% Encoding: UTF-8
@COMMENT{BibTeX export based on data in FAU CRIS: https://cris.fau.de/}
@COMMENT{For any questions please write to cris-support@fau.de}
@article{faucris.269963479,
abstract = {In this work, we study the spectrum of the normalized Laplacian and its regularized version for random geometric graphs (RGGs) in various scaling regimes. Two scaling regimes are of special interest, the connectivity and the thermodynamic regime. In the connectivity regime, the average vertex degree grows logarithmically in the graph size or faster. In the thermodynamic regime, the average vertex degree is a constant. We introduce a deterministic geometric graph (DGG) with nodes in a grid and provide an upper bound to the probability that the Hilbertâ€“Schmidt norm of the difference between the normalized Laplacian matrices of the RGG and DGG is greater than a certain threshold in both the connectivity and thermodynamic regime. Using this result, we show that the RGG and DGG normalized Laplacian matrices are asymptotically equivalent with high probability (w.h.p.) in the full range of the connectivity regime. The equivalence is even stronger and holds almost surely when the average vertex degree an satisfies the inequality an> 24 log (n). Therefore, we use the regular structure of the DGG to show that the limiting eigenvalue distribution of the RGG normalized Laplacian matrix converges to a distribution with a Dirac atomic measure at zero. In the thermodynamic regime, we approximate the eigenvalues of the regularized normalized Laplacian matrix of the RGG by the eigenvalues of the DGG regularized normalized Laplacian and we provide an error bound which is valid w.h.p. and depends upon the average vertex degree.},
author = {Hamidouche, Mounia and Cottatellucci, Laura and Avrachenkov, Konstantin},
doi = {10.1007/s10959-022-01158-0},
faupublication = {yes},
journal = {Journal of Theoretical Probability},
keywords = {Connectivity regime; Limiting eigenvalue distribution; Normalized Laplacian; Random geometric graph; Thermodynamic regime},
note = {CRIS-Team Scopus Importer:2022-02-25},
peerreviewed = {Yes},
title = {{On} the {Normalized} {Laplacian} {Spectra} of {Random} {Geometric} {Graphs}},
year = {2022}
}