Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
110 tokens/sec
GPT-4o
56 tokens/sec
Gemini 2.5 Pro Pro
44 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Spectral bounds of the regularized normalized Laplacian for random geometric graphs (1910.08873v1)

Published 20 Oct 2019 in math.SP and cs.DM

Abstract: In this work, we study the spectrum of the regularized normalized Laplacian for random geometric graphs (RGGs) in both the connectivity and thermodynamic regimes. We prove that the limiting eigenvalue distribution (LED) of the normalized Laplacian matrix for an RGG converges to the Dirac measure in one in the full range of the connectivity regime. In the thermodynamic regime, we propose an approximation for the LED and we provide a bound on the Levy distance between the approximation and the actual distribution. In particular, we show that the LED of the regularized normalized Laplacian matrix for an RGG can be approximated by the LED of the regularized normalized Laplacian for a deterministic geometric graph with nodes in a grid (DGG). Thereby, we obtain an explicit approximation of the eigenvalues in the thermodynamic regime.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (3)
  1. Mounia Hamidouche (10 papers)
  2. Laura Cottatellucci (31 papers)
  3. Konstantin Avrachenkov (75 papers)
Citations (1)

Summary

We haven't generated a summary for this paper yet.