SearcharxivSearch

arXiv · 2601.09950

Recursive Packing Bounds for Supercritical Disconnection in Bernoulli Site Percolation

Abstract

For Bernoulli site percolation on an infinite, connected, locally finite graph $G=(V,E)$, we obtain quantitative upper bounds on the supercritical disconnection probability \[ \mathbb{P}_p(S\nleftrightarrow\infty) \] for arbitrary finite or infinite sets $S\subset V$ and all $p>p^{\mathrm{site}}_c(G)$. The key quantity is a recursive packing number $\mathbf{PK}_{p,\eps,c}(S)$. It is the maximal number of vertices that can be extracted from $S$ so that, after deleting witness balls around the previously chosen vertices, each selected vertex still connects to infinity with probability at least $c$, while its failure to connect to infinity is already detected, up to a factor $1+\eps$, by failure to reach the inner boundary of its witness ball. Thus $\mathbf{PK}_{p,\eps,c}(S)$ counts essentially independent local witnesses for the global event $\{S\nleftrightarrow\infty\}$. We prove the structural estimate \[ \mathbb{P}_p(S\nleftrightarrow\infty) \le \frac{\eps(1-c)}{c} +(1-c)^{\mathbf{PK}_{p,\eps,c}(S)}. \] Combining this bound with the local functional characterization of $p^{\mathrm{site}}_c(G)$ from \cite{ZL24} yields an explicit supercritical estimate valid on every infinite, connected, locally finite graph. We also illustrate the packing number on ray-homogeneous trees. In particular, sparse finite subsets of a distinguished ray have packing number equal to their cardinality, both for regular trees and for a non-regular decorated spine. This shows that the packing number is explicit on concrete graph families.

Explore related subjects

Keep this discovery

BibTeXRIS

Zhongyang Li. 2026-01-15. Recursive Packing Bounds for Supercritical Disconnection in Bernoulli Site Percolation. https://arxiv.org/abs/2601.09950

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Averaging principles for nonautonomous multiscale stochastic Burgers equations with reflection

In this paper, we study averaging principles for nonautonomous multiscale stochastic Burgers equations with reflection. First, we derive a general averaging principle applicable to such equations under minimal assumptions. Subsequently, since the coefficients of the obtained averaged equation still depend on the small scaling parameter $\e$, we impose either periodic or asymptotic conditions on the coefficients, thereby obtain two distinct averaged equations whose coefficients are independent of $\e$ and establish two averaging principles. Stopping times and Khasminskii's time discretization schemes play an important role. Finally, a concrete example is provided to illustrate the applicability and validity of the theoretical results.

math.PR

Spectral properties of Random Matrices

We give the theoretical foundations of random matrix theory through the definitions of a random matrix, a random probability measure and the corresponding empirical spectral distribution. The technical tool we use is the Stieltjes transform method through which we prove optimal convergence of the empirical spectral distribution of random sample covariance matrices to the deterministic Marchenko-Pastur distribution. We also give new results about the rigidity of the eigenvalues of this random sample covariance matrix and the rate of their convergence. We then define the Dyson equation method to prove new local laws about a random matrix model that interpolates between the Marchenko-Pastur distribution, the elliptical law and the circular law. Through our work these local laws can be considered universal.

math.PR

Moments approach for the elephant random walk

We discuss the method of moments for the one-dimensional elephant random walk (ERW). We first derive a differential recurrence relation for the characteristic function of the ERW, which yields a corresponding system of recurrence relations for its moments. We then obtain asymptotic approximations for the moments in each of the three parameter regimes of the ERW. Finally, by establishing the convergence of the moments and verifying the corresponding moment-determinacy conditions, we identify the limiting distributions of the ERW in each regime.

math.PR