A new framework for identifying most reliable graphs and a correction to the $K_{3,3}$-theorem
Lorents F. Landgren, Jeffrey E. Steif

TL;DR
This paper develops a framework to identify most reliable graphs under percolation, corrects a longstanding error regarding subdivisions of $K_{3,3}$, and explores how optimal graphs depend on parameters like $m$ and $p$.
Contribution
It introduces a new framework for identifying optimal graphs for reliability, rectifies a historical mistake about $K_{3,3}$ subdivisions, and analyzes the dependence of optimality on graph parameters.
Findings
Identified all optimal graphs for $m-n\\in\{1,2,3\}$, which are uniformly optimal in $p$.
Corrected the previous error in Wang's 1994 result about subdivisions of $K_{3,3}$.
Discovered new values of $m$ where optimal graphs depend on $p$, supporting conjectures about the finiteness of uniformly optimal graphs.
Abstract
Given a multigraph , the all-terminal reliability is the probability that remains connected under percolation with parameter . Fixing the number of vertices and edges , we investigate which graphs maximize -- such graphs are called optimal -- paying particular attention to uniqueness and to whether the answer depends upon . We generalize the concept of a distillation and build a framework with which we identify all optimal graphs for which . These graphs are uniformly optimal in . Most have been previously identified, but with serious problems, especially when . We obtain partial results for . For , the optimal graphs were incorrectly identified by Wang in 1994, in the infinite number of cases where and . This erroneous result concerns subdivisions of and has…
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Taxonomy
TopicsAlgorithms and Data Compression · Graph Theory and Algorithms · Complexity and Algorithms in Graphs
