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Central limit theorem on CAT\operatorname{\text{CAT}}(0) spaces with contracting isometries

Corentin Le Bars
Abstract

Let GG be a group with a non-elementary action on a proper CAT(0)\operatorname{\text{CAT}}(0) space XX, and let μ\mu be a measure on GG such that the random walk (Zn)n(Z_{n})_{n} generated by μ\mu has finite second moment on XX. Let oo be a basepoint in XX, and assume that there exists a rank one isometry in GG. We prove that in this context, (Zno)n(Z_{n}o)_{n} satisfies a central limit theorem, namely that the random variables 1n(d(Zno,o)nλ)\frac{1}{\sqrt{n}}(d(Z_{n}o,o)-n\lambda) converge in law to a Gaussian distribution NμN_{\mu}, for λ\lambda the (positive) drift of the random walk. The strategy relies on the use of hyperbolic models introduced by H. Petyt, A. Zalloum and D. Spriano in [PSZ22], which are analogues of curve graphs and cubical hyperplanes for the class of CAT\operatorname{\text{CAT}}(0) spaces. As a side result, we prove that the probability that the nth-step ZnZ_{n} acts on XX as a contracting isometry goes to 1 as nn goes to infinity.

1 Introduction

Let GG be a discrete group acting by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μ\mu be a probability measure on GG, which we always assume admissible, meaning that the support of μ\mu generates GG as a semigroup. Consider the sequence ω=(ωi)i\omega=(\omega_{i})_{i}, where the ωis\omega_{i}^{\prime}s are chosen independently according to the measure μ\mu. The random walk (Zn(ω))n(Z_{n}(\omega))_{n} on GG generated by μ\mu is then defined by Zn(ω)=ω1ωnZ_{n}(\omega)=\omega_{1}\dots\omega_{n}. Taking oXo\in X, we want to study the asymptotic behaviour of the random variables (Zn(ω)o)n(Z_{n}(\omega)o)_{n}. To be more precise, we want to study limit laws of the random walk in a natural compactification of XX. Even though these questions may be hard to solve for general metric spaces, the theory is very rich when XX possesses nice linear or hyperbolic-like properties. In the fundamental paper of V. Kaimanovich [Kai00], the convergence of (Zno)o(Z_{n}o)_{o} to a point of the visual boundary is proven for groups acting geometrically on proper hyperbolic spaces and several other classes of actions. More recently this result has been extended by J. Maher and G. Tiozzo in [MT18] for groups acting by isometries on non proper hyperbolic spaces. A major difficulty in the proof of the latter result was that in the non proper setting, the completion of a hyperbolic space by its Gromov boundary might be non compact. The results of Maher and Tiozzo will be fundamental in the sequel because we will deal with hyperbolic spaces without properness assumption. In [KM99, Theorem 2.1], Karlsson and Margulis proved a first general result of convergence of the random walk on CAT\operatorname{\text{CAT}}(0) spaces, under the assumption that the escape rate λ=lim infd(Zno,o)n\lambda=\liminf\frac{d(Z_{n}o,o)}{n} is positive.

In [LB22] we proved that if GG acts on a CAT\operatorname{\text{CAT}}(0) space XX with rank one isometries, then the random walk (Zn(ω))n(Z_{n}(\omega))_{n} almost surely converges to a point of the boundary of the visual compactification X\partial_{\infty}X. A rank one element is an axial isometry whose axes do not bound any flat half plane. We give more details on this notion in Section 2, but a rank one element must be thought of as a contracting isometry with features that typically arise in hyperbolic settings. In this context, we also prove that the escape rate (the drift) is almost surely positive: there exists λ>0\lambda>0 such that almost surely, limnd(Zno,o)n=λ\lim_{n}\frac{d(Z_{n}o,o)}{n}=\lambda. We review these results in Section 4. The present paper can be thought of as a continuation of [LB22], and the goal of this work is to study further limit laws of the random walk (Zno)n(Z_{n}o)_{n}, and more specifically central limit theorems for the random variables (d(Zno,o))n(d(Z_{n}o,o))_{n}.

In the case of a random product of matrices, a classical result of Furstenberg [Fur63] is the following. Take (Mn)(M_{n}) a sequence of matrices in GLn()\text{GL}_{n}(\mathbb{R}), independent and identically distributed according to a probability measure μ\mu whose support generates a noncompact subgroup of GLn()\text{GL}_{n}(\mathbb{R}) that does not preserve any proper linear subspace of n\mathbb{R}^{n}. Assume that μ\mu has finite first moment. Then there exists λ>0\lambda>0 such that for all vn{0}v\in\mathbb{R}^{n}-\{0\},

1nlogMnM1vnλ\frac{1}{n}\log\|M_{n}\dots M_{1}v\|\longrightarrow_{n}\lambda

almost surely. This result can be thought of as an analogue of a law of large numbers on the random walk (MnM1v)n(M_{n}\dots M_{1}v)_{n}. In this context, central limit theorems and other limit laws were proven by Furstenberg-Kesten [FK60], Le Page [LP82] and Guivarc’h-Raugi [GR85]. These state that there exists σμ>0\sigma_{\mu}>0 such that for every vn{0}v\in\mathbb{R}^{n}\setminus\{0\},

logMnM1vnλn𝑛𝒩(0,σμ2),\frac{\log\|M_{n}\dots M_{1}v\|-n\lambda}{\sqrt{n}}\underset{n}{\longrightarrow}\mathcal{N}(0,\sigma_{\mu}^{2}),

where 𝒩(0,σ2)\mathcal{N}(0,\sigma^{2}) is a centred Gaussian law on \mathbb{R}. We recall that the convergence in law means that for any bounded continuous function F:F:\mathbb{R}\rightarrow\mathbb{R}, one has

limnGF(logMnM1vnλn)𝑑μn(g)=F(t)exp(t2/2σ2)2πσ2𝑑t.\lim_{n\rightarrow\infty}\int_{G}F(\frac{\log\|M_{n}\dots M_{1}v\|-n\lambda}{\sqrt{n}})d\mu^{\ast n}(g)=\int_{\mathbb{R}}F(t)\frac{\exp(-t^{2}/2\sigma^{2})}{\sqrt{2\pi\sigma^{2}}}dt.

Those kinds of results were also obtained in negative curvature settings, for example in Gromov-hyperbolic groups [Bjö10]. However, the results stated thus far were proven under rather strong moment conditions. Typically, μ\mu was assumed to have a finite exponential moment, that is, for which there exists α>0\alpha>0 such that Gexp(αd(o,go))𝑑μ(g)<\int_{G}\exp(\alpha d(o,go))d\mu(g)<\infty.

Recently, Benoist and Quint have developed a new approach to this question and have proven central limit theorems in the linear context [BQ16b] and for hyperbolic groups [BQ16a]. They could weaken the moment condition and only assume that the measure μ\mu has finite second moment G(loggv)2𝑑μ(g)<\int_{G}(\log\|gv\|)^{2}d\mu(g)<\infty. Namely, if μ\mu is such a measure on a group GG acting non elementarily on a proper hyperbolic space YY with basepoint oo, then there exists λ>0\lambda>0 such that the random variables 1n(d(Zn(ω)o,o)nλ)\frac{1}{\sqrt{n}}(d(Z_{n}(\omega)o,o)-n\lambda) converge in law to a non-degenerate Gaussian distribution [BQ16a, Theorem 1.1].

Using this approach, C. Horbez proved central limit theorems for mapping class groups of closed connected orientable hyperbolic surfaces and on Out(FN)\operatorname{\text{Out}}(F_{N}) [Hor18]. More recently, T. Fernós, J. Lécureux and F. Mathéus proved that if GG is a group acting non-elementarily on a finite-dimensional CAT\operatorname{\text{CAT}}(0) cube complex, then we also have a central limit theorem for the random variables (d(Zn(ω)o,o))n(d(Z_{n}(\omega)o,o))_{n} [FLM24]. In both cases, the authors only assume a second moment condition.

The main result of this paper is to prove a similar result in the context of a group acting on a general CAT\operatorname{\text{CAT}}(0) space, under the assumption that an element of the group acts as a rank one isometry. We say that the group action GXG\curvearrowright X is non-elementary if there are no fixed points in X¯\overline{X} nor a fixed pair of points in X\partial_{\infty}{X}.

Theorem 1.1.

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite second moment, and assume that GG contains a rank one element. Let oXo\in X be a basepoint of the random walk. Let λ\lambda be the (positive) drift of the random walk. Then the random variables 1n(d(Zno,o)nλ)\frac{1}{\sqrt{n}}(d(Z_{n}o,o)-n\lambda) converge in law to a non-degenerate Gaussian distribution NμN_{\mu}.

Our strategy relies heavily on the approach developed by Benoist and Quint. To summarize, one needs to approximate the random walk by a well-chosen cocycle. Then, they give a general criterium (Theorem 5.3 below) under which this cocycle converges in law to a Gaussian distribution.

To apply this strategy, one needs to obtain good estimates on this cocycle. The general idea of this paper is then the following. In order to get a precise description of the random walk, we use a hyperbolic space that is conveniently attached to the original CAT\operatorname{\text{CAT}}(0) space. As the theory of random walks in hyperbolic spaces is rich, we study the behavior of {Zno}n\{Z_{n}o\}_{n} on this model, and then we lift this information back to the original CAT\operatorname{\text{CAT}}(0) space. This strategy was implemented successfully in [Hor18] and [FLM24]:

  • for Mod(S)\operatorname{\text{Mod}}(S), the hyperbolic model is the curve complex C(S)C(S), and the lifting to 𝒯(S)\mathcal{T}(S) is done in [Hor18, Section 3.4];

  • for a CAT\operatorname{\text{CAT}}(0) cube complex, the hyperbolic model is the contact graph 𝒞X\mathcal{C}X, and the lifting is implemented in [FLM24, section 5].

In [PSZ22], H. Petyt, D. Spriano and A. Zallum introduced analogues of curve graphs and cubical hyperplanes for the class of CAT\operatorname{\text{CAT}}(0) spaces. Using a generalized notion of hyperplane, they build a family of hyperbolic metrics (dL)L(d_{L})_{L} on XX which conserve many of the geometric features of the original CAT\operatorname{\text{CAT}}(0) space. These spaces capture hyperbolic behaviours in XX and behave very well under the isometric action of a group. Moreover, a rank one isometry of XX acts on some hyperbolic model as a loxodromic isometry. Our strategy will be to chose a good hyperbolic model XL=(X,dL)X_{L}=(X,d_{L}), and then to make use of the limit laws proven by Maher and Tiozzo in [MT18], or by Gouëzel in [Gou22]. A key fact is that there is an equivariant homeomorphic embedding of the Gromov boundary GromXL\partial_{\text{Grom}}X_{L} of the hyperbolic model XLX_{L} into the visual boundary of the CAT\operatorname{\text{CAT}}(0) space [PSZ22, Theorem 7.1].

Another interesting question in the study of (Zn(ω))n(Z_{n}(\omega))_{n} is the proportion of steps that are "hyperbolic". In the context of random walks on hyperbolic spaces, Maher and Tiozzo show that the probability that a random walk of size nn is a loxodromic isometry goes to 11 as nn goes to infinity [MT18, Theorem 1.4]. For a non-elementary action on an irreducible CAT\operatorname{\text{CAT}}(0) cube complex, Fernós, Lécureux and Mathéus show that the proportion of steps ZnZ_{n} that are contracting goes to 11 as nn goes to infinity. They use this result to show that if a group GG acts non-elementarily and essentially on a (possibly reducible) finite-dimensional CAT\operatorname{\text{CAT}}(0) cube complex, then there exist regular elements, extending a result of Caprace and Sageev [CS11]. In our context, we also prove that "most" of the steps in the random walk are rank one. This result is not involved in the proof of Theorem 1.1, but is of independent interest.

Theorem 1.2 (Rank one elements in the random walk).

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG, and assume that GG contains a rank one element. Then

(ω:Zn(ω) is a contracting isometry )n1.\displaystyle\mathbb{P}(\omega\,:\,Z_{n}(\omega)\text{ is a contracting isometry })\underset{n\rightarrow\infty}{\rightarrow}1.

Using the curtain models from [PSZ22], such a result is actually straightforward. We emphasize the idea that a systematic approach of dynamics on CAT\operatorname{\text{CAT}}(0) spaces using these hyperbolic models can prove fruitful, especially when quantitative estimates are required. Indeed, curtain models also benefit from their combinatorial structure. In this paper, we exploit this richness in several ways, especially in the main geometric lemma 6.1. In [LB23, Section 5], the author develops these connections in order to study other limit laws on general Hadamard spaces.

A different approach for the study of such limit laws was implemented in [MS20], where the authors prove central limit theorems on acylindrically hyperbolic groups. Their strategy relies on a control of deviation inequalities, which encapsulate the way the random walk progresses in an “almost aligned” way, hence their approach apply to possibly non-proper spaces. While there is a slight overlap with the results stated here (especially [MS20, Theorem 13.4]), Mathieu and Sisto study random walks on acylindrically hyperbolic groups with a word metric. This situation does not immediately apply here. Indeed, in our main theorem, the pull-back metric induced on G by an orbit map need not be quasi-isometric to a word metric, and in fact need not even be proper. Also, their assumptions on the measure μ\mu are much more restrictive: they assume that μ\mu has finite exponential moment. In particular, their assumption is not optimal, while it is the case here. Last, the techniques involved are completely different: their approach has a “local” flavor, whereas here we use boundary theory and compactifications.

While we were working on this project, Inhyeok Choi released a paper in which he states central limit theorems along with other limit laws in CAT\operatorname{\text{CAT}}(0) spaces, Teichmüller spaces and outer spaces [Cho22]. One of the main assumptions is still the presence of a pair of independent contracting isometries in the group, but the methods and the proofs are different. Indeed, Choi uses a pivotal technique introduced by Boulanger, Mathieu and Sisto in [MS20] and [BMSS23] and further developed by Gouëzel in [Gou22]. These techniques have a “local flavor”, while our paper relies on boundary theory, and uses hyperbolic models that depend on specific features of CAT\operatorname{\text{CAT}}(0) spaces. We think this approach is natural from a geometric point of view, and we believe that the interplay between CAT\operatorname{\text{CAT}}(0) spaces and their underlying hyperbolic models will be useful in the study of still open questions about limit laws. In any case, it is always interesting to have different strategies and techniques for studying radom walks and limit laws.

The essential assumption in these results is the presence of contracting elements for the action of GG on the CAT\operatorname{\text{CAT}}(0) space XX. In [LB23, Chapter 5], the author proves that actually, all the results presented here hold in the more general context of a Hadamard space, i.e. a separable and complete CAT\operatorname{\text{CAT}}(0) space, removing the properness assumption on XX. Notice that the boundary of a general Hadamard spaces may be no longer compact, and that the embedding of the boundaries GromXLX\partial_{\text{Grom}}X_{L}\hookrightarrow\partial_{\infty}X is only stated for proper CAT\operatorname{\text{CAT}}(0) spaces in [PSZ22]. In [LB23, Theorem 5.3.5], we prove that this embedding actually holds in this more general setting. Once this is done, the general strategy for proving the central limit theorem 1.1 is similar, although with some additional technical difficulties. We refer to the manuscript [LB23, Chapter 5] for details.

We believe our approach can be of use in order to determine if the boundary X\partial_{\infty}X endowed with the hitting measure is actually the Poisson boundary of (G,μ)(G,\mu), extending a result of Karlsson and Margulis for cocompact actions [KM99, Corollary 6.2].

Moreover, it seems natural to use these hyperbolic spaces to prove that if μ\mu has finite first moment, then limit points of the random walk almost surely belong to the sublinear Morse boundary constructed by Qing and Rafi in [QR22]. Note that this question is linked to the previous one, because it is believed that the sublinear Morse boundary is often a good candidate for the Poisson boundary, especially for finitely supported measures, see for example [QR22, Theorem F] and [QRT20, Theorem B]. In both cases, the use of hyperbolic models seems useful because of precision of estimates that can be derived from the combinatorial structure of these spaces.

In Section 2, we review basic definitions about random walks, rank one isometries and explain our setting. In Section 3, we explicit the construction and properties of the hyperbolic models (X,dL)(X,d_{L}), and give various geometric lemmas that will be useful afterwards. Section 4 is dedicated to presenting the works of Maher and Tiozzo in [MT18] and of Gouëzel in [Gou22], and the first results in proper CAT(0)\operatorname{\text{CAT}}(0) spaces that were found in [LB22]. We explain the strategy developed by Benoist and Quint in Section 5, and give the proof of our main Theorem in Section 6.

Acknowledgement.

This work was done during the trimester "Groups acting on fractals, hyperbolicity and self-similarity", which was held at IHP from April 11th to July 8th, 2022. The author acknowledges support of the Institut Henri Poincaré (UAR 839 CNRS-Sorbonne Université), and LabEx CARMIN (ANR-10-LABX-59-01). We thank Jean Lécureux for his help and commentaries on this paper. The author is also thankful to A. Sisto for drawing our attention on another approach for these questions, and to I. Choi for discussions on this matter. We are very grateful to H. Petyt, D. Spriano and A. Zalloum for allowing us to discuss the details of their construction and for their friendly remarks. We are grateful to the anonymous referee for pointing out some mistakes and giving advice on how to improve the presentation of this paper.

2 Background

2.1 Random walks and CAT\operatorname{\text{CAT}}(0) spaces

Let GG be a discrete countable group and μProb(G)\mu\in\text{Prob}(G) a probability measure on GG. Recall that the support of μ\mu is

supp(μ):={gG|μ(g)>0}.\operatorname{\text{supp}}(\mu):=\{g\in G\,|\,\mu(g)>0\}.
Definition 2.1.

We say that a measure μ\mu on a discrete countable group is admissible if its support supp(μ)\operatorname{\text{supp}}(\mu) generates GG as a semigroup.

Throughout the article we will assume that μ\mu is admissible. Let (Ω,)(\Omega,\mathbb{P}) be the probability space (G,δe×μ)(G^{\mathbb{N}},\delta_{e}\times\mu^{\mathbb{N^{\ast}}}), where δe\delta_{e} is the Dirac measure at ee. The application

(n,ω)×ΩZn(ω)=ω1ω2ωn,(n,\omega)\in\mathbb{N}\times\Omega\mapsto Z_{n}(\omega)=\omega_{1}\omega_{2}\dots\omega_{n},

where ω\omega is chosen according to the law \mathbb{P}, defines the random walk on GG generated by the measure μ\mu.

Let now (X,d)(X,d) be a proper CAT\operatorname{\text{CAT}}(0) metric space, on which GG acts by isometries. If the reader wants a detailed introduction to CAT(0)\operatorname{\text{CAT}}(0) spaces, the main references that we will use are [BH99] and [Bal95]. We recall that the boundary X\partial_{\infty}X of a CAT(0)\operatorname{\text{CAT}}(0) space XX is the set of equivalent classes of rays σ:[0,)X\sigma:[0,\infty)\rightarrow X, where two rays σ1,σ2\sigma_{1},\sigma_{2} are equivalent if they are asymptotic, i.e. if d(σ1(t),σ2(t))d(\sigma_{1}(t),\sigma_{2}(t)) is bounded uniformly in tt.

Given two points on the boundary ξ\xi and η\eta, if there exists a geodesic line σ:X\sigma:\mathbb{R}\rightarrow X such that the geodesic ray σ[0,)\sigma_{[0,\infty)} is in the class of ξ\xi and the geodesic ray t[0,)σ(t)t\in[0,\infty)\mapsto\sigma(-t) is in the class of η\eta, we will say that the points ξ\xi and η\eta are joined by a geodesic line. The reader should be aware that in general, such a geodesic need not exist between any two points of the boundary, as can be seen in 2\mathbb{R}^{2}. A point ξ\xi of the boundary is called a visibility point if, for all ηX{ξ}\eta\in\partial_{\infty}X-\{\xi\}, there exists a geodesic from ξ\xi to η\eta. We will see in the next section a criterion to prove that a given boundary point is a visibility point.

An important feature in CAT\operatorname{\text{CAT}}(0) spaces is the existence of closest-point projections on complete convex subsets. More precisely, given a complete convex subset CC in a CAT\operatorname{\text{CAT}}(0) space, there exists a map πC:XC\pi_{C}:X\rightarrow C such that πC(x)\pi_{C}(x) minimizes the distance d(x,C)d(x,C):

Proposition 2.2 ([BH99, Lemma 2.4]).

The projection πC\pi_{C} onto a convex complete subset in a CAT\operatorname{\text{CAT}}(0) space satisfies the following properties:

  • xX\forall x\in X, πC(x)\pi_{C}(x) is uniquely defined and d(x,πC(x))=d(x,C)=infcCd(x,c)d(x,\pi_{C}(x))=d(x,C)=\inf_{c\in C}d(x,c);

  • if xx^{\prime} belongs to the geodesic segment [x,π(x)][x,\pi(x)], then πC(x)=πC(x)\pi_{C}(x^{\prime})=\pi_{C}(x);

  • πC\pi_{C} is a retraction of XX onto CC that does not increase the distances: for all x,yXx,y\in X, we have d(πC(x),πC(y))d(x,y)d(\pi_{C}(x),\pi_{C}(y))\leq d(x,y).

It is immediate to see that the above properties can be applied to geodesic segments, which are convex and complete with the induced metric. When γ:[a,b]X\gamma:[a,b]\rightarrow X is a geodesic segment, we will write πγ\pi_{\gamma} for the projection onto the image [γ(a),γ(b)]X[\gamma(a),\gamma(b)]\subseteq X.

When XX is a proper space, the space X¯=XX\overline{X}=X\cup\partial X is a compactification of XX, that is, X¯\overline{X} is compact and XX is an open and dense subset of X¯\overline{X}. We recall that the action of GG on XX extends to an action on X\partial_{\infty}X by homeomorphisms.

Another equivalent construction of the boundary can be done using horofunctions. If xnξXx_{n}\rightarrow\xi\in\partial_{\infty}X and xXx\in X, we denote by bξx:Xb_{\xi}^{x}:X\mapsto\mathbb{R} the horofunction given by

bξx(z)=limnd(xn,z)d(xn,x).b_{\xi}^{x}(z)=\lim_{n}d(x_{n},z)-d(x_{n},x).

It is a standard result in CAT\operatorname{\text{CAT}}(0) geometry (see for example [Bal95, Proposition II.2.5]) that this limit exists and that given any basepoint xx, a horofunction characterizes the boundary point ξ\xi. When the context is clear we will often omit the basepoint and just write bξb_{\xi}.

2.2 Rank one elements

Let gGg\in G. We say that gg is a semisimple isometry if its displacement function xXτg(x)=d(x,gx)x\in X\mapsto\tau_{g}(x)=d(x,gx) has a minimum in XX. If this minimum is non-zero, it is a standard result (see for example [Bal95, Proposition II.3.3]) that the set on which this minimum is obtained is of the form C×C\times\mathbb{R}, where CC is a closed convex subset of X. On the set {c}×\{c\}\times\mathbb{R} for cCc\in C, gg acts as a translation, which is why gg is called axial and the subset {c}×\{c\}\times\mathbb{R} is called an axis of gg. A flat half-plane in XX is defined as a euclidean half plane isometrically embedded in XX.

Definition 2.3.

We say that a geodesic in XX is rank one if it does not bound a flat half-plane. If gg is an axial isometry of XX, we say that gg is rank one if no axis of gg bounds a flat half-plane.

If GG acts on XX by isometries and possesses a rank one element gGg\in G for this action, we may say that GG is rank one. However, the theory of CAT\operatorname{\text{CAT}}(0) groups is not as clear as for Gromov hyperbolic groups. For example, there is no good (i.e. invariant under quasi isometry) notion of boundary of a CAT\operatorname{\text{CAT}}(0) group, as shown by Croke and Kleiner in [CK00]. To summarize, it is better to keep in mind that "rank one" is always attached to a given action GXG\curvearrowright X on a CAT\operatorname{\text{CAT}}(0) space.

More information on rank one isometries and geodesics can be found in [Bal95, Section III. 3], and more recently in [CF10] and in [BF09].

Definition 2.4.

We say that the action GXG\curvearrowright X of a rank one group GG on a CAT(0)\operatorname{\text{CAT}}(0) space XX is non-elementary if GG neither fixes a point in X\partial_{\infty}X nor stabilizes a geodesic line in XX.

To justify this definition, we use a result from Caprace and Fujiwara in [CF10]. What follows comes from the aforementioned paper.

Definition 2.5.

Let g1,g2Gg_{1},\,g_{2}\in G be axial isometries of GG, and fix x0Xx_{0}\in X. The elements g1,g2Gg_{1},g_{2}\in G are called independent if the map

×[0,):(m,n)d(g1mx0,g2nx0)\mathbb{Z}\times\mathbb{Z}\rightarrow[0,\infty):(m,n)\mapsto d(g_{1}^{m}x_{0},g_{2}^{n}x_{0}) (1)

is proper.

Remark 2.6.

In particular, the fixed points of two independent axial elements form four distinct points of the visual boundary.

Let us end this section by stating two results about rank one isometries. The first one was proven by P-E. Caprace and K. Fujiwara in [CF10].

Proposition 2.7 ([CF10, Proposition 3.4]).

Let XX be a proper CAT\operatorname{\text{CAT}}(0) space and let G<Isom(X)G<\operatorname{Isom}(X). Assume that GG contains a rank one element. Then exactly one of the following assertions holds:

  1. 1.

    GG either fixes a point in X\partial_{\infty}X or stabilizes a geodesic line. In both cases, it possesses a subgroup of index at most 2 of infinite Abelianization. Furthermore, if XX has a cocompact isometry group, then G¯<Isom(X)\overline{G}<\operatorname{Isom}(X) is amenable.

  2. 2.

    G contains two independent rank one elements. In particular, G¯\overline{G} contains a discrete non-Abelian free subgroup.

As a consequence, the action GXG\curvearrowright X of a rank one group GG on a CAT(0)\operatorname{\text{CAT}}(0) space XX is non-elementary if and only if alternative 2 of the previous Proposition holds.

Rank one isometries are especially interesting because they induce natural contracting properties on the space. These properties mimic how loxodromic isometries behave in the hyperbolic setting.

Definition 2.8.

A geodesic σ\sigma in a CAT\operatorname{\text{CAT}}(0) space is said to be CC-contracting with C>0C>0 if for every metric ball BB disjoint from σ\sigma, the projection πσ(B)\pi_{\sigma}(B) of the ball BB onto σ\sigma has diameter at most CC. An axial isometry is contracting if there exists C>0C>0 such that one of its axes is CC-contracting.

It is clear that a contracting isometry is rank one. It turns out that the converse is true if XX is a proper CAT\operatorname{\text{CAT}}(0) space, as was shown by M. Bestvina and K. Fujiwara in [BF09]. This result will allow us to use the hyperbolic models described in Section 3.

Theorem 2.9 ([BF09, Theorem 5.4]).

Let XX be a proper CAT\operatorname{\text{CAT}}(0) space, g:XXg:X\rightarrow X be an axial isometry and σ\sigma be an axis of gg. Then there exists BB such that σ\sigma is BB-contracting if and only if σ\sigma does not bound a half-flat. In other words, gg is contracting if and only if gg is a rank one isometry.

2.3 Gromov products

Let (X,d)(X,d) be a metric space. One defines the Gromov product of x,yXx,y\in X with respect to oXo\in X as

(x|y)o=12(d(x,o)+d(y,o)d(x,y)).\displaystyle(x|y)_{o}=\frac{1}{2}(d(x,o)+d(y,o)-d(x,y)).

The quantity (x|y)o(x|y)_{o} must be thought of as representing the distance between oo and the geodesic between xx and yy. This notion is particularly interesting because it does not require XX to be actually geodesic, and in fact we often deal with only quasigeodesic spaces. Also, we can use Gromov products to characterize hyperbolic spaces. We recall that a metric space (X,d)(X,d) is hyperbolic if there is δ>0\delta>0 such that for all x,y,zXx,y,z\in X,

(x|z)omin((x|y)o,(y|z)o)δ.\displaystyle(x|z)_{o}\geq\min((x|y)_{o},(y|z)_{o})-\delta.

If the reader wants a detailed introduction to hyperbolic spaces, a standard reference is [BH99].

If (X,d)(X,d) is a proper CAT(0)\operatorname{\text{CAT}}(0) space, the Gromov product can be extended to the visual boundary X\partial_{\infty}X of XX by the following formulas: for x,yXx,y\in\partial_{\infty}X, o,mXo,m\in X,

(m|x)o\displaystyle(m|x)_{o} :=\displaystyle:= 12(d(o,m)bxo(m));\displaystyle\frac{1}{2}(d(o,m)-b^{o}_{x}(m));
(x|y)o\displaystyle(x|y)_{o} :=\displaystyle:= 12infqX(bx(q)+by(q)).\displaystyle-\frac{1}{2}\,\underset{q\in X}{\inf}\,(b_{x}(q)+b_{y}(q)). (2)

Assume that x,yXx,y\in X. A quick computation shows that the infimum of Equation (2) is attained for any q[x,y]q\in[x,y]. Indeed, for any other pXp\in X,

bx(p)+by(p)(bx(q)+by(q))\displaystyle b_{x}(p)+b_{y}(p)-(b_{x}(q)+b_{y}(q)) =\displaystyle= d(x,p)+d(y,p)(d(o,x)+d(o,y))\displaystyle d(x,p)+d(y,p)-(d(o,x)+d(o,y))
(d(x,q)+d(y,q))+(d(o,x)+d(o,y))\displaystyle-(d(x,q)+d(y,q))+(d(o,x)+d(o,y))
=\displaystyle= d(x,p)+d(y,p)d(x,y) because q[x,y]\displaystyle d(x,p)+d(y,p)-d(x,y)\text{ because $q\in[x,y]$}
\displaystyle\geq 0 by the triangular inequality.\displaystyle 0\text{ by the triangular inequality}.

When x,yXx,y\in\partial_{\infty}X, take (xn)(x_{n}) and (yn)(y_{n}) sequences converging to x,yXx,y\in\partial_{\infty}X respectively for the visual topology. Since the visual compactification is equivalent to the compactification by Busemann functions (see for instance [BH99, Theorem II.8.13]), {bxn}\{b_{x_{n}}\} and {byn}\{b_{y_{n}}\} converge to bxb_{x} and byb_{y} respectively (for the topology of uniform converge on bounded sets). In particular, if there exists a geodesic line γ\gamma such that γ(t)tx\gamma(t)\underset{t\to\infty}{\to}x and γ(t)ty\gamma(t)\underset{t\to-\infty}{\to}y, then the previous computation shows that for any point qγq\in\gamma:

(x|y)o\displaystyle(x|y)_{o} =\displaystyle= limn,m12(bγ(n)(q)+bγ(m)(q))\displaystyle\lim_{n,m\to\infty}-\frac{1}{2}\,(b_{\gamma(n)}(q)+b_{\gamma(-m)}(q))
=\displaystyle= limn,m(xn|ym)o.\displaystyle\lim_{n,m\to\infty}(x_{n}|y_{m})_{o}.

3 Hyperbolic models for proper CAT\operatorname{\text{CAT}}(0) spaces

The goal of this section is to briefly present some ideas of [PSZ22], in which the authors build a way of attaching a family of hyperbolic metric spaces XL=(X,dL)LX_{L}=(X,d_{L})_{L} to a proper CAT\operatorname{\text{CAT}}(0) space. What is interesting about these spaces is that they convey much of the geometry of the original space, especially at infinity, and they behave very well under isometric actions. More specifically, rank one isometries will act on some well-chosen spaces as loxodromic isometries. This construction can be understood as the analogue (and generalization) of the curve graphs that exist in the context of CAT\operatorname{\text{CAT}}(0) cube complexes, see [Hag14] and [Gen19].

Definition 3.1.

Let XX be a CAT(0)\operatorname{\text{CAT}}(0) space, and let γ:IX\gamma:I\rightarrow X be a geodesic. Let πγ\pi_{\gamma} be the projection onto the geodesic γ\gamma characterized by Proposition 2.2. Let tIt\in I be such that [t12,t+12][t-\frac{1}{2},t+\frac{1}{2}] belongs to II. Then the curtain dual to γ\gamma at tt is

h=hγ,t=πγ1(γ([t12,t+12])).\displaystyle h=h_{\gamma,t}=\pi^{-1}_{\gamma}(\gamma([t-\frac{1}{2},t+\frac{1}{2}])).

The pole of hγ,th_{\gamma,t} is γ([t12,t+12])\gamma([t-\frac{1}{2},t+\frac{1}{2}]). Borrowing from the vocabulary of hyperplanes, we will call h=πγ1(γ((,t12)I))h^{-}=\pi^{-1}_{\gamma}(\gamma((-\infty,t-\frac{1}{2})\cap I)) and h+=πγ1(γ((t+12,+)I))h^{+}=\pi^{-1}_{\gamma}(\gamma((t+\frac{1}{2},+\infty)\cap I)) the halfspaces determined by hh. Note that {h,h,h+}\{h^{-},h,h^{+}\} is a partition of XX. If AhA\subseteq h^{-} and Bh+B\subseteq h^{+} are subsets of XX, we say that hh separates AA from BB.

We will often denote a curtain by the letter hh, even though one must keep in mind that h=hγ,th=h_{\gamma,t} is characterized by a given geodesic γ:IX\gamma:I\rightarrow X and a point tIt\in I (which defines a unique pole PγP\subseteq\gamma). Sometimes, we may also write h=hγ,Ph=h_{\gamma,P} to emphasize on the pole PP.

Remark 3.2.

By Proposition 2.2, it is immediate that curtains are closed subsets of XX, and that they are thick: if hh is a curtain, then d(h,h+)=1d(h^{-},h^{+})=1.

Curtains can fail to be convex: if x,yhx,y\in h^{-}, it may happen that there exists z[x,y]h+z\in[x,y]\cap h^{+}, see [PSZ22, Remark 3.4]. Nonetheless, we have a weaker notion of convexity that the authors call star convexity:

Proposition 3.3 ([PSZ22, Lemma 2.6]).

Let hh be a curtain dual to γ\gamma and PγP\subseteq\gamma be its pole. For every xhx\in h, then [x,πP(x)]h[x,\pi_{P}(x)]\subseteq h.

Definition 3.4.

A family of curtains {hi}\{h_{i}\} is said to be a chain if hih_{i} separates hi1h_{i-1} from hi+1h_{i+1} for every ii. Chains can be used in order to define a metric on XX by the following: for xyXx\neq y\in X,

d(x,y)=1+max{|c|:c is a chain separating x from y}.\displaystyle d_{\infty}(x,y)=1+\max\{\,|c|\,:\,c\text{ is a chain separating }x\text{ from }y\}.

One can check that this definition gives a metric. If hh is a curtain, we have seen that d(h,h+)=1d(h^{-},h^{+})=1, hence for any x,yXx,y\in X, d(x,y)d(x,y)d_{\infty}(x,y)\leq\lceil d(x,y)\rceil. Conversely, it turns out that dd and dd_{\infty} may differ by at most 1, as shown by the following lemma.

Lemma 3.5 ([PSZ22, Lemma 2.10]).

Let x,yXx,y\in X. Then there is a chain of curtains cc dual to [x,y][x,y] that realizes d(x,y)=1+|c|d_{\infty}(x,y)=1+|c|. and for which 1+|c|=d(x,y)1+|c|=\lceil d(x,y)\rceil.

We are now ready to refine the notion of separation in order to capture only some of the hyperbolic features of the space.

We say that a chain cc of curtains meets a curtain hh if every single curtain hich_{i}\in c intersects hh.

Definition 3.6 (LL-separation).

Let LL\in\mathbb{N}^{\ast}, we say that disjoint curtains are LL-separated if every chain meeting both has cardinality at most LL. A chain of pairwise LL-separated curtains is called an LL-chain.

The following geometric Lemma is a key ingredient for the proof of Theorem 3.10, and will be used several times in the sequel. It means that LL-separation induces good Morse properties. The picture one has to keep in mind is given by Figure 1.

Lemma 3.7 ([PSZ22, Lemma 2.14]).

Suppose that AA, BB are two sets which are separated by an L-chain {h1,h2,h3}\{h_{1},h_{2},h_{3}\} all of whose elements are dual to a geodesic γ=[x1,y1]\gamma=[x_{1},y_{1}] with x1Ax_{1}\in A and y1By_{1}\in B. Then for any x2Ax_{2}\in A, y2By_{2}\in B, if ph2[x2,y2]p\in h_{2}\cap[x_{2},y_{2}], then d(p,πγ(p))2L+1d(p,\pi_{\gamma}(p))\leq 2L+1.

2L+1\leq 2L+1x1x_{1}h2h_{2}h1h_{1}h3h_{3}x2x_{2}y1y_{1}y2y_{2}
Figure 1: Illustration of Lemma 3.7.

The next Lemma states that if there is a LL-chain separating two points xx and yy, we can find a (smaller) LL-chain of curtains separating those, which is dual to the geodesic [x,y][x,y] and whose size can be controlled. It will prove useful later on, especially when we want to use Lemma 3.7.

Lemma 3.8 ([PSZ22, Lemma 2.21]).

Let L,nL,n\in\mathbb{N}, and let {h1,,h(4L+10)n}\{h_{1},\dots,h_{(4L+10)n}\} be an LL-chain separating AA, BXB\subseteq X. Take xAx\in A, yBy\in B. Then AA and BB are separated by an LL-chain of size n+1\geq n+1 dual to [x,y][x,y].

We are now ready to define a family of metrics using LL-separation.

Definition 3.9.

Given distinct points xyXx\neq y\in X, we define

dL(x,y)=1+max{|c|:c is an L-chain separating x from y}.\displaystyle d_{L}(x,y)=1+\max\{|c|\,:\,c\text{ is an }L\text{-chain separating }x\text{ from }y\}.

It turns out that for every LL, dLd_{L} gives a metric on XX [PSZ22, Lemma 2.17]. We will denote by XL=(X,dL)X_{L}=(X,d_{L}) the resulting metric space. With this definition in hand, Petyt, Spriano and Zalloum prove that the metric spaces (X,dL)(X,d_{L}) are hyperbolic.

Theorem 3.10 ([PSZ22, Theorem 3.1]).

For any CAT\operatorname{\text{CAT}}(0) space XX and any integer LL, the space (X,dL)(X,d_{L}) is a quasi-geodesic hyperbolic space with hyperbolicity constants depending only on LL. Moreover, Isom(X)\operatorname{Isom}(X) acts by isometries on (X,dL)(X,d_{L}).

We will then call (X,dL)(X,d_{L}) a hyperbolic model for the CAT\operatorname{\text{CAT}}(0) space XX. Another useful fact about these spaces is that they behave well under isometries with "hyperbolic-like" properties.

Theorem 3.11 ([PSZ22, Theorem 4.9]).

Let gg be a semisimple isometry of XX. The following are equivalent:

  1. 1.

    gg is a contracting isometry of the CAT\operatorname{\text{CAT}}(0) space XX;

  2. 2.

    there exists LL\in\mathbb{N} such that gg acts loxodromically on XLX_{L}.

Another piece of information brought by this construction is the relation between the Gromov boundaries XL\partial X_{L} of the hyperbolic models XL=(X,dL)X_{L}=(X,d_{L}) and the visual boundary of the original CAT\operatorname{\text{CAT}}(0) space (X,d)(X,d).

Definition 3.12.

We say that a geodesic ray γ:[0,)X\gamma:[0,\infty)\rightarrow X crosses a curtain hh if there exists t0[0,)t_{0}\in[0,\infty) such that hh separates γ(0)\gamma(0) from γ([t0,))\gamma([t_{0},\infty)). Alternatively, we may say that hh separates γ(0)\gamma(0) from γ()\gamma(\infty). Similarly, we say that a geodesic line γ:X\gamma:\mathbb{R}\rightarrow X crosses a curtain hh if there exist t1,t2t_{1},t_{2}\in\mathbb{R} such that hh separates γ((,t1])\gamma((-\infty,t_{1}]) from γ([t2,))\gamma([t_{2},\infty)). We say that γ\gamma crosses a chain c={hi}c=\{h_{i}\} if it crosses each individual curtain hih_{i}.

As a consequence of Lemma 3.7 and Lemma 3.8, if two geodesic rays with the same starting point cross an infinite LL-chain cc, then they are asymptotic, and hence equal.

Remark 3.13.

Since curtains are not convex, it is not obvious that any geodesic ray γ\gamma meeting a given curtain hh must cross it (γ\gamma could meet hh infinitely often). However, by [PSZ22, Corollary 3.2] if γ\gamma is a geodesic ray that meets every element of an infinite LL-chain c={hi}ic=\{h_{i}\}_{i\in\mathbb{N}}, then γ\gamma must cross cc: for every ii, there exists ti[0,)t_{i}\in[0,\infty) such that hih_{i} separates γ(0)\gamma(0) from γ([ti,))\gamma([t_{i},\infty)).

Given oXo\in X, we define L\mathcal{B}_{L} as the subspace of X\partial_{\infty}X consisting of all geodesic rays γ:[0,)X\gamma:[0,\infty)\rightarrow X starting from oo and such that there exists an infinite LL-chain crossed by γ\gamma. In the case of the contact graph associated to a CAT\operatorname{\text{CAT}}(0) cube complex XX, we had the existence of an Isom(X)\operatorname{Isom}(X)-equivariant embedding of the boundary of the contact graph into the Roller boundary X\partial_{\mathcal{R}}X. The following result is the analogue in the context of CAT\operatorname{\text{CAT}}(0) spaces.

Theorem 3.14 ([PSZ22, Theorem 7.1]).

Let XX be a proper CAT\operatorname{\text{CAT}}(0) space. Then, for every LL\in\mathbb{N}^{\ast}, the identity map ι:XXL\iota:X\longrightarrow X_{L} induces an Isom(X)\operatorname{Isom}(X)-equivariant homeomorphism L:LXL\partial_{L}:\mathcal{B}_{L}\longrightarrow\partial X_{L}.

Recall that the support of a Borel measure mm on a topological space YY is the smallest closed set CC such that m(YC)=0m(Y\setminus C)=0. In other words ysupp(m)y\in\operatorname{\text{supp}}(m) if and only if for all UU open containing yy, m(U)>0m(U)>0.

Definition 3.15.

We say that the action by isometries of a group GG on a hyperbolic space YY (not assumed to be proper) is non-elementary if there are two loxodromic isometries with disjoint fixed points on the Gromov boundary. A probability measure μ\mu on GG is said to be non-elementary if its support generates a group acting non-elementarily on YY.

In order to use the results concerning random walks in hyperbolic spaces, we must show that the action of a group GG on a proper CAT\operatorname{\text{CAT}}(0) space with rank one isometries induces a non-elementary action on some hyperbolic model (X,dL)(X,d_{L}).

Proposition 3.16.

Let GG be a group acting non-elementarily by isometries on a proper CAT\operatorname{\text{CAT}}(0) space (X,d)(X,d), and assume that GG possesses a rank one element for this action. Then there exists LL\in\mathbb{N} such that GG acts on the hyperbolic space (X,dL)(X,d_{L}) non-elementarily by isometries.

Proof.

The action G(X,d)G\curvearrowright(X,d) is non elementary and contains a rank one element, hence by Theorem 2.7 there exist two independent rank one isometries g,hg,h in GG. By Theorem 2.9, those rank one isometries are BB-contracting for some BB. Now, applying Theorem 3.11, there exists LL\in\mathbb{N} such that gg and hh act on (X,dL)(X,d_{L}) as loxodromic isometries. As gg and hh are independent, their fixed points form four distinct points of the visual boundary X\partial_{\infty}X. Now seen in XL=(X,dL)X_{L}=(X,d_{L}), their fixed points sets must also form four distinct points of XL\partial X_{L} because of the homeomorphism L:LXL\partial_{L}:\mathcal{B}_{L}\longrightarrow\partial X_{L}. This means that the action GXLG\curvearrowright X_{L} is non-elementary. ∎

4 Random walks and hyperbolicity

The results of Section 3 allow us to read some information about the random walk in the hyperbolic models XL=(X,dL)X_{L}=(X,d_{L}), and then translate this information back to the original CAT\operatorname{\text{CAT}}(0) space. As the theory of random walks on hyperbolic spaces is well-studied, one may hope that this process is fruitful.

4.1 Random walks on hyperbolic spaces

In this section, we summarize what is known concerning random walks in hyperbolic spaces. Most of the work for the non-proper case was done by Maher and Tiozzo in [MT18]. The first result is the convergence of the random walk to the Gromov boundary.

Theorem 4.1 ([MT18, Theorem 1.1]).

Let GG be a countable group of isometries of a separable hyperbolic space YY. Let μ\mu be a non-elementary probability distribution on GG, and oYo\in Y a basepoint. Then the random walk (Zn(ω)o)n(Z_{n}(\omega)o)_{n} induced by μ\mu converges to a point z+(ω)Xz^{+}(\omega)\in\partial_{\infty}X, and the resulting hitting measure is the unique μ\mu-stationary measure on X\partial_{\infty}X.

Remark 4.2.

Note that the previous result is stated for separable hyperbolic spaces, while in our case, the hyperbolic models are not separable. However, Gouëzel shows in [Gou22, Theorem 1.3] that this result of convergence remains true for possibly non-separable hyperbolic spaces.

Assume that the measure μ\mu has finite first moment d(go,o)𝑑μ(g)<\int d(go,o)d\mu(g)<\infty. Let us define the drift (or escape rate) of the random walk.

Definition 4.3.

The drift of the random walk (Zno)n(Z_{n}o)_{n} on a metric space (Y,d)(Y,d) is defined as

l(μ):=infnΩd(Zn(ω)o,o)𝑑(ω)=infnGd(go,o)𝑑μn(g)\displaystyle l(\mu):=\inf_{n}\int_{\Omega}d(Z_{n}(\omega)o,o)d\mathbb{P}(\omega)=\inf_{n}\int_{G}d(go,o)d\mu^{\ast n}(g)

if μ\mu has finite first moment, and l(μ):=l(\mu):=\infty otherwise.

If μ\mu has finite first moment, then a classical application of Kingmann subadditive Theorem sows that

l(μ)=limn1nd(Zn(ω)o,o),\displaystyle l(\mu)=\lim_{n}\frac{1}{n}d(Z_{n}(\omega)o,o),

and the above limit is essentially constant and finite.

In the context of a group acting on a hyperbolic space, Gouëzel proves that the drift is almost surely positive with no moment condition. This can be seen as a law of large numbers.

Theorem 4.4 ([Gou22, Theorems 1.1 and 1.2]).

Let GG be a countable group of isometries of a hyperbolic space (Y,dY)(Y,d_{Y}). Let μ\mu be a non-elementary probability distribution on GG, and oYo\in Y a basepoint. Then the drift l(μ):=limn1nd(Zno,o)l(\mu):=\lim_{n}\frac{1}{n}d(Z_{n}o,o) is well-defined, essentially constant and positive (possibly infinite).

Moreover, for every r<l(μ)r<l(\mu), there exists κ>0\kappa>0 such that

(ωΩ:dY(Zn(ω)o,o)rn)<eκn.\displaystyle\mathbb{P}\big{(}\omega\in\Omega\,:\,d_{Y}(Z_{n}(\omega)o,o)\leq rn\big{)}<e^{-\kappa n}. (3)

Another piece of information that can be given about the random walk is the proportion of hyperbolic isometries in the random variables (Zn)n(Z_{n})_{n}. Recall that the translation length of an isometry in a hyperbolic space is defined as |g|:=limn1nd(gno,o)|g|:=\lim_{n}\frac{1}{n}d(g^{n}o,o), which does not depend on the basepoint oo.

Theorem 4.5 ([MT18, Theorem 1.4]).

Let GG be a countable group of isometries of a separable hyperbolic space YY. Let μ\mu be a non-elementary probability distribution on GG, and oYo\in Y is a basepoint. Then the translation length |Zn(ω)||Z_{n}(\omega)| grows almost surely at least linearly in nn: there exists K>0K>0 such that

(ω:|Zn(ω)|Kn)n0.\displaystyle\mathbb{P}(\omega\,:\,|Z_{n}(\omega)|\leq Kn)\underset{n\rightarrow\infty}{\longrightarrow}0.

The above result thus implies that the probability that Zn(ω)Z_{n}(\omega) is not a loxodromic isometry goes to zero as nn goes to infinity.

4.2 First results for random walks in CAT\operatorname{\text{CAT}}(0) spaces

In CAT(0)\operatorname{\text{CAT}}(0) spaces, many of the previous theorems hold if we assume that there are elements in the acting group GG that share "hyperbolic-like" properties. Namely, if XX is a proper CAT\operatorname{\text{CAT}}(0) space, we will assume that GG contains rank one isometries of XX. The first result deals with stationary measures on X¯\overline{X}. Recall that a measure νProb(X¯)\nu\in\text{Prob}(\overline{X}) is called stationary if μν=ν\mu\ast\nu=\nu.

Theorem 4.6 ([LB22, Theorem 1.1]).

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG, and assume that GG contains a rank one element. Then there exists a unique μ\mu-stationary measure νProb(X¯)\nu\in\text{Prob}(\overline{X}).

The convergence of the random walk to the boundary can then be established in this setting. It is the analogue of Theorem 4.1.

Theorem 4.7 ([LB22, Theorem 1.2]).

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG, and assume that GG contains a rank one element. Then for every xXx\in X, and for \mathbb{P}-almost every ωΩ\omega\in\Omega, the random walk (Zn(ω)x)n(Z_{n}(\omega)x)_{n} converges almost surely to a boundary point z+(ω)Xz^{+}(\omega)\in\partial_{\infty}X. Moreover, z+(ω)z^{+}(\omega) is distributed according to the stationary measure ν\nu.

Interestingly, we can prove that the limit points are almost surely rank one, meaning that for almost any pair of limit points ξ,ηX\xi,\eta\in\partial_{\infty}X, there exists a rank one geodesic in XX joining ξ\xi to η\eta ([LB22, Corollary 1.3]). This feature suggests the use of hyperbolic models. First, we establish a result concerning the proportion of rank one elements in the random walk.

Theorem 4.8.

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG, and assume that GG contains a rank one element. Then

(ω:Zn(ω) is a contracting isometry )n1.\displaystyle\mathbb{P}(\omega\,:\,Z_{n}(\omega)\text{ is a contracting isometry })\underset{n\rightarrow\infty}{\rightarrow}1.
Proof.

Because of Proposition 3.16, we can then apply the results of Maher-Tiozzo and Gouëzel. In particular, by Theorem 4.5, the translation length |Zn(ω)|L|Z_{n}(\omega)|_{L} of (Zn(ω))n(Z_{n}(\omega))_{n} grows almost surely at least linearly in nn. Therefore, the probability that Zn(ω)Z_{n}(\omega) is a loxodromic element of XLX_{L} goes to 1 as nn goes to \infty. But thanks to Theorem 3.11, an isometry gg of the CAT\operatorname{\text{CAT}}(0) space XX is contracting if and only if there is an LL such that gg acts as a loxodromic isometry on XLX_{L}. The previous argument now implies that the probability that Zn(ω)Z_{n}(\omega) is a contracting isometry of XX goes to 1 as nn goes to \infty. ∎

Remark 4.9.

There is a slight omission in the proof of Theorem 4.8. Indeed, Theorem 4.5 is stated for geodesic, separable hyperbolic spaces, while hyperbolic models are non-separable and only almost geodesic. However, thanks to Bonk and Schramm [BS00, Theorem 4.1 ], this result extends to non-geodesic hyperbolic spaces. The key thing is that due to Theorem 4.4 we have control of the displacement variables d(Zno,o)d(Z_{n}o,o) up to the escape rate l(μ)l(\mu). A detailed proof of Theorem 4.8 can be found in [LB23, Section 5.3.5].

The analogue of Theorem 4.4 also holds in the context of CAT\operatorname{\text{CAT}}(0) spaces with rank one isometries.

Theorem 4.10 ([LB22, Theorem 1.4]).

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite first moment, and assume that GG contains a rank one element. Let oXo\in X be a basepoint of the random walk. Then the drift λ\lambda is almost surely positive:

limn1nd(Zno,o)=λ>0.\lim_{n\rightarrow\infty}\frac{1}{n}d(Z_{n}o,o)=\lambda>0.

Actually H. Izeki worked on the drift-free case in [Ize23]. The author proves a strengthening of Theorem 4.10, in that it is valid even for finite dimensional, non proper CAT\operatorname{\text{CAT}}(0) spaces, and without the assumption that there are rank one isometries. The counterpart is that one needs to assume that μ\mu has finite second moment. Namely, Izeki proves that in this context, either the drift λ\lambda is strictly positive, or there is a GG-invariant flat subspace in XX [Ize23, Theorem A]. However, for our purpose, we will only need Theorem 4.10.

In the proof of Theorem 4.10, we actually show that the displacement d(Zn(ω)x,x)d(Z_{n}(\omega)x,x) is almost surely well approximated by the Busemann functions bξ(Zn(ω)x)b_{\xi}(Z_{n}(\omega)x). This result will be used later when we give geometric estimates for the action.

Proposition 4.11 ([LB22, Proposition 5.2]).

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite first moment, and assume that GG contains a rank one element. Let xXx\in X be a basepoint. Then for ν\nu-almost every ξX\xi\in\partial X, and \mathbb{P}-almost every ωΩ\omega\in\Omega, there exists C>0C>0 such that for all n0n\geq 0 we have

|bξ(Zn(ω)x)d(Zn(ω)x,x)|<C.|b_{\xi}(Z_{n}(\omega)x)-d(Z_{n}(\omega)x,x)|<C. (4)

5 Central Limit Theorems and general strategy

In order to prove our main result, we use a strategy that is largely inspired by the works of Benoist and Quint on linear spaces and hyperbolic spaces, see [BQ16a] and [BQ16b]. They developed a method for proving central limit theorems for cocycles, relying on results due to Brown in the case of martingales [Bro71].

5.1 Centerable cocycle

Let GG be a discrete group, ZZ a compact GG-space and cc a cocycle c:G×Zc:G\times Z\rightarrow\mathbb{R}, meaning that c(g1g2,x)=c(g1,g2x)+c(g2,x)c(g_{1}g_{2},x)=c(g_{1},g_{2}x)+c(g_{2},x), and assume that cc is continuous. Let μ\mu be a probability measure on GG.

Definition 5.1.

Let cc be a continuous cocycle c:G×Zc:G\times Z\rightarrow\mathbb{R}. We say that cc has constant drift cμc_{\mu} if cμ=Gc(g,x)𝑑μ(g)c_{\mu}=\int_{G}c(g,x)d\mu(g) does not depend on xZx\in Z. We say that cc is centerable if there exists a bounded measurable map ψ:Z\psi:Z\rightarrow\mathbb{R} and a cocycle c0:G×Zc_{0}:G\times Z\rightarrow\mathbb{R} with constant drift c0,μ=Gc0(g,x)𝑑μ(g)c_{0,\mu}=\int_{G}c_{0}(g,x)d\mu(g) such that

c(g,x)=c0(g,x)+ψ(x)ψ(gx).\displaystyle c(g,x)=c_{0}(g,x)+\psi(x)-\psi(gx). (5)

We say that cc and c0c_{0} are cohomologous. In this case, the average of cc is defined to be c0,μc_{0,\mu}.

Remark 5.2.

Let νProb(Z)\nu\in\text{Prob}(Z) be a μ\mu-stationary measure, and let c:G×Zc:G\times Z\rightarrow\mathbb{R} be a centerable continuous cocycle: for gG,xZg\in G,x\in Z, c(g,x)=c0(g,x)+ψ(x)ψ(gx)c(g,x)=c_{0}(g,x)+\psi(x)-\psi(gx) with c0c_{0} having constant drift and ψ\psi bounded measurable. The following computation shows that the average of cc does not depend on the particular choices of c0c_{0} and ψ\psi. Indeed:

G×Zc(g,x)𝑑μ(g)𝑑ν(x)\displaystyle\int_{G\times Z}c(g,x)d\mu(g)d\nu(x) =\displaystyle= G×Zc0(g,x)𝑑μ(g)𝑑ν(x)+Zψ(x)𝑑ν(x)\displaystyle\int_{G\times Z}c_{0}(g,x)d\mu(g)d\nu(x)+\int_{Z}\psi(x)d\nu(x)
G×Zψ(gx)𝑑μ(g)𝑑ν(x)\displaystyle-\int_{G\times Z}\psi(gx)d\mu(g)d\nu(x)
=\displaystyle= Gc0(g,x)𝑑μ(g)+Zψ(x)𝑑ν(x)G×Zψ(gx)𝑑μ(g)𝑑ν(x)\displaystyle\int_{G}c_{0}(g,x)d\mu(g)+\int_{Z}\psi(x)d\nu(x)-\int_{G\times Z}\psi(gx)d\mu(g)d\nu(x)
=\displaystyle= Gc0(g,x)𝑑μ(g)+Zψ(x)𝑑ν(x)\displaystyle\int_{G}c_{0}(g,x)d\mu(g)+\int_{Z}\psi(x)d\nu(x)
Zψ(x)𝑑ν(x) because ν is μ-stationary\displaystyle-\int_{Z}\psi(x)d\nu(x)\text{ because $\nu$ is $\mu$-stationary}
=\displaystyle= c0,μ because c0 has constant drift.\displaystyle c_{0,\mu}\text{ because $c_{0}$ has constant drift}.

Hence the average of cc is given by c(g,x)𝑑μ(g)𝑑ν(x)\int c(g,x)d\mu(g)d\nu(x), which explains the terminology. Moreover, the average of cc does not depend on the choices of c0c_{0} and ψ\psi.

The reason why we study limit laws on cocycles is the following result. This version is borrowed from Benoist and Quint, who improved previous results from Brown about central limit theorems for martingales [Bro71].

Theorem 5.3 ([BQ16b, Theorem 3.4]).

Let GG be a locally compact group acting by homeomorphisms on a compact metrizable space ZZ. Let c:G×Zc:G\times Z\rightarrow\mathbb{R} be a continuous cocycle such that GsupxZ|c(g,x)|2dμ(g)<\int_{G}\sup_{x\in Z}|c(g,x)|^{2}d\mu(g)<\infty. Let μ\mu be a Borel probability measure on GG. Assume that cc is centerable with average λc\lambda_{c} and that there exists a unique μ\mu-stationary probability measure ν\nu on ZZ.

Then the random variables 1n(c(Zn,x)nλc)\frac{1}{\sqrt{n}}(c(Z_{n},x)-n\lambda_{c}) converge in law to a Gaussian law NμN_{\mu}. In other words, for any bounded continuous function FF on \mathbb{R}, one has

GF(c(g,x)nλcn)d(μn)(g)F(t)𝑑Nμ(t).\displaystyle\int_{G}F\big{(}\frac{c(g,x)-n\lambda_{c}}{\sqrt{n}}\big{)}d(\mu^{\ast n})(g)\longrightarrow\int_{\mathbb{R}}F(t)dN_{\mu}(t).

Moreover, if we write c(g,z)=c0(g,z)+ψ(z)ψ(gz)c(g,z)=c_{0}(g,z)+\psi(z)-\psi(gz) with ψ\psi bounded and c0c_{0} with constant drift cμc_{\mu}, then the covariance 2-tensor of the limit law is

G×Z(c0(g,z)cμ)2𝑑μ(g)𝑑ν(z).\displaystyle\int_{G\times Z}(c_{0}(g,z)-c_{\mu})^{2}d\mu(g)d\nu(z).

5.2 Busemann cocycle and strategy

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite first moment, and assume that GG contains a rank one element. Let oXo\in X be a basepoint of the random walk. Theorems 4.7 and 4.10 ensure that the random walk (Zn(ω)o)n(Z_{n}(\omega)o)_{n} converges to a point of the boundary and that the drift λ=limn1nd(Zn(ω)o,o)\lambda=\lim_{n}\frac{1}{n}d(Z_{n}(\omega)o,o) is well-defined and almost surely positive.

We denote by μˇ\check{\mu} the probability measure on GG defined by μˇ(g)=μ(g1)\check{\mu}(g)=\mu(g^{-1}). Let (Zˇn)n(\check{Z}_{n})_{n} be the right random walk associated to μˇ\check{\mu}. Since μ\mu is admissible and has finite first moment, so does μˇ\check{\mu}. We can then apply Theorems 4.6, 4.7 and 4.10 to μˇ\check{\mu}. We will denote by νˇ\check{\nu} the unique μˇ\check{\mu}-stationary measure on X¯\overline{X}, and by λˇ\check{\lambda} the positive drift of the random walk (Zˇno)n(\check{Z}_{n}o)_{n}.

Remark 5.4.

One can check that

λˇ\displaystyle\check{\lambda} =\displaystyle= infn1nd(go,o)𝑑μˇn(g)\displaystyle\inf_{n}\frac{1}{n}\int d(go,o)d\check{\mu}^{\ast n}(g)
=\displaystyle= infn1nd(o,g1o)𝑑μˇn(g)\displaystyle\inf_{n}\frac{1}{n}\int d(o,g^{-1}o)d\check{\mu}^{\ast n}(g)
=\displaystyle= infn1nd(o,go)𝑑μn(g),\displaystyle\inf_{n}\frac{1}{n}\int d(o,go)d\mu^{\ast n}(g),

hence λ=λˇ\lambda=\check{\lambda}.

In our context, the continuous cocycle that we consider is the Busemann cocycle on the visual compactification of the CAT\operatorname{\text{CAT}}(0) space XX: for xX¯,gGx\in\overline{X},\ g\in G and oXo\in X a basepoint,

β(g,x)=bx(g1o).\beta(g,x)=b_{x}(g^{-1}o).

It is straightforward to show that β\beta is continuous. Observe that for all g1,g2G,xYg_{1},g_{2}\in G,\,x\in Y, horofunctions satisfy a cocycle relation:

bξ(g1g2o)\displaystyle b_{\xi}(g_{1}g_{2}o) =\displaystyle= limxnξd(g1g2,xn)d(xn,x)\displaystyle\lim_{x_{n}\rightarrow\xi}d(g_{1}g_{2},x_{n})-d(x_{n},x) (6)
=\displaystyle= limxnξd(g2,g11xn)d(g1o,xn)+d(g1o,xn)d(xn,o)\displaystyle\lim_{x_{n}\rightarrow\xi}d(g_{2},g_{1}^{-1}x_{n})-d(g_{1}o,x_{n})+d(g_{1}o,x_{n})-d(x_{n},o)
=\displaystyle= limxnξd(g2x,g11xn)d(o,g11xn)+d(g1x,xn)d(xn,o)\displaystyle\lim_{x_{n}\rightarrow\xi}d(g_{2}x,g_{1}^{-1}x_{n})-d(o,g_{1}^{-1}x_{n})+d(g_{1}x,x_{n})-d(x_{n},o)
=\displaystyle= bg11ξ(g2o)+bξ(g1o).\displaystyle b_{g_{1}^{-1}\xi}(g_{2}o)+b_{\xi}(g_{1}o).

By (6), β\beta satisfies the cocycle relation β(g1g2,x)=β(g1,g2x)+β(g2,x)\beta(g_{1}g_{2},x)=\beta(g_{1},g_{2}x)+\beta(g_{2},x). Thanks to Proposition 4.11, for every oXo\in X, for ν\nu-almost every xXx\in\partial X, and \mathbb{P}-almost every ωΩ\omega\in\Omega, there exists C>0C>0 such that for all n0n\geq 0 we have

|β(Zn(ω)1,x)d(Zn(ω)o,o)|<C.|\beta(Z_{n}(\omega)^{-1},x)-d(Z_{n}(\omega)o,o)|<C. (7)

Equation (7) shows that the cocycle β(Zn(ω),x)\beta(Z_{n}(\omega),x) "behaves" like d(Zn(ω)o,o)d(Z_{n}(\omega)o,o). Thus it makes sense to try and apply Theorem 5.3 to the Busemann cocycle β(g,x)\beta(g,x).

Henceforth, we will assume that μ\mu is an admissible probability measure on GG with finite second moment Gd(go,o)2𝑑μ(g)<\int_{G}d(go,o)^{2}d\mu(g)<\infty.

The following proposition summarizes some properties of the Busemann cocycle. It shows that obtaining a central limit theorem on β\beta will imply our main result.

Proposition 5.5.

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite second moment, and assume that GG contains a rank one element. Let oXo\in X be a basepoint of the random walk. Let λ\lambda be the (positive) drift of the random walk, and β:G×X¯\beta:G\times\overline{X}\rightarrow\mathbb{R} be the Busemann cocycle β(g,x)=bx(g1o)\beta(g,x)=b_{x}(g^{-1}o). Then

  1. 1.

    GsupxX¯|β(g,x)|2dμ(g)<\int_{G}\sup_{x\in\overline{X}}|\beta(g,x)|^{2}d\mu(g)<\infty and GsupxX¯|β(g,x)|2dμˇ(g)<\int_{G}\sup_{x\in\overline{X}}|\beta(g,x)|^{2}d\check{\mu}(g)<\infty;

  2. 2.

    For ν\nu-almost every ξX\xi\in\partial_{\infty}X, λ=limn1nβ(Zn(ω),ξ)\lambda=\lim_{n}\frac{1}{n}\beta(Z_{n}(\omega),\xi) \mathbb{P}-almost surely;

  3. 3.

    \mathbb{P}-almost surely, λ=G×X¯β(g,x)𝑑μ(g)𝑑ν(x)=G×X¯β(g,x)𝑑μˇ(g)𝑑νˇ(x)\lambda=\int_{G\times\overline{X}}\beta(g,x)d\mu(g)d\nu(x)=\int_{G\times\overline{X}}\beta(g,x)d\check{\mu}(g)d\check{\nu}(x).

Proof.

As a consequence of Proposition 4.11, equation (7) gives that for ν\nu-almost every xXx\in\partial X, and \mathbb{P}-almost every ωΩ\omega\in\Omega, there exists C>0C>0 such that for all n0n\geq 0 we have

|β(Zn(ω)1,x)d(Zn(ω)o,o)|<C.\displaystyle|\beta(Z_{n}(\omega)^{-1},x)-d(Z_{n}(\omega)o,o)|<C. (8)

Because the action is isometric and μ\mu has finite second moment Gd(go,o)2𝑑μ(g)<\int_{G}d(go,o)^{2}d\mu(g)\leavevmode\nobreak\ <\leavevmode\nobreak\ \infty, we obtain

GsupxX¯|β(g,x)|2dμ(g)<.\displaystyle\int_{G}\sup_{x\in\overline{X}}|\beta(g,x)|^{2}d\mu(g)<\infty.

With the same argument:

GsupxX¯|β(g,x)|2dμˇ(g)<.\displaystyle\int_{G}\sup_{x\in\overline{X}}|\beta(g,x)|^{2}d\check{\mu}(g)<\infty.

Now thanks to Theorem 4.10, the variables {1nd(Zn(ω)o,o)}\{\frac{1}{n}d(Z_{n}(\omega)o,o)\} converge almost surely to λ>0\lambda>0. Since the action is isometric, we immediately get that

1nd(Zn(ω)o,o)nλ\frac{1}{n}d(Z_{n}(\omega)o,o)\leavevmode\nobreak\ \to_{n}\leavevmode\nobreak\ \lambda

almost surely. Again, because the action is isometric, Equation (8) tells that for ν\nu-almost every xXx\in\partial X, and \mathbb{P}-almost every ωΩ\omega\in\Omega, there exists C>0C>0 such that for all n0n\geq 0 we have

|β(Zn(ω),x)d(Zn(ω)1o,o)|<C.\displaystyle|\beta(Z_{n}(\omega),x)-d(Z_{n}(\omega)^{-1}o,o)|<C.

Combining these results, we obtain that for ν\nu-almost every ξX¯\xi\in\overline{X}, and \mathbb{P}-almost every ωΩ\omega\in\Omega,

λ=limn1nβ(Zn(ω),ξ).\displaystyle\lambda=\lim_{n}\frac{1}{n}\beta(Z_{n}(\omega),\xi).

The ideas in the proof of 3 are classical. We give the details for the convenience of the reader.

Let T:(Ω×X¯,×νˇ)(Ω×X¯,×νˇ)T:(\Omega\times\overline{X},\mathbb{P}\times\check{\nu})\rightarrow(\Omega\times\overline{X},\mathbb{P}\times\check{\nu}) be defined by T(ω,ξ)(Sω,ω01ξ)T(\omega,\xi)\mapsto(S\omega,\omega_{0}^{-1}\xi), with S((ωi)i)=(ωi+1)iS((\omega_{i})_{i\in\mathbb{N}})=(\omega_{i+1})_{i\in\mathbb{N}} the usual shift on Ω\Omega. By [LB22, Proposition 5.4], TT preserves the measure ×νˇ\mathbb{P}\times\check{\nu} and is an ergodic transformation. Define H:Ω×X¯H:\Omega\times\overline{X}\rightarrow\mathbb{R} by

H(ω,ξ)=hξ(ω0o)=β(ω01,ξ).H(\omega,\xi)=h_{\xi}(\omega_{0}o)=\beta(\omega_{0}^{-1},\xi).

By 1, it is clear that |H(ω,ξ)|𝑑(ω)𝑑νˇ(ξ)<\int|H(\omega,\xi)|d\mathbb{P}(\omega)d\check{\nu}(\xi)<\infty.

By cocycle relation (6) one gets that

bξ(Zno)=k=1nhZk1ξ(ωko)=k=1nH(Tk(ω,ξ)).\displaystyle b_{\xi}(Z_{n}o)=\sum_{k=1}^{n}h_{Z_{k}^{-1}\xi}(\omega_{k}o)=\sum_{k=1}^{n}H(T^{k}(\omega,\xi)). (9)

Then β(Zn(ω)1,ξ)=k=1nH(Tk(ω,ξ))\beta(Z_{n}(\omega)^{-1},\xi)=\sum_{k=1}^{n}H(T^{k}(\omega,\xi)), and by 2,

λ=limn1nk=1nH(Tk(ω,ξ)).\displaystyle\lambda=\lim_{n}\frac{1}{n}\sum_{k=1}^{n}H(T^{k}(\omega,\xi)). (10)

Now, by Birkhoff ergodic theorem, one obtains that almost surely,

λ\displaystyle\lambda =\displaystyle= Ω×X¯H(ω,ξ)𝑑(ω)𝑑νˇ(x).\displaystyle\int_{\Omega\times\overline{X}}H(\omega,\xi)d\mathbb{P}(\omega)d\check{\nu}(x). (11)
=\displaystyle= Ω×X¯hξ(ω0o)𝑑(ω)𝑑νˇ(x)\displaystyle\int_{\Omega\times\overline{X}}h_{\xi}(\omega_{0}o)d\mathbb{P}(\omega)d\check{\nu}(x)
=\displaystyle= G×X¯β(g1,ξ)𝑑μ(g)𝑑νˇ(x)\displaystyle\int_{G\times\overline{X}}\beta(g^{-1},\xi)d\mu(g)d\check{\nu}(x)
=\displaystyle= G×X¯β(g,ξ)𝑑μˇ(g)𝑑νˇ(x)\displaystyle\int_{G\times\overline{X}}\beta(g,\xi)d\check{\mu}(g)d\check{\nu}(x)

The previous computations can be done similarly for μ\mu and ν\nu, hence we also have that

λ=G×X¯β(g,x)𝑑μ(g)𝑑ν(x).\displaystyle\lambda=\int_{G\times\overline{X}}\beta(g,x)d\mu(g)d\nu(x).

In order to apply Theorem 5.3 on the Busemann cocycle β\beta, it remains to show that β\beta is centerable. If this is the case, by 3 and Remark 5.2, its average must be the positive drift λ\lambda. In other words, we need to show that there exists a bounded measurable function ψ:X¯\psi:\overline{X}\rightarrow\mathbb{R} such that the cocycle

β0(g,x)=β(g,x)ψ(x)+ψ(gx)\displaystyle\beta_{0}(g,x)=\beta_{(}g,x)-\psi(x)+\psi(gx)

has constant drift, so that the cohomological equation

β(g,x)=β0(g,x)+ψ(x)ψ(gx).\displaystyle\beta(g,x)=\beta_{0}(g,x)+\psi(x)-\psi(gx). (12)

is verified. Then, proving the Central Limit Theorem in our context amounts to finding such a ψ\psi that is well defined and bounded. This will be done by using a hyperbolic model that can give nice estimates on the random walk.

6 Proof of the Central Limit Theorem

6.1 Geometric estimates

In this section, we prove our main Theorem, following the strategy explained in Section 5. First, we will provide geometric estimates on the random walk that will be used later on. This is where we use the specific contraction properties provided by the curtains and the hyperbolic models discussed in Section 3. The goal is ultimately to prove that the candidate ψ\psi for the cohomological equation is bounded.

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX, and assume that GG contains a rank one element. Let oXo\in X be a basepoint of the random walk. Recall that BLB_{L} is defined to be the subspace of X\partial_{\infty}X consisting of all geodesic rays γ:[0,)X\gamma:[0,\infty)\rightarrow X starting from oo and such that there exists an infinite LL-chain crossed by γ\gamma. By Theorem 3.14, there exists an Isom(X)\operatorname{Isom}(X)-equivariant embedding :XLX\mathcal{I}:\partial X_{L}\rightarrow\partial_{\infty}X, whose image lies in L\mathcal{B}_{L}.

Proposition 6.1.

Let (gn)(g_{n}) be a sequence of isometries of GG, and let oXo\in X, x,yXx,y\in\partial_{\infty}X. Assume that there exists λ,ε,A>0\lambda,\varepsilon,A>0 such that:

  1. (i)

    {gno}n\{g_{n}o\}_{n} converges in (XL¯,dL)(\overline{X_{L}},d_{L}) to a point of the boundary zLXLz_{L}\in\partial X_{L}, whose image in X\partial_{\infty}X by the embedding \mathcal{I} is not yy;

  2. (ii)

    dL(gno,o)And_{L}(g_{n}o,o)\geq An;

  3. (iii)

    |bx(gn1o)nλ|εn|b_{x}(g_{n}^{-1}o)-n\lambda|\leq\varepsilon n;

  4. (iv)

    |by(gno)nλ|εn|b_{y}(g_{n}o)-n\lambda|\leq\varepsilon n;

  5. (v)

    |d(gno,o)nλ|εn|d(g_{n}o,o)-n\lambda|\leq\varepsilon n.

Then, one obtains:

  1. 1.

    (gnx|gno)o(λε)n(g_{n}x|g_{n}o)_{o}\geq(\lambda-\varepsilon)n;

  2. 2.

    (y|gno)oεn(y|g_{n}o)_{o}\leq\varepsilon n.

If moreover A2(4L+10)εA\geq 2(4L+10)\varepsilon, then we have:

  1. 3.

    (y|gnx)oεn+(2L+1)(y|g_{n}x)_{o}\leq\varepsilon n+(2L+1).

Before getting into the proof of this proposition, let us give an idea of what it represents. Assumptions (i) and (ii) express that the sequence {gno}n\{g_{n}o\}_{n} converge to the visual boundary following a “contracting direction”, with control on the size of the LL-chain that separates oo from gnog_{n}o. Assumptions (iii), (iv) are to be seen as "the distance between yy and gnog_{n}o grows linearly" and "the distance between xx and gn1og_{n}^{-1}o grows linearly" (even though xx and yy are boundary points). Assumption (v) simply means that the average escape rate of {gno}\{g_{n}o\} is close to λ\lambda. Proposition 6.1 states that in these circumstances, we can control the quantities (gnx|gno)o(g_{n}x|g_{n}o)_{o}, (y|gno)o(y|g_{n}o)_{o} and (y|gnx)o(y|g_{n}x)_{o}, represented by the size of the dashed segments E1E_{1}, E2E_{2} and E3E_{3} respectively in Figure 2. In Proposition 6.4, we shall need in particular the geometric estimate 3 in order to prove that the candidate ψ\psi for the cohomological equation (12) is bounded, see the parallel with Proposition 6.5 below.

ooyyE3E_{3}E2E_{2}E1E_{1}gnog_{n}ozzgnxg_{n}xAn\geq An
Figure 2: A geometric interpretation of Lemma 6.1

The proof of points 1 and 2 is straightforward, so we begin by these.

Proof of estimates 1 and 2.

A simple computation gives that

(gnx|gno)o=12(bx(gn1o)+d(gno,o))\displaystyle(g_{n}x|g_{n}o)_{o}=\frac{1}{2}(b_{x}(g^{-1}_{n}o)+d(g_{n}o,o))

Then using assumptions (iii) and (v) gives immediately that (gnx|gno)o(λϵ)n(g_{n}x|g_{n}o)_{o}\geq(\lambda-\epsilon)n, which proves 1.

Now, by definition,

(y|gno)o=12(d(gno,o)by(gno))\displaystyle(y|g_{n}o)_{o}=\frac{1}{2}(d(g_{n}o,o)-b_{y}(g_{n}o))

Then by assumptions (iv) and (v), we obtain 2. ∎

The proof of point 3 is the hard part. We prove it in two steps. First, we show that under the assumptions, for nn large enough, there exist at least three LL-separated curtains dual to [o,gno][o,g_{n}o] separating {gno,gnx}\{g_{n}o,g_{n}x\} on the one side and {o,y}\{o,y\} on the other, see Figure 3. Then we show that the presence of these curtains implies the result.

ooyygnog_{n}ognxg_{n}x
Figure 3: A "hyperbolic-like" 4 points inequality in Proposition 6.1.

By assumption (ii), for every nn0n\geq n_{0}, dL(gno,o)And_{L}(g_{n}o,o)\geq An. For nn0n\geq n_{0}, pick such a LL-chain separating oo and gnog_{n}o of size An\geq An and define S(n)S(n)\in\mathbb{N} as the size of this chain. By Proposition 3.8, there exists an LL-chain dual to [o,gno][o,g_{n}o] of size greater than or equal to S(n)4L+1\lfloor\frac{S(n)}{4L+1}\rfloor that separates oo and gnog_{n}o. Denote by cn={hin}i=1S(n)c_{n}=\{h^{n}_{i}\}_{i=1}^{S^{\prime}(n)} a maximal LL-chain dual to [o,gno][o,g_{n}o], separating oo and gnog_{n}o, and orient the half-spaces so that ohio\in h_{i}^{-} for all ii. When the context is clear, we might omit the dependence in nn for ease of notations, and just write {hi}i=1S(n)\{h_{i}\}_{i=1}^{S^{\prime}(n)} for a maximal LL-chain dual to [o,gno][o,g_{n}o]. Recall that S(n)AnS(n)\geq An, hence cnc_{n} must be of length S(n)AnS^{\prime}(n)\geq A^{\prime}n, where A=A4L+1A^{\prime}=\frac{A}{4L+1}.

Lemma 6.2.

Under the assumptions of Proposition 6.1, there exists a constant CC such that for all nn\in\mathbb{N}, the number of LL-separated hyperplanes in cnc_{n} that do not separate {o,y}\{o,y\} and {gno}\{g_{n}o\} is less than CC.

Proof of Lemma 6.2.

By assumption, {gno}n\{g_{n}o\}_{n} converges in (XL¯,dL)(\overline{X_{L}},d_{L}) to a point of the boundary zLXLz_{L}\in\partial X_{L}. By Theorem 3.14, there exists an Isom(X)\operatorname{Isom}(X)-equivariant embedding :XLX\mathcal{I}:\partial X_{L}\rightarrow\partial_{\infty}X that extends the canonical inclusion XLXX_{L}\rightarrow X, and whose image lies in L\mathcal{B}_{L}. Denote by z:=(zL)z:=\mathcal{I}(z_{L}) the image in X\partial_{\infty}X of the limit point zLz_{L} by this embedding.

Denote by β:[0,)X\beta:[0,\infty)\rightarrow X a geodesic ray joining oo to zz. Since zLz\in\mathcal{B}_{L}, there exists an infinite LL-chain c={ki}ic=\{k_{i}\}_{i\in\mathbb{N}} that separates oo from zz. Note that because of Lemma 3.8 and Remark 3.13, we can assume that cc is a chain of curtains which is dual to the geodesic ray β\beta. Since {gno}n\{g_{n}o\}_{n} converges in (XL¯,dL)(\overline{X_{L}},d_{L}) to zLXLz_{L}\in\partial X_{L}, and zz is the image of zLz_{L} by the equivariant embedding \mathcal{I}, it implies that {gno}n\{g_{n}o\}_{n} converges to zz in XX. The fact that zLz\in\mathcal{B}_{L} implies that for all ii\in\mathbb{N}, there exists n0n_{0}\in\mathbb{N} such that for all nn0n\geq n_{0}, kik_{i} separates oo from gnog_{n}o. Now, we denote by γ:[0,)X\gamma:[0,\infty)\rightarrow X the geodesic ray that represents yXy\in\partial_{\infty}X. See figure 4.

ooγ\gammazzyykpk_{p}kp+1k_{p+1}rrkp+2k_{p+2}gnog_{n}oβ\betarr^{\prime}
Figure 4: Illustration of Lemma 6.2.

Due to Remark 3.13, meeting cc infinitely often is equivalent to crossing it, then since yzy\neq z, there exists pp\in\mathbb{N} such that γkp\gamma\subseteq k_{p}^{-}. Now consider n0n_{0} such that for nn0n\geq n_{0}, gnokp+2+g_{n}o\in k_{p+2}^{+}. Fix nn0n\geq n_{0}. Recall that cnc_{n} is a maximal LL-chain dual to [o,gno][o,g_{n}o] separating oo and gnog_{n}o.

Denote by rβr\in\beta a point in the pole of kp+1k_{p+1}, and denote by r=r(n)r^{\prime}=r^{\prime}(n) the projection of rr onto the geodesic [o,gno][o,g_{n}o]. Then by Lemma 3.7,

d(o,r(n))d(o,r)+2L+1.d(o,r^{\prime}(n))\leq d(o,r)+2L+1.

Due to the thickness of the curtains (Remark 3.2), the number of curtains in cnc_{n} that separate oo and r(n)r^{\prime}(n) is d(o,r)+2L+2\leq d(o,r)+2L+2. We emphasize that this number does not depend on nn0n\geq n_{0}, because for all nn0n\geq n_{0}, gnkp+2+g_{n}\in k_{p+2}^{+} and the previous equation holds.

Recall that γkp\gamma\subseteq k_{p}^{-}, so in particular γkp+1\gamma\subseteq k_{p+1}^{-}. Then by star convexity of the curtains (Lemma 3.3), every curtain in cnc_{n} whose pole belongs to [r(n),gno][r^{\prime}(n),g_{n}o] separates {o,y}\{o,y\} from gnog_{n}o. Then by the previous argument, the number of curtains that do not separate {o,y}\{o,y\} from {gno}\{g_{n}o\} is less than d(o,r(n))d(o,r^{\prime}(n)). In particular, the number of curtains that do not separate {o,y}\{o,y\} from {gno}\{g_{n}o\} is less than d(o,r)+2L+2d(o,r)+2L+2. Since this quantity does not depend on nn, we have proven the Lemma. ∎

Now, for a fixed nn, let us give an estimate for the number of curtains in cn={h1n,,hS(n)n}c_{n}=\{h^{n}_{1},\dots,h^{n}_{S^{\prime}(n)}\} that separate oo and gnxg_{n}x. When a given nn is fixed, we omit the dependence in nn and just write cn={h1,,hS(n)}c_{n}=\{h_{1},\dots,h_{S^{\prime}(n)}\} to ease the notations. Let γn:[0,)X\gamma_{n}:[0,\infty)\rightarrow X be the geodesic ray joining oo and gnxg_{n}x. Let us take k0=k0(n)k_{0}=k_{0}(n) (depending on nn) large enough so that for all kk0k\geq k_{0},

|(gno|gnx)o(gno|γn(k))o|1.|(g_{n}o|g_{n}x)_{o}-(g_{n}o|\gamma_{n}(k))_{o}|\leq 1.
Lemma 6.3.

Under the assumptions of Proposition 6.1, the number of LL-separated hyperplanes in cnc_{n} that separate {o}\{o\} and {gno,γn(k0)}\{g_{n}o,\gamma_{n}(k_{0})\} is unbounded in nn. More precisely, for all MM\in\mathbb{N}, there exists n0n_{0} such that for all nn0n\geq n_{0}, the number of LL-separated hyperplanes in cnc_{n} that separate {o}\{o\} and {gno,γn(k)}\{g_{n}o,\gamma_{n}(k)\} is greater than MM for all kk0k\geq k_{0}.

Proof of Lemma 6.3.

Let kk0k\geq k_{0}. Suppose that the number of curtains in cn={h1,,hS(n)}c_{n}=\{h_{1},\dots,h_{S^{\prime}(n)}\} separating oo and γn(k)\gamma_{n}(k) is less than or equal to p[0,S(n)4]p\in[0,S^{\prime}(n)-4]. Then {hp+2,,hS(n)}\{h_{p+2},\dots,h_{S^{\prime}(n)}\} is an LL-chain separating {o,γn(k)}\{o,\gamma_{n}(k)\} and {gno}\{g_{n}o\}. We then denote by r(n)r(n) a point on hp+3[γn(k),gno]h_{p+3}\cap[\gamma_{n}(k),g_{n}o] and by r(n)r^{\prime}(n) the projection of r(n)r(n) onto [o,gno][o,g_{n}o], see Figure 5.

ooγn(k)\gamma_{n}(k)gnxg_{n}xr(n)r(n)hp+3h_{p+3}hph_{p}r(n)r^{\prime}(n)hp+2h_{p+2}gnog_{n}o
Figure 5: Illustration of Lemma 6.3.

By hypothesis on kk,

2((gnx|gno)o1)\displaystyle 2((g_{n}x|g_{n}o)_{o}-1) \displaystyle\leq 2(γn(k)|gno)o\displaystyle 2(\gamma_{n}(k)|g_{n}o)_{o}
=\displaystyle= d(γn(k),o)+d(gno,o)d(gno,γn(k)).\displaystyle d(\gamma_{n}(k),o)+d(g_{n}o,o)-d(g_{n}o,\gamma_{n}(k)).

Now by the bottleneck Lemma 3.7 and the triangular inequality,

2(γn(k)|gno)o\displaystyle 2(\gamma_{n}(k)|g_{n}o)_{o} =\displaystyle= d(γn(k),o)+d(gno,o)(d(gno,r(n))+d(r(n),γn(k)))\displaystyle d(\gamma_{n}(k),o)+d(g_{n}o,o)-(d(g_{n}o,r(n))+d(r(n),\gamma_{n}(k)))
\displaystyle\leq d(γn(k),o)+d(gno,o)(d(gno,r(n))(2L+1)+d(r(n),γn(k)))\displaystyle d(\gamma_{n}(k),o)+d(g_{n}o,o)-(d(g_{n}o,r^{\prime}(n))-(2L+1)+d(r(n),\gamma_{n}(k)))
\displaystyle\leq d(r(n),o)+d(gno,o)d(gno,r(n))+2L+1\displaystyle d(r(n),o)+d(g_{n}o,o)-d(g_{n}o,r^{\prime}(n))+2L+1
\displaystyle\leq d(r(n),o)+2L+1+d(gno,o)d(gno,r(n))+2L+1\displaystyle d(r^{\prime}(n),o)+2L+1+d(g_{n}o,o)-d(g_{n}o,r^{\prime}(n))+2L+1
\displaystyle\leq 2d(r(n),o)+2(2L+1).\displaystyle 2d(r^{\prime}(n),o)+2(2L+1).

Because the pole of a curtain is of diameter 1, d(o,r(n))d(gno,o)(S(n)(p+1))d(o,r^{\prime}(n))\leq d(g_{n}o,o)-(S^{\prime}(n)-(p+1)). However, by assumptions (ii) and (v) of Proposition 6.1, one gets that d(gno,o)(λ+ε)nd(g_{n}o,o)\leq(\lambda+\varepsilon)n and S(n)AnS(n)\geq An. Recall that by Lemma 3.8, this means that S(n)AnS^{\prime}(n)\geq A^{\prime}n, where A=A4L+10A^{\prime}=\frac{A}{4L+10}. Combining this with the previous result yields

(gnx|gno)o1d(o,r(n))+2L+1\displaystyle(g_{n}x|g_{n}o)_{o}-1\leq d(o,r^{\prime}(n))+2L+1
\displaystyle\Rightarrow (λε)n1(λ+ε)n(An(p+1))+2L+1 by Lemma 6.11\displaystyle(\lambda-\varepsilon)n-1\leq(\lambda+\varepsilon)n-(A^{\prime}n-(p+1))+2L+1\text{ by Lemma \ref{geometric lemma}, \ref{geom estimate 1}}
\displaystyle\Rightarrow 0(2εA)n+2L+p+3.\displaystyle 0\leq(2\varepsilon-A^{\prime})n+2L+p+3.

If A>2εA^{\prime}>2\varepsilon, there exists n0n_{0} large enough such that for all nn0n\geq n_{0}, the above inequality gives a contradiction. As a consequence, if A>2εA^{\prime}>2\varepsilon, or equivalently if A>2(4L+10)εA>2(4L+10)\varepsilon, there exists n0n_{0} such that for all nn0n\geq n_{0}, the number of curtains in cnc_{n} separating o{o} and {γn(k),gno}\{\gamma_{n}(k),g_{n}o\} is greater than pp. ∎

We can now conclude the proof of Proposition 6.1.

Proof of estimate 3.

Recall that we denote by γ:[0,)X\gamma:[0,\infty)\rightarrow X the geodesic ray that represents yXy\in\partial_{\infty}X such that γ(0)=o\gamma(0)=o and by γn:[0,)X\gamma_{n}:[0,\infty)\rightarrow X the geodesic ray joining oo and gnxg_{n}x. Combining Lemma 6.2 and Lemma 6.3, we get that if A>2(4L+10)εA>2(4L+10)\varepsilon, there exists n0n_{0}, k0k_{0} such that for all nn0n\geq n_{0} and all kk0k\geq k_{0}, cnc_{n} contains at least 3 pairwise LL-separated curtains that separate {o,γ(k)}\{o,\gamma(k)\} on the one side and {gno,γn(k)}\{g_{n}o,\gamma_{n}(k)\} on the other. Call these hyperplanes {h1,h2,h3}\{h_{1},h_{2},h_{3}\} and arrange the order so that hihi+1h_{i}\subseteq h_{i+1}^{-}. Denote by mk(n)h2m_{k}(n)\in h_{2} some point on the geodesic segment joining γ(k)\gamma(k) to γn(k)\gamma_{n}(k), and mk(n)m^{\prime}_{k}(n) belonging to the geodesic segment [o,gno][o,g_{n}o] such that d(mk(n),mk(n))2L+1d(m_{k}(n),m^{\prime}_{k}(n))\leq 2L+1, see Figure 6

ooγ\gammaγ(k)\gamma(k)h1h_{1}h2h_{2}h3h_{3}gnog_{n}oγn(k)\gamma_{n}(k)mk(n)m_{k}(n)mk(n)m^{\prime}_{k}(n)γn\gamma_{n}
Figure 6: Proof of Proposition 6.1

Then we have

2(γ(k)|γn(k))o\displaystyle 2(\gamma(k)|\gamma_{n}(k))_{o} =\displaystyle= d(γ(k),o)+d(o,γn(k))d(γ(k),γn(k))\displaystyle d(\gamma(k),o)+d(o,\gamma_{n}(k))-d(\gamma(k),\gamma_{n}(k))
\displaystyle\leq d(γ(k),o)+d(o,mk(n))+d(mk(n),mk(n))\displaystyle d(\gamma(k),o)+d(o,m^{\prime}_{k}(n))+d(m^{\prime}_{k}(n),m_{k}(n))
+d(mk(n),γn(k))d(γ(k),γn(k)) by the triangular inequality\displaystyle+\,d(m_{k}(n),\gamma_{n}(k))-d(\gamma(k),\gamma_{n}(k))\text{ by the triangular inequality }
\displaystyle\leq d(γ(k),o)+d(o,mk(n))d(γ(k),mk(n))+2L+1\displaystyle d(\gamma(k),o)+d(o,m^{\prime}_{k}(n))-d(\gamma(k),m_{k}(n))+2L+1

by Lemma 3.7. Since mk(n)m^{\prime}_{k}(n) is on [o,gno][o,g_{n}o], d(o,mk(n))=d(o,gno)d(gno,mk(n))d(o,m^{\prime}_{k}(n))=d(o,g_{n}o)-d(g_{n}o,m^{\prime}_{k}(n)). We then have:

2(γ(k)|γn(k))o\displaystyle 2(\gamma(k)|\gamma_{n}(k))_{o} \displaystyle\leq d(γ(k),o)+d(o,gno)d(gno,mk(n))d(γ(k),mk(n))+2L+1\displaystyle d(\gamma(k),o)+d(o,g_{n}o)-d(g_{n}o,m^{\prime}k(n))-d(\gamma(k),m_{k}(n))+2L+1
=\displaystyle= d(γ(k),o)+d(o,gno)(d(gno,mk(n))+d(γ(k),mk(n)))+2L+1.\displaystyle d(\gamma(k),o)+d(o,g_{n}o)-(d(g_{n}o,m^{\prime}_{k}(n))+d(\gamma(k),m_{k}(n)))+2L+1.

Now observe that

d(γ(k),gno)\displaystyle d(\gamma(k),g_{n}o) \displaystyle\leq d(gno,mk(n))+d(γ(k),mk(n))+d(mk,mk(n))\displaystyle d(g_{n}o,m^{\prime}_{k}(n))+d(\gamma(k),m_{k}(n))+d(m_{k},m^{\prime}_{k}(n))
\displaystyle\leq d(gno,mk(n))+d(γ(k),mk(n))+2L+1 by Lemma 3.7,\displaystyle d(g_{n}o,m^{\prime}_{k}(n))+d(\gamma(k),m_{k}(n))+2L+1\text{ by Lemma \ref{bottleneck}},

hence d(γ(k),gno)(2L+1)d(gno,mk(n))+d(γ(k),mk(n))d(\gamma(k),g_{n}o)-(2L+1)\leq d(g_{n}o,m^{\prime}_{k}(n))+d(\gamma(k),m_{k}(n)). Then

2(γ(k)|γn(k))o\displaystyle 2(\gamma(k)|\gamma_{n}(k))_{o} \displaystyle\leq d(γ(k),o)+d(o,gno)(d(γ(k),gno)(2L+1))+2L+1\displaystyle d(\gamma(k),o)+d(o,g_{n}o)-(d(\gamma(k),g_{n}o)-(2L+1))+2L+1
=\displaystyle= d(γ(k),o)+d(o,gno)d(γ(k),gno)+2(2L+1)\displaystyle d(\gamma(k),o)+d(o,g_{n}o)-d(\gamma(k),g_{n}o)+2(2L+1)
=\displaystyle= 2(γ(k)|gno)o+2(2L+1).\displaystyle 2(\gamma(k)|g_{n}o)_{o}+2(2L+1).

As kk\rightarrow\infty, one obtains that (gnx|y)o(gno|y)o+(2L+1)(g_{n}x|y)_{o}\leq(g_{n}o|y)_{o}+(2L+1), and the result follows from 2. ∎

6.2 Proof of the Central Limit Theorem

In this section, we prove the main result of the paper. Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite second moment, and assume that GG contains a rank one element. Let oXo\in X be a basepoint of the random walk. Let λ\lambda be the (positive) drift of the random walk provided by Theorem 4.10. We assume the action on XX to be non elementary and rank one, hence due to Proposition 3.16, there exists a number L0L\geq 0 such that GG acts by isometries on XL=(X,dL)X_{L}=(X,d_{L}) non elementarily. Then one can consider the random walk (Zn(ω)o)n(Z_{n}(\omega)o)_{n} as a random walk on (X,dL)(X,d_{L}), which we will write (Zno~)n(Z_{n}\tilde{o})_{n} when the context is not clear. The model (X,dL)(X,d_{L}) is hyperbolic, so we can apply the results of Maher and Tiozzo [MT18] summarized in Section 4. In particular, due to Theorem 4.1 (along with Gouël’s result recalled here in Remark 4.2 for non-separable hyperbolic spaces), the random walk (Zno~)n(Z_{n}\tilde{o})_{n} in XLX_{L} converges to a point of the Gromov boundary XL\partial X_{L} of (X,dL)(X,d_{L}).

Moreover, since we assume μ\mu to have finite first moment (for the action on the CAT\operatorname{\text{CAT}}(0) space XX), and since d(x,y)+1dL(x,y)d(x,y)+1\geq d_{L}(x,y) for all x,yXx,y\in X, the measure μ\mu is also of finite first moment for the action on the hyperbolic model (X,dL)(X,d_{L}). In particular, the drift λ~\tilde{\lambda} of the random walk (Zno~)n(Z_{n}\tilde{o})_{n} is almost surely positive. In other words, we have that \mathbb{P}-almost surely,

limn1nd(Zn(ω)o~,o~)=λ~>0.\lim_{n\rightarrow\infty}\frac{1}{n}d(Z_{n}(\omega)\tilde{o},\tilde{o})=\tilde{\lambda}>0.

Due to Theorem 4.6, there exists a unique μ\mu-stationary probability measure ν\nu on X¯\overline{X}. If we define μˇProb(G)\check{\mu}\in\text{Prob}(G) by μˇ(g)=μ(g1)\check{\mu}(g)=\mu(g^{-1}), μˇ\check{\mu} is still admissible and of finite second moment. We denote by νˇ\check{\nu} the unique μˇ\check{\mu}-stationary measure on X¯\overline{X}.

We recall that the Busemann cocycle β:G×X¯\beta:G\times\overline{X}\rightarrow\mathbb{R} is defined by:

β(g,x)=bx(g1o).\beta(g,x)=b_{x}(g^{-1}o).

Our goal is to apply Theorem 5.3 to the Busemann cocycle β\beta. The results of Section 5 show that proving a central limit theorem for the random walk (Zn(ω)o)n(Z_{n}(\omega)o)_{n} amounts to proving that β\beta is centerable. As in the works of [BQ16a], [Hor18] and [FLM24], the natural candidate to solving the cohomological equation (12) is the function:

ψ(x)=2X¯(x|y)o𝑑νˇ(y).\psi(x)=-2\int_{\overline{X}}(x|y)_{o}d\check{\nu}(y).
Proposition 6.4.

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite second moment, and assume that GG contains a rank one element. Let oXo\in X be a basepoint of the random walk. Then the Borel map ψ(x)=X¯(x|y)o𝑑νˇ(y)\psi(x)=\int_{\overline{X}}(x|y)_{o}\,d\check{\nu}(y) is well-defined and essentially bounded.

In order to show that ψ\psi is well-defined and bounded, we need the following statement, which resembles [BQ16a, Proposition 4.2].

Proposition 6.5.

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite second moment, and assume that GG contains a rank one element. Let oXo\in X be a basepoint for the random walk (Zn(ω)o)n(Z_{n}(\omega)o)_{n}. Let λ\lambda be the (positive) drift of the random walk, and ν\nu a μ\mu-stationary measure on X¯\overline{X}. Assume that there exists a>0a>0 and (Cn)n1()(C_{n})_{n}\in\ell^{1}(\mathbb{N}) such that for almost every x,yX¯x,y\in\overline{X}, we have, for every nn:

  1. 1.

    ((Zno|Znx)oan)Cn\mathbb{P}((Z_{n}o|Z_{n}x)_{o}\leq an)\leq C_{n};

  2. 2.

    ((Zno|y)oan)Cn\mathbb{P}((Z_{n}o|y)_{o}\geq an)\leq C_{n};

  3. 3.

    ((Znx|y)oan)Cn\mathbb{P}((Z_{n}x|y)_{o}\geq an)\leq C_{n}.

Then one has:

supxX¯X¯(x|y)o𝑑ν(y)<.\displaystyle\sup_{x\in\overline{X}}\int_{\overline{X}}(x|y)_{o}d\nu(y)<\infty.
Proof.

Suppose that there exist a>0a>0, (Cn)n1()(C_{n})_{n}\in\ell^{1}(\mathbb{N}) such that for almost every x,yX¯x,y\in\overline{X}, we have estimates 1, 2 and 3. We get:

ν({xX|(x|y)an})\displaystyle\nu(\{x\in X|(x|y)\geq an\}) =\displaystyle= X¯μn({gG|(gx|y)oan})𝑑ν(x) by μ-stationarity\displaystyle\int_{\overline{X}}\mu^{\ast n}(\{g\in G\,|\,(gx|y)_{o}\geq an\})d\nu(x)\text{ by $\mu$-stationarity}
\displaystyle\leq X¯Cn𝑑ν(x)=Cn by estimate 3.\displaystyle\int_{\overline{X}}C_{n}d\nu(x)=C_{n}\text{ by estimate \ref{estimate 3}}.

Then, define An,y:={xX¯|(x|y)oan}A_{n,y}:=\{x\in\overline{X}\,|\,(x|y)_{o}\geq an\}, so that by splitting along the subsets An1,yAn,yA_{n-1,y}-A_{n,y}, one gets

X¯(x|y)o𝑑ν(x)\displaystyle\int_{\overline{X}}(x|y)_{o}d\nu(x) \displaystyle\leq n1an(ν(An1,y)ν(An,y))\displaystyle\sum_{n\geq 1}an(\nu(A_{n-1,y})-\nu(A_{n,y}))
\displaystyle\leq n1an(Cn1Cn)\displaystyle\sum_{n\geq 1}an(C_{n-1}-C_{n})
=\displaystyle= a+n1aCn(n+1n)<.\displaystyle a+\sum_{n\geq 1}aC_{n}(n+1-n)<\infty.

We want to show that estimates from Proposition 6.5 hold. As we will see, estimates 1 and 2 are quite straightforward to check using the positivity of the drift. Most of the work concerns estimate 3.

Combining Proposition 5.5 with Theorem 4.10 and [BQ16b, Proposition 3.2], one obtains the following:

Proposition 6.6.

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite second moment, and assume that GG contains a rank one element. Let oXo\in X be a basepoint of the random walk. Let λ\lambda be the (positive) drift of the random walk. Then, for every ε>0\varepsilon>0, there exists (Cn)n1()(C_{n})_{n}\in\ell^{1}(\mathbb{N}) such that for any xX¯x\in\overline{X},

(|β(Zn,x)nλ|εn)Cn;\displaystyle\mathbb{P}(|\beta(Z_{n},x)-n\lambda|\geq\varepsilon n)\leq C_{n}; (13)
(|β(Zn1,x)nλ|εn)Cn;\displaystyle\mathbb{P}(|\beta(Z^{-1}_{n},x)-n\lambda|\geq\varepsilon n)\leq C_{n}; (14)
(|d(Zno,o)nλ|εn)Cn.\displaystyle\mathbb{P}(|d(Z_{n}o,o)-n\lambda|\geq\varepsilon n)\leq C_{n}. (15)
Proof.

Recall that by Proposition 5.5, β\beta is a continuous cocycle such that

GsupxX¯|β(g,x)|2dμ(g)< and GsupxX¯|β(g,x)|2dμˇ(g)<.\displaystyle\int_{G}\sup_{x\in\overline{X}}|\beta(g,x)|^{2}d\mu(g)<\infty\text{ and }\int_{G}\sup_{x\in\overline{X}}|\beta(g,x)|^{2}d\check{\mu}(g)<\infty.

Moreover,

λ=G×X¯β(g,x)𝑑μ(g)𝑑ν(x)=G×X¯β(g,x)𝑑μˇ(g)𝑑νˇ(x).\displaystyle\lambda=\int_{G\times\overline{X}}\beta(g,x)d\mu(g)d\nu(x)=\int_{G\times\overline{X}}\beta(g,x)d\check{\mu}(g)d\check{\nu}(x).

We can then apply [BQ16b, Proposition 3.2]: for every ε>0\varepsilon>0, there exists a sequence (Cn)1()(C_{n})\in\ell^{1}(\mathbb{N}) such that for every xX¯x\in\overline{X},

(ωΩ:|β(Zn(ω),x)nλ|ϵ)Cn.\displaystyle\mathbb{P}\big{(}\omega\in\Omega\,:\,\big{|}\frac{\beta(Z_{n}(\omega),x)}{n}-\lambda\big{|}\geq\epsilon\big{)}\leq C_{n}.

The same goes for μˇ\check{\mu} and νˇ\check{\nu}, which gives estimates (13) and (14).

Estimate (15) is then a straightforward consequence of Proposition 4.11. ∎

The following Lemma will also be important in the proof of Proposition 6.4.

Lemma 6.7.

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite second moment, and assume that GG contains a rank one element. Let oXo\in X be a basepoint of the random walk. Let λ\lambda be the (positive) drift of the random walk.

Then there exist L>0L>0, λL>0\lambda_{L}>0 such that almost surely, lim infndL(Zno,o)n=λL\liminf_{n}\frac{d_{L}(Z_{n}o,o)}{n}=\lambda_{L}. Moreover, there exists A>0A>0 and (Cn)1()(C_{n})\in\ell^{1}(\mathbb{N}) such that

(dL(Zno,o)<An)Cn.\displaystyle\mathbb{P}\big{(}d_{L}(Z_{n}o,o)<An\big{)}\leq C_{n}.
Proof.

The action G(X,d)G\curvearrowright(X,d) is non elementary and contains a rank one element, hence by Proposition 3.16, there exists LL such that the action G(X,dL)G\curvearrowright(X,d_{L}) is non-elementary as the loxodromic isometries gg and hh are independent. We can then apply Theorem 4.4, which gives the Lemma. ∎

Let us now complete the proof of Proposition 6.4.

Proof of Proposition 6.4.

By assumptions, we can apply Theorem 4.1: there exists L>0L>0 such that (Zn(ω)o)n(Z_{n}(\omega)o)_{n} converges in (XL,dL)(X_{L},d_{L}) to a point zLz_{L} of the boundary. By Theorem 4.6, there is a unique μ\mu-stationary measure ν\nu on X\partial_{\infty}X, and this measure is non-atomic.

Fix AA as in Lemma 6.7, and (Cn)n1()(C_{n})_{n}\in\ell^{1}(\mathbb{N}) such that

(dL(Zno,o)<An)<Cn.\displaystyle\mathbb{P}\big{(}d_{L}(Z_{n}o,o)<An\big{)}<C_{n}.

Now take 0<ε<min(A2(4L+10),λ/2)0<\varepsilon<\min(\frac{A}{2(4L+10)},\lambda/2). Due to Proposition 6.6, there exists a sequence Cn1()C^{\prime}_{n}\in\ell^{1}(\mathbb{N}) such that

(|β(Zn,x)nλ|εn)Cn\displaystyle\mathbb{P}(|\beta(Z_{n},x)-n\lambda|\geq\varepsilon n)\leq C^{\prime}_{n}
(|β(Zn1,x)nλ|εn)Cn\displaystyle\mathbb{P}(|\beta(Z^{-1}_{n},x)-n\lambda|\geq\varepsilon n)\leq C^{\prime}_{n}
(|d(Zno,o)nλ|εn)Cn.\displaystyle\mathbb{P}(|d(Z_{n}o,o)-n\lambda|\geq\varepsilon n)\leq C^{\prime}_{n}.

We can assume that Cn=CnC_{n}=C^{\prime}_{n} for all nn. Then for ν\nu-almost every x,yXx,y\in\partial_{\infty}X, we have the quantitative assumptions in Proposition 6.1:

  1. (i)

    {Zno}n\{Z_{n}o\}_{n} converges in (XL¯,dL)(\overline{X_{L}},d_{L}) to a point of the boundary zLXLz_{L}\in\partial X_{L}, whose image in X\partial_{\infty}X by the embedding \mathcal{I} is not yy;

  2. (ii)

    (dL(Zno,o)An)1Cn\mathbb{P}\big{(}d_{L}(Z_{n}o,o)\geq An\big{)}\geq 1-C_{n};

  3. (iii)

    (|bx(Zn1o)nλ|εn)1Cn\mathbb{P}\big{(}|b_{x}(Z_{n}^{-1}o)-n\lambda|\leq\varepsilon n\big{)}\geq 1-C_{n};

  4. (iv)

    (|by(Zno)nλ|εn)1Cn\mathbb{P}\big{(}|b_{y}(Z_{n}o)-n\lambda|\leq\varepsilon n\big{)}\geq 1-C_{n};

  5. (v)

    (|d(gZno,o)nλ|εn)1Cn\mathbb{P}\big{(}|d(gZ_{n}o,o)-n\lambda|\leq\varepsilon n\big{)}\geq 1-C_{n}.

As a consequence, one obtains that for ν\nu-almost every x,yXx,y\in\partial_{\infty}X, the probability that these estimates are not satisfied is bounded above by 4Cn4C_{n}. Now choosing a(ε,λε)a\in(\varepsilon,\lambda-\varepsilon), we get that for nn large enough,

  1. 1.

    ((gnx|gno)oan)14Cn\mathbb{P}\big{(}(g_{n}x|g_{n}o)_{o}\geq an\big{)}\geq 1-4C_{n};

  2. 2.

    ((y|gno)oan)14Cn\mathbb{P}\big{(}(y|g_{n}o)_{o}\leq an\big{)}\geq 1-4C_{n};

  3. 3.

    ((y|gnx)oan)14Cn\mathbb{P}\big{(}(y|g_{n}x)_{o}\leq an\big{)}\geq 1-4C_{n}.

Since the sequence (4Cn)n(4C_{n})_{n} is still summable, we can apply Proposition 6.5, that states that the function ψ\psi defined by

ψ(x)=2X¯(x|y)o𝑑νˇ(y)\psi(x)=-2\int_{\overline{X}}(x|y)_{o}d\check{\nu}(y)

is well-defined, and Borel by Fubini. Moreover, ψ\psi is essentially bounded:

supxX¯X¯(x|y)o𝑑ν(y)<.\displaystyle\sup_{x\in\overline{X}}\int_{\overline{X}}(x|y)_{o}d\nu(y)<\infty.

Corollary 6.8.

Under the same assumptions as in Proposition 6.4, the cocycle β(g,x)=bx(g1o)\beta(g,x)=b_{x}(g^{-1}o) is centerable.

Proof.

By Proposition 6.4, the function ψ\psi defined by

ψ(x)=2X¯(x|y)o𝑑νˇ(y).\psi(x)=-2\int_{\overline{X}}(x|y)_{o}d\check{\nu}(y).

is well-defined, Borel and essentially bounded. Also, as observed in [BQ16a, Lemma 1.2], a quick computation shows that for all gGg\in G, x,yX¯x,y\in\overline{X}:

bx(g1o)=2(x|g1y)o+2(gx|y)o+by(go).\displaystyle b_{x}(g^{-1}o)=-2(x|g^{-1}y)_{o}+2(gx|y)_{o}+b_{y}(go).

Fix xXx\in X. Integrate this equality on (G×X,μνˇ)(G\times\partial_{\infty}X,\mu\otimes\check{\nu}) gives

Gβ(g,x)𝑑μ(g)\displaystyle\int_{G}\beta(g,x)d\mu(g) =\displaystyle= 2GX(x|g1y)o𝑑μ(g)𝑑νˇ(y)\displaystyle-2\int_{G}\int_{\partial_{\infty}X}(x|g^{-1}y)_{o}d\mu(g)d\check{\nu}(y)
+2GX(gx|y)o𝑑μ(g)𝑑νˇ(y)+GXβ(g1,x)𝑑μ(g)𝑑νˇ(y)\displaystyle+2\int_{G}\int_{\partial_{\infty}X}(gx|y)_{o}d\mu(g)d\check{\nu}(y)+\int_{G}\int_{\partial_{\infty}X}\beta(g^{-1},x)d\mu(g)d\check{\nu}(y)
=\displaystyle= 2GX(x|gy)o𝑑μˇ(g)𝑑νˇ(y)Gψ(gx)𝑑μ(g)\displaystyle-2\int_{G}\int_{\partial_{\infty}X}(x|gy)_{o}d\check{\mu}(g)d\check{\nu}(y)-\int_{G}\psi(gx)d\mu(g)
+GXβ(g,x)𝑑μˇ(g)𝑑νˇ(y).\displaystyle+\int_{G}\int_{\partial_{\infty}X}\beta(g,x)d\check{\mu}(g)d\check{\nu}(y).

But GX(x|gy)o𝑑μˇ(g)𝑑νˇ(y)=X(x|y)o𝑑νˇ(y)\int_{G}\int_{\partial_{\infty}X}(x|gy)_{o}d\check{\mu}(g)d\check{\nu}(y)=\int_{\partial_{\infty}X}(x|y)_{o}d\check{\nu}(y) because νˇ\check{\nu} is μˇ\check{\mu}-stationary. Also, by point 3 in Proposition 5.5, we have that

GXβ(g,x)𝑑μˇ(g)𝑑νˇ(y)=λ.\displaystyle\int_{G}\int_{\partial_{\infty}X}\beta(g,x)d\check{\mu}(g)d\check{\nu}(y)=\lambda. (16)

Combining these, we get:

Gβ(g,x)𝑑μ(g)=ψ(x)Gψ(gx)𝑑μ(g)+λ.\displaystyle\int_{G}\beta(g,x)d\mu(g)=\psi(x)-\int_{G}\psi(gx)d\mu(g)+\lambda.

Hence if we define β0(g,x)=β(g,x)ψ(x)+ψ(gx)\beta_{0}(g,x)=\beta(g,x)-\psi(x)+\psi(gx), we obtain that for all xX¯x\in\overline{X},

Gβ0(g,x)𝑑μ(g)=λ,\displaystyle\int_{G}\beta_{0}(g,x)d\mu(g)=\lambda, (17)

and the cocycle β0\beta_{0} has constant drift λ\lambda. Then by Remark 5.2, β\beta is centerable with average λ\lambda, as wanted. ∎

We can now state the following.

Theorem 6.9.

Let GG be a discrete group and GXG\curvearrowright X a non-elementary action by isometries on a proper CAT\operatorname{\text{CAT}}(0) space XX. Let μProb(G)\mu\in\text{Prob}(G) be an admissible probability measure on GG with finite second moment, and assume that GG contains a rank one element. Let oXo\in X be a basepoint of the random walk. Let λ\lambda be the (positive) drift of the random walk. Then the random variables (1n(d(Zno,o)nλ))n(\frac{1}{\sqrt{n}}(d(Z_{n}o,o)-n\lambda))_{n} converge in law to a Gaussian distribution NμN_{\mu}. Furthermore, the variance of NμN_{\mu} is given by

G×X(bx(g1o)ψ(x)+ψ(gx)λ)2𝑑μ(g)𝑑ν(x).\displaystyle\int_{G\times\partial_{\infty}X}(b_{x}(g^{-1}o)-\psi(x)+\psi(gx)-\lambda)^{2}d\mu(g)d\nu(x). (18)
Proof.

By Corollary 6.8, the cocycle β\beta is centerable, with average λ\lambda. Since the measure ν\nu is the unique μ\mu-stationary measure on X¯\overline{X}, we can then apply Theorem 5.3: the random variables (1n(β(Zn(ω),x)nλ))n(\frac{1}{\sqrt{n}}(\beta(Z_{n}(\omega),x)-n\lambda))_{n} converge to a Gaussian law NμN_{\mu}. But thanks to Proposition 4.11, this is equivalent to the convergence of the random variables (1nd(Zn(ω)o,o)nλ)n(\frac{1}{\sqrt{n}}d(Z_{n}(\omega)o,o)-n\lambda)_{n} to a Gaussian law. Moreover, by Theorem 5.3 and Proposition 5.5, the covariance 2-tensor of the limit law is given by

G×X(β0(g,z)λ)2𝑑μ(g)𝑑ν(z),\displaystyle\int_{G\times\partial_{\infty}X}(\beta_{0}(g,z)-\lambda)^{2}d\mu(g)d\nu(z),

where β0(g,x)=β(g,x)ψ(x)+ψ(gx)\beta_{0}(g,x)=\beta(g,x)-\psi(x)+\psi(gx). This yields the result. ∎

In order to prove Theorem 1.1, it only remains to prove that the limit law is non-degenerate. This is what we do in the next Proposition.

Proposition 6.10.

With the same assumptions and notations as in Theorem 6.9, the covariance 2-tensor of the limit law satisfies:

G×X(β0(g,z)λ)2𝑑μ(g)𝑑ν(z)>0.\displaystyle\int_{G\times\partial_{\infty}X}(\beta_{0}(g,z)-\lambda)^{2}d\mu(g)d\nu(z)>0.

In particular, the limit law NμN_{\mu} of the random variables (1n(d(Zno,o)nλ))n(\frac{1}{\sqrt{n}}(d(Z_{n}o,o)-n\lambda))_{n} is non-degenerate.

Proposition 6.11.

With the same assumptions and notations as in Theorem 6.9, the covariance 2-tensor of the limit law satisfies:

G×X(β0(g,z)λ)2𝑑μ(g)𝑑ν(z)>0.\displaystyle\int_{G\times\partial_{\infty}X}(\beta_{0}(g,z)-\lambda)^{2}d\mu(g)d\nu(z)>0.

In particular, the limit law NμN_{\mu} of the random variables (1n(d(Zno,o)nλ))n(\frac{1}{\sqrt{n}}(d(Z_{n}o,o)-n\lambda))_{n} is non-degenerate.

In the course of the proof, we shall use the following fact. We give the proof for completeness.

Lemma 6.12.

We use the same assumptions and notations as in Theorem 6.9. Let gGg\in G be a contracting isometry of XX, and let ξ+X\xi^{+}\in\partial_{\infty}X be its attracting fixed point at infinity. Then ξ+supp(ν)\xi^{+}\in\operatorname{\text{supp}}(\nu), where ν\nu is the unique μ\mu-stationary measure on X¯\overline{X}.

Proof.

Denote by ξX\xi^{-}\in\partial_{\infty}X the repelling fixed point in of gg. The isometry gg is contracting, hence by [Ham09, Lemma 4.4] it acts on X\partial_{\infty}X with North-South dynamics. This means that for every neighbourhood UU of ξ+\xi^{+}, VV of ξ\xi^{-} in X\partial_{\infty}X, there exists kk such that for all nkn\geq k, gn(XV)Ug^{n}(\partial_{\infty}X-V)\subseteq U and gn(XU)Vg^{-n}(\partial_{\infty}X-U)\subseteq V. It is standard that ν\nu is non-atomic, see for instance [LB23, Lemme 4.2.6]. Hence there exists a neighbourhood VV of ξ\xi^{-} such that ν(XV)>0\nu(\partial_{\infty}X-V)>0. Fix such a VV, and let UU be any neighbourhood of ξ+\xi^{+}. Take kk large enough so that for all nkn\geq k, gn(XV)Ug^{n}(\partial_{\infty}X-V)\subseteq U. Since μ\mu is admissible, there exists pp^{\prime}\in\mathbb{N} such that gksupp(μp)g^{k}\in\operatorname{\text{supp}}(\mu^{\ast p^{\prime}}). Check that ν\nu is still μp\mu^{\ast p^{\prime}}-stationary, therefore

hGν(h1U)μp(h)=ν(U).\displaystyle\sum_{h\in G}\nu(h^{-1}U)\mu^{\ast p^{\prime}}(h)=\nu(U).

In particular, by North-South dynamics,

ν(U)ν(gkU)μp(gk)ν(XV)μp(gk)>0.\displaystyle\nu(U)\geq\nu(g^{-k}U)\mu^{\ast p^{\prime}}(g^{k})\geq\nu(\partial_{\infty}X-V)\mu^{\ast p^{\prime}}(g^{k})>0.

This is true for every neighbourhood UU of ξ+\xi^{+}, hence ξ+supp(ν)\xi^{+}\in\operatorname{\text{supp}}(\nu). ∎

Proof of Proposition 6.11.

Let gg be a contracting isometry in GG. Recall that gg has an axis γX\gamma\subseteq X on which gg acts as a translation, and let ξ+,ξ\xi^{+},\xi^{-} be its attracting and repelling fixed points in X\partial_{\infty}X respectively. We let l(g)=limd(gno,o)nl(g)=\lim\frac{d(g^{n}o,o)}{n} be the translation length of gg in (X,d)(X,d). Observe that

l(g)=limnbξ+(gno)n,\displaystyle l(g)=\lim_{n}\frac{b_{\xi^{+}}(g^{-n}o)}{n}, (19)

where bξ+b_{\xi^{+}} is the horofunction centered on ξ+\xi^{+} and based at oo. Indeed, if oo belongs to γ\gamma, then bξ+(gno)=d(gno,o)b_{\xi^{+}}(g^{-n}o)=d(g^{n}o,o) and equation (19) is true. If oo does not belong to γ\gamma, take oγo^{\prime}\in\gamma, and by triangular inequality,

|bξ+(g1o)bξ+o(g1o)|2d(o,o),\displaystyle|b_{\xi^{+}}(g^{-1}o)-b_{\xi^{+}}^{o^{\prime}}(g^{-1}o^{\prime})|\leq 2d(o,o^{\prime}),

where bξ+ob_{\xi^{+}}^{o^{\prime}} is the horofunction with basepoint oo^{\prime}. Since l(g)=limn1nbξ+o(gno)l(g)=\lim_{n}\frac{1}{n}b_{\xi^{+}}^{o^{\prime}}(g^{-n}o^{\prime}), we obtain that l(g)=limn1nbξ+(gno)l(g)=\lim_{n}\frac{1}{n}b_{\xi^{+}}(g^{-n}o).

Suppose by contradiction that G×X(β0(h,z)λ)2𝑑μ(h)𝑑ν(z)=0\int_{G\times\partial_{\infty}X}(\beta_{0}(h,z)-\lambda)^{2}d\mu(h)d\nu(z)=0. This means that for almost every ξsupp(ν)\xi\in\operatorname{\text{supp}}(\nu) and hsupp(μ)h\in\operatorname{\text{supp}}(\mu),

bξ(h1o)λ=ψ(ξ)ψ(hξ).\displaystyle b_{\xi}(h^{-1}o)-\lambda=\psi(\xi)-\psi(h\xi).

Since ψ\psi is bounded and continuous, we get that for every ξsupp(ν)\xi\in\operatorname{\text{supp}}(\nu) and every hsupp(μ)h\in\operatorname{\text{supp}}(\mu), |bξ(h1o)λ|2ψ|b_{\xi}(h^{-1}o)-\lambda|\leq 2\|\psi\|.

Now consider the random walk generated by μp\mu^{\ast p}, for p1p\geq 1. Observe that μp\mu^{\ast p} is still admissible of finite second moment and that ν\nu is still a μp\mu^{\ast p}-stationary measure on X\partial_{\infty}X. We can then apply Theorems 4.10 and 6.9, so that the random walk generated by μp\mu^{\ast p} converges to the boundary with positive drift lX(μp)=pλ>0l_{X}(\mu^{\ast p})=p\lambda>0. By the previous argument, for almost every ξsupp(ν)\xi\in\operatorname{\text{supp}}(\nu) and every hsupp(μp)h\in\operatorname{\text{supp}}(\mu^{\ast p}),

|bξ(h1o)pλ|2ψ.\displaystyle|b_{\xi}(h^{-1}o)-p\lambda|\leq 2\|\psi\|. (20)

Let gg be a contracting element in GG, and let ξ+\xi^{+} be its attracting fixed point. Because μ\mu is admissible, there exists mm such that μm(g)>0\mu^{\ast m}(g)>0. Then by Equation (20), for all n1n\geq 1, |bξ+(gno)nmλ|2ψ|b_{\xi^{+}}(g^{-n}o)-nm\lambda|\leq 2\|\psi\|. By Lemma 6.12, we can apply equation (19), and we obtain that

limnbξ+(gno)n=l(g)=mλ.\displaystyle\lim_{n}\frac{b_{\xi^{+}}(g^{-n}o)}{n}=l(g)=m\lambda.

But there also exists qq\in\mathbb{N}^{\ast} such that 1supp(μq)1\in\operatorname{\text{supp}}(\mu^{\ast q}), hence gsupp(μ(m+q))g\in\operatorname{\text{supp}}(\mu^{\ast(m+q)}) and by the same argument, l(g)=(m+q)λl(g)=(m+q)\lambda. Since by Theorem 4.10, λ\lambda is positive, we get a contradiction. ∎

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