Long paths and connectivity in {$1$}-independent random graphs
A. Nicholas Day, Victor Falgas-Ravry, Robert Hancock

TL;DR
This paper investigates connectivity and long path properties in 1-independent percolation models on graphs, providing new bounds on critical probabilities and exact results for specific finite graphs, extending classical percolation theory.
Contribution
It introduces improved bounds on the critical probability for infinite clusters in 1-independent models and determines exact connectivity probabilities for certain finite graphs.
Findings
New lower bounds on the critical probability p* for infinite clusters.
Exact formulas for connectivity probabilities in paths, cycles, and complete graphs.
Determination of the 1-independent critical probability for long paths on line and ladder lattices.
Abstract
Given a graph , a probability measure on the subsets of the edge set of is said to be -independent if events determined by edge sets that are at graph distance at least apart in are independent. Call such a probability measure a -ipm on , and denote by the associated random spanning subgraph of . Let (resp. ) denote the collection of -ipms on for which each edge is included in with probability at least (resp. at most ). Let denote the square integer lattice. Balister and Bollob\'as raised the question of determining the critical value such that for all and all , almost surely…
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