Hermitian normalized Laplacian matrix for directed networks

Guihai Yu, Matthias Dehmer, Frank Emmert-Streib, Herbert Jodlbauer

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


In this paper, we extend and generalize the spectral theory of undirected networks towards directed networks by introducing the Hermitian normalized Laplacian matrix for directed networks. In order to start, we discuss the Courant–Fischer theorem for the eigenvalues of Hermitian normalized Laplacian matrix. Based on the Courant–Fischer theorem, we obtain a similar result towards the normalized Laplacian matrix of undirected networks: for each i ∈ {1, 2,…, n}, any eigenvalue of Hermitian normalized Laplacian matrix λi ∈ [0, 2]. Moreover, we prove some special conditions if 0, or 2 is an eigenvalue of the Hermitian normalized Laplacian matrix L(X). On top of that, we investigate the symmetry of the eigenvalues of L(X)and the edge-version for the eigenvalue interlacing result. Finally we present two expressions for the coefficients of the characteristic polynomial of the Hermitian normalized Laplacian matrix. As an outlook, we sketch some novel and intriguing problems to which our apparatus could generally be applied.

Original languageEnglish
Pages (from-to)175-184
Number of pages10
JournalInformation Sciences
Publication statusPublished - Aug 2019


  • Characteristic polynomial
  • Courant–Fischer theorem
  • Directed networks
  • Eigenvalue interlacing inequality
  • Hermitian normalized Laplacian matrix


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