TL;DR
This paper investigates the conditions under which random graphs with latent geometric structures become indistinguishable from Erdős-Rényi graphs, providing new theoretical thresholds for different models.
Contribution
It establishes precise phase transition thresholds for random intersection and geometric graphs converging to Erdős-Rényi models, resolving open problems and conjectures.
Findings
Random intersection graphs converge to Erdős-Rényi when d = (n^3)
Conditions for convergence of intersection size matrices to Poisson matrices
Geometric graphs on spheres converge when d = (min{pn^3, p^2 n^{7/2}})
Abstract
Random graphs with latent geometric structure are popular models of social and biological networks, with applications ranging from network user profiling to circuit design. These graphs are also of purely theoretical interest within computer science, probability and statistics. A fundamental initial question regarding these models is: when are these random graphs affected by their latent geometry and when are they indistinguishable from simpler models without latent structure, such as the Erd\H{o}s-R\'{e}nyi graph ? We address this question for two of the most well-studied models of random graphs with latent geometry -- the random intersection and random geometric graph. Our results are as follows: (1) we prove that the random intersection graph converges in total variation to when , and does not if ,…
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Videos
Phase Transitions for Detecting Latent Geometry in Random Graphs· youtube
