
TL;DR
This paper introduces a correlated percolation model called the random length worms model, analyzing its connectivity properties and providing conditions for percolation at all intensities in high dimensions.
Contribution
The authors establish a sufficient condition on the length distribution that guarantees percolation for all positive intensities in dimensions five and higher.
Findings
Percolation occurs for all v > 0 under certain length distribution conditions.
The length distribution with a barely infinite second moment still guarantees percolation.
The model is closely related to the extremal behavior in the Poisson zoo family of models.
Abstract
We introduce a new correlated percolation model on the -dimensional lattice called the random length worms model. Assume given a probability distribution on the set of positive integers (the length distribution) and (the intensity parameter). From each site of we start independent simple random walks with this length distribution. We investigate the connectivity properties of the set of sites visited by this cloud of random walks. It is easy to show that if the second moment of the length distribution is finite then undergoes a percolation phase transition as varies. Our main contribution is a sufficient condition on the length distribution which guarantees that percolates for all if . E.g., if the probability mass function of the length distribution…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
