Laplacian matrix

Laplacian matrix

In the mathematical field of graph theory the Laplacian matrix, sometimes called admittance matrix or Kirchhoff matrix, is a matrix representation of a graph. Together with Kirchhoff's theorem it can be used to calculate the number of spanning trees for a given graph. The Laplacian matrix can be used to find many others properties of the graph, see spectral graph theory.

Definition

Given a graph "G" with "n" vertices (without loops or multiple edges), its Laplacian matrix L:=(ell_{i,j})_{n imes n} is defined as [Weisstein, Eric W. " [http://mathworld.wolfram.com/LaplacianMatrix.html Laplacian Matrix] ." From MathWorld—A Wolfram Web Resource.]

:ell_{i,j}:=egin{cases}deg(v_i) & mbox{if} i = j \-1 & mbox{if} i eq j mbox{and} v_i ext{ is adjacent to } v_j \0 & ext{otherwise}.end{cases}

That is, it is the difference of the degree matrix and the adjacency matrix of the graph.In the case of directed graphs, either the indegree or the outdegree might be used, depending on the application.

The normalized laplacian matrix is defined as [Weisstein, Eric W. " [http://mathworld.wolfram.com/LaplacianMatrix.html Laplacian Matrix] ." From MathWorld—A Wolfram Web Resource.]

:ell_{i,j}:=egin{cases}1 & mbox{if} i = j mbox{and} deg(v_i) eq 0\-frac{1}{sqrt{deg(v_i)deg(v_j) & mbox{if} i eq j mbox{and} v_i ext{ is adjacent to } v_j \0 & ext{otherwise}.end{cases}

Example

Here is a simple example of a labeled graph and its Laplacian matrix.

Properties

For a graph "G" and its Laplacian matrix "L" with eigenvalues lambda_0 le lambda_1 le cdots le lambda_{n-1}:

* "L" is always positive-semidefinite (forall i, lambda_i ge 0).
* The number of times 0 appears as an eigenvalue in the Laplacian is the number of connected components in the graph.
* lambda_0 is always 0.
* lambda_1 is called the algebraic connectivity.
* The smallest non-trivial eigenvalue of "L" is called the spectral gap or Fiedler value.

Deformed Laplacian

The deformed Laplacian is commonly defined as

:Delta(s)=I-sA+s^2(D-I)

where "I" is the unit matrix, "A" is the adjacency matrix, and "D" is the degree matrix, and "s" is a (complex-valued) number. Note that normal Laplacian is just Delta(1).

As an operator

The Laplacian matrix can be generalized to the case of graphs with an infinite number of vertices and edges; this generalization is known as the discrete Laplace operator.

ee also

*Kirchhoff's theorem

References


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