Breadth-first search on a Ramanujan graph

08/26/2019 ∙ by Janko Boehm, et al. ∙ 0

The behavior of the randomized breadth-first search algorithm is analyzed on arbitrary regular and non-regular graphs. Our argument is based on the expander mixing lemma, which entails that the results are strongest for Ramanujan graphs, which asymptotically maximize the spectral gap. We compare our theoretical results with computational experiments on flip graphs of point configurations. The latter is relevant for enumerating triangulations.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.