Past exam of the mathematics course of the University of Cambridge / 2016 / iii / Paper 204 / 3

The cubic lattice has graph vertices ${\mathbb{Z}}^d$ and an edge between $x,y$ when ${\sum }_i|x_i-y_i|=1$. In independent site percolation, every graph vertex is open with probability $p$ and closed with probability $1-p$, independently. The open subgraph contains only open graph vertices and the edges between them. Let $C_p(0)$ be the open connected component of a graph containing $0$, with $C_p(0)=\varnothing$ when $0$ is closed. The percolation probability isSince the cubic lattice is a locally finite graph, the König infinity lemma identifies an infinite open connected component of a graph with the existence of an infinite open graph ray from the origin. In particular, the origin itself must be open. The percolation critical probability is $p_c=\inf \{p:\theta (p)>0\}$.

Let $A_n$ be the event that the origin has an open graph path to the boundary of $[-n,n{]}^d\cap {\mathbb{Z}}^d$. The graph path can be stopped on its first boundary visit, so $A_n$ depends on only finitely many sites. Its probability $f_n(p)={\mathbb{P}}_p(A_n)$ is a finite sum of terms $p^a(1-p{)}^b$, and is therefore a continuous function of $p$. Also $A_{n+1}\subseteq A_n$, and the König infinity lemma gives ${\bigcap }_n{A}_n=\{0\leftrightarrow \infty \}$. By continuity from above of a measure,The monotone coupling of Bernoulli percolation described below shows that $\theta$ is nondecreasing. For $p<1$, its right limit of a function $\theta (p+)$ exists and is at least $\theta (p)$. For every fixed $n$,Taking the infimum in $n$ proves $\theta (p+)=\theta (p)$. This proves right continuity of percolation probability throughout $[0,1)$; at $1$ right continuity is understood relative to the parameter domain. The argument does not interchange two uncontrolled limits.

Use the probability space $([0,1{]}^{{\mathbb{Z}}^d},\mathcal{F},\mathbb{P})$ with the product measure of the uniform distribution on $[0,1]$. Its coordinate random variables $U_v$ are independent and identically distributed random variables. Define simultaneously for every parameterFor $r\le s$, the indicator function inequality $X_r(v)\le X_s(v)$ holds pointwise at every graph vertex. For fixed $p$, each coordinate has the Bernoulli distribution with parameter $p$, and the coordinates are independent because they are functions of distinct independent $U_v$. Thus every marginal configuration is exactly the required site percolation model. This is a continuum-indexed family of processes, all on one probability space, and is the standard monotone coupling of Bernoulli percolation.

Work on the common probability space from part (c). For a configuration of all the uniforms, the set $S=\{r\in [0,1]:I_r\text{ occurs}\}$ is an upper interval, possibly with or without its lower endpoint. It is nonempty because $I_1$ occurs, and the coupled onset parameter for origin percolation is $M=\inf S$. For $0<p\le 1$,Indeed, occurrence at some $r<p$ implies $M<p$. Conversely, if $M<p$, the definition of infimum yields occurrence at some $s<p$, and a rational $r$ between $s$ and $p$ also satisfies $I_r$. This also proves measurability of $M$ through its strict sublevel sets.

Choose a rational sequence increasing to $p$. By continuity from below of a measure and the monotone coupling of Bernoulli percolation,Moreover, $\{M<p\}\subseteq I_p\subseteq \{M\le p\}$. Hence $I_p$ is the disjoint union of $\{M<p\}$ and $I_p\cap \{M=p\}$, givingIt is important to retain the intersection with $I_p$: occurrence at the infimum is not automatic. At $p=0$ there is no left limit within the parameter domain, so the displayed left-limit assertion is for $p>0$.

Use the following general result, including its site version: independent site percolation on ${\mathbb{Z}}^d$ has almost surely at most one infinite percolation cluster at each fixed parameter; for every fixed $r>p_c$ it has exactly one almost surely. This is the uniqueness of the infinite percolation cluster, also called the Burton-Keane theorem. For $d\ge 2$, the additional general fact $p_c<1$ ensures a choice of a parameter strictly between $p_c$ and $1$. In dimension one, $p_c=1$ and the asserted interval is empty.

Fix $p\in (p_c,1]$ and choose $q\in (p_c,p)$. Let ${\mathcal{C}}_q$ be the unique infinite open connected component of a graph at $q$. Under the monotone coupling of Bernoulli percolation, it is contained in the unique infinite open connected component of a graph at $p$. On $I_p$, the origin and ${\mathcal{C}}_q$ therefore lie in that same connected component of a graph, and a finite $p$-open graph path connects $0$ to some graph vertex of ${\mathcal{C}}_q$.

For this fixed deterministic $p$, the countable set of uniforms satisfies $U_v\ne p$ at every graph vertex almost surely. Thus all uniforms on that finite graph path are strictly less than $p$, including its endpoints. If $t$ is their maximum, choose $r$ with $\max (q,t)<r<p$. The graph path is then $r$-open, and its endpoint remains connected to infinity through ${\mathcal{C}}_q$. Consequently $I_r$ occurs and $M<p$. We have provedPart (d) gives left continuity at this $p$; part (b) supplies right continuity when $p<1$. The same finite-path proof gives left continuity at $p=1$, since all uniforms are strictly less than $1$ almost surely. Thus $\theta$ is continuous on $(p_c,1]$, without asserting continuity at $p_c$. This is supercritical continuity of percolation probability.