Algorithms, Combinatorics and Optimization Seminar Philip Matchett Wood
University of Wisconsin-Madison
Title: Limiting eigenvalue distribution for the non-backtracking matrix of an Erdos-Renyi random graph

Abstract: A non-backtracking random walk on a graph is a directed walk with the constraint that the last edge crossed may not be immediately crossed again in the opposite direction. This talk will give a precise description of the eigenvalues of the transition matrix for the non-backtracking random walk when the underlying graph is an Erdos-Renyi random graph on n vertices, where edges present independently with probability p. We allow p to be constant or decreasing with n, so long as np/log n tends to infinity. The key ideas in the proof are partial derandomization, applying the Tao-Vu Replacement Principle in a novel context, and showing that partial derandomization may be interpreted as a perturbation, allowing one to apply the Bauer-Fike Theorem. Joint work with Ke Wang at HKUST (Hong Kong University of Science and Technology).

Date: Thursday, January 25, 2018
Time: 3:30 pm
Location: Wean Hall 8220
Note: Before the talk, at 3:10 pm, there will be tea and cookies in Wean Hall 6220.