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Article
Using Markov Chains to Determine Expected Propagation Time for Probabilistic Zero Forcing
Electronic Journal of Linear Algebra
  • Yu Chan, Iowa State University
  • Emelie Curl, Iowa State University
  • Jesse Geneson, Iowa State University
  • Leslie Hogben, Iowa State University
  • Kevin Liu, Iowa State University
  • Issac Odegard, Iowa State University
  • Michael S. Ross, Iowa State University
Document Type
Article
Publication Version
Published Version
Publication Date
6-1-2020
DOI
10.13001/ela.2020.5127
Abstract

Zero forcing is a coloring game played on a graph where each vertex is initially colored blue or white and the goal is to color all the vertices blue by repeated use of a (deterministic) color change rule starting with as few blue vertices as possible. Probabilistic zero forcing yields a discrete dynamical system governed by a Markov chain. Since in a connected graph any one vertex can eventually color the entire graph blue using probabilistic zero forcing, the expected time to do this is studied. Given a Markov transition matrix for a probabilistic zero forcing process, an exact formula is established for expected propagation time. Markov chains are applied to determine bounds on expected propagation time for various families of graphs.

Comments

This article is published as Chan, Yu, Emelie Curl, Jesse Geneson, Leslie Hogben, Kevin Liu, Issac Odegard, and Michael Ross. "Using Markov Chains to Determine Expected Propagation Time for Probabilistic Zero Forcing." The Electronic Journal of Linear Algebra 36, no. 36 (2020): 318-333. DOI: 10.13001/ela.2020.5127. Posted with permission.

Copyright Owner
The Author(s)
Language
en
File Format
application/pdf
Citation Information
Yu Chan, Emelie Curl, Jesse Geneson, Leslie Hogben, et al.. "Using Markov Chains to Determine Expected Propagation Time for Probabilistic Zero Forcing" Electronic Journal of Linear Algebra Vol. 36 Iss. 36 (2020) p. 318 - 333
Available at: http://works.bepress.com/leslie-hogben/108/