Admin: /* Euler Tours */

2017-09-07T12:42:31Z

Euler Tours

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	===Euler Tours===		===Euler Tours===

			{{Main\|Graphs/Euler Tours}}

	An Euler tour is a closed walk on a graph that traverses each edge of the graph exactly once. Some graphs have an Euler tour (and are called Eulerian), other graphs are not.		An Euler tour is a closed walk on a graph that traverses each edge of the graph exactly once. Some graphs have an Euler tour (and are called Eulerian), other graphs are not.

Admin: /* Degree definitions */

2017-08-28T00:05:57Z

Degree definitions

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	Vertex of degree 0 is '''isolated'''		Vertex of degree 0 is '''isolated'''

			A graph G where all of the vertices have the same degree, k, is called '''k-regular''' (or, just '''regular''').

	The vertex on the graph with the smallest degree <math>\delta(G) = \min \left( d(v) \| v \in V \right)</math> is the '''minimum degree of G'''		The vertex on the graph with the smallest degree <math>\delta(G) = \min \left( d(v) \| v \in V \right)</math> is the '''minimum degree of G'''

Admin: /* Flags */

2017-08-18T03:23:06Z

Flags

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	==Flags==		==Flags==

	{{~~GraphFlag~~}}		{{GraphsFlag}}

	{{AlgorithmsFlag}}		{{AlgorithmsFlag}}

Admin: Created page with "==Dietel Chapter 1: Graph Definitions and Concepts== Outline: * Definitions * graph, * degree, * path, * cycle, * connectivity, * tree, forest, * k-partite, * contract..."

2017-08-18T03:18:27Z

Created page with "==Dietel Chapter 1: Graph Definitions and Concepts== Outline: * Definitions * graph, * degree, * path, * cycle, * connectivity, * tree, forest, * k-partite, * contract..."

New page

==Dietel Chapter 1: Graph Definitions and Concepts==

Outline:
* Definitions
* graph,
* degree,
* path,
* cycle,
* connectivity,
* tree, forest,
* k-partite,
* contraction,
* Euler tours

===Graph definitions===

A '''graph''' G consist of a set of nodes (vertices) V and edges E, denoted <math>G(V,E)</math>

'''Vertex set''' on graph G is denoted <math>V(G)</math>

'''Edge set''' on graph G is denoted <math>E(G)</math>

Number of vertices in a graph is called the '''order''' and is denoted <math>|G|</math>

Number of edges in a graph is denoted <math>||G||</math>

Vertex <math>v \in V</math> and edge <math>e \in E</math> are '''incident''' if the edge connects to the vertex.

Set of all edges at a particular vertex v is denoted <math>E(v)</math>

Two vertices x, y are '''adjacent''' on a graph if there is an edge with endpoints x and y

If all vertices are pairwise adjacent, the graph is '''complete'''

For two graphs <math>G = (V,E)</math> and <math>G' = (V',E')</math>, the graphs are isomorphic if there exists a biijection from G to G'.

If we have two graphs G and G', we say that G' is a subgraph of G if all V' subset of V and all E' subset of E

A subgraph G' is a '''spanning subgraph''' of G if all V' span all of G (if V' = V)

===Degree definitions===

Set of neighbors of a vertex v is denoted <math>N(v)</math>

Degree of a vertex v is denoted <math>d(v)</math> and is equal to the number of edges <math>|E(v)|</math> at v

Vertex of degree 0 is '''isolated'''

The vertex on the graph with the smallest degree <math>\delta(G) = \min \left( d(v) | v \in V \right)</math> is the '''minimum degree of G'''

The vertex on the graph with the largest degree <math>\Delta(G) = \max \left( d(v) | v \in V \right)</math> is the '''maximum degree of G'''

The average degree of G is given by the expression <math>d(G) = \dfrac{1}{|V|} \sum_{v \in V} d(v)</math>

Ratio of edges to vertices on a graph is <math>\epsilon(G) = \dfrac{|E|}{|V|}</math>

If we define edges as having two endpoints, then adding up the degrees of all vertices will lead to twice the number of edges. Mathematically: <math>|E| = \dfrac{1}{2} \sum_{v \in V} d(v) = \dfrac{1}{2} d(G) |V|</math>

This leads to the identity <math> \epsilon(G) = \dfrac{1}{2} d(G)</math> and the theorem that the number of vertices of odd degree in a graph must always be even. Contrawise proof: if the number of vertices of odd degree is odd, the number of edges is not be an integer.

===Path and Cycle Definitions===

A path P on a graph G is a non-empty graph that contains vertices and edges that are in G: <math>V = \{ x_1, x_2, \dots, x_k\}</math> and <math>E = \{ x_0 x_1, x_1 x_2, \dots, x_{k-1} x_k \}</math>

A path is usually referred to by the sequence of vertices it visits, or as a path "from/between x1 to xk"

'''Independent paths''' are paths containing no common (internal) vertices. Independent paths may share endpoints though.

We can denote parts of a path using special notation: if a path <math>P = x_0 \dots x_{k}</math>, then the following notation is used to denote only a part of that path:

<math>
\begin{align}
P x_i = x_0 \dots x_i \qquad 0 \leq i \leq k \\
x_i P = x_i \dots x_k \\
x_i P x_j = x_i \dots x_j
\end{align}
</math>

We can also connect paths using unions, or by using more shorthand:

<math>
P x \bigcup x Q y \bigcup y R = P x Q y R
</math>

A '''cycle C''' consists of a path whose final edge connects the last node to the first node. Given a path <math>P = x_0 \dots x_{k-1}</math> the cycle is then <math>C = P + x_{k-1} x_0</math>

A k-cycle is denoted <math>C^k</math> and is a cycle of length k.

The girth of a cycle is the number of edges or vertices in a cycle in a graph G. The circumference of a graph is the maximum length of a cycle in a graph G.

The distance of two vertices x and y is the length of the shortest path from x to y <math>d_G(x,y)</math>.

A vertex is '''central''' if greatest distance from any other vertex is as small as possible. This minimum distance is the radius of the graph G. Formally:

<math>
rad(G) = \min_{x \in V(G)} \max_{y \in V(G)} d_G(x,y)
</math>

Note that the radius of a graph is different from the minimum/average degree.

===Connectivity===

A graph is '''connected''' if any two arbitrary vertices are connected.

If the graph is directed, a connected graph means that for any two arbitrary vertices u and v, there is an edge connecting u to v or v to u. A '''strongly connected''' graph means that for any two arbitrary nodes u and v, there is an edge connecting u to v and another edge connecting v to u.

Suppose we have two sets of vertices A and B, and a third set of vertices X. Further suppose that any path that connects a vertex from A to a vertex from B contains a vertex from X. Then we say that X '''separates''' the vertex sets A and B.

A subgraph of G that is maximally connected (contains every vertex in G) is a '''component''' of G. If a component is connected, it is always non empty.

Vertex connectivity: A graph G is '''k-connected''' if it has more than k vertices and if no two vertices of G are separated by fewer than k vertices. The maximum value of k such that G is k-connected is the '''connectivity''' of G and is denoted <math>\kappa(G)</math>.

Edge connectivity: A graph G is '''l-edge-connected''' if every vertex is connected with fewer than l edges (this is a bit unclear). The edge connectivity is denoted <math>\lambda(G)</math>.

Theorem due to Mader 1972: Every graph of average degree at least 4k has a k-connected subgraph. (Can prove inductively.)

===Trees and Forests===

Acyclic graphs are called forests. Connected forests are called trees.

A connected graph with n vertices is a tree if and only if it has n-1 edges.

We can (but don't have to) pick a particular node to be special - the root of the tree. In that case it is a rooted tree. When we pick a root, this imposes an ordering (assuming vertices can be compared). Given two nodes x and y, we say that <Math>x \leq y \mbox{ if } x \in rTy</math>.

A rooted tree T is called normal if any two vertices that are adjacent in the graph are comparable. Every graph has a normal spanning tree.

===Bipartite Graphs===

A '''k-partite''' graph is a graph where the set of vertices V can be partitioned into k classes, such that every edge that starts in one partition will end in a different partition.

If we can select any two vertices from two different classes and they are connected, the k-partite graph is '''complete'''.

Bipartite graphs cannot contain cycles of odd lengths. This is always true, so that we can identify bipartite graphs using this property: a graph is bipartite iff it contains no odd cycle.

===Edge Contraction===

Given a graph G with vertex set V and edge set E. Let e be an edge connecting vertex x to vertex y. Then <math>G/e</math> denotes the graph obtained by contracting the edge into a new vertex, which is now adjacent to all former neighbors of x and y.

===Euler Tours===

An Euler tour is a closed walk on a graph that traverses each edge of the graph exactly once. Some graphs have an Euler tour (and are called Eulerian), other graphs are not.

A connected graph is Eulerian if and only if every vertex has even degree. This is because any vertex appearing k times in an Euler tour must have degree 2k.

===Other Definitions===

A hypergraph is a pair of disjoint sets (V,E) where the elements of the edge sets are non-empty subsets of V. (That is, a given edge e in the set E can connect multiple vertices.)

A directed graph is a pair of disjoint sets (V,E) along with two maps: the init map from V to E (denoting the initialization or origin of the directed edge) and the term map from V to E (denoting the termination of the directed edge).

A multigraph is a pair of disjoint sets (V,E) together with a map from E to V or to V^2. In other words, it is a graph in which we can have edges that begin and end at the same vertex.

==Flags==

{{GraphFlag}}

{{AlgorithmsFlag}}

[[Category:Graphs]]
[[Category:Algorithms]]
[[Category:Diestel]]

Graphs/Definitions - Revision history

Admin: /* Euler Tours */

Admin: /* Degree definitions */

Admin: /* Flags */

Admin: Created page with "==Dietel Chapter 1: Graph Definitions and Concepts== Outline: * Definitions * graph, * degree, * path, * cycle, * connectivity, * tree, forest, * k-partite, * contract..."