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Limiting empirical spectral distribution for the non-backtracking matrix of an Erdős-Rényi random graph

Ke Wang, Philip Matchett Wood

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Source: Crossref

Published: Jul 31, 2023

DOI: 10.1017/s096354832300024x

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Abstract In this note, we give a precise description of the limiting empirical spectral distribution for the non-backtracking matrices for an Erdős-Rényi graph G(n,p)G(n,p) assuming np/log⁡nnp/\log n tends to infinity. We show that derandomizing part of the non-backtracking random matrix simplifies the spectrum considerably, and then, we use Tao and Vu’s replacement principle and the Bauer-Fike theorem to show that the partly derandomized spectrum is, in fact, very close to the original spectrum.

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Limiting empirical spectral distribution for the non-backtracking matrix of an Erdős-Rényi random graph — Mathematical Frontier Network