Disentangling Giant Component and Finite Cluster Contributions in Sparse Matrix Spectra
Reimer Kuehn
TL;DR
This paper introduces a method to separate the spectral contributions of the giant component and finite clusters in sparse random matrices, using Erdős-Rényi graphs as a test case.
Contribution
A novel approach for disentangling spectral effects of giant components and finite clusters in sparse matrices, demonstrated on Erdős-Rényi graphs.
Findings
Effective separation of spectral contributions achieved
Method validated on Erdős-Rényi graph models
Provides insights into spectral structure of sparse matrices
Abstract
We describe a method for disentangling giant component and finite cluster contributions to sparse random matrix spectra, using sparse symmetric random matrices defined on Erdos-Renyi graphs as an example and test-bed.
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