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Near-critical Ornstein--Zernike theory for the planar random-cluster model

Lucas D'Alimonte, Ioan Manolescu

TL;DR

This work develops a near-critical Ornstein--Zernike theory for the two-dimensional FK/random-cluster model with $1\le q<4$, producing a uniform asymptotic for the two-point function in the subcritical regime that blends subcritical decay with near-critical prefactors. The core strategy is a dynamical, correlation-length-scale exploration of the cluster in a fixed direction, reformulated as a killed Markov renewal process whose mass-gap and renewal structure yield OZ-type formulas, strict convexity of the inverse correlation length, and invariance principles. Key contributions include a uniform OZ formula $\phi_p[0\leftrightarrow \lfloor n\vec v\rfloor] \asymp \pi_1(\xi_p(\vec v))^2 \sqrt{\xi_p(\vec v) n} e^{-n\xi_p(\vec v)}$, along with corollaries on the pure-exponential survival, endpoint concentration, and strict Wulff-shape convexity, all established at the correlation-length scale. The approach departs from skeleton/diamond decompositions, employing a direct, cone-mominated exploration that yields a robust, flexible framework for near-critical OZ analysis in two dimensions.

Abstract

We develop an Ornstein--Zernike theory for the two-dimensional random-cluster model with $1 \leq q <4$ that also applies in its near-critical regime. In particular, we prove an asymptotic formula for the two-point function which holds uniformly for~$p < p_c$ and blends the subcritical and near-critical behaviours of the model. The analysis is carried out by studying the renewal properties of a subcritical percolation cluster, \emph{at the scale of the correlation length}. More precisely, we explore sequentially the cluster in a given direction, by slices of thickness comparable to the correlation length. We show that this exploration satisfies the properties of a {\em killed Markov renewal process} -- a class of processes that may be analysed independently and have Brownian behaviour. In addition to the two-point function estimate, we derive other consequences of the Ornstein--Zernike theory such as an invariance principle for the rescaled cluster and the strict convexity of the inverse correlation length -- all at the scale of the correlation length, uniformly in~$p<p_c$. Finally, our approach differs from that of earlier papers of Campanino, Ioffe, Velenik and others, with the cluster being dynamically explored rather than constructed from its diamond decomposition.

Near-critical Ornstein--Zernike theory for the planar random-cluster model

TL;DR

This work develops a near-critical Ornstein--Zernike theory for the two-dimensional FK/random-cluster model with , producing a uniform asymptotic for the two-point function in the subcritical regime that blends subcritical decay with near-critical prefactors. The core strategy is a dynamical, correlation-length-scale exploration of the cluster in a fixed direction, reformulated as a killed Markov renewal process whose mass-gap and renewal structure yield OZ-type formulas, strict convexity of the inverse correlation length, and invariance principles. Key contributions include a uniform OZ formula , along with corollaries on the pure-exponential survival, endpoint concentration, and strict Wulff-shape convexity, all established at the correlation-length scale. The approach departs from skeleton/diamond decompositions, employing a direct, cone-mominated exploration that yields a robust, flexible framework for near-critical OZ analysis in two dimensions.

Abstract

We develop an Ornstein--Zernike theory for the two-dimensional random-cluster model with that also applies in its near-critical regime. In particular, we prove an asymptotic formula for the two-point function which holds uniformly for~ and blends the subcritical and near-critical behaviours of the model. The analysis is carried out by studying the renewal properties of a subcritical percolation cluster, \emph{at the scale of the correlation length}. More precisely, we explore sequentially the cluster in a given direction, by slices of thickness comparable to the correlation length. We show that this exploration satisfies the properties of a {\em killed Markov renewal process} -- a class of processes that may be analysed independently and have Brownian behaviour. In addition to the two-point function estimate, we derive other consequences of the Ornstein--Zernike theory such as an invariance principle for the rescaled cluster and the strict convexity of the inverse correlation length -- all at the scale of the correlation length, uniformly in~. Finally, our approach differs from that of earlier papers of Campanino, Ioffe, Velenik and others, with the cluster being dynamically explored rather than constructed from its diamond decomposition.
Paper Structure (22 sections, 20 theorems, 156 equations, 9 figures)

This paper contains 22 sections, 20 theorems, 156 equations, 9 figures.

Key Result

Theorem 1.1

Fix $q \in [1,4)$. Then, uniformly in $\vec{v} \in \mathbb S^1$, $n \geq \xi_p(\vec{v})$ and $p < p_c$,

Figures (9)

  • Figure 1: Left: in the proof of \ref{['eq:u_k_rec']} we consider two translates $H_+$ and $H_-$ of the event in $u_k$, one in the upper half-plane, one in the lower one. Here the red path ensures that $H_+$ occurs. The blue paths (also part of $\omega^* \cup A^*$) produce the events $B_L$ and $B_R$. When at least one of $H_+$ and $H_-$ occur, and both $B_L$ and $B_R$, then the two horizontal translates of $\Lambda_{N/2}$ connect to each-other. Right: To produce a path separating $\Lambda_{2^k L}$ from $\partial \Lambda_{2^{k+1} L}$, it suffices for two vertical translates of the events in $u_{k-1}$ to occur, and for the blue paths to occur in $\omega^* \cup A^*$. As for $B_L$ and $B_R$, the latter occur with exponentially high probability in $2^k$.
  • Figure 2: Left: the dotted line represents the points at equal distance from $\mathcal{D}$ and $\partial \mathcal{H}_\geq 0$; the solid black lines represent wired boundary conditions. The blue segment is the top half of a batch $S_k$. For it to be connected to $\mathcal{D}$, the annulus surrounding it should be crossed, which occurs with an exponentially small probability in $k$. For small values of $k$, use \ref{['eq:RSWnc']} to complete the dual path separating $\partial\mathcal{H}_{\geq 0}$ form $\mathcal{D}$. Right: For the second part of the argument, consider a domain $\Omega$ containing $\mathcal{D}$ and prove that the probability of $B$ with arbitrary boundary conditions on $\Omega$ is not much larger than that with free boundary conditions --- we use here the first estimate of \ref{['eq:cone_to_cone']}. One bound of \ref{['eq:mixing_bc']} follows directly. The opposite bound is proved by considering $\Omega$ to be the complement of the cluster of $\partial \mathcal{H}_{\geq 0}$ and using the second bound of \ref{['eq:cone_to_cone']} to show that $\mathcal{D} \subset \Omega$ with positive probability.
  • Figure 3: Left: The occurence of $S_a$ conditionally on $\Lambda_{ L } \leftrightarrow \mathcal{H}_{\geq n}$ induces an "unforced" connection between $\mathcal{Y}_{\rm in}$ and $\mathcal{Y}_{\rm out}^c$, which has an exponential cost in $k$. Middle: To bound $S_b$, consider the right-most translate of $\mathcal{Y}_{\rm in}$ that contains a connection between $\Lambda_L$ and $\mathcal{H}_{\geq n}$. Its boundary intersects a "pivotal" box $\Lambda_L(x)$, that is a box that is connected to $\Lambda_L$ and $\mathcal{H}_{\geq n}$ inside $\mathcal{Y}(x)$ by distinct clusters. Right: When working with an arbitrary potential past $A$, the connection between $\Lambda_L$ and $\mathcal{H}_{\geq n}$ may use the left half-plane. Nevertheless, there exists a vertical translate of $\Lambda_L$ that is connected to $\mathcal{H}_{\geq n}$ inside $\mathcal{H}_{\geq 0}$. We will consider the closest such translate to $0$.
  • Figure 4: Left: An example of a successful exploration (purple), with the arcs $\chi_0$ and $\chi_1$ being the top and bottom sides of the interface and the tubes depicted in grey. The solid blue lines form $\mathcal{A}$, while $\mathcal{B}$ is the solid black segment above $y_-$. An exploration is needed when either $\mathcal{A}$ or the dual arc between $x_+$ and $y_-$ are inaccessible. Right: For a successful exploration, $\chi_1$ may be connected to $\mathcal{H}_{\geq n}$ by a primal cluster that does not intersect $\mathcal{B}$ with probability at least $s_{n-t}$. After exploring the cluster $\mathsf C_{\chi}$ of $\chi_1$ (red) $\mathcal{B}$ may be separated from $\mathcal{H}_{\geq n}$ with uniformly positive probability due to our assumption on $\mathsf C_{\leq t}$.
  • Figure 5: The different scenarios that may occur when exploring $\Gamma$, and potentially $\tilde{\Gamma}$. The exploration up to $\tau$ and the resulting connection is drawn in red, the subsequent construction is in purple. The red and purple arrow refer connections to the paths from $\Lambda_{R}(x + (5R,\pm R))$ to $\mathcal{H}_{\geq n}$ and $\infty$, which occur with probability comparable to $s_{n-t}$. From left to right: scenarios 1(a), 2(a), 2(b) and 3. Note that in scenario 2(b), the exploration path $\Gamma$ never exposes an accessible primal arc. That is why we do not explore $\Gamma$ between $\tau$ and $\tau'$ (grey) but rather explore $\tilde{\Gamma}$ up to $\tau"$ (purple).
  • ...and 4 more figures

Theorems & Definitions (48)

  • Theorem 1.1: Ornstein--Zernike asymptotics at the scale of the correlation length
  • Remark 1.2
  • Lemma 2.1
  • Proposition 2.2: RSW in the critical window
  • Theorem 2.3
  • proof : Proof of Lemma \ref{['lem:L(p)expdecay']}
  • Definition 3.1
  • Theorem 3.2
  • Remark 3.3
  • Remark 3.4
  • ...and 38 more