An Inverse Approach for Finding Graphs with a Failed Zero Forcing Number of k

Chirag Kaudan, Rachel Taylor and Darren A. Narayan ()
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Chirag Kaudan: Department of Computer Science, San José State University, San Jose, CA 95192, USA
Rachel Taylor: Deapartment of Mathematical Sciences, DePaul University, Chicago, IL 60614, USA
Darren A. Narayan: School of Mathematical and Statistics, Rochester Institute of Technology, Rochester, NY 14623, USA

Mathematics, 2023, vol. 11, issue 19, 1-13

Abstract: For a given a graph G , the zero forcing number of G , Z ( G ) , is the smallest cardinality of any set S of vertices on which repeated applications of the forcing rule results in all vertices being included in S . The forcing rule is as follows: if a vertex v is in S , and exactly one neighbor u of v is not in S , then u is added to S in the next iteration. The failed zero forcing number of a graph was introduced by Fetcie, Jacob, and Saavedra and was defined as the cardinality of the largest set of vertices which fails to force all vertices in the graph. In 2021, Gomez et al. proved that there were exactly 15 graphs with a failed zero forcing number of two, but their proof was complicated, requiring the analysis of many graph families. We present an “inverse” approach where we start with a set of vertices S and then see which graphs have S as a maximum-sized failed zero forcing set. This results in not only a shorter proof but characterizes which graphs have a particular failed zero forcing set. In our proof, we characterize the graphs which have a failed zero forcing set S where | S | = 2 , meaning considering all simple graphs of order two as induced subgraphs. This approach also has greater potential for characterizing graphs where F ( G ) > 2 since many general arguments on the structure of graphs are developed in this type of analysis and are applicable for failed zero forcing sets of any size.

Keywords: zero forcing; failed zero forcing (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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