Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant 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 87 tok/s
Gemini 2.5 Pro 45 tok/s Pro
GPT-5 Medium 32 tok/s Pro
GPT-5 High 29 tok/s Pro
GPT-4o 105 tok/s Pro
Kimi K2 202 tok/s Pro
GPT OSS 120B 461 tok/s Pro
Claude Sonnet 4 39 tok/s Pro
2000 character limit reached

Chemical distance for smooth Gaussian fields in higher dimension (2503.22434v1)

Published 28 Mar 2025 in math.PR

Abstract: Gaussian percolation can be seen as the generalization of standard Bernoulli percolation on $\mathbb{Z}d$. Instead of a random discrete configuration on a lattice, we consider a continuous Gaussian field $f$ and we study the topological and geometric properties of the random excursion set $\mathcal{E}\ell(f) := {x\in \mathbb{R}d\ |\ f(x)\geq -\ell}$ where $\ell\in \mathbb{R}$ is called a level. It is known that for a wide variety of fields $f$, there exists a phase transition at some critical level $\ell_c$. When $\ell> \ell_c$, the excursion set $\mathcal{E}\ell(f)$ presents a unique unbounded component while if $\ell<\ell_c$ there are only bounded components in $\mathcal{E}\ell(f)$. In the supercritical regime, $\ell>\ell_c$, we study the geometry of the unbounded cluster. Inspired by the work of Peter Antal and Agoston Pisztora for the Bernoulli model \cite{Antal}, we introduce the chemical distance between two points $x$ and $y$ as the Euclidean length of the shortest path connecting these points and staying in $\mathcal{E}\ell(f)$. In this paper, we show that when $\ell>-\ell_c$ then with high probability, the chemical distance between two points has a behavior close to the Euclidean distance between those two points.

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

Collections

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

Summary

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

Dice Question Streamline Icon: https://streamlinehq.com

Follow-Up Questions

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

Authors (1)

X Twitter Logo Streamline Icon: https://streamlinehq.com

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube