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Slightly supercritical percolation on nonamenable graphs II: Growth and isoperimetry of infinite clusters

Tom Hutchcroft
Abstract

We study the growth and isoperimetry of infinite clusters in slightly supercritical Bernoulli bond percolation on transitive nonamenable graphs under the L2L^{2} boundedness condition (pc<p22p_{c}<p_{2\to 2}). Surprisingly, we find that the volume growth of infinite clusters is always purely exponential (that is, the subexponential corrections to growth are bounded) in the regime pc<p<p22p_{c}<p<p_{2\to 2}, even when the ambient graph has unbounded corrections to exponential growth. For pp slightly larger than pcp_{c}, we establish the precise estimates

𝐄p[#Bint(v,r)]\displaystyle\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right] (r1ppc)eγint(p)r\displaystyle\asymp\left(r\wedge\frac{1}{p-p_{c}}\right)^{\phantom{2}}e^{\gamma_{\mathrm{int}}(p)r}
𝐄p[#Bint(v,r)v]\displaystyle\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\mid v\leftrightarrow\infty\right] (r1ppc)2eγint(p)r\displaystyle\asymp\left(r\wedge\frac{1}{p-p_{c}}\right)^{2}e^{\gamma_{\mathrm{int}}(p)r}

for every vVv\in V, r0r\geq 0, and pc<ppc+δp_{c}<p\leq p_{c}+\delta, where the growth rate γint(p)=lim1rlog𝐄p#B(v,r)\gamma_{\mathrm{int}}(p)=\lim\frac{1}{r}\log\mathbf{E}_{p}\#B(v,r) satisfies γint(p)ppc\gamma_{\mathrm{int}}(p)\asymp p-p_{c}. We also prove a percolation analogue of the Kesten-Stigum theorem that holds in the entire supercritical regime and states that the quenched and annealed exponential growth rates of an infinite cluster always coincide. We apply these results together with those of the first paper in this series to prove that the anchored Cheeger constant of every infinite cluster KK satisfies

(ppc)2log[1/(ppc)]Φ(K)(ppc)2\frac{(p-p_{c})^{2}}{\log[1/(p-p_{c})]}\preceq\Phi^{*}(K)\preceq(p-p_{c})^{2}

almost surely for every pc<p1p_{c}<p\leq 1.

1 Introduction

This paper is the second in a series of three papers analyzing slightly supercritical percolation on nonamenable graphs transitive graphs, where the retention parameter pp approaches its critical value pcp_{c} from above. This regime is typically very difficult to study rigorously, with many of its conjectured features remaining unproven even for high-dimensional Euclidean lattices where most other regimes are well-understood [15, 13, 18]; see the first paper in this series [23] for a detailed introduction to the topic.

We work primarily under the L2L^{2} boundedness condition pc<p22p_{c}<p_{2\to 2}, where p22p_{2\to 2} is the supremal value of pp for which the infinite matrix Tp[0,1]V×VT_{p}\in[0,1]^{V\times V} defined by Tp(u,v)=𝐏p(uv)T_{p}(u,v)=\mathbf{P}_{p}(u\leftrightarrow v) defines a bounded operator on 2(V)\ell^{2}(V). This condition, which was introduced in [19] and developed further in [21], is conjectured to hold for every transitive nonamenable graph and proven to hold for various large classes of graphs including highly nonamenable graphs [21, 31, 30, 33], Gromov hyperbolic graphs [19], and graphs admitting a transitive nonunimodular group of automorphisms [22]. In the first paper in this series we proved sharp estimates on the distribution of finite clusters near pcp_{c} under the L2L^{2} boundedness condition. In the present paper we apply these results to analyze the growth and isoperimetry of infinite clusters. In a forthcoming third paper we will use these results to study the behaviour of random walk on infinite slightly supercritical clusters. The present paper can be read independently of [23] provided that one is willing to take the main results of that paper as a black box.

Notation: We write \asymp, \succeq, and \preceq to denote equalities and inequalities that hold up to positive multiplicative constants depending only on the graph GG. For example, “f(n)g(n)f(n)\asymp g(n) for every n1n\geq 1” means that there exist positive constants cc and CC such that cg(n)f(n)Cg(n)cg(n)\leq f(n)\leq Cg(n) for every n1n\geq 1. We also use Landau’s asymptotic notation similarly, so that f(n)=Θ(g(n))f(n)=\Theta(g(n)) if and only if fgf\asymp g, and f(n)g(n)f(n)\preceq g(n) if and only if f(n)=O(g(n))f(n)=O(g(n)). Given a matrix MM indexed by a countable set VV, we write M22=sup{Mf2/f2:f\|M\|_{2\to 2}=\sup\{\|Mf\|_{2}/\|f\|_{2}\mathrel{\mathop{\ordinarycolon}}f a non-zero finitely supported function on V}V\} for the norm of MM considered as an operator on 2(V)\ell^{2}(V), which is finite if and only if MM extends continuously to a bounded operator on 2(V)\ell^{2}(V). We write 𝐏p\mathbf{P}_{p} and 𝐄p\mathbf{E}_{p} for probabilities and expectations taken with respect to the law of Bernoulli-pp bond percolation.

1.1 Expected volume growth

We begin by stating our results concerning the volume growth of slightly supercritical clusters. We will prove results of two kinds: precise estimates on the expected volume of an intrinsic ball for pp close to pcp_{c}, and limit theorems stating that the almost sure volume growth is well-described by its expectation in various senses. This leads to a rather complete description of the volume growth of clusters for percolation with pc<p<p22p_{c}<p<p_{2\to 2}, as well as some partial understanding of the remaining supercritical regime p22p<1p_{2\to 2}\leq p<1.

We begin with some relevant definitions. Let G=(V,E)G=(V,E) be a countable graph. For each p[0,1]p\in[0,1] and r0r\geq 0 we define

Grp(r):=supvV𝐄p[#Bint(v,r)],\operatorname{Gr}_{p}(r)\mathrel{\mathop{\ordinarycolon}}=\sup_{v\in V}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right],

where Bint(v,r)B_{\mathrm{int}}(v,r) denotes the intrinsic ball of radius rr around vv, i.e., the graph distance ball in the cluster of vv. By a standard abuse of notation we write Bint(v,r)B_{\mathrm{int}}(v,r) both for the set of vertices in the ball and the subgraph of the cluster induced by the ball, writing #Bint(v,r)\#B_{\mathrm{int}}(v,r) for the number of vertices that have intrinsic distance at most rr from vv. If GG has degrees bounded by MM then Grp(r)M(M1)r1\operatorname{Gr}_{p}(r)\leq M(M-1)^{r-1} for every r1r\geq 1, so that Grp(r)\operatorname{Gr}_{p}(r) is finite for every r0r\geq 0. It is a consequence of Reimer’s inequality [21, Lemma 3.4] that

𝐄p[#Bint(v,r+)]𝐄p[#Bint(v,r1)]+𝐄p[#Bint(v,r)]Grp()\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r+\ell)\right]\leq\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r-1)\right]+\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\operatorname{Gr}_{p}(\ell) (1.1)

for every r,0r,\ell\geq 0, p[0,1]p\in[0,1], and vVv\in V, and hence that Grp(r)\operatorname{Gr}_{p}(r) satisfies the submultiplicative-type inequality

Grp(r+)sup{𝐄p[#Bint(v,r1)]+𝐄p[#Bint(v,r)]Grp():vV}Grp(r)Grp()\operatorname{Gr}_{p}(r+\ell)\leq\sup\left\{\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r-1)\right]+\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\operatorname{Gr}_{p}(\ell)\mathrel{\mathop{\ordinarycolon}}v\in V\right\}\leq\operatorname{Gr}_{p}(r)\operatorname{Gr}_{p}(\ell) (1.2)

for every p[0,1]p\in[0,1] and r,0r,\ell\geq 0. It follows by Fekete’s lemma [12, Appendix II] that if GG has degrees bounded by MM then for each p[0,1]p\in[0,1] there exists γint(p)[0,M1]\gamma_{\mathrm{int}}(p)\in[0,M-1] such that

γint(p)=limr1rlogGrp(r)=infr11rlogGrp(r).\gamma_{\mathrm{int}}(p)=\lim_{r\to\infty}\frac{1}{r}\log\operatorname{Gr}_{p}(r)=\inf_{r\geq 1}\frac{1}{r}\log\operatorname{Gr}_{p}(r). (1.3)

Note that γint(p)\gamma_{\mathrm{int}}(p) is an increasing function of pp. When p=1p=1 we have that Bint(v,r)=B(v,r)B_{\mathrm{int}}(v,r)=B(v,r) for every r0r\geq 0, so that γint(1)=γ(G)\gamma_{\mathrm{int}}(1)=\gamma(G) is simply the exponential growth rate of GG. It follows from (1.2) and (1.3) that for each p[0,1]p\in[0,1] there exists a non-negative, subadditive function hp:{0,1,}h_{p}\mathrel{\mathop{\ordinarycolon}}\{0,1,\ldots\}\to\mathbb{R} with limr1rhp(r)=0\lim_{r\to\infty}\frac{1}{r}h_{p}(r)=0 such that

Grp(r)=exp[γint(p)r+hp(r)]\operatorname{Gr}_{p}(r)=\exp\left[\gamma_{\mathrm{int}}(p)r+h_{p}(r)\right] (1.4)

for every r0r\geq 0. We refer to the function ehp(r)=eγint(p)rGrp(r)e^{h_{p}(r)}=e^{-\gamma_{\mathrm{int}}(p)r}\operatorname{Gr}_{p}(r) as the subexponential correction to growth for Bernoulli-pp percolation on GG.

Our first theorem states that infinite clusters have have purely exponential growth between pcp_{c} and p22p_{2\to 2} in the sense that the subexponential corrections to growth are bounded.

Theorem 1.1 (Bounded subexponential corrections to growth below p22p_{2\to 2}).

Let GG be a connected, locally finite, quasi-transitive graph, and let pc<p<p22p_{c}<p<p_{2\to 2}. Then there exist positive constants cpc_{p} and CpC_{p} such that

cpeγint(p)r𝐄p[#Bint(v,r)]𝐄p[#Bint(v,r)]Cpeγint(p)rc_{p}e^{\gamma_{\mathrm{int}}(p)r}\leq\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\leq\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right]\leq C_{p}e^{\gamma_{\mathrm{int}}(p)r} (1.5)

for every vVv\in V and r0r\geq 0.

We do not expect the conclusion of Theorem 1.1 to extend to the entire supercritical phase, even under the assumption of nonamenability. Indeed, the product T×dT\times\mathbb{Z}^{d} has #B(0,r)=Θ(rdeγr)\#B(0,r)=\Theta(r^{d}e^{\gamma r}) for appropriate choice of γ\gamma, and it seems plausible that this rdr^{d} subexponential correction to growth should also be present in percolation on this graph with pp close to 11. It is therefore an interesting and non-trivial fact that, in our setting, subexponential corrections to growth are always bounded when pp is supercritical but not too large.

Our next theorem sharpens Theorem 1.1 by giving precise control over the asymptotics of the subexponential corrections to growth when pp is close to pcp_{c}.

Theorem 1.2 (Volume growth near criticality).

Let GG be a connected, locally finite, quasi-transitive graph, and suppose that pc<p22p_{c}<p_{2\to 2}. Then there exists a positive constant δ\delta such that

γint(p)\displaystyle\gamma_{\mathrm{int}}(p) ppc,\displaystyle\asymp p-p_{c}, (1.6)
𝐄p[#Bint(v,r)]\displaystyle\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right] (r1ppc)eγint(p)r,\displaystyle\asymp\left(r\wedge\frac{1}{p-p_{c}}\right)^{\phantom{2}}e^{\gamma_{\mathrm{int}}(p)r}, (1.7)
and𝐄p[#Bint(v,r)v]\displaystyle\text{and}\qquad\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\mid v\leftrightarrow\infty\right] (r1ppc)2eγint(p)r\displaystyle\asymp\left(r\wedge\frac{1}{p-p_{c}}\right)^{2}e^{\gamma_{\mathrm{int}}(p)r} (1.8)

for every vVv\in V, r0r\geq 0, and pc<ppc+δp_{c}<p\leq p_{c}+\delta.

The critical version of this estimate, stating that 𝐄pc#Bint(v,r)r\mathbf{E}_{p_{c}}\#B_{\mathrm{int}}(v,r)\asymp r for every r1r\geq 1, was proven to hold for any transitive graph satisfying the triangle condition (which is implied by the L2L^{2} boundedness condition [21, p.4]) in [27, 32]. The transition from critical-like to supercritical-like behaviour outside a scaling window of intrinsic radius |ppc|1|p-p_{c}|^{-1} is typical of off-critical percolation in high-dimensional settings [23, 24, 7]. As is common to such analyses, our proofs will often treat the inside-window and outside-window cases separately, with the inside-window results following straightforwardly from what is known about critical percolation.

Remark 1.3.

The estimates of Theorems 1.1 and 1.2 are both significantly stronger than they would be if the right hand sides of (1.7) and (1.8) contained terms of the form eΘ(γint(p)r)e^{\Theta(\gamma_{\mathrm{int}}(p)r)}, where the implicit constants in the upper and lower bounds could be different, rather than the exact exponential term eγint(p)re^{\gamma_{\mathrm{int}}(p)r}. In fact it is rather unusual to have such a sharp near-critical estimate in which the exact constant in the exponential is determined, and we are not aware of any other works in which this has been possible. (Indeed, for the near-critical two-point function on the high-dimensional lattice d\mathbb{Z}^{d} the constant in the exponential must be different at distances on the order of the correlation length than it is at very large distances, as the equality of exponential rates across these scales would be inconsistent with Ornstein-Zernike decay at very large scales [24].)

Remark 1.4.

It remains an open problem to establish an analogue of Theorem 1.2 for infinite slightly supercritical percolation clusters on d\mathbb{Z}^{d} with dd large, i.e., to determine the precise manner in which quadratic growth within the scaling window [27, 32] transitions to dd-dimensional growth on large scales [3]. This problem is, in turn, closely related to the problem of computing the asymptotics of the time constant for supercritical percolation as ppcp\downarrow p_{c}. An analogous problem for high-dimensional random interlacements has recently been solved to within subpolynomial factors in [17], and regularity results for the percolation time constant have been established in [6, 9, 10].

1.2 Almost sure volume growth

Our next theorem, which holds for the entire supercritical regime, shows that γint(p)\gamma_{\mathrm{int}}(p) also describes the almost sure growth rate of the volume of intrinsic balls in infinite clusters in a rather strong sense. It is an analogue of the Kesten-Stigum theorem for supercritical branching processes [25, 28], and shows that the expectations studied in Theorems 1.1 and 1.2 are indeed the correct quantities to study if one wishes to understand the asymptotic growth of infinite clusters. The proof of this theorem, given in Section 4, can be read independently of the proofs of Theorems 1.1 and 1.2.

Theorem 1.5 (Expected and almost sure growth rates always coincide).

Let GG be a connected, locally finite, quasi-transitive graph, let vv be a vertex of GG and let pc<p1p_{c}<p\leq 1. Then

limr1rlog|Bint(v,r)|=limr1rlog|Bint(v,r)|=γint(p)\lim_{r\to\infty}\frac{1}{r}\log|\partial B_{\mathrm{int}}(v,r)|=\lim_{r\to\infty}\frac{1}{r}\log|B_{\mathrm{int}}(v,r)|=\gamma_{\mathrm{int}}(p)

𝐏p\mathbf{P}_{p}-almost surely on the event that KvK_{v} is infinite. Moreover, we also have that

lim infreγint(p)r|Bint(v,r)|>0\liminf_{r\to\infty}e^{-\gamma_{\mathrm{int}}(p)r}|\partial B_{\mathrm{int}}(v,r)|>0 (1.9)

𝐏p\mathbf{P}_{p}-almost surely on the event that KvK_{v} is infinite.

As an aside, we also prove that γint(p)\gamma_{\mathrm{int}}(p) is always positive for p>pcp>p_{c} whenever the underlying graph has exponential volume growth. In the nonamenable case this is an easy consequence of the results of, say, [4] or [16]; we show that a simple and direct proof is also possible in the amenable case.

Theorem 1.6.

Let GG be a connected, locally finite, quasi-transitive graph. If GG has exponential volume growth then γint(p)>0\gamma_{\mathrm{int}}(p)>0 for every pc<p1p_{c}<p\leq 1.

Remark 1.7.

In general, the clusters of invariant percolation processes need not have well-defined rates of exponential growth as shown by Timár [34]. Interesting recent work of Abert, Fraczyk, and Hayes [1] has initiated a systematic study of the growth of unimodular random graphs and established criteria in which the growth must exist for unimodular random trees. In light of Theorems 1.1 and 1.5, Bernoulli percolation may already provide a surprisingly rich test case for this theory.

1.3 The anchored Cheeger constant

Our final set of results concern the isoperimetry of the infinite clusters in slightly supercritical percolation. Recall that the anchored Cheeger constant of a connected, locally finite graph GG is defined to be

Φ(G)=lim infn{|EW|wWdeg(w):vWV connected, nwWdeg(w)<},\Phi^{*}(G)=\liminf_{n\to\infty}\Biggl{\{}\frac{|\partial_{E}W|}{\sum_{w\in W}\deg(w)}\mathrel{\mathop{\ordinarycolon}}v\in W\subseteq V\text{ connected, }n\leq\sum_{w\in W}\deg(w)<\infty\Biggr{\}},

where vv is a fixed vertex of GG whose choice does not affect the value of Φ(G)\Phi^{*}(G). We say that GG has anchored expansion if Φ(G)>0\Phi^{*}(G)>0. This notion was introduced by Benjamini, Lyons, and Schramm [4], who conjectured that infinite supercritical percolation clusters on nonamenable transitive graphs have anchored expansion. This conjecture was proven in [16], following earlier partial results of Chen, Peres, and Pete [8]. The following theorem establishes a quantitative version of this result for graphs satisfying the L2L^{2} boundedness condition. Unfortunately we have not quite been able to prove a sharp version of the theorem, but rather are left with a presumably unnecessary logarithmic term in the lower bound.

Theorem 1.8 (The anchored Cheeger constant near criticality).

Let GG be a connected, locally finite, quasi-transitive graph with pc<p22p_{c}<p_{2\to 2}. Then there exist constants cc and CC such that every infinite cluster in Bernoulli-pp bond percolation on GG has anchored expansion with anchored Cheeger constant

c(ppc)2log[1/(ppc)]Φ(K)C(ppc)2\frac{c(p-p_{c})^{2}}{\log[1/(p-p_{c})]}\leq\Phi^{*}(K)\leq C(p-p_{c})^{2}

𝐏p\mathbf{P}_{p}-almost surely for every pc<p1p_{c}<p\leq 1.

In the forthcoming third paper in this series we prove stronger bounds giving high-probability control of the entire isoperimetric profile both for the infinite clusters and their cores.

2 The growth rate near criticality

In this section we apply the results of [21] to prove the part of Theorem 1.2 concerning the limiting exponential growth rate γint(p)=limr1rlogGrp(r)\gamma_{\mathrm{int}}(p)=\lim_{r\to\infty}\frac{1}{r}\log\operatorname{Gr}_{p}(r).

Proposition 2.1.

Let GG be a connected, locally finite, quasi-transitive graph, and suppose that pc<p22p_{c}<p_{2\to 2}. Then γint(p)ppc\gamma_{\mathrm{int}}(p)\asymp p-p_{c} for every ppcp\geq p_{c}.

We begin with the following simple lemma, which is closely related to the results of [32, 27]. We recall that the triangle diagram p\nabla_{p} is defined by p=supvVTp3(v,v)\nabla_{p}=\sup_{v\in V}T_{p}^{3}(v,v), and that a quasi-transitive graph is said to satisfy the triangle condition if pc<\nabla_{p_{c}}<\infty.

Lemma 2.2.

Let GG be a connected, locally finite, quasi-transitive graph satisfying pc<\nabla_{p_{c}}<\infty. Then

𝐄p[#Bint(v,r)]\displaystyle\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right] r\displaystyle\asymp r (2.1)

for every vVv\in V, pcp1p_{c}\leq p\leq 1, and 1r(ppc)11\leq r\leq(p-p_{c})^{-1}.

The proof of this lemma will apply Russo’s formula, which expresses the derivative of the probability of an increasing event in terms of the expected number of pivotal edges; see e.g. [12, Chapter 2] for background.

Proof of Lemma 2.2.

For each u,vVu,v\in V and r1r\geq 1, let {u𝑟v}={uBint(v,r)}\{u\xleftrightarrow{r}v\}=\{u\in B_{\mathrm{int}}(v,r)\} be the event that there exists an open path of length at most rr connecting uu and vv. Observe that there are always at most rr open pivotals for this event: Indeed, if this event holds and γ\gamma is an open path of length at most rr connecting vv to uu, then any open pivotal for the event must belong to γ\gamma. As such, summing over uVu\in V and applying Russo’s formula yields that

ddp𝐄p#Bint(v,r)rp𝐄p#Bint(v,r)\frac{d}{dp}\mathbf{E}_{p}\#B_{\mathrm{int}}(v,r)\leq\frac{r}{p}\mathbf{E}_{p}\#B_{\mathrm{int}}(v,r)

for every r0r\geq 0 and p[0,1]p\in[0,1] and hence that

ddplog𝐄p#Bint(v,r)rp\frac{d}{dp}\log\mathbf{E}_{p}\#B_{\mathrm{int}}(v,r)\leq\frac{r}{p}

for every r0r\geq 0 and p[0,1]p\in[0,1]. Integrating this differential inequality yields that

log𝐄p#Bint(v,r)(pq)rq+log𝐄q#Bint(v,r)\log\mathbf{E}_{p}\#B_{\mathrm{int}}(v,r)\leq\frac{(p-q)r}{q}+\log\mathbf{E}_{q}\#B_{\mathrm{int}}(v,r) (2.2)

for every r0r\geq 0 and 0qp10\leq q\leq p\leq 1. When q=pcq=p_{c} and r(ppc)1r\leq(p-p_{c})^{-1} the first term is bounded and we deduce that 𝐄p#Bint(v,r)𝐄pc#Bint(v,r)\mathbf{E}_{p}\#B_{\mathrm{int}}(v,r)\asymp\mathbf{E}_{p_{c}}\#B_{\mathrm{int}}(v,r). The claim then follows from the fact that 𝐄pc#Bint(v,r)r\mathbf{E}_{p_{c}}\#B_{\mathrm{int}}(v,r)\asymp r under the triangle condition as established in [27, 32]. ∎

Proof of Proposition 2.1.

We begin with the upper bound. It follows from the inequality (2.2) that

γint(p)pqq+γint(q)\gamma_{\mathrm{int}}(p)\leq\frac{p-q}{q}+\gamma_{\mathrm{int}}(q) (2.3)

for every 0<q<p10<q<p\leq 1. Since γint(q)=0\gamma_{\mathrm{int}}(q)=0 for every 0<q<pc0<q<p_{c} by sharpness of the phase transition, it follows by taking the limit as qpcq\uparrow p_{c} that

γint(p)ppcpc\gamma_{\mathrm{int}}(p)\leq\frac{p-p_{c}}{p_{c}} (2.4)

for every pcp1p_{c}\leq p\leq 1. Note that this inequality holds on every connected, locally finite, quasi-transitive graph; the resulting equality γint(pc)=0\gamma_{\mathrm{int}}(p_{c})=0 was already observed to hold for every such graph by Kozma in [26, Lemma 1].

We now deduce the lower bound γint(p)ppc\gamma_{\mathrm{int}}(p)\succeq p-p_{c} under the assumption that pc<p22p_{c}<p_{2\to 2} from the results of our earlier paper [21], which contains both an extrinsic version of the same estimate and tools to convert between intrinsic and extrinsic estimates. First, [21, Corollary 4.3] gives that

lim sup1log𝐄p[#KvB(v,)]ppc\limsup_{\ell\to\infty}\frac{1}{\ell}\log\mathbf{E}_{p}\left[\#K_{v}\cap B(v,\ell)\right]\asymp p-p_{c} (2.5)

for every vVv\in V and ppcp\geq p_{c}. (We only need the lower bound, which is the easier of the two estimates.) For each p[0,1]p\in[0,1] and r0r\geq 0 we define the matrix Cp,rint[0,]V2C^{\mathrm{int}}_{p,r}\in[0,\infty]^{V^{2}} by

Cp,rint(u,v)=p(uv,dint(u,v)r).C^{\mathrm{int}}_{p,r}(u,v)=\mathbb{P}_{p}\left(u\leftrightarrow v,d_{\mathrm{int}}(u,v)\geq r\right).

The norm of this operator is bounded in [21, Proposition 3.2], which states that

Cp,rint223Tp22exp[reTp22]\|C^{\mathrm{int}}_{p,r}\|_{2\to 2}\leq 3\|T_{p}\|_{2\to 2}\exp\left[-\frac{r}{e\|T_{p}\|_{2\to 2}}\right] (2.6)

for every 0p<p220\leq p<p_{2\to 2} and r0r\geq 0. We can apply this estimate to deduce by Cauchy-Schwarz that

𝐄p[#B(v,)(KvBint(v,r))]\displaystyle\mathbf{E}_{p}\!\left[\#B(v,\ell)\cap\left(K_{v}\setminus B_{\mathrm{int}}(v,r)\right)\right] =Cp,rint𝟙v,𝟙B(v,)Cp,rint22𝟙v2𝟙B(v,)2\displaystyle=\langle C_{p,r}^{\mathrm{int}}\mathbbm{1}_{v},\mathbbm{1}_{B(v,\ell)}\rangle\leq\|C_{p,r}^{\mathrm{int}}\|_{2\to 2}\|\mathbbm{1}_{v}\|_{2}\|\mathbbm{1}_{B(v,\ell)}\|_{2}
=Cp,rint22#B(v,)3Tp22exp[reTp22]#B(v,)\displaystyle=\|C_{p,r}^{\mathrm{int}}\|_{2\to 2}\sqrt{\#B(v,\ell)}\leq 3\|T_{p}\|_{2\to 2}\exp\left[-\frac{r}{e\|T_{p}\|_{2\to 2}}\right]\sqrt{\#B(v,\ell)}

for every vVv\in V, ,r0\ell,r\geq 0, and 0p<p220\leq p<p_{2\to 2}. Setting αp=c/Tp22\alpha_{p}=c/\|T_{p}\|_{2\to 2} for an appropriately small constant cc, setting =αpr\ell=\lceil\alpha_{p}r\rceil, and taking the limit as rr\to\infty, we deduce that

lim supr1rlog𝐄p[#B(v,αpr)(KvBint(v,r))]<0\limsup_{r\to\infty}\frac{1}{r}\log\mathbf{E}_{p}\left[\#B(v,\alpha_{p}r)\cap\left(K_{v}\setminus B_{\mathrm{int}}(v,r)\right)\right]<0

and hence that

γint(p)lim supr1rlog𝐄p[#B(v,αpr)Bint(v,r)]=lim supr1rlog𝐄p[#B(v,αpr)Kv]αp(ppc)\gamma_{\mathrm{int}}(p)\geq\limsup_{r\to\infty}\frac{1}{r}\log\mathbf{E}_{p}\left[\#B(v,\alpha_{p}r)\cap B_{\mathrm{int}}(v,r)\right]\\ =\limsup_{r\to\infty}\frac{1}{r}\log\mathbf{E}_{p}\left[\#B(v,\alpha_{p}r)\cap K_{v}\right]\asymp\alpha_{p}(p-p_{c})

for every pcp<p22p_{c}\leq p<p_{2\to 2}. The claim follows since, by the L2L^{2} boundedness condition, αp\alpha_{p} is bounded away from zero on a neighbourhood of pcp_{c}. ∎

3 Subexponential corrections to growth in the L2L^{2} regime

We now begin the proof of our results concerning subexponential corrections to growth for slightly supercritical percolation, Theorems 1.1 and 1.2. Both theorems will be proven via essentially the same method, although the details required to prove Theorem 1.2 are a little more involved. In fact we will prove a slightly more general version of Theorem 1.1 which may apply at p22p_{2\to 2} in some examples. We begin by explaining how each of these results can be deduced from a certain generating function estimate which we then prove in Section 3.2.

We first introduce some relevant definitions. Recall that a locally finite quasi-transitive graph G=(V,E)G=(V,E) is said to satisfy the open triangle condition at pp if for every ε>0\varepsilon>0 there exists rr such that Tp3(u,v)εT_{p}^{3}(u,v)\leq\varepsilon whenever d(u,v)rd(u,v)\geq r. We say that GG satisfies the modified open triangle condition at pp if

limksupvVTp2PkTp(v,v)=0,\lim_{k\to\infty}\sup_{v\in V}T_{p}^{2}P^{k}T_{p}(v,v)=0,

where PP is the transition matrix of simple random walk on GG. It is easily seen that any unimodular quasi-transitive graph satisfying the open triangle condition at pp also satisfies the modified open triangle condition at pp. Moreover, we have by Cauchy-Schwarz that

supvVTp2PkTp(v,v)P22kTp223\sup_{v\in V}T_{p}^{2}P^{k}T_{p}(v,v)\leq\|P\|_{2\to 2}^{k}\|T_{p}\|_{2\to 2}^{3}

and hence that if GG is nonamenable then it satisfies the modified open triangle condition at every 0p<p220\leq p<p_{2\to 2}. Let [0,p22)I[0,1)[0,p_{2\to 2})\subseteq I_{\nabla}\subseteq[0,1) be the set of pp for which the modified open triangle condition holds. (We believe it is possible to prove that (0,p22)I(0,p22](0,p_{2\to 2})\subseteq I_{\nabla}\subseteq(0,p_{2\to 2}] whenever GG is a connected, locally finite, quasi-transitive graph, but do not pursue this here.)

The following proposition generalizes Theorem 1.1.

Proposition 3.1 (Bounded subexponential corrections to growth under the modified open triangle condition).

Let GG be a connected, locally finite, quasi-transitive graph, and let p>pcp>p_{c} be such that pIp\in I_{\nabla}. Then there exist positive constants cpc_{p} and CpC_{p} such that

cpeγint(p)r𝐄p[#Bint(v,r)]𝐄p[#Bint(v,r)]Cpeγint(p)rc_{p}e^{\gamma_{\mathrm{int}}(p)r}\leq\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\leq\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right]\leq C_{p}e^{\gamma_{\mathrm{int}}(p)r} (3.1)

for every vVv\in V and r0r\geq 0.

The upper bounds of both Theorem 1.2 and Proposition 3.1 will be proven by analysis of the generating function 𝒢(p,α,u)\mathscr{G}(p,\alpha,u) defined by

𝒢(p,α,u)=𝐄p[vKuαdint(u,v)]=r0αr𝐄p[#Bint(u,r)]\mathscr{G}(p,\alpha,u)=\mathbf{E}_{p}\left[\sum_{v\in K_{u}}\alpha^{d_{\mathrm{int}}(u,v)}\right]=\sum_{r\geq 0}\alpha^{r}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(u,r)\right]

for each p,α[0,1]p,\alpha\in[0,1] and uVu\in V. Note that if α<1\alpha<1 then we can equivalently write

𝒢(p,α,u)=(1α)r0αr𝐄p[#Bint(u,r)]\mathscr{G}(p,\alpha,u)=(1-\alpha)\sum_{r\geq 0}\alpha^{r}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(u,r)\right] (3.2)

for each p,α[0,1)p,\alpha\in[0,1), and uVu\in V. We also write

𝒢(p,α)=infuV𝒢(p,α,u) and 𝒢(p,α)=supuV𝒢(p,α,u)\mathscr{G}_{*}(p,\alpha)=\inf_{u\in V}\mathscr{G}(p,\alpha,u)\qquad\text{ and }\qquad\mathscr{G}^{*}(p,\alpha)=\sup_{u\in V}\mathscr{G}(p,\alpha,u)

for each p[0,1]p\in[0,1] and α[0,1]\alpha\in[0,1]. An easy FKG argument yields that if GG is connected and quasi-transitive then there exists a constant CC such that

(pα)C𝒢(p,α)𝒢(p,α,u)(pα)C𝒢(p,α)(p\alpha)^{C}\mathscr{G}^{*}(p,\alpha)\leq\mathscr{G}(p,\alpha,u)\leq(p\alpha)^{-C}\mathscr{G}_{*}(p,\alpha) (3.3)

for every p,α(0,1]p,\alpha\in(0,1] and uVu\in V. It follows from (1.3) that if GG is a connected, locally finite, quasi-transitive graph and pc<p1p_{c}<p\leq 1, then 𝒢(p,α,u)<\mathscr{G}(p,\alpha,u)<\infty if and only if γint(p)<logα\gamma_{\mathrm{int}}(p)<-\log\alpha. For each α0\alpha\geq 0, we define pα=sup{p[0,1]:𝒢(p,α,u)<p_{\alpha}=\sup\{p\in[0,1]\mathrel{\mathop{\ordinarycolon}}\mathscr{G}(p,\alpha,u)<\infty for every uV}=sup{p[0,1]:γint(p)<logα}u\in V\}=\sup\{p\in[0,1]\mathrel{\mathop{\ordinarycolon}}\gamma_{\mathrm{int}}(p)<-\log\alpha\}. Similarly, for each 0p10\leq p\leq 1 we define αp\alpha_{p} to be supremal so that 𝒢(p,α)<\mathscr{G}^{*}(p,\alpha)<\infty, so that αp=eγint(p)\alpha_{p}=e^{-\gamma_{\mathrm{int}}(p)} for pcp1p_{c}\leq p\leq 1.

We now state our main result regarding this generating function.

Proposition 3.2.

Let GG be a connected, locally finite, quasi-transitive graph. There exists a continuous function κ:I(0,)\kappa\mathrel{\mathop{\ordinarycolon}}I_{\nabla}\to(0,\infty) such that

𝒢(p,α)κ(p)αpα\mathscr{G}^{*}(p,\alpha)\leq\frac{\kappa(p)}{\alpha_{p}-\alpha}

for every pIp\in I_{\nabla} with ppcp\geq p_{c} and every α<1αp\alpha<1\wedge\alpha_{p}.

Note in particular that the constant κ(p)\kappa(p) is bounded in a neighbourhood of pcp_{c} when pc<p22p_{c}<p_{2\to 2}. We will first show how Theorems 1.2 and 3.1 can be deduced from Proposition 3.2 in Section 3.1 before proving Proposition 2.1 in Section 3.2.

3.1 Deduction of Theorems 1.2 and 3.1 from Proposition 3.2

In this section we show how Proposition 3.2 can be used to prove Theorem 1.2 and Proposition 3.1. We will apply the following “Tauberian theorem” that lets us extract pointwise estimates on the growth from the exponentially averaged estimates provided by Proposition 3.2. The resulting lemma also relies on the submultiplicative-type estimate of (1.2) and is similar in spirit to the submultiplicative Tauberian theorem of [20, Lemma 3.4]. We will apply this lemma with α=e1/rαp\alpha=e^{-1/r}\alpha_{p}, so that αrαpr\alpha^{-r}\asymp\alpha_{p}^{-r} and 𝒢(p,α)r\mathscr{G}^{*}(p,\alpha)\preceq r by Proposition 3.2.

Lemma 3.3.

Let GG be a connected, quasi-transitive graph with CC vertex orbits. Then the inequality

Grp(r)Grp(r/2)+4C2𝒢(p,α)2r2(1α)αr\operatorname{Gr}_{p}(r)\leq\operatorname{Gr}_{p}(\lfloor r/2\rfloor)+\frac{4C^{2}\mathscr{G}^{*}(p,\alpha)^{2}}{r^{2}(1-\alpha)}\cdot\alpha^{-r}

holds for every vVv\in V, r1r\geq 1, and 0<α<10<\alpha<1.

Proof of Lemma 3.3.

For each u,vVu,v\in V, we have by Cauchy-Schwarz that

=0rαr𝐄p[#Bint(u,)]𝐄p[#Bint(v,r)]=0rα𝐄p[#Bint(u,)]=0rαr𝐄p[#Bint(v,r)]11α𝒢(p,α),\sum_{\ell=0}^{r}\sqrt{\alpha^{r}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(u,\ell)\right]\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r-\ell)\right]}\\ \leq\sqrt{\sum_{\ell=0}^{r}\alpha^{\ell}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(u,\ell)\right]}\sqrt{\sum_{\ell=0}^{r}\alpha^{r-\ell}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r-\ell)\right]}\leq\frac{1}{\sqrt{1-\alpha}}\cdot\mathscr{G}^{*}(p,\alpha),

for each r1r\geq 1 and α>0\alpha>0, where we used (3.2) in the final inequality. Letting 𝒪\mathcal{O} be a complete set of orbit representatives for the action of Aut(G)\operatorname{Aut}(G) on VV, so that |𝒪|=C|\mathcal{O}|=C, it follows that

u𝒪=0rαr𝐄p[#Bint(u,)]𝐄p[#Bint(v,r)]C1α𝒢(p,α).\sum_{u\in\mathcal{O}}\sum_{\ell=0}^{r}\sqrt{\alpha^{r}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(u,\ell)\right]\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r-\ell)\right]}\leq\frac{C}{\sqrt{1-\alpha}}\cdot\mathscr{G}^{*}(p,\alpha).

Thus, for each r1r\geq 1 there exists an integer r/2rr/2\leq\ell\leq r such that

supu𝒪αr𝐄p[#Bint(u,)]𝐄p[#Bint(v,r)]2Cr1α𝒢(p,α).\sup_{u\in\mathcal{O}}\sqrt{\alpha^{r}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(u,\ell)\right]\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r-\ell)\right]}\leq\frac{2C}{r\sqrt{1-\alpha}}\cdot\mathscr{G}^{*}(p,\alpha).

Applying (1.2) with this choice of \ell it follows that

𝐄p[#Bint(v,r)]\displaystyle\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right] 𝐄p[#Bint(v,r)]+supuV𝐄p[#Bint(u,)]𝐄p[#Bint(v,r)]\displaystyle\leq\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r-\ell)\right]+\sup_{u\in V}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(u,\ell)\right]\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r-\ell)\right]
𝐄p[#Bint(v,r/2)]+4C2𝒢(p,α)2r2(1α)αr\displaystyle\leq\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,\lfloor r/2\rfloor)\right]+\frac{4C^{2}\mathscr{G}^{*}(p,\alpha)^{2}}{r^{2}(1-\alpha)}\cdot\alpha^{-r}

for every r1r\geq 1 and α>0\alpha>0 as claimed. ∎

The proof will also apply the following refinement of Fekete’s lemma, which lets us relate γint(p)\gamma_{\mathrm{int}}(p) directly to the expected size of a sphere (rather than to a ball) when it is positive. This lemma will be used to establish the lower bounds of both Theorem 1.2 and Proposition 3.1.

Lemma 3.4.

Let GG be a connected, locally finite, quasi-transitive graph. There exists a positive constant C1C\geq 1 such that

γint(p)=infr1infvV1rlog(CpC𝐄p[#Bint(v,r)])=limrinfvV1rlog𝐄p[#Bint(v,r)]\gamma_{\mathrm{int}}(p)=\inf_{r\geq 1}\inf_{v\in V}\frac{1}{r}\log\left(Cp^{-C}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\right)=\lim_{r\to\infty}\inf_{v\in V}\frac{1}{r}\log\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]

for every ppcp\geq p_{c}. In particular, the limit on the right exists for every ppcp\geq p_{c}.

Proof of Lemma 3.4.

Fix p[0,1]p\in[0,1]. We trivially have that

infr1infvV1rlog(CpC𝐄p[#Bint(v,r)])\displaystyle\inf_{r\geq 1}\inf_{v\in V}\frac{1}{r}\log\left(Cp^{-C}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\right) lim infrinfvV1rlog𝐄p[#Bint(v,r)]\displaystyle\leq\liminf_{r\to\infty}\inf_{v\in V}\frac{1}{r}\log\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]
lim suprsupvV1rlog𝐄p[#Bint(v,r)]\displaystyle\leq\limsup_{r\to\infty}\sup_{v\in V}\frac{1}{r}\log\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]
limr1rlogsupvV𝐄p[#Bint(v,r)]=γint(p)\displaystyle\leq\lim_{r\to\infty}\frac{1}{r}\log\sup_{v\in V}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right]=\gamma_{\mathrm{int}}(p)

for every C1C\geq 1 and p>0p>0. Thus, it suffices to prove that there exists a constant C1C^{\prime}\geq 1 such that

γint(p)infr1infvV1rlog(CpC𝐄p[#Bint(v,r)])\gamma_{\mathrm{int}}(p)\leq\inf_{r\geq 1}\inf_{v\in V}\frac{1}{r}\log\left(C^{\prime}p^{-C^{\prime}}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\right) (3.4)

whenever ppcp\geq p_{c}. It follows straightforward from quasi-transitivity and the Harris-FKG inequality that there exists a constant CC such that

pCGrp(r)𝐄p[#Bint(v,r+C)]MC𝐄p[#Bint(v,r)]p^{C}\operatorname{Gr}_{p}(r)\leq\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r+C)\right]\leq M^{C}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right] (3.5)

for every vVv\in V and r1r\geq 1, where MM is the maximum degree of GG. Substituting this inequality into (1.1) yields that

𝐄p[#Bint(v,(k+1)r)]\displaystyle\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,(k+1)r)\right] 𝐄p[#Bint(v,kr)]+𝐄p[#Bint(v,r)]Grp(kr)\displaystyle\leq\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,kr)\right]+\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\operatorname{Gr}_{p}(kr)
𝐄p[#Bint(v,kr)]+(Mp)C𝐄p[#Bint(v,r)]𝐄p[#Bint(v,kr)]\displaystyle\leq\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,kr)\right]+\left(\frac{M}{p}\right)^{C}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,kr)\right]

for every r,k0r,k\geq 0, and it follows by induction on kk that

𝐄p[#Bint(v,kr)](1+(Mp)C𝐄p[#Bint(v,r)])k1𝐄p[#Bint(v,r)]\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,kr)\right]\leq\left(1+\left(\frac{M}{p}\right)^{C}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\right)^{k-1}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right]

for every r,k1r,k\geq 1. Since 𝐄p[#Bint(v,kr)]\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,kr)\right]\to\infty as kk\to\infty when ppcp\geq p_{c}, the claimed inequality (3.4) follows easily from this together with a further application of (3.5). ∎

We are now ready to prove Proposition 3.1 and hence Theorem 1.1.

Proof of Proposition 3.1.

The lower bound follows immediately from Lemma 3.4. We now prove the upper bound; we will take care to keep track of how the relevant constants blow up as ppcp\downarrow p_{c} so that the estimates we derive here can also be used in the proof of Theorem 1.2. We apply Proposition 3.2 together with Lemma 3.3 to deduce that there exists a continuous function κ1:I(0,)\kappa_{1}\mathrel{\mathop{\ordinarycolon}}I_{\nabla}\to(0,\infty) such that

Grp(r)Grp(r/2)+4r2(1α)αr𝒢(p,α)Grp(r/2)+4κ1(p)2r2(αpα)2(1α)αr\operatorname{Gr}_{p}(r)\leq\operatorname{Gr}_{p}(\lfloor r/2\rfloor)+\frac{4}{r^{2}(1-\alpha)}\cdot\alpha^{-r}\mathscr{G}^{*}(p,\alpha)\leq\operatorname{Gr}_{p}(\lfloor r/2\rfloor)+\frac{4\kappa_{1}(p)^{2}}{r^{2}(\alpha_{p}-\alpha)^{2}(1-\alpha)}\cdot\alpha^{-r}

for every r1r\geq 1, pIp\in I_{\nabla} with ppcp\geq p_{c}, and α<αp:=elogγint(p)\alpha<\alpha_{p}\mathrel{\mathop{\ordinarycolon}}=e^{-\log\gamma_{\mathrm{int}}(p)}. Taking α=rαp/(r+1)\alpha=r\alpha_{p}/(r+1) we deduce that

Grp(r)Grp(r/2)+4κ1(p)2(rr+1)rr+1αp2(r+1rαp)αpr\operatorname{Gr}_{p}(r)\leq\operatorname{Gr}_{p}(\lfloor r/2\rfloor)+4\kappa_{1}(p)^{2}\left(\frac{r}{r+1}\right)^{-r}\frac{r+1}{\alpha_{p}^{2}(r+1-r\alpha_{p})}\cdot\alpha_{p}^{-r}

for every r1r\geq 1, pIp\in I_{\nabla} with ppcp\geq p_{c}, and α<αp\alpha<\alpha_{p}. Since αp1/M\alpha_{p}\geq 1/M for every pp, where MM is the maximum degree of GG, it follows that there exists a continuous function κ2:I(0,)\kappa_{2}\mathrel{\mathop{\ordinarycolon}}I_{\nabla}\to(0,\infty) such that

Grp(r)Grp(r/2)+κ2(p)r+1r+1rαpαpr\operatorname{Gr}_{p}(r)\leq\operatorname{Gr}_{p}(\lfloor r/2\rfloor)+\kappa_{2}(p)\frac{r+1}{r+1-r\alpha_{p}}\alpha_{p}^{-r} (3.6)

for every r1r\geq 1 and pIp\in I_{\nabla} with ppcp\geq p_{c}. Fix r1r\geq 1, let ri+1=ri/2r_{i+1}=\lfloor r_{i}/2\rfloor for each i0i\geq 0, and let k(r)=min{i1:ri=0}log2rk(r)=\min\{i\geq 1\mathrel{\mathop{\ordinarycolon}}r_{i}=0\}\leq\log_{2}r. It follows recursively that

Grp(r)κ2(p)r+1r+1rαpi=0k(r)αpriκ2(p)r+1(r+1rαp)(1αp)αpr,\operatorname{Gr}_{p}(r)\leq\kappa_{2}(p)\frac{r+1}{r+1-r\alpha_{p}}\sum_{i=0}^{k(r)}\alpha_{p}^{-r_{i}}\leq\kappa_{2}(p)\frac{r+1}{(r+1-r\alpha_{p})(1-\alpha_{p})}\alpha_{p}^{-r}, (3.7)

where we used that (r+1)/(r+1rαp)(r+1)/(r+1-r\alpha_{p}) is an increasing function of rr in the first inequality and bounded i=0k(r)αpriαpri=0αi=(1αp)1αpr\sum_{i=0}^{k(r)}\alpha_{p}^{-r_{i}}\leq\alpha_{p}^{-r}\sum_{i=0}^{\infty}\alpha^{i}=(1-\alpha_{p})^{-1}\alpha_{p}^{-r} in the second inequality. (This last bound is rather coarse, and we will need a slightly more refined analysis when we prove Theorem 1.2.) When p>pcp>p_{c} we have by Proposition 2.1 that αp<1\alpha_{p}<1 so that the prefactor on the right is bounded by a pp-dependent constant as required. ∎

We now prove the unconditional growth estimates of Theorem 1.2 by a slight variation on the proof of Proposition 3.1 above.

Lemma 3.5.

Let GG be a connected, locally finite, quasi-transitive graph, and suppose that pc<p22p_{c}<p_{2\to 2}. Then there exists a positive constant δ\delta such that

𝐄p[#B(v,r)]\displaystyle\mathbf{E}_{p}\left[\#B(v,r)\right] (r1ppc)eγint(p)r\displaystyle\asymp\left(r\wedge\frac{1}{p-p_{c}}\right)^{\phantom{2}}e^{\gamma_{\mathrm{int}}(p)r} (3.8)

for every vVv\in V, r0r\geq 0, and pcppc+δp_{c}\leq p\leq p_{c}+\delta.

Proof of Theorem 1.2.

It follows from Lemmas 2.2 and 2.1 that the estimate

Grp(r)rreγint(p)r for every r(ppc)1\operatorname{Gr}_{p}(r)\asymp r\asymp re^{\gamma_{\mathrm{int}}(p)r}\qquad\text{ for every $r\leq(p-p_{c})^{-1}$} (3.9)

holds for every ppcp\geq p_{c} and r1r\geq 1. Moreover, it follows from Propositions 2.1 and 3.4 and a little elementary analysis that

Grp(r)supvV=0r𝐄p[#Bint(v,r)]=0reγint(p)(r1ppc)eγint(p)r\operatorname{Gr}_{p}(r)\geq\sup_{v\in V}\sum_{\ell=0}^{r}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r)\right]\succeq\sum_{\ell=0}^{r}e^{\gamma_{\mathrm{int}}(p)\ell}\succeq\left(r\vee\frac{1}{p-p_{c}}\right)e^{\gamma_{\mathrm{int}}(p)r}

for every r1r\geq 1, so that it remains only to prove the desired upper bounds on Grp(r)\operatorname{Gr}_{p}(r) in the case that p>pcp>p_{c} and r(ppc)1r\geq(p-p_{c})^{-1}. Similarly to the proof of Proposition 3.1, we fix r(ppc)1r\geq(p-p_{c})^{-1} and let ri+1=ri/2r_{i+1}=\lfloor r_{i}/2\rfloor for each i0i\geq 0, but now define k(r)=min{i1:ri(ppc)1}k(r)=\min\{i\geq 1\mathrel{\mathop{\ordinarycolon}}r_{i}\leq(p-p_{c})^{-1}\}. With these definitions in hand, we may apply the estimate (3.6) recursively as before to deduce that

Grp(r)Grp((ppc)1)+κ2(p)r+1r+1rαpi=0k(i)exp[γint(p)ri],\operatorname{Gr}_{p}(r)\leq\operatorname{Gr}_{p}(\lfloor(p-p_{c})^{-1}\rfloor)+\kappa_{2}(p)\frac{r+1}{r+1-r\alpha_{p}}\sum_{i=0}^{k(i)}\exp\left[\gamma_{\mathrm{int}}(p)r_{i}\right], (3.10)

where we recall that αp=eγint(p)\alpha_{p}=e^{-\gamma_{\mathrm{int}}(p)}. We have by Proposition 2.1 that 1αpppc1-\alpha_{p}\asymp p-p_{c} forevery p>pcp>p_{c} and hence that the prefactor multiplying the sum of exponentials in (3.10) satisfies

(r+1r+1rαp)1=1(11r+1)αp=1r+1+(1αp)1αpr+1(ppc)1r\left(\frac{r+1}{r+1-r\alpha_{p}}\right)^{-1}=1-(1-\frac{1}{r+1})\alpha_{p}=\frac{1}{r+1}+(1-\alpha_{p})-\frac{1-\alpha_{p}}{r+1}\asymp(p-p_{c})\vee\frac{1}{r} (3.11)

for every p>pcp>p_{c} and r1r\geq 1. To control the sum of exponentials itself, we note that for each 0i<k(i)0\leq i<k(i) we have that riri+1ri/2(ppc)1/2r_{i}-r_{i+1}\geq r_{i}/2\geq(p-p_{c})^{-1}/2. It follows from Proposition 2.1 that there exists a positive constant cc such that

exp[γint(p)ri+1]exp[γint(p)ric]\exp\left[\gamma_{\mathrm{int}}(p)r_{i+1}\right]\leq\exp\left[\gamma_{\mathrm{int}}(p)r_{i}-c\right]

for every 0i<k(i)0\leq i<k(i) and hence that

i=0k(i)exp[γint(p)ri]exp[γint(p)r]i=0k(i)eciexp[γint(p)r].\sum_{i=0}^{k(i)}\exp\left[\gamma_{\mathrm{int}}(p)r_{i}\right]\leq\exp\left[\gamma_{\mathrm{int}}(p)r\right]\sum_{i=0}^{k(i)}e^{-ci}\preceq\exp\left[\gamma_{\mathrm{int}}(p)r\right]. (3.12)

The claimed upper bound follows by substituting (3.9), (3.11), and (3.12) into (3.10) and using that κ2(p)\kappa_{2}(p) is bounded on a neighbourhood of pcp_{c}. ∎

We are now ready to conclude the proof of Theorem 1.2 given Proposition 3.2. The proof of the lower bound on the conditional expectation outside the scaling window will make use of the precise control on the tail of the radius of finite slightly supercritical clusters established in [23, Theorem 1.2]. The proof will apply the BK inequality and the attendant notion of the disjoint occurrence ABA\circ B of two increasing events AA and BB; see e.g. [12, Chapter 2] for background.

Proof of Theorem 1.2.

The estimates of (1.6) and (1.7) are provided by Proposition 2.1 and Lemma 3.5 respectively, so that it remains only to prove (1.8). Let δ>0\delta>0 be such that pc+δ<p22p_{c}+\delta<p_{2\to 2} and such that Lemma 3.5 and the results of [23] hold for every pc<ppc+δp_{c}<p\leq p_{c}+\delta, and fix one such pc<p<pc+δp_{c}<p<p_{c}+\delta. All constants appearing below will be independent of this choice of pp. (They may a priori depend on the choice of δ\delta, but this is not a problem since δ\delta may be chosen once-and-for-all as a function of the graph.)

We begin with the upper bound. For the ‘outside the scaling window’ case r(ppc)1r\geq(p-p_{c})^{-1}, we simply note that

𝐄p[#Bint(v,r)v]𝐄p[#Bint(v,r)]𝐏p(v)1(ppc)2eγint(p)\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\mid v\leftrightarrow\infty\right]\leq\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right]\mathbf{P}_{p}(v\leftrightarrow\infty)^{-1}\preceq(p-p_{c})^{-2}e^{\gamma_{\mathrm{int}}(p)} (3.13)

by (1.7) as claimed. We now consider the ‘inside the scaling window’ case r(ppc)1r\leq(p-p_{c})^{-1}. Let u,vVu,v\in V and r1r\geq 1. By considering the final intersection of some simple open path of length at most rr connecting vv to uu and some infinite simple open path starting at uu, we see that we have the inclusion of events

{v𝑟u}{v}wV{v𝑟w}{w𝑟u}{w}.\{v\xleftrightarrow{r}u\}\cap\{v\leftrightarrow\infty\}\subseteq\bigcup_{w\in V}\{v\xleftrightarrow{r}w\}\circ\{w\xleftrightarrow{r}u\}\circ\{w\leftrightarrow\infty\}. (3.14)

Thus, we have by a union bound and the BK inequality that

𝐄p[𝟙(v)#Bint(v,r)]supwV𝐄p[#Bint(v,r)]2supwV𝐏p(w)\mathbf{E}_{p}\left[\mathbbm{1}(v\leftrightarrow\infty)\cdot\#B_{\mathrm{int}}(v,r)\right]\leq\sup_{w\in V}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right]^{2}\sup_{w\in V}\mathbf{P}_{p}(w\leftrightarrow\infty) (3.15)

for every r1r\geq 1. Since GG is connected and quasi-transitive we have by the Harris-FKG inequality that there exists a constant CC such that supwV𝐏p(u)pCinfwV𝐏p(u)\sup_{w\in V}\mathbf{P}_{p}(u\leftrightarrow\infty)\leq p^{C}\inf_{w\in V}\mathbf{P}_{p}(u\leftrightarrow\infty) for every pp and hence that

𝐄p[#Bint(v,r)v]supwV𝐄p[#Bint(v,r)]2\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\mid v\leftrightarrow\infty\right]\preceq\sup_{w\in V}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right]^{2} (3.16)

for every r1r\geq 1. This implies the claimed upper bound within the scaling window in conjunction with the upper bound of (1.7).

We now prove the lower bound on the conditional expectation. We begin with the ‘inside the scaling window’ case r(ppc)1r\leq(p-p_{c})^{-1}. Suppose that we explore the cluster of the origin in a breadth-first manner, revealing the status of all edges incident to the intrinsic ball of radius ii at step ii of the exploration process. Conditional on this exploration up to step ii, the probability that any vertex in Bint(v,i)\partial B_{\mathrm{int}}(v,i) is connected to infinity by an open path that does not visit Bint(v,i)B_{\mathrm{int}}(v,i) after its first step is at most supwV𝐏p(w)(ppc)\sup_{w\in V}\mathbf{P}_{p}(w\leftrightarrow\infty)\asymp(p-p_{c}). As such, if we define i\mathcal{F}_{i} to be the σ\sigma-algebra generated by Bint(v,i)B_{\mathrm{int}}(v,i) then we have by Markov’s inequality that

𝐏p(vi)(ppc)#Bint(v,i)\mathbf{P}_{p}\left(v\leftrightarrow\infty\mid\mathcal{F}_{i}\right)\preceq(p-p_{c})\cdot\#\partial B_{\mathrm{int}}(v,i) (3.17)

for each i0i\geq 0 and pc<p1p_{c}<p\leq 1. For each r1r\geq 1 and ε>0\varepsilon>0, let Tr,ε=inf{ir:#Bint(v,i)εr}T_{r,\varepsilon}=\inf\{i\geq r\mathrel{\mathop{\ordinarycolon}}\#\partial B_{\mathrm{int}}(v,i)\leq\varepsilon r\}, where we set inf=\inf\emptyset=\infty. It follows from the above discussion that there exist positive constants C1C_{1} and C2C_{2} such that

𝐏p(v and Tr,ε2rBint(v,r))C1εr(ppc)C2εr𝐏p(v).\mathbf{P}_{p}(v\leftrightarrow\infty\text{ and }T_{r,\varepsilon}\leq 2r\mid\partial B_{\mathrm{int}}(v,r)\neq\emptyset)\leq C_{1}\varepsilon r(p-p_{c})\leq C_{2}\varepsilon r\mathbf{P}_{p}(v\leftrightarrow\infty). (3.18)

On the other hand, since r(ppc)1r\leq(p-p_{c})^{-1}, we have by [23, Lemma 2.1] that there exists a positive constant C3C_{3} such that 𝐏p(Bint(v,r))C3/r\mathbf{P}_{p}(\partial B_{\mathrm{int}}(v,r)\neq\emptyset)\leq C_{3}/r and hence that

𝐏p(Tr,ε2rv)C2C3ε.\mathbf{P}_{p}(T_{r,\varepsilon}\leq 2r\mid v\leftrightarrow\infty)\leq C_{2}C_{3}\varepsilon. (3.19)

Thus, if we take ε=1/(2C2C3)\varepsilon=1/(2C_{2}C_{3}), we find that Tr,ε>2rT_{r,\varepsilon}>2r with probability at least 1/21/2 on the event that vv belongs to an infinite cluster. It follows that

𝐄p[#Bint(v,2r)v]εr2𝐏p(Tr,ε>2rv)r22C2C3,\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,2r)\mid v\leftrightarrow\infty\right]\geq\varepsilon r^{2}\mathbf{P}_{p}(T_{r,\varepsilon}>2r\mid v\leftrightarrow\infty)\geq\frac{r^{2}}{2C_{2}C_{3}}, (3.20)

for every r(ppc)1r\leq(p-p_{c})^{-1}, which is easily seen to imply the claimed lower bound in this regime.

It remains only to prove the lower bound on the conditional expectation in the case r(ppc)1r\geq(p-p_{c})^{-1}. Fix vVv\in V. Suppose that yy and zz both belong to Bint(v,r)B_{\mathrm{int}}(v,r), and let η1\eta_{1} and η2\eta_{2} be intrinsic geodesics from vv to yy and vv to zz respectively. If η1\eta_{1} and η2\eta_{2} coincide for the last time at some vertex xx, then we must have that there exists 0=dint(v,x)r0\leq\ell=d_{\mathrm{int}}(v,x)\leq r such that the disjoint occurence {xBint(v,)}{yBint(x,r)}{zBint(x,r)}\{x\in\partial B_{\mathrm{int}}(v,\ell)\}\circ\{y\in B_{\mathrm{int}}(x,r-\ell)\}\circ\{z\in B_{\mathrm{int}}(x,r-\ell)\} occurs. Indeed, if we take any three intrinsic geodesics γ1\gamma_{1}, γ2\gamma_{2}, and γ3\gamma_{3} from vv to xx, xx to yy and xx to zz respectively, then the union of γ1\gamma_{1} with all the closed edges incident to Bint(v,)B_{\mathrm{int}}(v,\ell) is a witness for the event {xBint(x,)}\{x\in\partial B_{\mathrm{int}}(x,\ell)\}, the two paths γ2\gamma_{2} and γ3\gamma_{3} are witnesses for the events {yBint(x,r)}\{y\in B_{\mathrm{int}}(x,r-\ell)\} and {zBint(x,r)}\{z\in B_{\mathrm{int}}(x,r-\ell)\}, and all three sets are disjoint from each other. It follows by a union bound that

𝐄p[(#Bint(v,r))2]=0rx,y,z𝐏p({xBint(u,)}{yBint(x,r)}{zBint(x,r)})\mathbf{E}_{p}\left[(\#B_{\mathrm{int}}(v,r))^{2}\right]\leq\sum_{\ell=0}^{r}\sum_{x,y,z}\mathbf{P}_{p}\bigl{(}\{x\in\partial B_{\mathrm{int}}(u,\ell)\}\circ\{y\in B_{\mathrm{int}}(x,r-\ell)\}\circ\{z\in B_{\mathrm{int}}(x,r-\ell)\}\bigr{)} (3.21)

for every r0r\geq 0 and hence by Reimer’s inequality that

𝐄p[(#Bint(v,r))2]\displaystyle\mathbf{E}_{p}\left[(\#B_{\mathrm{int}}(v,r))^{2}\right] =0r𝐄p[#Bint(u,)]supvV𝐄p[#Bint(v,r)]2\displaystyle\leq\sum_{\ell=0}^{r}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(u,\ell)\right]\sup_{v\in V}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(v,r-\ell)\right]^{2}
1(ppc)2e2γint(p)r=0r𝐄p[#Bint(u,)]e2γint(p)\displaystyle\leq\frac{1}{(p-p_{c})^{2}}e^{2\gamma_{\mathrm{int}}(p)r}\sum_{\ell=0}^{r}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(u,\ell)\right]e^{-2\gamma_{\mathrm{int}}(p)\ell} (3.22)

for every r0r\geq 0, where we applied Lemma 3.5 in the second line. We may bound the sum appearing here in terms of the generating function 𝒢\mathscr{G} and apply Proposition 3.2 to obtain that

=0r𝐄p[#Bint(u,)]e2γint(p)𝒢(p,αp2)1αpαp21ppc,\sum_{\ell=0}^{r}\mathbf{E}_{p}\left[\#\partial B_{\mathrm{int}}(u,\ell)\right]e^{-2\gamma_{\mathrm{int}}(p)\ell}\leq\mathscr{G}^{*}(p,\alpha_{p}^{2})\preceq\frac{1}{\alpha_{p}-\alpha_{p}^{2}}\asymp\frac{1}{p-p_{c}}, (3.23)

so that

𝐄p[(#Bint(v,r))2]1(ppc)3e2γint(p)r1(ppc)𝐄p[#Bint(u,r)]2\mathbf{E}_{p}\left[(\#B_{\mathrm{int}}(v,r))^{2}\right]\preceq\frac{1}{(p-p_{c})^{3}}e^{2\gamma_{\mathrm{int}}(p)r}\asymp\frac{1}{(p-p_{c})}\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(u,r)\right]^{2} (3.24)

for every pc<p1p_{c}<p\leq 1 and r(ppc)1r\geq(p-p_{c})^{-1}. Now, it follows from Lemma 3.5 that there exists a positive constant c1c_{1} such that

𝐄p[#(Bint(v,r)Bint(v,c1r))]\displaystyle\mathbf{E}_{p}\left[\#\left(B_{\mathrm{int}}(v,r)\setminus B_{\mathrm{int}}(v,\lfloor c_{1}r\rfloor)\right)\right] =𝐄p[#Bint(v,r)]𝐄p[#Bint(v,c1r)]\displaystyle=\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right]-\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,\lfloor c_{1}r\rfloor)\right]
𝐄p[#Bint(v,r)](r1ppc)eγint(p)r\displaystyle\succeq\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\right]\asymp\left(r\wedge\frac{1}{p-p_{c}}\right)e^{\gamma_{\mathrm{int}}(p)r} (3.25)

for every r1r\geq 1. Letting Zr=#(Bint(v,r)Bint(v,c1r))Z_{r}=\#(B_{\mathrm{int}}(v,r)\setminus B_{\mathrm{int}}(v,\lfloor c_{1}r\rfloor)), we conclude that if r(ppc)1r\geq(p-p_{c})^{-1} then

𝐄pZr1ppceγint(p)r and 𝐄p[Zr2]1(ppc)3e2γint(p)r1ppc(𝐄pZr)2.\mathbf{E}_{p}Z_{r}\asymp\frac{1}{p-p_{c}}e^{\gamma_{\mathrm{int}}(p)r}\qquad\text{ and }\qquad\mathbf{E}_{p}\left[Z_{r}^{2}\right]\preceq\frac{1}{(p-p_{c})^{3}}e^{2\gamma_{\mathrm{int}}(p)r}\asymp\frac{1}{p-p_{c}}\left(\mathbf{E}_{p}Z_{r}\right)^{2}. (3.26)

Since the random variable ZrZ_{r} is non-zero if and only if KvK_{v} has intrinsic radius at least c1rc_{1}r, it follows from [23, Theorem 1.2] that there exist positive constants C4C_{4} and c2c_{2} such that if r(ppc)1r\geq(p-p_{c})^{-1} then

𝐏p(Zr>0,v)C4(ppc)ec2(ppc)r.\mathbf{P}_{p}(Z_{r}>0,v\nleftrightarrow\infty)\leq C_{4}(p-p_{c})e^{-c_{2}(p-p_{c})r}. (3.27)

As such, we have by Cauchy-Schwarz that there exists a constant C5C_{5} such that

𝐄p[Zr𝟙(Zr>0,v)]𝐄p[Zr2]𝐏p(Zr>0,v)C5ec2(ppc)r𝐄pZr\mathbf{E}_{p}\left[Z_{r}\mathbbm{1}(Z_{r}>0,v\nleftrightarrow\infty)\right]\leq\sqrt{\mathbf{E}_{p}\left[Z_{r}^{2}\right]\mathbf{P}_{p}(Z_{r}>0,v\nleftrightarrow\infty)}\leq C_{5}e^{-c_{2}(p-p_{c})r}\mathbf{E}_{p}Z_{r} (3.28)

for every r1r\geq 1. It follows that there exists a constant C6C_{6} such that if rC6(ppc)1r\geq C_{6}(p-p_{c})^{-1} then

𝐄p[Zr𝟙(Zr>0,v)]12𝐄pZr\mathbf{E}_{p}\left[Z_{r}\mathbbm{1}(Z_{r}>0,v\nleftrightarrow\infty)\right]\leq\frac{1}{2}\mathbf{E}_{p}Z_{r} (3.29)

and hence

𝐄p[Zr𝟙(v)]=𝐄p[Zr]𝐄p[Zr𝟙(Zr>0,v)]12𝐄p[Zr]1ppceγint(p)r.\mathbf{E}_{p}\left[Z_{r}\mathbbm{1}(v\leftrightarrow\infty)\right]=\mathbf{E}_{p}\left[Z_{r}\right]-\mathbf{E}_{p}\left[Z_{r}\mathbbm{1}(Z_{r}>0,v\nleftrightarrow\infty)\right]\geq\frac{1}{2}\mathbf{E}_{p}\left[Z_{r}\right]\asymp\frac{1}{p-p_{c}}e^{\gamma_{\mathrm{int}}(p)r}. (3.30)

It follows that

𝐄p[#Bint(v,r)v]𝐄p[Zrv]1(ppc)2eγint(p)r.\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\mid v\leftrightarrow\infty\right]\geq\mathbf{E}_{p}\left[Z_{r}\mid v\leftrightarrow\infty\right]\succeq\frac{1}{(p-p_{c})^{2}}e^{\gamma_{\mathrm{int}}(p)r}. (3.31)

for every rC6(ppc)1r\geq C_{6}(p-p_{c})^{-1}. This is easily seen to conclude the proof since the remaining cases (ppc)1<r<C6(ppc)1(p-p_{c})^{-1}<r<C_{6}(p-p_{c})^{-1} can be handled by monotonicity in rr. ∎

Remark 3.6.

The proof of Theorem 1.2 also yields that there exists δ>0\delta>0 such that

𝐄p[(#Bint(v,r))2v]𝐄p[#Bint(v,r)v]2(r1ppc)2e2γint(p)r\mathbf{E}_{p}\left[(\#B_{\mathrm{int}}(v,r))^{2}\mid v\leftrightarrow\infty\right]\asymp\mathbf{E}_{p}\left[\#B_{\mathrm{int}}(v,r)\mid v\leftrightarrow\infty\right]^{2}\asymp\left(r\wedge\frac{1}{p-p_{c}}\right)^{2}e^{2\gamma_{\mathrm{int}}(p)r} (3.32)

for every pc<ppc+δp_{c}<p\leq p_{c}+\delta and r1r\geq 1, and hence that #Bint(v,r)\#B_{\mathrm{int}}(v,r) is of order (r(ppc)1)eγint(p)r(r\wedge(p-p_{c})^{-1})e^{\gamma_{\mathrm{int}}(p)r} with good probability conditioned on {v}\{v\leftrightarrow\infty\} for each r1r\geq 1. It should be possible to prove similar estimates for higher moments with a little further work.

3.2 Proof of Proposition 3.2

In this section we prove Proposition 3.2 and thereby complete the proofs of Theorems 1.1, 1.2 and 3.1. Our proof will work by deriving and analyzing a certain differential inequality concerning the generating function 𝒢(p,α,u)\mathscr{G}(p,\alpha,u). To this end, we define for each p[0,1]p\in[0,1], α>0\alpha>0, and uVu\in V the formal derivative

α𝒢(p,α,u):=𝐄p[vKudint(u,v)αdint(u,v)1].\frac{\partial}{\partial\alpha}\mathscr{G}(p,\alpha,u)\mathrel{\mathop{\ordinarycolon}}=\mathbf{E}_{p}\left[\sum_{v\in K_{u}}d_{\mathrm{int}}(u,v)\alpha^{d_{\mathrm{int}}(u,v)-1}\right].

Note that, being defined as a convergent power series, 𝒢(p,α,u)\mathscr{G}(p,\alpha,u) is an analytic function of α\alpha with derivative α𝒢(p,α,u)\frac{\partial}{\partial\alpha}\mathscr{G}(p,\alpha,u) on (0,αp)(0,\alpha_{p}) for each p[0,1]p\in[0,1] and uVu\in V. We will deduce Proposition 3.2 from the following differential inequality.

Proposition 3.7.

Let GG be a connected, locally finite, quasi-transitive graph. Then there exists a continuous function η:I×(0,1](0,1]\eta\mathrel{\mathop{\ordinarycolon}}I_{\nabla}\times(0,1]\to(0,1] such that

α𝒢(p,α,u)η(p,α)𝒢(p,α,u)2\frac{\partial}{\partial\alpha}\mathscr{G}(p,\alpha,u)\geq\eta(p,\alpha)\mathscr{G}(p,\alpha,u)^{2}

for every p[0,1]p\in[0,1], uVu\in V, and 0<α10<\alpha\leq 1 such that 𝒢p,α<\mathscr{G}_{p,\alpha}^{*}<\infty.

Proof of Proposition 3.2 given Proposition 3.7.

Note that αp1/(M1)>0\alpha_{p}\geq 1/(M-1)>0 for every p[0,1]p\in[0,1], where MM is the maximum degree of GG. Fix pcpIp_{c}\leq p\in I_{\nabla}. It follows from Lemma 3.4 that 𝒢(p,αp)=𝒢(p,αp)=\mathscr{G}_{*}(p,\alpha_{p})=\mathscr{G}^{*}(p,\alpha_{p})=\infty and 𝒢(p,α)<\mathscr{G}^{*}(p,\alpha)<\infty for every α<αp\alpha<\alpha_{p}. (Since 𝒢(p,α,v)\mathscr{G}(p,\alpha,v) can be written as a power series in α\alpha with non-negative coefficients and with radius of convergence αp\alpha_{p}, this conclusion may also be derived from the Vivanti–Pringsheim theorem.) The differential inequality of Proposition 3.7 implies that

α𝒢(p,α,u)1=𝒢(p,α,u)2α𝒢(p,α,u)1η(p,α)inf{η(p,β):β[1/2M,1]}\frac{\partial}{\partial\alpha}\mathscr{G}(p,\alpha,u)^{-1}=-\mathscr{G}(p,\alpha,u)^{-2}\frac{\partial}{\partial\alpha}\mathscr{G}(p,\alpha,u)^{-1}\leq-\eta(p,\alpha)\leq-\inf\{\eta(p,\beta)\mathrel{\mathop{\ordinarycolon}}\beta\in[1/2M,1]\}

for every uVu\in V and αp/2α<αp\alpha_{p}/2\leq\alpha<\alpha_{p}. Integrating this differential inequality yields that

𝒢(p,α,u)1(αpα)inf{η(p,β):β[1/2M,1]}\mathscr{G}(p,\alpha,u)^{-1}\geq(\alpha_{p}-\alpha)\inf\{\eta(p,\beta)\mathrel{\mathop{\ordinarycolon}}\beta\in[1/2M,1]\}

for every αp/2α<αp\alpha_{p}/2\leq\alpha<\alpha_{p} and uVu\in V, and the claim follows by rearranging. ∎

We now begin to work towards the proof of Proposition 3.7. We begin by proving the following lemma, which can be thought of as a ‘well-separated’ version of the same inequality.

Lemma 3.8.

Let GG be a countable graph, and let PP be the transition matrix of simple random walk on GG. Then

v,wVPk(v,w)𝐄p[yV𝟙(vw)αdint(u,v)+dint(w,y)]𝒢(p,α)2𝒢(p,α)2supaV[Tp2PkTp](a,a).\sum_{v,w\in V}P^{k}(v,w)\mathbf{E}_{p}\left[\sum_{y\in V}\mathbbm{1}(v\nleftrightarrow w)\alpha^{d_{\mathrm{int}}(u,v)+d_{\mathrm{int}}(w,y)}\right]\geq\mathscr{G}_{*}(p,\alpha)^{2}-\mathscr{G}^{*}(p,\alpha)^{2}\sup_{a\in V}\left[T_{p}^{2}P^{k}T_{p}\right](a,a).

for every p[0,1]p\in[0,1], uVu\in V, and 0<α10<\alpha\leq 1 such that 𝒢(p,α)<\mathscr{G}^{*}(p,\alpha)<\infty.

The proof of this lemma (along with the general strategy of proving a differential inequality for percolation by first proving a well-separated variant on the same inequality) is adapted from proofs of similar statements concerning the the α=1\alpha=1 case, such as that of [27, Lemma 3.2] and [21, Section 5]; the basic idea is ultimately due to Aizenman and Newman [2].

Proof of Lemma 3.8.

We prove the estimate in the case α<1\alpha<1, which is the case we are primarily interested in. The case α=1\alpha=1 is simpler, and is very similar to arguments already in the literature such those appearing in [21, Section 5]. (Moreover, when GG is quasi-transitive, the case α=1\alpha=1 can be deduced from the case α<1\alpha<1 by taking the limit as α1\alpha\uparrow 1.) Fix uVu\in V and 0<α<10<\alpha<1. Writing {x𝑟y}\{x\xleftrightarrow{r}y\} for the event that xx and yy are connected by an open path of length at most rr, we have that

v,wVPk(v,w)𝐄p[yV𝟙(vw)αdint(u,v)+dint(w,y)]=(1α)2v,w,yVr1,r20αr1+r2Pk(v,w)𝐏p(vw,ur1v,wr2y).\sum_{v,w\in V}P^{k}(v,w)\mathbf{E}_{p}\left[\sum_{y\in V}\mathbbm{1}(v\nleftrightarrow w)\alpha^{d_{\mathrm{int}}(u,v)+d_{\mathrm{int}}(w,y)}\right]\\ =(1-\alpha)^{2}\sum_{v,w,y\in V}\sum_{r_{1},r_{2}\geq 0}\alpha^{r_{1}+r_{2}}P^{k}(v,w)\mathbf{P}_{p}\left(v\nleftrightarrow w,u\xleftrightarrow{r_{1}}v,w\xleftrightarrow{r_{2}}y\right).

Observe that for each u,v,w,yVu,v,w,y\in V and r1,r20r_{1},r_{2}\geq 0 we have that

𝐏p(vw,ur1v,wr2yKu)=𝟙(ur1v,wKu)𝐏p(wr2y off KuKu),\mathbf{P}_{p}\left(v\nleftrightarrow w,u\xleftrightarrow{r_{1}}v,w\xleftrightarrow{r_{2}}y\mid K_{u}\right)=\mathbbm{1}(u\xleftrightarrow{r_{1}}v,w\notin K_{u})\mathbf{P}_{p}(w\xleftrightarrow{r_{2}}y\text{ off }K_{u}\mid K_{u}),

where we write {x𝑟y off A}\{x\xleftrightarrow{r}y\text{ off }A\} for the event that xx and yy are connected by an open path of length at most rr that does not visit any vertices of AA, including at its endpoints. Define Qr(a,b;A)=𝟙(aA)𝐏p(a𝑟b off A)Q_{r}(a,b;A)=\mathbbm{1}(a\notin A)\mathbf{P}_{p}(a\xleftrightarrow{r}b\text{ off }A) for each a,bVa,b\in V, AVA\subseteq V, and r0r\geq 0. Since the event {wr2y\{w\xleftrightarrow{r_{2}}y off Ku}K_{u}\} is conditionally independent given KuK_{u} of the status of any edge both of whose endpoints belong to KuK_{u}, we have that

𝐏p(vw,ur1v,wr2yKu)=𝟙(ur1v)Qp,r2(w,y;Ku)\mathbf{P}_{p}\left(v\nleftrightarrow w,u\xleftrightarrow{r_{1}}v,w\xleftrightarrow{r_{2}}y\mid K_{u}\right)=\mathbbm{1}(u\xleftrightarrow{r_{1}}v)Q_{p,r_{2}}(w,y;K_{u}) (3.33)

for every u,v,w,yVu,v,w,y\in V and r1,r20r_{1},r_{2}\geq 0.

We now apply a standard argument similar to that appearing in the proof of [27, Lemma 3.2] to prove that

Qr,A(a,b):=𝟙(aA)𝐏p(a𝑟b off A)𝐏p(a𝑟b)xA𝐏p(ax)𝐏p(x𝑟b)Q_{r,A}(a,b)\mathrel{\mathop{\ordinarycolon}}=\mathbbm{1}(a\notin A)\mathbf{P}_{p}(a\xleftrightarrow{r}b\text{ off }A)\geq\mathbf{P}_{p}(a\xleftrightarrow{r}b)-\sum_{x\in A}\mathbf{P}_{p}(a\xleftrightarrow{}x)\mathbf{P}_{p}(x\xleftrightarrow{r}b) (3.34)

for every a,bVa,b\in V, AVA\subseteq V, an r0r\geq 0. Fix such an a,b,Aa,b,A, and rr. The inequality holds trivially if aAa\in A, so suppose not. In this case, we have that

𝐏p(a𝑟b off A)=𝐏p(a𝑟b)𝐏p(a𝑟b only via A),\mathbf{P}_{p}(a\xleftrightarrow{r}b\text{ off }A)=\mathbf{P}_{p}(a\xleftrightarrow{r}b)-\mathbf{P}_{p}(a\xleftrightarrow{r}b\text{ only via }A),

where we write {a𝑟b only via A}\{a\xleftrightarrow{r}b\text{ only via }A\} for the event that aa is connected to bb by a simple open path of length at most rr and every such path passes through AA. Next observe that

{a𝑟b only via A}xA{ax}{x𝑟b}.\{a\xleftrightarrow{r}b\text{ only via }A\}\subseteq\bigcup_{x\in A}\{a\leftrightarrow x\}\circ\{x\xleftrightarrow{r}b\}.

Indeed, if γ\gamma is a simple open path of length at most rr from aa to bb that visits AA at some vertex xx, then the portions of γ\gamma before and after visiting xx are disjoint witnesses for the events {ax}\{a\leftrightarrow x\} and {x𝑟b}\{x\xleftrightarrow{r}b\}. The claimed inequality (3.34) follows by applying the union bound and the BK inequality. Putting the estimates (3.33) and (3.34) together, we deduce that

𝐏p(vw,ur1v,wr2yKu)=𝟙(ur1v)𝐏p(wr2y)xKu𝟙(ur1v,wKu)𝐏p(wx)𝐏p(xr2y),\mathbf{P}_{p}\left(v\nleftrightarrow w,u\xleftrightarrow{r_{1}}v,w\xleftrightarrow{r_{2}}y\mid K_{u}\right)=\mathbbm{1}(u\xleftrightarrow{r_{1}}v)\mathbf{P}_{p}(w\xleftrightarrow{r_{2}}y)\\ -\sum_{x\in K_{u}}\mathbbm{1}(u\xleftrightarrow{r_{1}}v,w\notin K_{u})\mathbf{P}_{p}(w\xleftrightarrow{}x)\mathbf{P}_{p}(x\xleftrightarrow{r_{2}}y),

and hence that

𝐏p(vw,ur1v,wr2y)𝐏p(ur1v)𝐏p(wr2y)xV𝐏p(ur1v,ux)𝐏p(wx)𝐏p(xr2y)\mathbf{P}_{p}\left(v\nleftrightarrow w,u\xleftrightarrow{r_{1}}v,w\xleftrightarrow{r_{2}}y\right)\geq\mathbf{P}_{p}(u\xleftrightarrow{r_{1}}v)\mathbf{P}_{p}(w\xleftrightarrow{r_{2}}y)\\ -\sum_{x\in V}\mathbf{P}_{p}(u\xleftrightarrow{r_{1}}v,u\leftrightarrow x)\mathbf{P}_{p}(w\xleftrightarrow{}x)\mathbf{P}_{p}(x\xleftrightarrow{r_{2}}y)

for every v,w,yVv,w,y\in V and r1,r20r_{1},r_{2}\geq 0. Summing over v,w,yVv,w,y\in V and r1,r20r_{1},r_{2}\geq 0 yields that

v,wVPk\displaystyle\sum_{v,w\in V}P^{k} (v,w)𝐄p[yV𝟙(vw)αdint(u,v)+dint(w,y)]\displaystyle(v,w)\mathbf{E}_{p}\left[\sum_{y\in V}\mathbbm{1}(v\nleftrightarrow w)\alpha^{d_{\mathrm{int}}(u,v)+d_{\mathrm{int}}(w,y)}\right]
=(1α)2v,w,yVr1,r20αr1+r2Pk(v,w)𝐏p(vw,ur1v,wr2y)\displaystyle=(1-\alpha)^{2}\sum_{v,w,y\in V}\sum_{r_{1},r_{2}\geq 0}\alpha^{r_{1}+r_{2}}P^{k}(v,w)\mathbf{P}_{p}\left(v\nleftrightarrow w,u\xleftrightarrow{r_{1}}v,w\xleftrightarrow{r_{2}}y\right)
(1α)2v,w,yVr1,r20αr1+r2Pk(v,w)𝐏p(ur1v)𝐏p(wr2y)\displaystyle\geq(1-\alpha)^{2}\sum_{v,w,y\in V}\sum_{r_{1},r_{2}\geq 0}\alpha^{r_{1}+r_{2}}P^{k}(v,w)\mathbf{P}_{p}(u\xleftrightarrow{r_{1}}v)\mathbf{P}_{p}(w\xleftrightarrow{r_{2}}y)
(1α)2v,w,y,xVr1,r20αr1+r2Pk(v,w)𝐏p(ur1v,ux)𝐏p(wx)𝐏p(xr2y)\displaystyle\hskip 20.00003pt-(1-\alpha)^{2}\sum_{v,w,y,x\in V}\sum_{r_{1},r_{2}\geq 0}\alpha^{r_{1}+r_{2}}P^{k}(v,w)\mathbf{P}_{p}(u\xleftrightarrow{r_{1}}v,u\leftrightarrow x)\mathbf{P}_{p}(w\xleftrightarrow{}x)\mathbf{P}_{p}(x\xleftrightarrow{r_{2}}y)
𝒢(p,α)2(1α)v,w,xVr10αr1Pk(v,w)𝐏p(ur1v,ux)𝐏p(wx)𝒢(p,α)\displaystyle\geq\mathscr{G}_{*}(p,\alpha)^{2}-(1-\alpha)\sum_{v,w,x\in V}\sum_{r_{1}\geq 0}\alpha^{r_{1}}P^{k}(v,w)\mathbf{P}_{p}(u\xleftrightarrow{r_{1}}v,u\leftrightarrow x)\mathbf{P}_{p}(w\xleftrightarrow{}x)\mathscr{G}^{*}(p,\alpha)

for every vVv\in V, p[0,1]p\in[0,1], and 0<α<10<\alpha<1 such that the second term on the right of the last line is finite. To control this second term, first note that a standard BK inequality argument yields that

𝐏p(ur1v,ux)aV𝐏p(ur1a)𝐏p(av)𝐏p(ax)\mathbf{P}_{p}(u\xleftrightarrow{r_{1}}v,u\leftrightarrow x)\leq\sum_{a\in V}\mathbf{P}_{p}(u\xleftrightarrow{r_{1}}a)\mathbf{P}_{p}(a\leftrightarrow v)\mathbf{P}_{p}(a\leftrightarrow x)

for every u,v,xVu,v,x\in V and r10r_{1}\geq 0, so that

(1α)v,w,xVr10αr1Pk(v,w)𝐏p(ur1v,ux)𝐏p(wx)(1α)aVr10αr1𝐏p(ur1a)v,w,xVPk(v,w)𝐏p(av)𝐏p(ax)𝐏p(wx)=(1α)aVr10αr1𝐏p(ur1a)[Tp2PkTp](a,a)𝒢(p,α)supaV[Tp2PkTp](a,a)(1-\alpha)\sum_{v,w,x\in V}\sum_{r_{1}\geq 0}\alpha^{r_{1}}P^{k}(v,w)\mathbf{P}_{p}(u\xleftrightarrow{r_{1}}v,u\leftrightarrow x)\mathbf{P}_{p}(w\xleftrightarrow{}x)\\ \leq(1-\alpha)\sum_{a\in V}\sum_{r_{1}\geq 0}\alpha^{r_{1}}\mathbf{P}_{p}(u\xleftrightarrow{r_{1}}a)\sum_{v,w,x\in V}P^{k}(v,w)\mathbf{P}_{p}(a\leftrightarrow v)\mathbf{P}_{p}(a\leftrightarrow x)\mathbf{P}_{p}(w\xleftrightarrow{}x)\\ =(1-\alpha)\sum_{a\in V}\sum_{r_{1}\geq 0}\alpha^{r_{1}}\mathbf{P}_{p}(u\xleftrightarrow{r_{1}}a)\left[T_{p}^{2}P^{k}T_{p}\right](a,a)\leq\mathscr{G}^{*}(p,\alpha)\sup_{a\in V}\left[T_{p}^{2}P^{k}T_{p}\right](a,a)

for every vVv\in V, p[0,1]p\in[0,1], and 0<α<10<\alpha<1. Putting everything together, we get that

v,wVPk(v,w)𝐄p[yV𝟙(vw)αdint(u,v)+dint(w,y)]𝒢(p,α)2𝒢(p,α)2supaV[Tp2PkTp](a,a).\sum_{v,w\in V}P^{k}(v,w)\mathbf{E}_{p}\left[\sum_{y\in V}\mathbbm{1}(v\nleftrightarrow w)\alpha^{d_{\mathrm{int}}(u,v)+d_{\mathrm{int}}(w,y)}\right]\geq\mathscr{G}_{*}(p,\alpha)^{2}-\mathscr{G}^{*}(p,\alpha)^{2}\sup_{a\in V}\left[T_{p}^{2}P^{k}T_{p}\right](a,a).

for every uVu\in V, p[0,1]p\in[0,1] and 0α<10\leq\alpha<1 such that 𝒢(p,α)<\mathscr{G}^{*}(p,\alpha)<\infty, as claimed. (It may seem that we need to assume that 𝒢(p,α)2supaV[Tp2PkTp](a,a)\mathscr{G}^{*}(p,\alpha)^{2}\sup_{a\in V}\left[T_{p}^{2}P^{k}T_{p}\right](a,a) is finite, but in fact the inequality is trivial if 𝒢(p,α)2supaV[Tp2PkTp](a,a)\mathscr{G}^{*}(p,\alpha)^{2}\sup_{a\in V}\left[T_{p}^{2}P^{k}T_{p}\right](a,a) is infinite and 𝒢(p,α)𝒢(p,α)\mathscr{G}_{*}(p,\alpha)\leq\mathscr{G}^{*}(p,\alpha) is not.) ∎

We now deduce Proposition 3.7 from Lemma 3.8.

Proof of Proposition 3.7.

For each u,v,w,yVu,v,w,y\in V, let γ=γv,w\gamma=\gamma_{v,w} be a geodesic from vv to ww in GG, and let 𝒜(u,v,w,y)\mathscr{A}(u,v,w,y) be the event that that u,v,w,u,v,w, and yy all belong to the same cluster, that every edge of γ\gamma is open, and that every open path from uu to yy passes through a vertex of γ\gamma. Since |γ|k|\gamma|\leq k when Pk(v,w)>0P^{k}(v,w)>0, we have that

v,w,yVPk(v,w)𝐄p[αdint(u,y)𝟙(𝒜(u,v,w,y))]αkv,w,yVPk(v,w)𝐄p[αdint(u,v)+dint(w,y)𝟙(𝒜(u,v,w,y))].\sum_{v,w,y\in V}P^{k}(v,w)\mathbf{E}_{p}\left[\alpha^{d_{\mathrm{int}}(u,y)}\mathbbm{1}(\mathscr{A}(u,v,w,y))\right]\\ \geq\alpha^{k}\sum_{v,w,y\in V}P^{k}(v,w)\mathbf{E}_{p}\left[\alpha^{d_{\mathrm{int}}(u,v)+d_{\mathrm{int}}(w,y)}\mathbbm{1}(\mathscr{A}(u,v,w,y))\right].

We claim furthermore that

αkv,w,yVPk(v,w)𝐄p[αdint(u,v)+dint(w,y)𝟙(𝒜(u,v,w,y))](pα)ku,w,yVPk(v,w)𝐄p[αdint(u,v)+dint(w,y)𝟙(vw)].\alpha^{k}\sum_{v,w,y\in V}P^{k}(v,w)\mathbf{E}_{p}\left[\alpha^{d_{\mathrm{int}}(u,v)+d_{\mathrm{int}}(w,y)}\mathbbm{1}(\mathscr{A}(u,v,w,y))\right]\\ \geq(p\alpha)^{k}\sum_{u,w,y\in V}P^{k}(v,w)\mathbf{E}_{p}\left[\alpha^{d_{\mathrm{int}}(u,v)+d_{\mathrm{int}}(w,y)}\mathbbm{1}(v\nleftrightarrow w)\right]. (3.35)

Indeed, let ω\omega and ω\omega^{\prime} be two independent instances of Bernoulli-pp bond percolation, and let ω′′\omega^{\prime\prime} be defined by letting ω′′(e)=ω(e)\omega^{\prime\prime}(e)=\omega^{\prime}(e) if ee is traversed by γ\gamma and by letting ω′′(e)=ω(e)\omega^{\prime\prime}(e)=\omega(e) otherwise, so that ω′′\omega^{\prime\prime} is also distributed as Bernoulli-pp bond percolation. Condition on ω\omega, and suppose that the event {uv,vw,wy}\{u\leftrightarrow v,v\nleftrightarrow w,w\leftrightarrow y\} holds for ω\omega. The conditional probability that every edge ee traversed by γ\gamma is ω′′\omega^{\prime\prime}-open is pd(v,w)pkp^{d(v,w)}\geq p^{k}, and on this event the event 𝒜(u,v,w,y)\mathscr{A}(u,v,w,y) holds for ω′′\omega^{\prime\prime}. Moreover, on this event we have that ω′′ω\omega^{\prime\prime}\geq\omega and hence that all intrinsic distances are smaller in ω′′\omega^{\prime\prime} than in ω\omega, so that the claimed inequality follows easily.

Let u,yVu,y\in V. Suppose that uu and yy belong to the same cluster, let η\eta be an intrinsic geodesic from uu to yy, and let ηi\eta_{i} be the iith vertex visited by η\eta. Then we have the coarse bounds

v,wVPk(u,w)𝟙(𝒜(u,v,w,y))\displaystyle\sum_{v,w\in V}P^{k}(u,w)\mathbbm{1}(\mathscr{A}(u,v,w,y)) i=0dint(u,y)v,wV𝟙(γv,w visits ηi)Pk(u,w)\displaystyle\leq\sum_{i=0}^{d_{\mathrm{int}}(u,y)}\sum_{v,w\in V}\mathbbm{1}(\gamma_{v,w}\text{ visits }\eta_{i})P^{k}(u,w)
i=0dint(u,y)|B(ηi,k)|2dint(v,y)supvV|B(v,k)|2.\displaystyle\leq\sum_{i=0}^{d_{\mathrm{int}}(u,y)}|B(\eta_{i},k)|^{2}\leq d_{\mathrm{int}}(v,y)\sup_{v\in V}|B(v,k)|^{2}. (3.36)

Taking expectations and rearranging, it follows that

𝐄p[dint(u,y)αdint(u,y)][supvV|B(v,k)|2]1v,wVPk(v,w)𝐄p[αdint(u,y)𝟙(𝒜(u,v,w,y))]\mathbf{E}_{p}\left[d_{\mathrm{int}}(u,y)\alpha^{d_{\mathrm{int}}(u,y)}\right]\geq\left[\sup_{v\in V}|B(v,k)|^{2}\right]^{-1}\sum_{v,w\in V}P^{k}(v,w)\mathbf{E}_{p}\left[\alpha^{d_{\mathrm{int}}(u,y)}\mathbbm{1}(\mathscr{A}(u,v,w,y))\right]

for every u,yVu,y\in V, and hence by (3.35) that

𝐄p[yVdint(u,y)αdint(u,y)](pα)k[supvV|B(v,k)|2]1u,w,yVPk(v,w)𝐄p[αdint(u,v)+dint(w,y)𝟙(vw)].\mathbf{E}_{p}\left[\sum_{y\in V}d_{\mathrm{int}}(u,y)\alpha^{d_{\mathrm{int}}(u,y)}\right]\\ \geq(p\alpha)^{k}\left[\sup_{v\in V}|B(v,k)|^{2}\right]^{-1}\sum_{u,w,y\in V}P^{k}(v,w)\mathbf{E}_{p}\left[\alpha^{d_{\mathrm{int}}(u,v)+d_{\mathrm{int}}(w,y)}\mathbbm{1}(v\nleftrightarrow w)\right].

Applying Lemma 3.8, we obtain that

α𝒢(p,α,u)(pα)k[supvV|B(v,k)|2]1[1(pα)CsupaV[Tp2PkTp](a,a)]𝒢(p,α)2.\frac{\partial}{\partial\alpha}\mathscr{G}(p,\alpha,u)\geq(p\alpha)^{k}\left[\sup_{v\in V}|B(v,k)|^{2}\right]^{-1}\left[1-(p\alpha)^{-C}\sup_{a\in V}\left[T_{p}^{2}P^{k}T_{p}\right](a,a)\right]\mathscr{G}^{*}(p,\alpha)^{2}.

It follows by definition of the open triangle condition that there exists k(p,α)k(p,\alpha), bounded on compact subsets of I×(0,1]I_{\nabla}\times(0,1], such that

(pα)CsupaV[Tp2Pk(p,α)Tp](a,a)12(p\alpha)^{-C}\sup_{a\in V}\left[T_{p}^{2}P^{k(p,\alpha)}T_{p}\right](a,a)\leq\frac{1}{2}

and hence that

α𝒢(p,α,u)12(pα)k(p,α)[supvV|B(v,k(p,α))|2]1𝒢(p,α)2\frac{\partial}{\partial\alpha}\mathscr{G}(p,\alpha,u)\geq\frac{1}{2}(p\alpha)^{k(p,\alpha)}\left[\sup_{v\in V}\left|B\left(v,k\left(p,\alpha\right)\right)\right|^{2}\right]^{-1}\mathscr{G}^{*}(p,\alpha)^{2}

for every pIp\in I_{\nabla} and α(0,1]\alpha\in(0,1] such that 𝒢(p,α)<\mathscr{G}^{*}(p,\alpha)<\infty. This is easily seen to imply the claim. ∎

4 Expected and almost sure growth rates coincide

In this section we prove Theorem 1.5, which states that the expected and almost sure exponential growth rates of an infinite cluster always coincide. Note that an easier proof of this theorem is possible in the case pc<p<p22p_{c}<p<p_{2\to 2} by applying Theorem 1.1; in the general supercritical case we have to contend with the possibility that the subexponential corrections to growth are unbounded, which make the second moment calculations more involved.

Proof of Theorem 1.5.

In contrast to the rest of the paper, we will allow all the constants appearing in this proof to depend on pp. The almost sure upper bound

lim supn1rlog|Bint(v,r)|lim supn1rlog|Bint(v,r)|γint(p)\limsup_{n\to\infty}\frac{1}{r}\log|\partial B_{\mathrm{int}}(v,r)|\leq\limsup_{n\to\infty}\frac{1}{r}\log|B_{\mathrm{int}}(v,r)|\leq\gamma_{\mathrm{int}}(p) (4.1)

follows immediately from Markov’s inequality and Borel-Cantelli. Thus, to prove the theorem it suffices to prove that the event

𝒜v={lim infreγint(p)r|Bint(v,r)|>0}\mathscr{A}_{v}=\left\{\liminf_{r\to\infty}e^{-\gamma_{\mathrm{int}}(p)r}|\partial B_{\mathrm{int}}(v,r)|>0\right\}

satisfies 𝐏p(𝒜vv)=1\mathbf{P}_{p}(\mathscr{A}_{v}\mid v\to\infty)=1 for every vVv\in V. This claim is trivial when γint(p)=0\gamma_{\mathrm{int}}(p)=0, so we may assume that it is positive. It is a consequence of the indistinguishability theorem of Häggström, Peres, and Schonmann [14, Theorem 4.1.6] that 𝐏p(𝒜vv)\mathbf{P}_{p}(\mathscr{A}_{v}\mid v\to\infty) belongs to {0,1}\{0,1\} and does not depend on vv, so that it suffices to prove that 𝐏p(𝒜vv)>0\mathbf{P}_{p}(\mathscr{A}_{v}\mid v\to\infty)>0 for some vv. (If GG is unimodular then one can alternatively use the indistinguishability theorem of Lyons and Schramm [29] in this argument to achieve the same effect.)

Let hph_{p}, defined by ehp(r)=eγint(p)rsupvV𝐄p|Bint(v,r)|e^{h_{p}(r)}=e^{-\gamma_{\mathrm{int}}(p)r}\sup_{v\in V}\mathbf{E}_{p}|B_{\mathrm{int}}(v,r)| for each r0r\geq 0, describe the subexponential correction to growth of the expected cluster size as in (1.4). Let λ1\lambda\geq 1 and consider the set

λ={r0:hp(r)max0rhp()λ and supvV𝐄p[|Bint(v,r)|2]λsupvV𝐄p[|Bint(v,r)|]2}.\mathscr{R}_{\lambda}=\left\{r\geq 0\mathrel{\mathop{\ordinarycolon}}h_{p}(r)\geq\max_{0\leq\ell\leq r}h_{p}(\ell)-\lambda\,\text{ and }\,\sup_{v\in V}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r)|^{2}\right]\leq\lambda\sup_{v\in V}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r)|\right]^{2}\right\}.

We claim that there exists λ1\lambda\geq 1 such that λ\mathscr{R}_{\lambda} is infinite. To prove this, we first use a union bound and Reimer’s inequality as in (3.21) to obtain that

𝐄p[|Bint(u,r)|2]=0r𝐄p[|Bint(u,)|]supvV𝐄p[|Bint(v,r)|]2\mathbf{E}_{p}\left[|B_{\mathrm{int}}(u,r)|^{2}\right]\leq\sum_{\ell=0}^{r}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(u,\ell)|\right]\sup_{v\in V}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r-\ell)|\right]^{2} (4.2)

for every uVu\in V and r0r\geq 0. Taking the supremum over uu, this inequality may then be rewritten in terms of hph_{p} and γint\gamma_{\mathrm{int}} as

supvV𝐄p[|Bint(v,r)|2]=0rexp[γint(p)+2γint(p)(r)+hp()+2hp(r)]=supvV𝐄p[|Bint(v,r)|]2=0rexp[γint(p)(2hp(r)hp()2hp(r))].\sup_{v\in V}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r)|^{2}\right]\leq\sum_{\ell=0}^{r}\exp\left[\gamma_{\mathrm{int}}(p)\ell+2\gamma_{\mathrm{int}}(p)(r-\ell)+h_{p}(\ell)+2h_{p}(r-\ell)\right]\\ =\sup_{v\in V}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r)|\right]^{2}\sum_{\ell=0}^{r}\exp\left[-\gamma_{\mathrm{int}}(p)\ell-(2h_{p}(r)-h_{p}(\ell)-2h_{p}(r-\ell))\right]. (4.3)

We now split into two cases according to whether or not hp(r)h_{p}(r) is bounded as rr\to\infty. If hph_{p} is bounded by some constant C1C_{1}, then the sum on the right hand side of the last line is also bounded by the constant C2==0exp[γint(p)+3C1]C_{2}=\sum_{\ell=0}^{\infty}\exp\left[-\gamma_{\mathrm{int}}(p)\ell+3C_{1}\right]. Meanwhile, since hph_{p} is non-negative, we trivially have that hp(r)max0rhp()C1h_{p}(r)\geq\max_{0\leq\ell\leq r}h_{p}(\ell)-C_{1} for every r1r\geq 1 so that C1C2=\mathscr{R}_{C_{1}\vee C_{2}}=\mathbb{N} is infinite in this case as claimed. On the other hand, if hph_{p} is not bounded, then the set of running maxima ={r0:hp(r)=max0rhp(r)}\mathscr{R}^{\prime}=\{r\geq 0\mathrel{\mathop{\ordinarycolon}}h_{p}(r)=\max_{0\leq\ell\leq r}h_{p}(r-\ell)\} must be infinite, and if rr\in\mathscr{R}^{\prime} then

𝐄p[|Bint(v,r)|2]\displaystyle\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r)|^{2}\right] supvV𝐄p[|Bint(v,r)|]2=0rexp[γint(p)+hp()]\displaystyle\leq\sup_{v\in V}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r)|\right]^{2}\sum_{\ell=0}^{r}\exp\left[-\gamma_{\mathrm{int}}(p)\ell+h_{p}(\ell)\right]
supvV𝐄p[|Bint(v,r)|]2=0exp[γint(p)+hp()].\displaystyle\leq\sup_{v\in V}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r)|\right]^{2}\sum_{\ell=0}^{\infty}\exp\left[-\gamma_{\mathrm{int}}(p)\ell+h_{p}(\ell)\right]. (4.4)

Since lim1hp()=0\lim_{\ell\to\infty}\frac{1}{\ell}h_{p}(\ell)=0, the series on the last line converges. Thus, if we set the constant C3C_{3} to be =0exp[γint(p)+hp()]\sum_{\ell=0}^{\infty}\exp\left[-\gamma_{\mathrm{int}}(p)\ell+h_{p}(\ell)\right] then C3\mathscr{R}_{C_{3}} contains \mathscr{R}^{\prime} and is therefore infinite since we assumed hph_{p} to be unbounded. This completes the proof of the claim.

Fix λ\lambda such that λ\mathscr{R}_{\lambda} is infinite. Since GG is quasi-transitive, we have by the pigeonhole principle that there exists v0Vv_{0}\in V such that

λ,v0=λ{𝐄p[|Bint(v0,r)|]=supvV𝐄p[|Bint(v,r)|]}\mathscr{R}_{\lambda,v_{0}}=\mathscr{R}_{\lambda}\cap\left\{\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\right]=\sup_{v\in V}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r)|\right]\right\} (4.5)

is infinite also. Note that if rλ,v0r\in\mathscr{R}_{\lambda,v_{0}} then we have by the definitions that

eγint(p)supvV𝐄p[|Bint(v,r)|]=eγint(p)r+hp(r)eγint(p)r+hp(r)+λ=eλ𝐄p[|Bint(v0,r)|]e^{\gamma_{\mathrm{int}}(p)\ell}\sup_{v\in V}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r-\ell)|\right]=e^{\gamma_{\mathrm{int}}(p)r+h_{p}(r-\ell)}\leq e^{\gamma_{\mathrm{int}}(p)r+h_{p}(r)+\lambda}=e^{\lambda}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\right] (4.6)

for every 0r0\leq\ell\leq r. For each ε>0\varepsilon>0, let

Rε=inf{r0:|Bint(v0,r)|εeγint(p)r},R_{\varepsilon}=\inf\Bigl{\{}r\geq 0\mathrel{\mathop{\ordinarycolon}}|\partial B_{\mathrm{int}}(v_{0},r)|\leq\varepsilon e^{\gamma_{\mathrm{int}}(p)r}\Bigr{\}},

where we take inf=\inf\emptyset=\infty. It suffices to prove that there exists ε>0\varepsilon>0 such that 𝐏p(Rε=)>0\mathbf{P}_{p}(R_{\varepsilon}=\infty)>0. Let ε\mathcal{F}_{\varepsilon} be the σ\sigma-algebra generated by RεR_{\varepsilon} and Bint(v0,Rε)B_{\mathrm{int}}(v_{0},R_{\varepsilon}). Conditional on ε\mathcal{F}_{\varepsilon}, we have for each vBint(v,Rε)v\in\partial B_{\mathrm{int}}(v,R_{\varepsilon}) that the set of wVw\in V that are connected to vv by an open path of length at most rRεr-R_{\varepsilon} that is disjoint from Bint(v,Rε)B_{\mathrm{int}}(v,R_{\varepsilon}) except at its endpoints is stochastically dominated by the unconditioned law of Bint(v,rRε)B_{\mathrm{int}}(v,r-R_{\varepsilon}). Thus for each r0r\geq 0 and 0r0\leq\ell\leq r we have that

𝐄p[|Bint(v0,r)|ε]\displaystyle\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\mid\mathcal{F}_{\varepsilon}\right] {|Bint(v0,Rε)|+εeγint(p)RεsupvV𝐄p|Bint(v,rRε)|Rεr|Bint(v0,r)|Rε>r\displaystyle\leq\begin{cases}|B_{\mathrm{int}}(v_{0},R_{\varepsilon})|+\varepsilon e^{\gamma_{\mathrm{int}}(p)R_{\varepsilon}}\sup_{v\in V}\mathbf{E}_{p}|B_{\mathrm{int}}(v,r-R_{\varepsilon})|&R_{\varepsilon}\leq r\\ |B_{\mathrm{int}}(v_{0},r)|&R_{\varepsilon}>r\end{cases} (4.7)

and hence by (4.6) that

𝐄p[|Bint(v0,r)|ε]\displaystyle\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\mid\mathcal{F}_{\varepsilon}\right] {|Bint(v0,Rε)|+εeλ𝐄p[|Bint(v0,r)|]Rεr|Bint(v0,r)|Rε>r\displaystyle\leq\begin{cases}|B_{\mathrm{int}}(v_{0},R_{\varepsilon})|+\varepsilon e^{\lambda}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\right]&R_{\varepsilon}\leq r\\ |B_{\mathrm{int}}(v_{0},r)|&R_{\varepsilon}>r\end{cases} (4.8)

for every rλ,v0r\in\mathscr{R}_{\lambda,v_{0}} and ε>0\varepsilon>0. Taking expectations, it follows that

𝐄p[|Bint(v0,r)|𝟙(Rε)]\displaystyle\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\mathbbm{1}(R_{\varepsilon}\leq\ell)\right]
𝐄p[|Bint(v0,Rε)|𝟙(Rε)]+εeγint(p)RεsupvV𝐄p[|Bint(v,rRε)|]𝐏p(Rε)\displaystyle\hskip 99.58464pt\leq\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},R_{\varepsilon})|\mathbbm{1}(R_{\varepsilon}\leq\ell)\right]+\varepsilon e^{\gamma_{\mathrm{int}}(p)R_{\varepsilon}}\sup_{v\in V}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v,r-R_{\varepsilon})|\right]\mathbf{P}_{p}(R_{\varepsilon}\leq\ell)
𝐄p[|Bint(v0,Rε)|𝟙(Rε)]+εeλ𝐄p[|Bint(v0,r)|]𝐏p(Rε)\displaystyle\hskip 99.58464pt\leq\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},R_{\varepsilon})|\mathbbm{1}(R_{\varepsilon}\leq\ell)\right]+\varepsilon e^{\lambda}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\right]\mathbf{P}_{p}(R_{\varepsilon}\leq\ell)
𝐄p[|Bint(v0,)|]+εeλ𝐄p[|Bint(v0,r)|]\displaystyle\hskip 99.58464pt\leq\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},\ell)|\right]+\varepsilon e^{\lambda}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\right]
eλ(eγint(p)(r)+ε)𝐄p[|Bint(v0,r)|]\displaystyle\hskip 99.58464pt\leq e^{\lambda}\left(e^{-\gamma_{\mathrm{int}}(p)(r-\ell)}+\varepsilon\right)\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\right] (4.9)

for every rλ,v0r\in\mathscr{R}_{\lambda,v_{0}}, ε>0\varepsilon>0, and 0r0\leq\ell\leq r, where we applied (4.6) in the first and last inequalities. On the other hand, we have by Cauchy-Schwarz and the definition of λ,v0\mathscr{R}_{\lambda,v_{0}} that

𝐄p[|Bint(v0,r)|𝟙(Rε>)]\displaystyle\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\mathbbm{1}(R_{\varepsilon}>\ell)\right] 𝐄p[|Bint(v0,r)|2]1/2𝐏p(Rε>)1/2\displaystyle\leq\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|^{2}\right]^{1/2}\mathbf{P}_{p}(R_{\varepsilon}>\ell)^{1/2}
λ1/2𝐄p[|Bint(v0,r)|]𝐏p(Rε>)1/2\displaystyle\leq\lambda^{1/2}\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\right]\mathbf{P}_{p}(R_{\varepsilon}>\ell)^{1/2} (4.10)

for every rλ,v0r\in\mathscr{R}_{\lambda,v_{0}}, ε>0\varepsilon>0, and 0r0\leq\ell\leq r. Putting these two bounds together yields that

𝐄p[|Bint(v0,r)|](eλε+eλeγint(p)(r)+λ1/2𝐏p(Rε>)1/2)𝐄p[|Bint(v0,r)|]\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\right]\leq\left(e^{\lambda}\varepsilon+e^{\lambda}e^{-\gamma_{\mathrm{int}}(p)(r-\ell)}+\lambda^{1/2}\mathbf{P}_{p}(R_{\varepsilon}>\ell)^{1/2}\right)\mathbf{E}_{p}\left[|B_{\mathrm{int}}(v_{0},r)|\right] (4.11)

for every rλ,v0r\in\mathscr{R}_{\lambda,v_{0}}, ε>0\varepsilon>0, and 0r0\leq\ell\leq r. Rearranging, we deduce that

𝐏p(Rε>)1/21λ1/2[1eλε+eλγint(p)(r)]\mathbf{P}_{p}(R_{\varepsilon}>\ell)^{1/2}\geq\frac{1}{\lambda^{1/2}}\left[1-e^{\lambda}\varepsilon+e^{\lambda-\gamma_{\mathrm{int}}(p)(r-\ell)}\right] (4.12)

for every rλ,v0r\in\mathscr{R}_{\lambda,v_{0}}, ε>0\varepsilon>0, and 0r0\leq\ell\leq r. Since λ,v0\mathscr{R}_{\lambda,v_{0}} is infinite and γint(p)\gamma_{\mathrm{int}}(p) is positive, it follows by taking the limit as rr\to\infty along λ,v0\mathscr{R}_{\lambda,v_{0}} that

𝐏p(Rε>)1/21λ1/2[1eλε]\mathbf{P}_{p}(R_{\varepsilon}>\ell)^{1/2}\geq\frac{1}{\lambda^{1/2}}\left[1-e^{\lambda}\varepsilon\right] (4.13)

for every ε>0\varepsilon>0 and 0\ell\geq 0. If ε<eλ\varepsilon<e^{-\lambda} then the right hand side is positive and does not depend on \ell, so that

𝐏p(Rε=)=lim𝐏p(Rε>)λ1[1eλε]2>0\mathbf{P}_{p}(R_{\varepsilon}=\infty)=\lim_{\ell\to\infty}\mathbf{P}_{p}(R_{\varepsilon}>\ell)\geq\lambda^{-1}\left[1-e^{\lambda}\varepsilon\right]^{2}>0 (4.14)

for every ε<eλ\varepsilon<e^{-\lambda}. This completes the proof. ∎

4.1 Positivity of the intrinsic growth on amenable graphs of exponential growth

In this section we prove Theorem 1.6.

Proof of Theorem 1.6.

The case that GG is nonamenable follows from either [4, Theorem 3.1] (yielding that the infinite cluster always contains a subgraph with positive Cheeger constant) or the results of [16] (since anchored expansion implies exponential growth). As such, it suffices to consider the case that GG is amenable, in which case the infinite cluster is unique for every p>pcp>p_{c}. Fix one such p>pcp>p_{c}. The Harris-FKG inequality implies that

𝐏p(uv)𝐏p(u)𝐏p(v)θ(p)2\mathbf{P}_{p}(u\leftrightarrow v)\geq\mathbf{P}_{p}(u\leftrightarrow\infty)\mathbf{P}_{p}(v\leftrightarrow\infty)\geq\theta_{*}(p)^{2}

for every u,vVu,v\in V, where we define θ(p)=minv𝐏p(v)\theta_{*}(p)=\min_{v}\mathbf{P}_{p}(v\leftrightarrow\infty). Since GG is quasi-transitive, it follows by continuity of measure that for each r1r\geq 1 there exists R(r,p)<R(r,p)<\infty such that

min{𝐏p(uR(r,p)v):u,vV,d(u,v)r}12θ(p)2,\min\bigl{\{}\mathbf{P}_{p}\bigl{(}u\xleftrightarrow{R(r,p)}v\bigr{)}\mathrel{\mathop{\ordinarycolon}}u,v\in V,d(u,v)\leq r\bigr{\}}\geq\frac{1}{2}\theta_{*}(p)^{2},

where {uR(r,p)v}\{u\xleftrightarrow{R(r,p)}v\} denotes the event that uu and vv are connected by a path of length at most R(r,p)R(r,p). Note that if uu and vv have distance at most krkr then there exists a sequence u=u0,u1,,uk=vu=u_{0},u_{1},\ldots,u_{k}=v such that d(ui,ui+1)rd(u_{i},u_{i+1})\leq r for each 0ik10\leq i\leq k-1, and if the events {uiR(r,p)ui+1}\{u_{i}\xleftrightarrow{R(r,p)}u_{i+1}\} all hold for every 0ik10\leq i\leq k-1 then uu is connected to vv by an open path of length at most kR(r,p)kR(r,p). Applying Harris-FKG again, we deduce that

min{𝐏p(ukR(r,p)v):u,vV,d(u,v)kr}(12θ(p)2)k\min\bigl{\{}\mathbf{P}_{p}\bigl{(}u\xleftrightarrow{kR(r,p)}v\bigr{)}\mathrel{\mathop{\ordinarycolon}}u,v\in V,d(u,v)\leq kr\bigr{\}}\geq\left(\frac{1}{2}\theta_{*}(p)^{2}\right)^{k}

for every k,r1k,r\geq 1. Letting γ=limn1nlog|B(v,n)|\gamma=\lim_{n\to\infty}\frac{1}{n}\log|B(v,n)| be the exponential growth rate of GG, it follows that

γint(p)\displaystyle\gamma_{\mathrm{int}}(p) limk1kR(r,p)log[|B(v,kr)|min{𝐏p(ukR(r,p)v):u,vV,d(u,v)kr}]\displaystyle\geq\lim_{k\to\infty}\frac{1}{kR(r,p)}\log\left[|B(v,kr)|\min\bigl{\{}\mathbf{P}_{p}\bigl{(}u\xleftrightarrow{kR(r,p)}v\bigr{)}\mathrel{\mathop{\ordinarycolon}}u,v\in V,d(u,v)\leq kr\bigr{\}}\right]
rγR(r,p)1R(r,p)log2θ(p)2\displaystyle\geq\frac{r\gamma}{R(r,p)}-\frac{1}{R(r,p)}\log\frac{2}{\theta_{*}(p)^{2}}

for every r1r\geq 1. The claim follows by taking rr sufficiently large that rγ>log2θ(p)2r\gamma>\log\frac{2}{\theta_{*}(p)^{2}}. ∎

5 The anchored Cheeger constant

In this section we prove Theorem 1.8. We begin by establishing the upper bound.

Lemma 5.1.

Let GG be a connected, locally finite, quasi-transitive graph, and suppose that pc<p22p_{c}<p_{2\to 2}. Then there exists a constant CC such that for every pc<p1p_{c}<p\leq 1, every infinite cluster KK in Bernoulli-pp bond percolation on GG has

Φ(K)C(ppc)2\Phi^{*}(K)\leq C(p-p_{c})^{2}

𝐏p\mathbf{P}_{p}-almost surely.

Before proving this lemma, we first prove the following simple concentration lemma for the number of vertices in a set that belong to an infinite cluster. We define θ(p):=supvV𝐏p(v)\theta^{*}(p)\mathrel{\mathop{\ordinarycolon}}=\sup_{v\in V}\mathbf{P}_{p}(v\leftrightarrow\infty).

Lemma 5.2.

Let G=(V,E)G=(V,E) be a countable graph, and let 0p<p22(G)0\leq p<p_{2\to 2}(G). Let AVA\subset V be a finite set of vertices and let A={vA:v}A_{\infty}=\{v\in A\mathrel{\mathop{\ordinarycolon}}v\leftrightarrow\infty\}. Then the variance of |A||A_{\infty}| satisfies

𝐕𝐚𝐫p|A|:=𝐄p[(|A|𝐄p[|A|])2]θ(p)Tp222|A|.\mathbf{Var}_{p}|A_{\infty}|\mathrel{\mathop{\ordinarycolon}}=\mathbf{E}_{p}\left[\left(|A_{\infty}|-\mathbf{E}_{p}\left[|A_{\infty}|\right]\right)^{2}\right]\leq\theta^{*}(p)\|T_{p}\|_{2\to 2}^{2}|A|.
Proof of Lemma 5.2.

Consider the matrix Tp,[0,1]V2T_{p,\infty}\in[0,1]^{V^{2}} defined by setting Tp,(u,v):=𝐏p(uv and u)T_{p,\infty}(u,v)\mathrel{\mathop{\ordinarycolon}}=\mathbf{P}_{p}(u\leftrightarrow v\text{ and }u\leftrightarrow\infty) for each u,vVu,v\in V. We claim that

Tp,θ(p)Tp2 and hence that Tp,22θ(p)Tp222T_{p,\infty}\preccurlyeq\theta^{*}(p)T_{p}^{2}\qquad\text{ and hence that }\qquad\|T_{p,\infty}\|_{2\to 2}\leq\theta^{*}(p)\|T_{p}\|_{2\to 2}^{2} (5.1)

for every 0p10\leq p\leq 1, where \preccurlyeq denotes entrywise inequality of matrices. Indeed, if uu is connected to both vv and \infty then there must exist a vertex ww (possibly equal to either uu or vv) such that the event {uw}{w}{wv}\{u\leftrightarrow w\}\circ\{w\leftrightarrow\infty\}\circ\{w\leftrightarrow v\} occurs. Applying the BK inequality, it follows that

Tp,(u,v)w𝐏p(uw)𝐏p(w)𝐏p(wv),T_{p,\infty}(u,v)\leq\sum_{w}\mathbf{P}_{p}(u\leftrightarrow w)\mathbf{P}_{p}(w\leftrightarrow\infty)\mathbf{P}_{p}(w\leftrightarrow v), (5.2)

which clearly implies the claimed inequality (5.1). We deduce that

𝐄p|A|2\displaystyle\mathbf{E}_{p}|A_{\infty}|^{2} =u,vA𝐏p(u,v,uv)+u,vA𝐏p(u,v,uv)\displaystyle=\sum_{u,v\in A}\mathbf{P}_{p}(u\leftrightarrow\infty,v\leftrightarrow\infty,u\nleftrightarrow v)+\sum_{u,v\in A}\mathbf{P}_{p}(u\leftrightarrow\infty,v\leftrightarrow\infty,u\leftrightarrow v)
u,vA𝐏p(u)𝐏p(v)+u,vA𝐏p(u,uv)\displaystyle\leq\sum_{u,v\in A}\mathbf{P}_{p}(u\leftrightarrow\infty)\mathbf{P}_{p}(v\leftrightarrow\infty)+\sum_{u,v\in A}\mathbf{P}_{p}(u\leftrightarrow\infty,u\leftrightarrow v)
=(𝐄p|A|)2+Tp,𝟙A,𝟙A(𝐄p|A|)2+θ(p)Tp222|A|\displaystyle=\left(\mathbf{E}_{p}|A_{\infty}|\right)^{2}+\langle T_{p,\infty}\mathbbm{1}_{A},\mathbbm{1}_{A}\rangle\leq\left(\mathbf{E}_{p}|A_{\infty}|\right)^{2}+\theta^{*}(p)\|T_{p}\|^{2}_{2\to 2}|A| (5.3)

as required, where the inequality in the second line follows from the BK inequality. ∎

Given a set of vertices KK in GG, we write EωK={eEK:ω(e)=1}\partial^{\omega}_{E}K=\{e\in\partial_{E}K\mathrel{\mathop{\ordinarycolon}}\omega(e)=1\} for the set of open edges belonging to the edge boundary of KK.

Proof of Lemma 5.1.

Let α\alpha be a constant to be chosen, let p0=(pc+p22)/2p_{0}=(p_{c}+p_{2\to 2})/2, and fix vVv\in V. Since the inequality Φ(K)1\Phi^{*}(K)\leq 1 holds vacuously, it suffices to prove the claim for pc<pp0p_{c}<p\leq p_{0}. Fix one such pc<pp0p_{c}<p\leq p_{0} and a vertex vv of GG. By Propositions 2.1 and 1.5 there exists a constant C1C_{1} such that

i=0r1(1+|Bint(v,i+1)||Bint(v,i)|)=|Bint(v,r)|eC1(ppc)r\prod_{i=0}^{r-1}\left(1+\frac{|\partial B_{\mathrm{int}}(v,i+1)|}{|B_{\mathrm{int}}(v,i)|}\right)=|B_{\mathrm{int}}(v,r)|\leq e^{C_{1}(p-p_{c})r}

for all sufficiently large rr almost surely. (Note that we are only using the easy parts of Propositions 2.1 and 1.5 to reach this conclusion.) Rearranging, this implies that there exists a constant C2C_{2} such that

lim infr|Bint(v,r)||Bint(v,r)|eC1(ppc)1eC1(ppc)C2(ppc)\liminf_{r\to\infty}\frac{|\partial B_{\mathrm{int}}(v,r)|}{|B_{\mathrm{int}}(v,r)|}\leq\frac{e^{C_{1}(p-p_{c})}-1}{e^{C_{1}(p-p_{c})}}\leq C_{2}(p-p_{c})

almost surely on the event that vv is in an infinite cluster.

We now perform a breadth-first search of the cluster of vv: At stage 0 we expose the value of every edge touching vv. At each subsequent stage i1i\geq 1 we expose the value of those edges that touch Bint(v,i1)\partial B_{\mathrm{int}}(v,i-1) and have not yet been exposed, stopping if and when Bint(v,i)=\partial B_{\mathrm{int}}(v,i)=\emptyset. Let TjT_{j} be the jjth time that |Bint(v,r)|2C2(ppc)|Bint(v,r)||\partial B_{\mathrm{int}}(v,r)|\leq 2C_{2}(p-p_{c})|B_{\mathrm{int}}(v,r)|, so that jTj<j\leq T_{j}<\infty for every j1j\geq 1 almost surely on the event that vv is in an infinite cluster. Let i\mathcal{F}_{i} be the σ\sigma-algebra generated by the exploration up to time ii, and let Tj\mathcal{F}_{T_{j}} be the stopped σ\sigma-algebra generated by by the exploration up to time TjT_{j}. For each i1i\geq 1, let XiX_{i} be the number of vertices of Bint(v,i)B_{\mathrm{int}}(v,i) that are connected to infinity off of Bint(v,i)B_{\mathrm{int}}(v,i), and note that any such vertex must belong to Bint(v,i)\partial B_{\mathrm{int}}(v,i). Conditional on Tj<T_{j}<\infty and on the stopped σ\sigma-algebra Tj\mathcal{F}_{T_{j}}, the expectation 𝐄p[XTjTj]\mathbf{E}_{p}[X_{T_{j}}\mid\mathcal{F}_{T_{j}}] is at most θ(p)|Bint(v,Tj)|C3(ppc)2|Bint(v,Tj)|\theta^{*}(p)|\partial B_{\mathrm{int}}(v,T_{j})|\leq C_{3}(p-p_{c})^{2}|B_{\mathrm{int}}(v,T_{j})| for some constant C3C_{3}. By Lemma 5.2 (applied to the subgraph of GG spanned by those edges that have not yet been queried by stage TjT_{j}), the conditional variance of XTjX_{T_{j}} is at most C4(ppc)2|Bint(v,Tj)|C_{4}(p-p_{c})^{2}|B_{\mathrm{int}}(v,T_{j})| for some constant C4C_{4}. It follows by Chebyshev’s inequality that there exist positive constants C5C_{5} and C6C_{6} such that

𝐏p(XTjC5(ppc)2|Bint(v,Tj)|Tj)C6𝟙(Tj<)(ppc)2|Bint(v,Tj)|.\mathbf{P}_{p}\left(X_{T_{j}}\geq C_{5}(p-p_{c})^{2}|B_{\mathrm{int}}(v,T_{j})|\mid\mathcal{F}_{T_{j}}\right)\leq\frac{C_{6}\mathbbm{1}(T_{j}<\infty)}{(p-p_{c})^{2}|B_{\mathrm{int}}(v,T_{j})|}.

Since the right hand side tends to zero as jj\to\infty, it follows by Fatou’s lemma that

lim infiXi|Bint(v,i)|lim infjXTj|Bint(v,Tj)|C5(ppc)2\liminf_{i\to\infty}\frac{X_{i}}{|B_{\mathrm{int}}(v,i)|}\leq\liminf_{j\to\infty}\frac{X_{T_{j}}}{|B_{\mathrm{int}}(v,T_{j})|}\leq C_{5}(p-p_{c})^{2}

almost surely on the event that vv is in an infinite cluster. Let Hull(v,i)Bint(v,i)\operatorname{Hull}(v,i)\supseteq B_{\mathrm{int}}(v,i) be the set of all vertices uu in the cluster of vv such that any path from uu to \infty in KvK_{v} must pass through Bint(v,i)B_{\mathrm{int}}(v,i). Then we have that |EωHull(v,i)|MXi|\partial_{E}^{\omega}\operatorname{Hull}(v,i)|\leq MX_{i}, where MM is the maximum degree of GG, so that

lim infi|EωHull(v,i)||Hull(v,i)|lim infiMXi|Bint(v,i)|MC5(ppc)2\liminf_{i\to\infty}\frac{|\partial_{E}^{\omega}\operatorname{Hull}(v,i)|}{|\operatorname{Hull}(v,i)|}\leq\liminf_{i\to\infty}\frac{MX_{i}}{|B_{\mathrm{int}}(v,i)|}\leq MC_{5}(p-p_{c})^{2}

almost surely on the event that vv is in an infinite cluster. The claim follows since vv was arbitrary. ∎

Our final goal is to apply [23, Theorem 1.1] and [16, Proposition 3.2] to complete the proof of Theorem 1.8. The case of the inequality in which pp is very close to 11 will require the following estimate on the exponential decay rate

ζ(p):=lim infn1nsupvVlog𝐏p(n|Kv|<),\zeta(p)\mathrel{\mathop{\ordinarycolon}}=\liminf_{n\to\infty}-\frac{1}{n}\sup_{v\in V}\log\mathbf{P}_{p}(n\leq|K_{v}|<\infty),

which is adapted from [5, Theorem 2].

Lemma 5.3.

Let GG be a nonamenable locally finite graph with Cheeger constant Φ(G)>0\Phi(G)>0. Then

ζ(p)Φ(G)logΦ(G)1p+(1Φ(G))logΦ(G)p\displaystyle\zeta(p)\geq\Phi(G)\log\frac{\Phi(G)}{1-p}+(1-\Phi(G))\log\frac{\Phi(G)}{p} (5.4)

for every 0<p<10<p<1.

Note that this bound is only positive for p>1Φ(G)p>1-\Phi(G).

Proof of Lemma 5.3.

Let (Xi)i1(X_{i})_{i\geq 1} be an i.i.d. sequence of Beroulli-pp random variables and let vv be a vertex of GG. We can couple percolation on GG with the sequence XiX_{i} so that the cluster of vv touches i=1nXi\sum_{i=1}^{n}X_{i} open edges and ni=1nXin-\sum_{i=1}^{n}X_{i} closed edges on the event that |E(Kv)|=n|E(K_{v})|=n. The number of closed edges in the boundary of KvK_{v} must be at least Φ(G)|E(Kv)|\Phi(G)|E(K_{v})|, and it follows that

ζ(p)=lim supn1nlog𝐏p(|E(Kv)|=n)\displaystyle\zeta(p)=\limsup_{n\to\infty}-\frac{1}{n}\log\mathbf{P}_{p}(|E(K_{v})|=n) lim supn1nlog(i=1nXi(1Φ(G))n)\displaystyle\geq\limsup_{n\to\infty}-\frac{1}{n}\log\mathbb{P}\left(\sum_{i=1}^{n}X_{i}\leq(1-\Phi(G))n\right)
=Φ(G)logΦ(G)1p+(1Φ(G))logΦ(G)p\displaystyle=\Phi(G)\log\frac{\Phi(G)}{1-p}+(1-\Phi(G))\log\frac{\Phi(G)}{p} (5.5)

for every 0<p<10<p<1, where the second line follows by standard large deviations theory (i.e., Cramér’s theorem). ∎

Proof of Theorem 1.8.

The upper bound is immediate from Lemma 5.1. On the other hand, [16, Proposition 3.2], which is based on an argument of Pete [8, Theorem A.1], states that if p>pcp>p_{c} then every infinite cluster KK of Bernoulli-pp bond percolation on GG has anchored expansion with anchored cheeger constant

Φ(K)12sup{α[0,p]:αα(1α)(1α)[p1p]α<eζ(p)}\Phi^{*}(K)\geq\frac{1}{2}\sup\left\{\alpha\in[0,p]\mathrel{\mathop{\ordinarycolon}}\alpha^{-\alpha}(1-\alpha)^{-(1-\alpha)}\left[\frac{p}{1-p}\right]^{\alpha}<e^{\zeta(p)}\right\} (5.6)

almost surely, where

ζ(p):=lim infn1nsupvVlog𝐏p(n|Kv|<)\zeta(p)\mathrel{\mathop{\ordinarycolon}}=\liminf_{n\to\infty}-\frac{1}{n}\sup_{v\in V}\log\mathbf{P}_{p}(n\leq|K_{v}|<\infty)

for each p[0,1]p\in[0,1]. It follows from [23, Theorem 1.1 and Corollary 1.3] that there exist positive constants cc and δ\delta such that ζ(p)c(ppc)2\zeta(p)\geq c(p-p_{c})^{2} for every pc<ppc+δp_{c}<p\leq p_{c}+\delta. Meanwhile, the main result of [16] states that ζ(p)>0\zeta(p)>0 for every pc<p1p_{c}<p\leq 1, and it follows by continuity of ζ\zeta (see e.g. [11, Theorem 10.1]) that there exists a constant c2c_{2} such that ζ(p)c2\zeta(p)\geq c_{2} for every pc+δp1p_{c}+\delta\leq p\leq 1. Putting these estimates together with Lemma 5.3, we deduce that there exists a positive constant c1c_{1} such that

ζ(p)c1(ppc)2log11p\zeta(p)\geq c_{1}(p-p_{c})^{2}\log\frac{1}{1-p} (5.7)

for every pc<p<1p_{c}<p<1. The claim follows from this and (5.6) by direct calculation, since if α=c2(ppc)2/log1/(ppc)\alpha=c_{2}(p-p_{c})^{2}/\log 1/(p-p_{c}) for a sufficiently small positive constant c2c_{2} then αp\alpha\leq p and

αα(1α)(1α)[p1p]α<ec1(ppc)2log11p\alpha^{-\alpha}(1-\alpha)^{-(1-\alpha)}\left[\frac{p}{1-p}\right]^{\alpha}<e^{c_{1}(p-p_{c})^{2}\log\frac{1}{1-p}}

for every pc<p<1p_{c}<p<1. ∎

6 Open problems

Let us end the paper with some natural questions raised by our work. Some of these questions are similar in spirit to those raised by Benjamini, Lyons and Schramm in their 1999 work [4], many of which remain open.

Question 6.1.

Let GG be a nonamenable Cayley graph with pc<p22p_{c}<p_{2\to 2} and for which the volume of GG has unbounded subexponential corrections to growth, such as G=T×dG=T\times\mathbb{Z}^{d}. At which values of pp do the infinite clusters of GG have unbounded subexponential corrections to growth? Is the growth of clusters always either pure exponential or of the same form as GG? If a transition from one behaviour to the other occurs, does it do so at p22p_{2\to 2}, pup_{u}, or some other point?

Question 6.2.

Under the hypotheses of Theorem 1.5, do we have that

0<lim infr|Bint(v,r)|𝐄p|Bint(v,r)|lim supr|Bint(v,r)|𝐄p|Bint(v,r)|<0<\liminf_{r\to\infty}\frac{|\partial B_{\mathrm{int}}(v,r)|}{\mathbf{E}_{p}|\partial B_{\mathrm{int}}(v,r)|}\leq\limsup_{r\to\infty}\frac{|\partial B_{\mathrm{int}}(v,r)|}{\mathbf{E}_{p}|\partial B_{\mathrm{int}}(v,r)|}<\infty

almost surely on the event that vv belongs to an infinite cluster?

Question 6.3.

Can the 1/log1/(ppc)1/\log 1/(p-p_{c}) factor be removed from the lower bound of Theorem 1.8?

Acknowledgments

This work was carried out in part while the author was a Senior Research Associate at the University of Cambridge, during which time he was supported by ERC starting grant 804166 (SPRS).

References

  • [1] M. Abert, M. Fraczyk, and B. Hayes. Co-spectral radius, equivalence relations and the growth of unimodular random rooted trees. arXiv preprint arXiv:2205.06692, 2022.
  • [2] M. Aizenman and C. M. Newman. Tree graph inequalities and critical behavior in percolation models. J. Statist. Phys., 36(1-2):107–143, 1984.
  • [3] P. Antal and A. Pisztora. On the chemical distance for supercritical Bernoulli percolation. Ann. Probab., 24(2):1036–1048, 1996.
  • [4] I. Benjamini, R. Lyons, and O. Schramm. Percolation perturbations in potential theory and random walks. In Random walks and discrete potential theory (Cortona, 1997), Sympos. Math., XXXIX, pages 56–84. Cambridge Univ. Press, Cambridge, 1999.
  • [5] I. Benjamini and O. Schramm. Percolation beyond d\mathbb{Z}^{d}, many questions and a few answers. volume 1, pages no. 8, 71–82. 1996.
  • [6] R. Cerf and B. Dembin. The time constant for bernoulli percolation is lipschitz continuous strictly above pcp_{c}. arXiv preprint arXiv:2101.11858, 2021.
  • [7] S. Chatterjee, J. Hanson, and P. Sosoe. Subcritical connectivity and some exact tail exponents in high dimensional percolation. arXiv preprint arXiv:2107.14347, 2021.
  • [8] D. Chen, Y. Peres, and G. Pete. Anchored expansion, percolation and speed. Annals of probability, pages 2978–2995, 2004.
  • [9] B. Dembin. Regularity of the time constant for a supercritical Bernoulli percolation. ESAIM Probab. Stat., 25:109–132, 2021.
  • [10] O. Garet, R. Marchand, E. B. Procaccia, and M. Théret. Continuity of the time and isoperimetric constants in supercritical percolation. Electron. J. Probab., 22:Paper No. 78, 35, 2017.
  • [11] A. Georgakopoulos and C. Panagiotis. On the exponential growth rates of lattice animals and interfaces, and new bounds on pcp_{c}. arXiv preprint arXiv:1908.03426, 2019.
  • [12] G. Grimmett. Percolation, volume 321 of Grundlehren der Mathematischen Wissenschaften [Fundamental Principles of Mathematical Sciences]. Springer-Verlag, Berlin, second edition, 1999.
  • [13] G. R. Grimmett and J. M. Marstrand. The supercritical phase of percolation is well behaved. Proc. Roy. Soc. London Ser. A, 430(1879):439–457, 1990.
  • [14] O. Häggström, Y. Peres, and R. H. Schonmann. Percolation on transitive graphs as a coalescent process: relentless merging followed by simultaneous uniqueness. In Perplexing problems in probability, volume 44 of Progr. Probab., pages 69–90. Birkhäuser Boston, Boston, MA, 1999.
  • [15] T. Hara and G. Slade. Mean-field behaviour and the lace expansion. In Probability and phase transition, pages 87–122. Springer, 1994.
  • [16] J. Hermon and T. Hutchcroft. Supercritical percolation on nonamenable graphs: isoperimetry, analyticity, and exponential decay of the cluster size distribution. Invent. Math., 224(2):445–486, 2021.
  • [17] S. Hernandez-Torres, E. B. Procaccia, and R. Rosenthal. The chemical distance in random interlacements in the low-intensity regime. arXiv preprint arXiv:2112.13390, 2021.
  • [18] M. Heydenreich and R. van der Hofstad. Progress in high-dimensional percolation and random graphs. CRM Short Courses. Springer, Cham; Centre de Recherches Mathématiques, Montreal, QC, 2017.
  • [19] T. Hutchcroft. Percolation on hyperbolic graphs. Geometric and Functional Analysis, 29(3):766–810, Jun 2019.
  • [20] T. Hutchcroft. Self-avoiding walk on nonunimodular transitive graphs. Ann. Probab., 47(5):2801–2829, 2019.
  • [21] T. Hutchcroft. The L2L^{2} boundedness condition in nonamenable percolation. Electron. J. Probab., 25:Paper No. 127, 27, 2020.
  • [22] T. Hutchcroft. Nonuniqueness and mean-field criticality for percolation on nonunimodular transitive graphs. J. Amer. Math. Soc., 33(4):1101–1165, 2020.
  • [23] T. Hutchcroft. Slightly supercritical percolation on nonamenable graphs I: The distribution of finite clusters. arXiv preprint arXiv:2002.02916, 2020.
  • [24] T. Hutchcroft, E. Michta, and G. Slade. High-dimensional near-critical percolation and the torus plateau. arXiv preprint arXiv:2107.12971, 2021.
  • [25] H. Kesten and B. P. Stigum. A limit theorem for multidimensional Galton-Watson processes. Ann. Math. Statist., 37:1211–1223, 1966.
  • [26] G. Kozma. Percolation on a product of two trees. The Annals of Probability, pages 1864–1895, 2011.
  • [27] G. Kozma and A. Nachmias. The Alexander-Orbach conjecture holds in high dimensions. Invent. Math., 178(3):635–654, 2009.
  • [28] R. Lyons, R. Pemantle, and Y. Peres. Conceptual proofs of LlogLL\log L criteria for mean behavior of branching processes. Ann. Probab., 23(3):1125–1138, 1995.
  • [29] R. Lyons and O. Schramm. Indistinguishability of percolation clusters. Ann. Probab., 27(4):1809–1836, 1999.
  • [30] A. Nachmias and Y. Peres. Non-amenable Cayley graphs of high girth have pc<pup_{c}<p_{u} and mean-field exponents. Electron. Commun. Probab., 17:no. 57, 8, 2012.
  • [31] I. Pak and T. Smirnova-Nagnibeda. On non-uniqueness of percolation on nonamenable Cayley graphs. C. R. Acad. Sci. Paris Sér. I Math., 330(6):495–500, 2000.
  • [32] A. Sapozhnikov. Upper bound on the expected size of the intrinsic ball. Electronic Communications in Probability, 15:297–298, 2010.
  • [33] R. H. Schonmann. Multiplicity of phase transitions and mean-field criticality on highly non-amenable graphs. Comm. Math. Phys., 219(2):271–322, 2001.
  • [34] Á. Timár. A stationary random graph of no growth rate. In Annales de l’IHP Probabilités et statistiques, volume 50, pages 1161–1164, 2014.