Spectral theory of the non-backtracking Laplacian for graphs
arXiv:2203.10824 · doi:10.1016/j.disc.2023.113536
Abstract
We introduce a non-backtracking Laplace operator for graphs and we investigate its spectral properties. With the use of both theoretical and computational techniques, we show that the spectrum of this operator captures several structural properties of the graph in a more precise way than the classical operators that have been studied so far in the literature, including the non-backtracking matrix.
References in corpus (6)
- Spectral redemption: clustering sparse networks
- Localization and centrality in networks
- Non-backtracking random walks mix faster
- A message-passing approach for recurrent-state epidemic models on networks
- Relevance of backtracking paths in epidemic spreading on networks
- Distinguishing graphs with zeta functions and generalized spectra