On the spectra of nonsymmetric Laplacian matrices
Rafig Agaev, Pavel Chebotarev
Abstract
A Laplacian matrix is a square real matrix with nonpositive off-diagonal entries and zero row sums. As a matrix associated with a weighted directed graph, it generalizes the Laplacian matrix of an ordinary graph. A standardized Laplacian matrix is a Laplacian matrix with the absolute values of the off-diagonal entries not exceeding 1/n, where n is the order of the matrix. We study the spectra of Laplacian matrices and relations between Laplacian matrices and stochastic matrices. We prove that the standardized Laplacian matrices are semiconvergent. The multiplicities of 0 and 1 as the eigenvalues of a standardized Laplacian matrix are equal to the in-forest dimension of the corresponding digraph and one less than the in-forest dimension of the complementary digraph, respectively. These eigenvalues are semisimple. The spectrum of a standardized Laplacian matrix belongs to the meet of two closed disks, one centered at 1/n, another at 1-1/n, each having radius 1-1/n, and two closed angles, one bounded with two half-lines drawn from 1, another with two half-lines drawn from 0 through certain points. The imaginary parts of the eigenvalues are bounded from above by 1/(2n) cot(pi/2n); this maximum converges to 1/pi as n goes to infinity. Keywords: Laplacian matrix; Laplacian spectrum of graph; Weighted directed graph; Forest dimension of digraph; Stochastic matrix
Create a lesson
Related papers
Off-Diagonal Induced Ramsey Numbers
Bruno Andrades, Marcelo Campos, Rafael Filipe et al.
Largest Sperner families with bounded VC-dimension
Gennian Ge, Hanyu Wang, Zixiang Xu et al.
Proof of two conjectures on the log-concavity of partition ranks and cranks
Jianxi Mao, Wenle Shi, Bao-Xuan Zhu
The Exact Number of Pentagons in Book-Free Graphs
Wentao Hu
A family of symmetric counterexamples to the bent sum decomposition conjecture
Máté Róbert Kepes, Anita Kercsó-Molnár, Viczián András
Counting graphs admitting a strictly matched involution
Stephan Dominique Andres, Igor Režan