Meaning of Eigenvectors in a Graph

In summary, the eigenvectors in a graph, specifically an adjacency matrix without self-loops, can be interpreted as representing the number of walks of a certain length between two vertices. This can be computed using eigenvalues and eigenvectors through diagonalization. This concept falls under the field of spectral graph theory and further resources can be found in university libraries.
  • #1
gigaJoule
1
0
What interpretation could the eigenvectors in a graph have? By graph I mean an adjaceny matrix not counting self-loops. If you can draw any physical meanings or point to any examples, that'd be even better.

Thank you!
 
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  • #2
This may not be quite what you're after, but I do know this: the i,j component of

[itex]A^{n}[/itex]

represents the number of walks of length n from vertex i to vertex j. Now, if you wish to compute this explicitly, the eigenvalues and eigenvectors will let you do that via diagonalization. So here I'm demonstrating a use for the eigenvectors, but not, perhaps, a physical meaning directly.

The relevant field here is spectral graph theory. Maybe you could find some books in a university library related to spectral graph theory.
 

1. What is the meaning of eigenvectors in a graph?

Eigenvectors in a graph represent the directions in which a graph is stretched or compressed during a transformation.

2. How are eigenvectors related to eigenvalues in a graph?

Eigenvectors and eigenvalues are related in that an eigenvector is a vector that, when multiplied by a transformation matrix, results in a scalar multiple of itself, which is the corresponding eigenvalue.

3. Can eigenvectors in a graph have negative values?

Yes, eigenvectors in a graph can have negative values. The sign of an eigenvector is not important, as it only represents the direction of the vector.

4. How are eigenvectors used in graph theory?

Eigenvectors are used in graph theory to find important nodes or structures in a graph. They can also be used for clustering and community detection.

5. Are eigenvectors unique for a given graph?

Yes, eigenvectors are unique for a given graph. However, different graphs can have the same eigenvectors if they have the same structure or adjacency matrix.

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