Random geometric graphs and the spherical Wishart matrix
Abstract
We consider the random geometric graph on vertices drawn uniformly from a --dimensional sphere. We focus on the sparse regime, when the expected degree is constant independent of and . We show that, when is larger than by logarithmic factors, this graph is comparable to the Erd\H{o}s--R\'enyi random graph of the same edge density in the \emph{inclusion divergence} between the graph laws. This divergence functions in certain ways like a relaxation of the total variation distance, but is strong enough to distinguish Erd\H{o}s--R\'enyi graphs of different densities with a higher resolution than the total variation distance. To do the analysis, we derive some exact statistics of the \emph{spherical Wishart matrix}, the Gram matrix of independent uniformly random --dimensional spherical vectors. In particular we give expressions for the characteristic function of the spherical Wishart matrix which are well--approximated using steepest descent.
Cite
@article{arxiv.2110.10785,
title = {Random geometric graphs and the spherical Wishart matrix},
author = {Elliot Paquette and Andrew Vander Werf},
journal= {arXiv preprint arXiv:2110.10785},
year = {2021}
}