Square graph: Difference between revisions
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| characteristic polynomial || <math>t(t - 2)(t - 1)^2</math>|| As complete bipartite graph <math>K_{m,n}, m = n = 2</math>: <math>t(t - 2)(t - 1)^{m+n-2}</math> | | characteristic polynomial || <math>t(t - 2)(t - 1)^2</math>|| As complete bipartite graph <math>K_{m,n}, m = n = 2</math>: <math>t(t - 2)(t - 1)^{m+n-2}</math> | ||
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| minimal polynomial || <math>t(t - 1)(t - 2)</math> || As complete bipartite graph <math>K_{m,n}, m = n = 2</math>: <math>t(t - 1)(t - 2)</math> | | minimal polynomial || <math>t(t - 1)(t - 2)</math> || As complete bipartite graph <math>K_{m,n}, m = n = 2</math>: <math>t(t - 1)(t - 2)</math> (independent of <math>m,n</math> as long as <math>m + n > 2</math>) | ||
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| rank of normalized Laplacian matrix || 3 || As complete bipartite graph <math>K_{m,n}, m = n = 2</math>: <math>m + n - 1 = 2 + 2 - 1 = | | rank of normalized Laplacian matrix || 3 || As complete bipartite graph <math>K_{m,n}, m = n = 2</math>: <math>m + n - 1 = 2 + 2 - 1 = 3</math> | ||
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| eigenvalues (roots of characteristic polynomial) || 0 (1 time), 2 (1 time), 1 (2 times) || As complete bipartite graph <math>K_{m,n}, m = n = 2</math>: 0 (1 time), 2 (1 time), 1 (<math>m + n - 2 = 2 + 2 - 2 = 2</math> times) | | eigenvalues (roots of characteristic polynomial) || 0 (1 time), 2 (1 time), 1 (2 times) || As complete bipartite graph <math>K_{m,n}, m = n = 2</math>: 0 (1 time), 2 (1 time), 1 (<math>m + n - 2 = 2 + 2 - 2 = 2</math> times) | ||
Latest revision as of 00:20, 26 May 2014
This article defines a particular undirected graph, i.e., the definition here determines the graph uniquely up to graph isomorphism.
View a complete list of particular undirected graphs
Definition
This undirected graph, called the square graph, is defined in the following equivalent ways:
- It is the cycle graph on 4 vertices, denoted .
- It is the complete bipartite graph
- It is the 2-dimensional hypercube graph.
- It is the 2-dimensional hyperoctahedron graph.
Explicit descriptions
Description of vertex set and edge set
Vertex set:
Edge set:
Note that with this description, the two parts in a bipartite graph description are and .
Adjacency matrix
With the ordering of the vertex set and edge set given above, the adjacency matrix is:
If we re-ordered the vertices by interchanging the roles of vertices 2 and 3, we would get the following adjacency matrix:
Arithmetic functions
Size measures
| Function | Value | Explanation |
|---|---|---|
| size of vertex set | 4 | As cycle graph : As complete bipartite graph : As -dimensional hypercube, : |
| size of edge set | 4 | As cycle graph : As complete bipartite graph : As -dimensional hypercube, : |
Numerical invariants associated with vertices
Since the graph is a vertex-transitive graph, any numerical invariant associated to a vertex must be equal on all vertices of the graph. Below are listed some of these invariants:
| Function | Value | Explanation |
|---|---|---|
| degree of a vertex | 2 | As cycle graph : 2 (independent of ) As complete bipartite graph : Since are equal, the graph is vertex-transitive and -regular, so we get As -dimensional hypercube, : As -dimensional hyperoctahedron, : |
| eccentricity of a vertex | 2 | As cycle graph : greatest integer of equals greater integer of 4/2 equals 2 As complete bipartite graph : 2 (independent of , though it uses that both numbers are greater than 1) As -dimensional hypercube, : As -dimensional hyperoctahedron, : 2 (independent of , for ) |
Other numerical invariants
| Function | Value | Explanation |
|---|---|---|
| clique number | 2 | As cycle graph : 2 (independent of for ) As : 2 (independent of , follows from being bipartite) As -dimensional hypercube, : 2 (independent of ) |
| independence number | 2 | As cycle graph : greatest integer of equals greatest integer of 4/2 equals 2 As : As -dimensional hypercube, : |
| chromatic number | 2 | As cycle graph : 2 (in general, it is 2 for even and 3 for odd As : 2 (independent of , follows from being bipartite) As -dimensional hypercube, : 2 (independent of , follows from being bipartite) |
| radius of a graph | 2 | Due to vertex-transitivity, the radius equals the eccentricity of any vertex, which has been computed above. |
| diameter of a graph | 2 | Due to vertex-transitivity, the radius equals the eccentricity of any vertex, which has been computed above. |
| odd girth | infinite | As cycle graph : infinite (since even) As : infinite, since bipartite As -dimensional hypercube, : infinite, since bipartite |
| even girth | 4 | As cycle graph : (since even) As complete bipartite graph : 4 (independent of as long as both are greater than 1) As -dimensional hypercube, : 4 (independent of for ) |
| girth of a graph | 4 | As cycle graph : As complete bipartite graph : 4 (independent of as long as both are greater than 1) As -dimensional hypercube, : 4 (independent of for ) |
Graph properties
| Property | Satisfied? | Explanation |
|---|---|---|
| connected graph | Yes | |
| regular graph | Yes | all vertices have degree two |
| vertex-transitive graph | Yes | |
| cubic graph | No | |
| edge-transitive graph | Yes | |
| symmetric graph | Yes | |
| distance-transitive graph | Yes | |
| bridgeless graph | Yes | |
| strongly regular graph | Yes | The graph is a |
| bipartite graph | Yes |
Graph operations
| Operation | Graph obtained as a result of the operation |
|---|---|
| complement of a graph | matching graph on 4 vertices |
| line graph | isomorphic to the original graph |
| prism of a graph | cube graph |
Algebraic theory
Adjacency matrix
The adjacency matrix is:
It can alternately be written in the following form, which is more computationally convenient because it clearly identifies blocks of 0s and 1s:
This matrix is uniquely defined up to conjugation by permutations. Below are some important associated algebraic invariants:
| Algebraic invariant | Value | Explanation |
|---|---|---|
| characteristic polynomial | As complete bipartite graph : | |
| minimal polynomial | As complete bipartite graph : | |
| rank of adjacency matrix | 2 | As complete bipartite graph : 2 (independent of ) |
| eigenvalues (roots of characteristic polynomial) | 0 (2 times), 2 (1 time), -2 (1 time) | As complete bipartite graph : 0 ( times), (1 time), (1 time) |
Laplacian matrix
The Laplacian matrix is as follows:
The matrix is uniquely defined up to permutation by conjugations. Below are some algebraic invariants associated with the matrix:
| Algebraic invariant | Value | Explanation |
|---|---|---|
| characteristic polynomial | As complete bipartite graph : | |
| minimal polynomial | As complete bipartite graph : | |
| rank of Laplacian matrix | 3 | As complete bipartite graph : |
| eigenvalues (roots of characteristic polynomial) | 0 (1 time), 4 (1 time), 2 (2 times) | As complete bipartite graph : 0 (1 time), (1 time), (2 times: times as and times as ) |
Normalized Laplacian matrix
The normalized Laplacian matrix is as follows:
The matrix is uniquely defined up to permutation by conjugations. Below are some algebraic invariants associated with the matrix:
| Algebraic invariant | Value | Explanation |
|---|---|---|
| characteristic polynomial | As complete bipartite graph : | |
| minimal polynomial | As complete bipartite graph : (independent of as long as ) | |
| rank of normalized Laplacian matrix | 3 | As complete bipartite graph : |
| eigenvalues (roots of characteristic polynomial) | 0 (1 time), 2 (1 time), 1 (2 times) | As complete bipartite graph : 0 (1 time), 2 (1 time), 1 ( times) |
Realization
As Cayley graph
Note that for this to be the Cayley graph of a group, the group must have order 4, and the generating set with respect to which we construct the Cayley graph must be a symmetric subset of the group of size 2.
| Group | Choice of symmetric set that is a generating set for which the Cayley graph is this |
|---|---|
| cyclic group:Z4 | cyclic generator and its inverse |
| Klein four-group | two distinct elements of order two |
Geometric embeddings
Planar embedding as a square
The graph has a very nice embedding as a square in the plane: the vertices embed as the vertices of the square, and the edges as the edges of the square. Explicitly, we can embed the vertices as:
This embedding is nice in a number of ways:
- It demonstrates that the graph is a planar graph.
- Moreover, it demonstrates that the graph can be embedded in the plane using straight line segments for edges. This is not possible for all planar graphs.
- It demonstrates that the graph is a unit distance graph: two points are adjacent in the embedding if and only if the distance between them in the Euclidean plane is 1.
- It preserves all the symmetries of the graph. Explicitly, for every automorphism of the cycle graph, there is a (unique) self-isometry of the Euclidean plane that induces that automorphism on the cycle graph.