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Electronic Journal of Combinatorics
Article . 2006 . Peer-reviewed
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Article . 2006
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Kernels of Directed Graph Laplacians

Kernels of directed graph Laplacians
Authors: Caughman, John S., IV; Veerman, J. J. P.;

Kernels of Directed Graph Laplacians

Abstract

Let $G$ denote a directed graph with adjacency matrix $Q$ and in-degree matrix $D$. We consider the Kirchhoff matrix $L=D-Q$, sometimes referred to as the directed Laplacian. A classical result of Kirchhoff asserts that when $G$ is undirected, the multiplicity of the eigenvalue 0 equals the number of connected components of $G$. This fact has a meaningful generalization to directed graphs, as was recently observed by Chebotarev and Agaev in 2005. Since this result has many important applications in the sciences, we offer an independent and self-contained proof of their theorem, showing in this paper that the algebraic and geometric multiplicities of 0 are equal, and that a graph-theoretic property determines the dimension of this eigenspace – namely, the number of reaches of the directed graph. We also extend their results by deriving a natural basis for the corresponding eigenspace. The results are proved in the general context of stochastic matrices, and apply equally well to directed graphs with non-negative edge weights.

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United States
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Keywords

Graphs and linear algebra (matrices, eigenvalues, etc.), stochastic matrices, Matrices, Kirchhoff matrix, Discrete Mathematics and Combinatorics, eigenvalue, Laplacian matrices -- Eigenvalues, Laplacian, Mathematics, Directed graphs, Stochastic matrices

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
58
Top 10%
Top 10%
Average
gold