Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 70 tok/s
Gemini 2.5 Pro 42 tok/s Pro
GPT-5 Medium 30 tok/s Pro
GPT-5 High 34 tok/s Pro
GPT-4o 111 tok/s Pro
Kimi K2 202 tok/s Pro
GPT OSS 120B 452 tok/s Pro
Claude Sonnet 4.5 34 tok/s Pro
2000 character limit reached

The effect of small quenched noise on connectivity properties of random interlacements (1109.5086v3)

Published 23 Sep 2011 in math.PR

Abstract: The random interlacements (at level u) is a one parameter family of random subsets of Zd introduced by Sznitman in arXiv:0704.2560. The vacant set at level u is the complement of the random interlacement at level u. In this paper, we study the effect of small quenched noise on connectivity properties of the random interlacement and the vacant set. While the random interlacement induces a connected subgraph of Zd for all levels u, the vacant set has a non-trivial phase transition in u, as shown in arXiv:0704.2560 and arXiv:0808.3344. For a positive epsilon, we allow each vertex of the random interlacement (referred to as occupied) to become vacant, and each vertex of the vacant set to become occupied with probability epsilon, independently of the randomness of the interlacement, and independently for different vertices. We prove that for any d>=3 and u>0, almost surely, the perturbed random interlacement percolates for small enough noise parameter epsilon. In fact, we prove the stronger statement that Bernoulli percolation on the random interlacement graph has a non-trivial phase transition in wide enough slabs. As a byproduct, we show that any electric network with i.i.d. positive resistances on the interlacement graph is transient, which strengthens our result in arXiv:1102.4758. As for the vacant set, we show that for any d>=3, there is still a non-trivial phase transition in u when the noise parameter epsilon is small enough, and we give explicit upper and lower bounds on the value of the critical threshold, when epsilon tends to 0.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.