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Noise sensitivity and variance lower bound for minimal left-right crossing of a square in first-passage percolation

Barbara Dembin, Dor Elboim

Abstract

We study first-passage percolation on $\mathbb Z ^2$ with independent and identically distributed weights, whose common distribution is uniform on $\{a,b\}$ with $0<a<b<\infty $. Following Ahlberg and De la Riva, we consider the passage time $τ(n,k)$ of the minimal left-right crossing of the square $[0,n]^2$, whose vertical fluctuations are bounded by $k$. We prove that when $k\le n^{1/2-ε}$, the event that $τ(n,k)$ is larger than its median is noise sensitive. This improves the main result of Ahlberg and De la Riva which holds when $k\le n^{1/22-ε}$. Under the additional assumption that the limit shape is not a polygon with a small number of sides, we extend the result to all $k\le n^{1-ε}$. This extension follows unconditionally when $a$ and $b$ are sufficiently close. Under a stronger curvature assumption, we extend the result to all $k\le n$. This in particular captures the noise sensitivity of the event that the minimal left-right crossing $T_n=τ(n,n)$ is larger than its median. Finally, under the curvature assumption, our methods give a lower bound of $n^{1/4-ε}$ for the variance of the passage time $T_n$ of the minimal left-right crossing of the square. We prove the last bound also for absolutely continuous weight distributions, generalizing a result of Damron--Houdré--Özdemir, which holds only for the exponential distribution. Our approach differs from the previous works mentioned above; the key idea is to establish a small ball probability estimate in the tail by perturbing the weights for tail events using a Mermin--Wagner type estimate.

Noise sensitivity and variance lower bound for minimal left-right crossing of a square in first-passage percolation

Abstract

We study first-passage percolation on with independent and identically distributed weights, whose common distribution is uniform on with . Following Ahlberg and De la Riva, we consider the passage time of the minimal left-right crossing of the square , whose vertical fluctuations are bounded by . We prove that when , the event that is larger than its median is noise sensitive. This improves the main result of Ahlberg and De la Riva which holds when . Under the additional assumption that the limit shape is not a polygon with a small number of sides, we extend the result to all . This extension follows unconditionally when and are sufficiently close. Under a stronger curvature assumption, we extend the result to all . This in particular captures the noise sensitivity of the event that the minimal left-right crossing is larger than its median. Finally, under the curvature assumption, our methods give a lower bound of for the variance of the passage time of the minimal left-right crossing of the square. We prove the last bound also for absolutely continuous weight distributions, generalizing a result of Damron--Houdré--Özdemir, which holds only for the exponential distribution. Our approach differs from the previous works mentioned above; the key idea is to establish a small ball probability estimate in the tail by perturbing the weights for tail events using a Mermin--Wagner type estimate.
Paper Structure (18 sections, 24 theorems, 122 equations, 1 figure)

This paper contains 18 sections, 24 theorems, 122 equations, 1 figure.

Key Result

Theorem 1.2

Suppose that $G$ satisfies eq:assumption atomic. Fix $\alpha \in (0,1)$ and for a sequence of integers $(k_n)_{n\ge 1}$, consider the events The following holds:

Figures (1)

  • Figure 1: The events $\Omega$ and $\Sigma$. When $x\ge k^{\delta }$, the event $\Omega$ depicted on the left, forces the geodesic $\tilde{\gamma}_u$ (in blue) to intersect $\mathcal{C}_x$ only inside $B(u,k^\delta )$. When $x< k^{\delta }$, the event $\Sigma$ on the right, forces the geodesic $\tilde{\gamma}_u$ to intersect $\mathcal{C}_x$ only inside $B(u,2h)$ with $h=\Theta (k^{\delta })$.

Theorems & Definitions (45)

  • Definition 1.1
  • Theorem 1.2
  • Theorem 1.3
  • Lemma 2.1
  • Proposition 2.2
  • Lemma 2.3
  • proof : Proof of Proposition \ref{['prop:MW']}
  • Lemma 2.4
  • proof
  • Corollary 2.5
  • ...and 35 more