Saved in:
Bibliographic Details
Main Authors: Wang, Ke, Wood, Philip Matchett
Format: Preprint
Published: 2017
Subjects:
Online Access:https://arxiv.org/abs/1710.11015
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911742545625088
author Wang, Ke
Wood, Philip Matchett
author_facet Wang, Ke
Wood, Philip Matchett
contents In this note, we give a precise description of the limiting empirical spectral distribution (ESD) for the non-backtracking matrices for an Erdős-Rényi graph assuming $np/\log n$ 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.
format Preprint
id arxiv_https___arxiv_org_abs_1710_11015
institution arXiv
publishDate 2017
record_format arxiv
spellingShingle Limiting empirical spectral distribution for the non-backtracking matrix of an Erdős-Rényi random graph
Wang, Ke
Wood, Philip Matchett
Probability
In this note, we give a precise description of the limiting empirical spectral distribution (ESD) for the non-backtracking matrices for an Erdős-Rényi graph assuming $np/\log n$ 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.
title Limiting empirical spectral distribution for the non-backtracking matrix of an Erdős-Rényi random graph
topic Probability
url https://arxiv.org/abs/1710.11015