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Non-Backtracking Random Walks and a Weighted Ihara’s Theorem
Author(s) -
Mark Kempton
Publication year - 2016
Publication title -
open journal of discrete mathematics
Language(s) - English
Resource type - Journals
eISSN - 2161-7643
pISSN - 2161-7635
DOI - 10.4236/ojdm.2016.64018
Subject(s) - adjacency matrix , random walk , mathematics , backtracking , combinatorics , discrete mathematics , stochastic matrix , random graph , graph , algorithm , statistics , markov chain
We study the mixing rate of non-backtracking random walks on graphs by looking at non-backtracking walks as walks on the directed edges of a graph. A result known as Ihara’s Theorem relates the adjacency matrix of a graph to a matrix related to non-backtracking walks on the directed edges. We prove a weighted version of Ihara’s Theorem which relates the transition probability matrix of a non-backtracking walk to the transition matrix for the usual random walk. This allows us to determine the spectrum of the transition probability matrix of a non-backtracking random walk in the case of regular graphs and biregular graphs. As a corollary, we obtain a result of Alon et al. in [1] that in most cases, a non-backtracking random walk on a regular graph has a faster mixing rate than the usual random walk. In addition, we obtain an analogous result for biregular graphs.

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