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Original citation:

Benjamini, Itai, Curien, Nicolas and Georgakopoulos, Agelos. (2012) The Liouville and

the intersection properties are equivalent for planar graphs. Electronic communications

in probability, Vol.17 . Article no. 42.

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ISSN:1083-589X in PROBABILITY

The Liouville and the intersection properties

are equivalent for planar graphs

Itai Benjamini

Nicolas Curien

Agelos Georgakopoulos

§

Abstract

It is shown that if a planar graph admits no non-constant bounded harmonic function then the trajectories of two independent simple random walks intersect almost surely.

Keywords:Random walks ; Planar graphs ; Liouville property ; intersection.

AMS MSC 2010:05C81.

Submitted to ECP on March 29, 2012, final version accepted on September 13, 2012.

1

Introduction

LetG= (V, E)be a connected (multi)graph. The graphGhas theintersection prop-erty if for anyx, yV, the trajectories of two independent simple random walks (SRW) started respectively fromxandyintersect almost surely. Recall thatGisLiouvilleif it admits no non-constant bounded harmonic function. The goal of this note is to prove the following:

Theorem 1.1. IfGis planar and Liouville thenGhas the intersection property.

Let us make a few comments on this result. We first recall the well-known sequence of implications as well as theZd, d>1lattices that satisfy them:

recurrence intersection Liouville

Zd, d= 1,2 Zd, d= 1,2,3,4 Zd, d>1.

In the case of bounded degree planar graphs the Liouville property is equivalent to recurrence of the simple random walk, see [3] (as in the case of non-compact planar Riemannian surfaces). If we drop the bounded degree assumption, it is easy to construct transient planar graphs which are Liouville: For example, start with a half lineN = {0,1,2, ...} and place2n parallel edges betweennand n+ 1forn

> 0. Yet this graph clearly has the intersection property.

Our result thus becomes interesting in the case of Liouville planar graphs of un-bounded degree. Such graphs arise for example as distributional limits of finite random planar graphs, a topic that has attracted a lot of research recently [1, 2, 6, 7].

Supported by FWF Grant P-24028-N18.

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The Liouville and the intersection properties are equivalent for planar graphs

2

Proof

The strategy of the proof is the following. We consider three independent simple random walk trajectories, and argue that if each two of them intersect only finitely many times, then they divide our planar graph into three regions (Fig.1). This allows us to talk about the probability for random walk to eventually stay in one of these regions, which we use to construct a non-constant bounded harmonic function, contradicting our Liouvilleness assumption.

Proof. FixG= (V, E)a connected planar multi-graph and suppose thatGhas the Liou-ville property. First note that ifGis recurrent then it has the intersection property and we thus suppose henceforth thatGis transient.

Denote byPx the law of a simple random walk(Xn)n>0started fromxinG. We write

X={X0, X1, X2, ...}for the trajectory of(Xn). Ifγ={γ0, γ1, ...}is a set of vertices inG define for anyxV

hγ(x) := Px #(X∩γ) =∞

.

It is clear thathγ(.)is harmonic (bounded) and is thus constant sinceGis Liouville. We writehγ for the common value hγ(y), y ∈ V. In fact, one hashγ ∈ {0,1}. Indeed, if

Fn=σ(X0, X1, ..., Xn)is the sigma-field generated by the SRW we have

1#(X∩γ)=∞ = lim

n→∞Ex[1#(X∩γ)=∞| Fn] = n→∞lim hγ(Xn) a.s.

Hencehγ(Xn)tends to0or1a.s. and the claim follows. Let us now randomize the pathγ and consider the random variablehXwhereXis the trajectory of a SRW underPx. The

last argument shows thathX ∈ {0,1}. We now claim thathXis almost surely constant.

Indeed, ifXandYare two independent simple random walk trajectories started from

xV(G)we havehX=hX(x) =1#(X∩Y)=∞a.s. (and similarly interchanging the roles ofXandY) thus

Ex[hXhY] = Px #(X∩Y) =∞and#(Y∩X) =∞

= Px #(X∩Y) =∞

= Ex[hX].

HenceEx[hX]2=Ex[hX]∈ {0,1}. EitherhX= 1 =hX(y)for ally∈V a.s. in which case

Theorem 1.1 is proved, or almost surely for allyV we havehX= 0 =hX(y). In words,

a.s. for anyx, yV, two simple random walk paths started fromxandy intersect only finitely many times. Let us suppose by contradiction that we are in the latter case.

We now make use of the planarity and consider a proper embedding1 of G inR2. Let us consider three independent simple random walk trajectoriesX(1),X(2)andX(3) started from somexV. Since almost surely these paths intersect each-other finitely often a.s., they distinguish, using the planarity, three regions in (the embedding of)G

calledR1,R2andR3as depicted in the figure below. Formally, the regionR1is defined as the set of all verticesyV\S3

k=1X

(k)such that for allnlarge enough, ifγis a path

linking y toXn(1) inG thenγ must intersect X(2)∪X(3). The regions R2 and R3 are defined similarly.

Now for anyy V, conditionally onX(1),X(2)andX(3)we consider a simple random walk trajectoryYunderPy. By our assumption the pathYintersects any of theX(i)’s

1Notice that sinceGis Liouville, it has precisely one transient endαand it is possible to embedGinR2

so that no ray inαhas an accumulation point inR2, which always exists [8].

ECP17(2012), paper 42.

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R1

R2

R3

X(1)

X(3)

[image:4.595.187.412.98.294.2]

X(2)

Figure 1: The three (random) regionsR1,R2andR3.

finitely many times a.s. so that Y is eventually trapped in one of the three regions

R1,R2orR3. We then define

H(y) := Py(Yis eventually trapped inR1).

Note thatH(.)is a random function and that for everyω it is (bounded) harmonic over

Gand thus constant by the Liouville property ofG. On the one hand an obvious sym-metry argument shows thatE[H(x)] = 1/3. On the other hand sinceHis almost surely constant we haveH(x) =H(Xn(1))for alln>0. Almost surely, for allnlarge enough, if a simple random walk started fromXn(1)is eventually trapped inR1then it has to cross one of the pathsX(2) orX(3). We thus have

E[H(x)] = lim sup

n→∞

E[H(Xn(1))]

= lim sup

n→∞

EhPX(1)

n (Yis trapped inR1)

i

6 lim sup

n→∞

EhPX(1)

n (YintersectsX (2)

∪X(3))i.

But sinceX(1) has only a finite intersection withX(2)

∪X(3) a.s. we deduce that the probability inside the expectation of the right-hand side of the last display goes to0as

n→ ∞. HenceE[H(x)] = 0and this is a contradiction. One deduces thathX= 1almost

surely as desired.

3

Concluding Remarks

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The Liouville and the intersection properties are equivalent for planar graphs

minor graphs (see, e.g., [10]). It is even more interesting to show that bounded de-gree transient excluded minor graphs admit non-constant bounded harmonic functions thus extending [3]. Another generalization of planarity is sphere-packability, see [4]. Weask whether a Liouville sphere-packable graph inR3should admit the intersection property?

Quasi-isometry. LetG1= (V1, E1)andG2= (V2, E2)be two graphs endowed respec-tivelly with their graph distancesd1andd2. These graphs are calledquasi-isometricif there existsφ:V1→V2and two constantsA, B >0such that for everyx, y∈V1

A−1d1(x, y)−B 6d2(φ(x), φ(y))6Ad1(x, y) +B,

and if for everyzV2there existsx∈V1withd2(z, φ(x))6B.

For bounded degree planar graphs, the Liouville property is quasi-isometry invariant since transience is. An example in [3] shows that Liouville property and almost sure intersection of simple random walks are not quasi-isometry invariants: there exist two graphsG1 andG2 that are quasi-isometric such thatG1 has the intersection property (hence Liouville) whereasG2is non Liouville and two independent simple random walk trajectories started from two different points inG2have a probability strictly in between

0and1 of having an infinite intersection. However it is possible to modify and iterate the construction of [3] in such a way that the last probability is actually0.

Finite Dirichlet energy. A concept related to Liouvilleness is the(Dirichlet) energy of a harmonic function f, defined by P

x∼y|f(x)−f(y)|2 where the sum ranges over all neighborsx, yof the graph. For example, it is known that if a graph admits a non-constant harmonic function of finite energy then it is not Liouville [9], but the converse is in general not true. Russ Lyons asked (private communication) whether the converse becomes true for planar graphs, i.e. whether there is a planar graph which admits non-constant bounded harmonic functions but yet none of finite energy. We construct such a graph here. Start with the integers Z = {0,1,2, ...}, and place 2|n| parallel edges betweennandn+ 1for everyn. Then, join eachntonby a new edge of resistance

n, or equivalently, with a path of lengthnof unit resistance edges. This graph is, easily, still non-Liouville, and the reader will be able to check that it does however admit no non-constant harmonic functions of finite energy, see for example [5, Lemma 3.1.].

References

[1] O. Angel and O. Schramm. Uniform infinite planar triangulation.Comm. Math. Phys., 241(2-3):191–213, 2003. MR-2013797

[2] I. Benjamini and N. Curien. Ergodic theory on stationary random graphs.arXiv:1011.2526. [3] I. Benjamini and O. Schramm. Harmonic functions on planar and almost planar graphs and

manifolds, via circle packings.Invent. Math., 126(3):565–587, 1996. MR-1419007

[4] I. Benjamini and O. Schramm. Lack of sphere packing of graphs via non-linear potential theory, arXiv:0910.3071

[5] A. Georgakopoulos. Lamplighter graphs do not admit harmonic functions of finite energy.

Proc. Am. Math. Soc., 138(9):3057–3061, 2010. MR-2653930

[6] O. Gurel-Gurevich and A. Nachmias. Recurrence of planar graph limits. Annals Math. (to appear).

[7] M. Krikun. Local structure of random quadrangulations.arXiv:0512304.

[8] R. B. Richter and C. Thomassen. 3-connected planar spaces uniquely embed in the sphere.

Trans. Amer. Math. Soc., 354(11):4585–4595, 2002. MR-1926890

[9] P. M. Soardi Potential theory on infinite networks. Springer-Verlag, 1994. MR-1324344

ECP17(2012), paper 42.

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Figure

Figure 1: The three (random) regions R1, R2 and R3.

References

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