Year: 2026
Type: preprint
Abstract: Network diffusion is a well-known model for studying how a quantity in a network propagates to reach a steady state, where its value becomes uniformly distributed across all nodes. Previous studies of network diffusion have mainly focused on the second-smallest eigenvalue of the network Laplacian to determine the timescale associated with the slowest decaying mode. However, this study investigates the eigenspectrum of the network Laplacian in terms of its statistical properties. This method is useful for studying the statistical properties of network diffusion without calculating all eigenvalues, which can be useful for large networks. Additionally, this study introduces a condition under which the system is less diffusive and investigates how changes in the network structure influence the overall diffusion dynamics.
Source: arXiv (Cornell University)
Author: Talebi, A.
Institution: Shahid Beheshti University
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7214090575