f d c 4 3

  19. To prove, that graphs are NOT isomorphic is enough to find, that in some structural properties ( e.g. number of edges, supgraphs, complements etc.) they differ.

  20. Isomorphic ic classes - path with n vertices P n - cycle with n vertices C n - complete graph with n vertices K n - complete bipartite graph, r,s are indexes of two K r , s sets of vertices K 2 , 3 C 5 K P 5 5

  21. Wh What i is the number o of simple graphs which can b be created on a s set o of N vertices?   N     2   m 2 From a set of four vertices we can create 64 different simple graphs, belonging to 11 isomorphism classes. Here are the representatives of all classes

  22. Connected and disconnected g graphs Definition: A graph G is connected if it has u,v – path whenever u, v are from V(G). Othervise G is dis isconnected. x e1 e6 e2 e5 w y e4 e7 e3 z

  23. v , e , v ,..., e k v , Definition: A walk lk is a list of vertices and edges 0 1 1 k e  i  such that for the edge has endpoints 1 k i v , v and . Edges and vertices can be repeated.  i 1 i A u,v -walk or u,v – trail has first vertex u and last vertex v . A trail is a walk with no repeated edge. A u,v- path is a path whose vertices of degree one are u,v (endpoints). Other vertices are internal. Edges and vertices are not repeated. A walk and trial is closed if its endpoints are the same.

  24. Euler’s ’s q questio ion Walk lk of lenght 4: x.e2,w,e5,y,e6,x,e2,w Konigsberg bridges Closed walk of lenght 5: x x.e2,w,e5,y,e6,x,e1,w,e2,x e1 e6 e2 Trail of length 4 x.e2,w,e5,y,e6,x,e1,w walk e5 w cycle y trail e4 Cycle of lenght 3: Subgraph e7 consisting of edges e1,e6,e5 and vertices w,x,y. Deleting e3 one of its edges we get a path of length 2. z

  25. Eulerian t trial: : Trial which visits every edge at most once. Euler’s lemma: Connected graph has closed eulerian trial if and only if all of its vertices have even degree. Why? x x e1 e e e 1 e 6 6 2 e w y w y 5 e e e 4 7 7 e e 3 3 z z

  26. Connectivity and adjacency   xw  E G G has w,z- path w and z are connected x and w are adjacent w is connected to z x is joined to w x is adjacent to w w b y e c a z d x

  27. Component o of graph Definitions: Maximal c connected subgraph of graph G is a subgraph, which is connected and is not contained in any other connected subgraph of G. The components of graph G are its maximal connected subgraphs. 4 components of graph G

  28. Proposition: Every graph with N nodes and m edges has at least N-m components. Proof: N isolated vertices create a graph with N components. Each added edge links vertices in the same component, or in different components merging them in one. So adding an edge decreases the number of components by 0 or one. If we add m edges, the number of components is at least N-m . Definition: Cut e edge or cut vertex is an edge or vertex whose deletion increases the number of components.

  29. Cut vertex increases the number of subgraphs by many Cut edge increases the number of subgraphs always by one

  30. Vertex d degrees De Degree o of vertices are f fundamental parameters of g graph .   Degree of a vertex v of graph G k G v   Maximum degree in graph G  G   Minimum degree in graph G  G Definitions: Graph G is regular if all degrees are equal. Graph G is k -regular if the common degree is k. N(v) – neigborhood of vertex v , set of vertices adjacent to v N(G)- order of G, number of vertices in G e(G)- size of G, number of edges in G

  31. First teorem of g graph theory       k v 2 e G If G is a graph, then :    v V G Proof: each edge adds to the degree of two vertices. What can be concluded from the theorem?     2 e G  2 e G     1. Average vertex degree is:    , G G     N G N G 2. Every graph has an even number of vertices of odd degree. No graph of odd order k is regular with the odd degree. 3. A k –regular graph of with N vertices has Nk/2 edges.

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