The weighted self-similar network is introduced in an iterative way.In order to understand the topological properties of the self-similar network,we have done a lot of research in this field.Firstly,according to the s...The weighted self-similar network is introduced in an iterative way.In order to understand the topological properties of the self-similar network,we have done a lot of research in this field.Firstly,according to the symmetry feature of the self-similar network,we deduce the recursive relationship of its eigenvalues at two successive generations of the transition-weighted matrix.Then,we obtain eigenvalues of the Laplacian matrix from these two successive generations.Finally,we calculate an accurate expression for the eigentime identity and Kirchhoff index from the spectrum of the Laplacian matrix.展开更多
基金supported by the Natural Science Foundation of China(Nos.11671172)。
文摘The weighted self-similar network is introduced in an iterative way.In order to understand the topological properties of the self-similar network,we have done a lot of research in this field.Firstly,according to the symmetry feature of the self-similar network,we deduce the recursive relationship of its eigenvalues at two successive generations of the transition-weighted matrix.Then,we obtain eigenvalues of the Laplacian matrix from these two successive generations.Finally,we calculate an accurate expression for the eigentime identity and Kirchhoff index from the spectrum of the Laplacian matrix.
