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Zero entropy actions of amenable groups are not dominant

Adam Lott Department of Mathematics, University of California, Los Angeles, Los Angeles, CA 90095 [email protected]
Abstract.

A probability measure preserving action of a discrete amenable group GG is said to be dominant if it is isomorphic to a generic extension of itself. In [AGTW21], it was shown that for G=G=\mathbb{Z}, an action is dominant if and only if it has positive entropy and that for any GG, positive entropy implies dominance. In this paper we show that the converse also holds for any GG, i.e. that zero entropy implies non-dominance.

1. Introduction

1.1. Definitions and results

Let (X,,μ)(X,\mathcal{B},\mu) be a standard Lebesgue space and let TT be a free, ergodic, μ\mu-preserving action of a discrete amenable group GG on XX. It is natural to ask what properties of TT are preserved by a generic extension (X¯,μ¯,T¯)(\overline{X},\overline{\mu},\overline{T}) (a precise definition of “generic extension” is discussed in section 3). For example, it was shown in [GTW21] that if TT is a nontrivial Bernoulli shift then a generic T¯\overline{T} is also Bernoulli and that a generic T¯\overline{T} has the same entropy as TT. A system (X,μ,T)(X,\mu,T) is said to be dominant if it is isomorphic to a generic extension (X¯,μ¯,T¯)(\overline{X},\overline{\mu},\overline{T}). So, for example, the aforementioned results from [GTW21] together with Ornstein’s famous isomorphism theorem [Orn70] imply that all nontrivial Bernoulli shifts are dominant. More generally, it has been shown in [AGTW21] that

  1. (1)

    if G=G=\mathbb{Z}, then (X,μ,T)(X,\mu,T) is dominant if and only if it has positive Kolmogorov-Sinai entropy, and

  2. (2)

    for any GG, if (X,μ,T)(X,\mu,T) has positive entropy, then it is dominant.

In this paper, we complete the picture by proving the following result.

Theorem 1.1.

Let GG be any discrete amenable group, and let (X,μ,T)(X,\mu,T) be any free ergodic action with zero entropy. Then (X,μ,T)(X,\mu,T) is not dominant.

The proof of result (2) above is based on the theory of “slow entropy” developed by Katok and Thouvenot in [KT97], and our proof of Theorem 1.1 uses the same ideas.

1.2. Outline

In section 2, we introduce the relevant ideas from slow entropy. In section 3, we describe a precise definition of “generic extension” and begin the proof of Theorem 1.1. Finally, in section 4, we prove the proposition that is the technical heart of Theorem 1.1.

1.3. Acknowledgements

I am grateful to Tim Austin for originally suggesting this project and for endless guidance. I also thank Benjy Weiss for pointing out an incorrect reference in an earlier version.

This project was partially supported by NSF grant DMS-1855694.

2. Slow entropy

Fix a Følner sequence (Fn)(F_{n}) for GG. For gGg\in G, write TgxT^{g}x for the action of gg on the point xXx\in X, and for a subset FGF\subseteq G, write TFx={Tfx:fF}T^{F}x=\{T^{f}x:f\in F\}. If Q={Q1,,Qk}Q=\{Q_{1},\dots,Q_{k}\} is a partition of XX, then for xXx\in X denote by Q(x)Q(x) the index of the cell of QQ containing xx. Sometimes we will use the same notation to mean the cell itself; which meaning is intended will be clear from the context. Given a finite subset FGF\subseteq G, the (𝐐,𝐅)\mathbf{(Q,F)}-name of xx for the action TT is the tuple QT,F(x):=(Q(Tfx))fF{1,2,,k}FQ_{T,F}(x):=(Q(T^{f}x))_{f\in F}\in\{1,2,\dots,k\}^{F}. Similarly, we also define the partition QT,F:=fFTf1QQ_{T,F}:=\bigvee_{f\in F}T^{f^{-1}}Q, and in some contexts we will use the same notation QT,F(x)Q_{T,F}(x) to refer to the cell of QT,FQ_{T,F} containing xx.

For a finite subset FGF\subseteq G and any finite alphabet Λ\Lambda, the symbolic space ΛF\Lambda^{F} is equipped with the normalized Hamming distance dF(w,w)=1|F|fF1w(f)w(f)d_{F}(w,w^{\prime})=\frac{1}{|F|}\sum_{f\in F}1_{w(f)\neq w^{\prime}(f)}.

Definition 2.1.

Given a partition Q={Q1,,Qk}Q=\{Q_{1},\dots,Q_{k}\}, a finite set FGF\subseteq G, and ϵ>0\epsilon>0, define

BHam(Q,T,F,x,ϵ):={yX:dF(QT,F(y),QT,F(x))<ϵ}.\ B_{\operatorname{Ham}}(Q,T,F,x,\epsilon)\ :=\ \{y\in X:d_{F}(Q_{T,F}(y),Q_{T,F}(x))<\epsilon\}.

We refer to this set as the “(Q,T,F)(Q,T,F)-Hamming ball of radius ϵ\epsilon centered at xx”. Formally, it is the preimage under the map QT,FQ_{T,F} of the ball of radius ϵ\epsilon centered at QT,F(x)Q_{T,F}(x) in the metric space ([k]F,dF)([k]^{F},d_{F}).

Definition 2.2.

The Hamming covering number of μ\mu is defined to be the minimum number of (Q,T,F)(Q,T,F)-Hamming balls of radius ϵ\epsilon required to cover a subset of XX of μ\mu-measure at least 1ϵ1-\epsilon, and is denoted by cov(Q,T,F,μ,ϵ)\operatorname{cov}(Q,T,F,\mu,\epsilon).

Lemma 2.3.

Let φ:(X,T,μ)(Y,S,ν)\varphi:(X,T,\mu)\to(Y,S,\nu) be an isomorphism. Also let QQ be a finite partition of XX, FF a finite subset of GG, and ϵ>0\epsilon>0. Then cov(Q,T,F,μ,ϵ)=cov(φQ,S,F,ν,ϵ)\operatorname{cov}(Q,T,F,\mu,\epsilon)=\operatorname{cov}(\varphi Q,S,F,\nu,\epsilon).

Proof.

It is immediate from the definition of isomorphism that for μ\mu-a.e. x,xX,x,x^{\prime}\in X,

dF(QT,F(x),QT,F(x))=dF((φQ)S,F(φx),(φQ)S,F(φx)).d_{F}\left(Q_{T,F}(x),Q_{T,F}(x^{\prime})\right)\ =\ d_{F}\left((\varphi Q)_{S,F}(\varphi x),(\varphi Q)_{S,F}(\varphi x^{\prime})\right).

Therefore it follows that φ(BHam(Q,T,F,x,ϵ))=BHam(φQ,S,F,φx,ϵ)\varphi\left(B_{\operatorname{Ham}}(Q,T,F,x,\epsilon)\right)=B_{\operatorname{Ham}}(\varphi Q,S,F,\varphi x,\epsilon) for μ\mu-a.e. xx. So any collection of (Q,T,F)(Q,T,F)-Hamming balls in XX covering a set of μ\mu-measure 1ϵ1-\epsilon is directly mapped by φ\varphi to a collection of (φQ,S,F)(\varphi Q,S,F)-Hamming balls in YY covering a set of ν\nu-measure 1ϵ1-\epsilon. Therefore cov(Q,T,F,μ,ϵ)cov(φQ,S,F,ν,ϵ)\operatorname{cov}(Q,T,F,\mu,\epsilon)\geq\operatorname{cov}(\varphi Q,S,F,\nu,\epsilon). The reverse inequality holds by doing the same argument with φ1\varphi^{-1} in place of φ\varphi. ∎

The goal of the rest of this section is to show that for a given action (X,T,μ)(X,T,\mu), the sequence of covering numbers cov(Q,T,Fn,μ,ϵ)\operatorname{cov}(Q,T,F_{n},\mu,\epsilon) grows at a rate that is bounded uniformly for any choice of partition QQ. A key ingredient is an analogue of the classical Shannon-McMillan theorem for actions of amenable groups [MO85, Theorem 4.4.2].

Theorem 2.4.

Let GG be a countable amenable group, and let (Fn)(F_{n}) be any Følner sequence for GG. Let (X,T,μ)(X,T,\mu) be an ergodic action of GG, and let QQ be any finite partition of XX. Then

1|Fn|logμ(QT,Fn(x))L1(μ)h(μ,T,Q)as n,\frac{-1}{|F_{n}|}\log\mu\left(Q_{T,F_{n}}(x)\right)\ \xrightarrow{L^{1}(\mu)}\ h(\mu,T,Q)\qquad\text{as $n\to\infty$},

where hh denotes the entropy. In particular, for any fixed γ>0\gamma>0,

μ{x:exp((hγ)|Fn|)<μ(QT,Fn(x))<exp((h+γ)|Fn|)} 1as n.\mu\left\{x:\exp((-h-\gamma)|F_{n}|)<\mu(Q_{T,F_{n}}(x))<\exp((-h+\gamma)|F_{n}|)\right\}\ \to\ 1\qquad\text{as $n\to\infty$}.
Lemma 2.5.

For any partition PP, any Følner sequence (Fn)(F_{n}), and any ϵ>0\epsilon>0, let (T,P,μ,n)\ell(T,P,\mu,n) be the minimum number of PT,FnP_{T,F_{n}}-cells required to cover a subset of XX of measure >1ϵ>1-\epsilon. Then

lim supn1|Fn|log(T,P,μ,n)h(μ,T,P).\limsup_{n\to\infty}\frac{1}{|F_{n}|}\log\ell(T,P,\mu,n)\ \leq\ h(\mu,T,P).
Proof.

Let h=h(μ,T,P)h=h(\mu,T,P). Let γ>0\gamma>0. By Theorem 2.4, for nn sufficiently large depending on γ\gamma, we have

μ{xX:μ(PT,Fn(x))exp((hγ)|Fn|)}> 1ϵ.\mu\left\{x\in X:\mu(P_{T,F_{n}}(x))\geq\exp((-h-\gamma)|F_{n}|)\right\}\ >\ 1-\epsilon.

Let XX^{\prime} denote the set in the above equation. Let 𝒢\mathcal{G} be the family of cells of the partition PT,FnP_{T,F_{n}} that meet XX^{\prime}. Then clearly μ(𝒢)>1ϵ\mu\left(\bigcup\mathcal{G}\right)>1-\epsilon and |𝒢|<exp((h+γ)|Fn|)|\mathcal{G}|<\exp((h+\gamma)|F_{n}|). Therefore

lim supn1|Fn|log(n)h+γ,\limsup_{n\to\infty}\frac{1}{|F_{n}|}\log\ell(n)\ \leq\ h+\gamma,

and this holds for arbitrary γ\gamma, so we are done. ∎

At this point, fix for all time ϵ=1/100\epsilon=1/100. We can also now omit ϵ\epsilon from all of the notations defined above, because it will never change. Also assume from now on that the system (X,T,μ)(X,T,\mu) has zero entropy.

Lemma 2.6.

If (Fn)(F_{n}) is a Følner sequence for GG and AA is any finite subset of GG, then (AFn)(AF_{n}) is also a Følner sequence for GG.

Proof.

First, because AA is finite and (Fn)(F_{n}) is Følner we have

limn|AFn||Fn|= 1.\lim_{n\to\infty}\frac{|AF_{n}|}{|F_{n}|}\ =\ 1.

Now fix any gGg\in G and observe that

|gAFnAFn||AFn||gAFnFn|+|FnAFn||Fn||Fn||AFn| 0as n,\frac{|gAF_{n}\,\triangle\,AF_{n}|}{|AF_{n}|}\ \leq\ \frac{|gAF_{n}\,\triangle\,F_{n}|+|F_{n}\,\triangle\,AF_{n}|}{|F_{n}|}\cdot\frac{|F_{n}|}{|AF_{n}|}\ \to\ 0\qquad\text{as $n\to\infty$},

which shows that (AFn)(AF_{n}) is a Følner sequence. ∎

Lemma 2.7.

Let b(m,n)0b(m,n)\geq 0 be real numbers satisfying

  • limnb(m,n)=0\lim_{n\to\infty}b(m,n)=0 for each fixed mm, and

  • b(m+1,n)b(m,n)b(m+1,n)\geq b(m,n) for all m,nm,n.

Then there exists a sequence (an)(a_{n}) such that an0a_{n}\to 0 and for each fixed mm, b(m,n)anb(m,n)\leq a_{n} for nn sufficiently large (depending on mm).

Proof.

For each mm, let NmN_{m} be such that b(m,n)<1/mb(m,n)<1/m for all n>Nmn>N_{m}. Without loss of generality, we may assume that Nm<Nm+1N_{m}<N_{m+1}. Then we define the sequence (an)(a_{n}) by an=b(1,n)a_{n}=b(1,n) for nN2n\leq N_{2} and an=b(m,n)a_{n}=b(m,n) for Nm<nNm+1N_{m}<n\leq N_{m+1}. We have an0a_{n}\to 0 because an<1/ma_{n}<1/m for all n>Nmn>N_{m}. Finally, the fact that b(m+1,n)b(m,n)b(m+1,n)\geq b(m,n) implies that for every fixed mm, anb(m,n)a_{n}\geq b(m,n) as soon as n>Nmn>N_{m}. ∎

Proposition 2.8.

There is a sequence (an)(a_{n}) such that

  1. (1)

    lim supn1|Fn|logan=0\limsup_{n\to\infty}\frac{1}{|F_{n}|}\log a_{n}=0, and

  2. (2)

    for any finite partition QQ, there exists an NN such that cov(Q,T,Fn,μ)an\operatorname{cov}(Q,T,F_{n},\mu)\leq a_{n} for all n>Nn>N.

Proof.

Because TT has zero entropy, there exists a finite generating partition for TT (see for example [Sew19, Corollary 1.2] or [Ros88, Theorem 2]). Fix such a partition PP and let Q={Q1,,Qr}Q=\{Q_{1},\dots,Q_{r}\} be any given partition. Because PP is generating, there is an integer mm and another partition Q={Q1,,Qr}Q^{\prime}=\{Q^{\prime}_{1},\dots,Q^{\prime}_{r}\} such that QQ^{\prime} is refined by PT,Fm=gFm(Tg)1PP_{T,F_{m}}=\bigvee_{g\in F_{m}}(T^{g})^{-1}P and

μ{x:Q(x)Q(x)}<ϵ4.\mu\{x:Q(x)\neq Q^{\prime}(x)\}\ <\ \frac{\epsilon}{4}.

By the mean ergodic theorem, we can write

dFn(QT,Fn(x),QT,Fn(x))=1|Fn|fFn1{y:Q(y)Q(y)}(Tfx)L1(μ)μ{y:Q(y)Q(y)}<ϵ4,d_{F_{n}}(Q_{T,F_{n}}(x),Q^{\prime}_{T,F_{n}}(x))\ =\ \frac{1}{|F_{n}|}\sum_{f\in F_{n}}1_{\{y:Q(y)\neq Q^{\prime}(y)\}}(T^{f}x)\ \xrightarrow{L^{1}(\mu)}\ \mu\{y:Q(y)\neq Q^{\prime}(y)\}\ <\ \frac{\epsilon}{4},

so in particular, for nn sufficiently large, we have

μ{x:dFn(QT,Fn(x),QT,Fn(x))<ϵ/2}> 1ϵ4.\mu\{x:d_{F_{n}}(Q_{T,F_{n}}(x),Q^{\prime}_{T,F_{n}}(x))<\epsilon/2\}\ >\ 1-\frac{\epsilon}{4}.

Let YY denote the set {x:dFn(QT,Fn(x),QT,Fn(x))<ϵ/2}\{x:d_{F_{n}}(Q_{T,F_{n}}(x),Q^{\prime}_{T,F_{n}}(x))<\epsilon/2\}.

Recall that QQ^{\prime} is refined by PT,FmP_{T,F_{m}}, so QT,FnQ^{\prime}_{T,F_{n}} is refined by (PT,Fm)T,Fn=PT,FmFn(P_{T,F_{m}})_{T,F_{n}}=P_{T,F_{m}F_{n}}. Let =(m,n)\ell=\ell(m,n) be the minimum number of PT,FmFnP_{T,F_{m}F_{n}} cells required to cover a set of μ\mu-measure at least 1ϵ/41-\epsilon/4, and let C1,,CC_{1},\dots,C_{\ell} be such a collection of cells satisfying μ(iCi)1ϵ/4\mu\left(\bigcup_{i}C_{i}\right)\geq 1-\epsilon/4. If any of the CiC_{i} do not meet the set YY, then drop them from the list. Because μ(Y)>1ϵ/4\mu(Y)>1-\epsilon/4 we can still assume after dropping that μ(iCi)>1ϵ/2\mu\left(\bigcup_{i}C_{i}\right)>1-\epsilon/2. Choose a set of representatives y1,yy_{1},\dots y_{\ell} with each yiCiYy_{i}\in C_{i}\cap Y.

Now we claim that YiCii=1BHam(Q,T,Fn,yi,ϵ)Y\cap\bigcup_{i}C_{i}\subseteq\bigcup_{i=1}^{\ell}B_{\operatorname{Ham}}(Q,T,F_{n},y_{i},\epsilon). To see this, let xYiCix\in Y\cap\bigcup_{i}C_{i}. Then there is one index jj such that xx and yjy_{j} are in the same cell of PT,FmFnP_{T,F_{m}F_{n}}. We can then estimate

dFn(QT,Fn(x),QT,Fn(yj))\displaystyle d_{F_{n}}\left(Q_{T,F_{n}}(x),Q_{T,F_{n}}(y_{j})\right)\ dFn(QT,Fn(x),QT,Fn(x))+dFn(QT,Fn(x),QT,Fn(yj))\displaystyle\leq\ d_{F_{n}}\left(Q_{T,F_{n}}(x),Q^{\prime}_{T,F_{n}}(x)\right)+d_{F_{n}}\left(Q^{\prime}_{T,F_{n}}(x),Q^{\prime}_{T,F_{n}}(y_{j})\right)
+dFn(QT,Fn(yj),QT,Fn(yj))\displaystyle\quad+d_{F_{n}}\left(Q^{\prime}_{T,F_{n}}(y_{j}),Q_{T,F_{n}}(y_{j})\right)
<ϵ2+0+ϵ2=ϵ.\displaystyle<\ \frac{\epsilon}{2}+0+\frac{\epsilon}{2}\ =\ \epsilon.

The bounds for the first and third terms come from the fact that x,yjYx,y_{j}\in Y. The second term is 0 because QFnQ^{\prime}_{F_{n}} is refined by PT,FmFnP_{T,F_{m}F_{n}} and yjy_{j} was chosen so that xx and yjy_{j} are in the same PT,FmFnP_{T,F_{m}F_{n}}-cell. Therefore, cov(Q,T,Fn,μ)(m,n)\operatorname{cov}(Q,T,F_{n},\mu)\leq\ell(m,n). So, the proof is complete once we find a fixed sequence (an)(a_{n}) that is subexponential in |Fn||F_{n}| and eventually dominates (m,n)\ell(m,n) for each fixed mm.

Because TT has zero entropy, Lemmas 2.5 and 2.6 imply that

lim supn1|Fn|log(m,n)=lim supn|FmFn||Fn|1|FmFn|log(m,n)= 0for each fixed m.\limsup_{n\to\infty}\frac{1}{|F_{n}|}\log\ell(m,n)\ =\ \limsup_{n\to\infty}\frac{|F_{m}F_{n}|}{|F_{n}|}\cdot\frac{1}{|F_{m}F_{n}|}\log\ell(m,n)\ =\ 0\qquad\text{for each fixed $m$}.

Note also that because PT,Fm+1FnP_{T,F_{m+1}F_{n}} refines PT,FmFnP_{T,F_{m}F_{n}}, we have (m+1,n)(m,n)\ell(m+1,n)\geq\ell(m,n) for all m,nm,n. Therefore, we can apply Lemma 2.7 to the numbers b(m,n)=|Fn|1log(m,n)b(m,n)=|F_{n}|^{-1}\log\ell(m,n) to produce a sequence (an)(a_{n}^{\prime}) satisfying an0a_{n}^{\prime}\to 0 and anb(m,n)a_{n}^{\prime}\geq b(m,n) eventually for each fixed mm. Then an:=exp(|Fn|an)a_{n}:=\exp(|F_{n}|a_{n}^{\prime}) is the desired sequence. ∎

3. Cocycles and extensions

Let II be the unit interval [0,1][0,1], and let mm be Lebesgue measure on II. Denote by Aut(I,m)\operatorname{Aut}(I,m) the group of invertible mm-preserving transformations of II. A cocycle on XX is a family of measurable maps αg:XAut(I,m)\alpha_{g}:X\to\operatorname{Aut}(I,m) indexed by gGg\in G that satisfies the cocycle condition: for every g,hGg,h\in G and μ\mu-a.e. xx, αhg(x)=αh(Tgx)αg(x)\alpha_{hg}(x)=\alpha_{h}(T^{g}x)\circ\alpha_{g}(x). A cocycle can equivalently be thought of as a measurable map α:RAut(I,m)\alpha:R\to\operatorname{Aut}(I,m), where RX×XR\subseteq X\times X is the orbit equivalence relation induced by TT (i.e. (x,y)R(x,y)\in R if and only if y=Tgxy=T^{g}x for some gGg\in G). With this perspective, the cocycle condition takes the form α(x,z)=α(y,z)α(x,y)\alpha(x,z)=\alpha(y,z)\circ\alpha(x,y). A cocycle α\alpha induces the skew product action TαT_{\alpha} of GG on the larger space X×IX\times I defined by

Tαg(x,t):=(Tgx,αg(x)(t)).T_{\alpha}^{g}(x,t)\ :=\ (T^{g}x,\alpha_{g}(x)(t)).

This action preserves the measure μ×m\mu\times m and factors onto the original action (X,T,μ)(X,T,\mu).

By a classical theorem of Rokhlin (see for example [Gla03, Theorem 3.18]), any infinite-to-one extension of (X,μ,T)(X,\mu,T) is isomorphic to a skew product action for some cocycle. Therefore, by topologizing the space of all cocycles on XX we can capture the notion of a “generic” extension – a property is said to hold for a generic extension if it holds for a dense GδG_{\delta} set of cocycles. Denote the space of all cocycles on XX by Co(X)\operatorname{Co}(X). Topologizing Co(X)\operatorname{Co}(X) is done in a few stages.

  1. (1)

    Let (I)\mathcal{B}(I) be the Borel sets in II, and let (En)(E_{n}) be a sequence in (I)\mathcal{B}(I) that is dense in the μ()\mu(\cdot\,\triangle\,\cdot) metric. For example, (En)(E_{n}) could be an enumeration of the family of all finite unions of intervals with rational endpoints.

  2. (2)

    Aut(I,m)\operatorname{Aut}(I,m) is completely metrizable via the metric

    dA(ϕ,ψ)=12n12n[m(ϕEnψEn)+m(ϕ1Enψ1En)].d_{A}(\phi,\psi)\ =\ \frac{1}{2}\sum_{n\geq 1}2^{-n}[m(\phi E_{n}\,\triangle\,\psi E_{n})+m(\phi^{-1}E_{n}\,\triangle\,\psi^{-1}E_{n})].

    Notice that with this metric, Aut(I,m)\operatorname{Aut}(I,m) has diameter at most 11. See for example [Kec10, Section 1.1]

  3. (3)

    If α0,β0\alpha_{0},\beta_{0} are maps XAut(I,m)X\to\operatorname{Aut}(I,m), then define dist(α0,β0)=dA(α0(x),β0(x))𝑑μ(x)\operatorname{dist}(\alpha_{0},\beta_{0})=\int d_{A}(\alpha_{0}(x),\beta_{0}(x))\,d\mu(x).

  4. (4)

    The metric defined in the previous step induces a topology on Aut(I,m)X\operatorname{Aut}(I,m)^{X}. Therefore, because Co(X)\operatorname{Co}(X) is just a certain (closed) subset of (Aut(I,m)X)G(\operatorname{Aut}(I,m)^{X})^{G}, it just inherits the product topology.

To summarize, if α\alpha is a cocycle, then a basic open neighborhood α\alpha is specified by two parameters: a finite subset FGF\subseteq G and η>0\eta>0. The (F,η)(F,\eta)-neighborhood of α\alpha is {βCo(X):dist(αg,βg)<η for all gF}\{\beta\in\operatorname{Co}(X):\operatorname{dist}(\alpha_{g},\beta_{g})<\eta\text{ for all $g\in F$}\}. In practice, we will always arrange things so that αg(x)=βg(x)\alpha_{g}(x)=\beta_{g}(x) for all gFg\in F on a set of xx of measure 1η\geq 1-\eta, which is sufficient to guarantee that β\beta is in the (F,η)(F,\eta)-neighborhood of α\alpha.

Let Q¯\overline{Q} be the partition {X×[0,1/2],X×(1/2,1]}\{X\times[0,1/2],X\times(1/2,1]\} of X×IX\times I. We derive Theorem 1.1 from the following result about covering numbers of extensions, which is the main technical result of the paper.

Theorem 3.1.

For any sequence (an)(a_{n}) satisfying lim supn1|Fn|logan=0\limsup_{n\to\infty}\frac{1}{|F_{n}|}\log a_{n}=0, there is a dense GδG_{\delta} set 𝒰Co(X)\mathcal{U}\subseteq\operatorname{Co}(X) such that for any α𝒰\alpha\in\mathcal{U}, cov(Q¯,Tα,Fn,μ×m)>2an\operatorname{cov}(\overline{Q},T_{\alpha},F_{n},\mu\times m)>2a_{n} for infinitely many nn.

Proof that Theorem 3.1 implies Theorem 1.1.

Choose a sequence (an)(a_{n}) as in Proposition 2.8 such that for any partition QQ, cov(Q,T,Fn,μ)an\operatorname{cov}(Q,T,F_{n},\mu)\leq a_{n} for sufficiently large nn. Let 𝒰\mathcal{U} be the dense GδG_{\delta} set of cocycles associated to (an)(a_{n}) as guaranteed by Theorem 3.1, and let α𝒰\alpha\in\mathcal{U}, so we know that cov(Q¯,Tα,Fn,μ×m)2an\operatorname{cov}(\overline{Q},T_{\alpha},F_{n},\mu\times m)\geq 2a_{n} for infinitely many nn. Now if φ:(X×I,Tα,μ×m)(X,T,μ)\varphi:(X\times I,T_{\alpha},\mu\times m)\to(X,T,\mu) were an isomorphism, then by Lemma 2.3, φQ¯\varphi\overline{Q} would be a partition of XX satisfying cov(φQ¯,T,Fn,μ)=cov(Q¯,Tα,Fn,μ×m)>2an\operatorname{cov}(\varphi\overline{Q},T,F_{n},\mu)=\operatorname{cov}(\overline{Q},T_{\alpha},F_{n},\mu\times m)>2a_{n} for infinitely many nn, contradicting the conclusion of Proposition 2.8. Therefore, we have produced a dense GδG_{\delta} set of cocycles α\alpha such that Tα≄TT_{\alpha}\not\simeq T, which implies Theorem 1.1. ∎

To prove Theorem 3.1, we need to show roughly that {αCo(X):cov(Q¯,Tα,Fn,μ×m) is large}\{\alpha\in\operatorname{Co}(X):\operatorname{cov}(\overline{Q},T_{\alpha},F_{n},\mu\times m)\text{ is large}\} is both open and dense. We will address the open part here and leave the density part until the next section. Let π\pi be the partition {[0,1/2),[1/2,1]}\{[0,1/2),[1/2,1]\} of II.

Lemma 3.2.

If β(n)\beta^{(n)} is a sequence of cocycles converging to α\alpha, then for any finite FGF\subseteq G, we have

(μ×m){(x,t):Q¯Tβ(n),F(x,t)=Q¯Tα,F(x,t)} 1as n.(\mu\times m)\left\{(x,t):\overline{Q}_{T_{\beta^{(n)}},F}(x,t)\ =\ \overline{Q}_{T_{\alpha},F}(x,t)\right\}\ \to\ 1\qquad\text{as $n\to\infty$}.
Proof.

For the names Q¯Tβ(n),F(x,t)\overline{Q}_{T_{\beta^{(n)}},F}(x,t) and Q¯Tα,F(x,t)\overline{Q}_{T_{\alpha},F}(x,t) to be the same means that for every gFg\in F,

Q¯(Tgx,βg(n)(x)t)=Q¯(Tgx,αg(x)t),\overline{Q}\left(T^{g}x,\beta^{(n)}_{g}(x)t\right)\ =\ \overline{Q}\left(T^{g}x,\alpha_{g}(x)t\right),

which is equivalent to

(1) π(βg(n)(x)t)=π(αg(x)t).\pi\left(\beta^{(n)}_{g}(x)t\right)\ =\ \pi\left(\alpha_{g}(x)t\right).

The idea is the following. For fixed gg and xx, if αg(x)\alpha_{g}(x) and βg(n)(x)\beta^{(n)}_{g}(x) are close in dAd_{A}, then (1) fails for only a small measure set of tt. And if β(n)\beta^{(n)} is very close to α\alpha in the cocycle topology, then βg(n)(x)\beta^{(n)}_{g}(x) and αg(x)\alpha_{g}(x) are close for all gFg\in F and most xXx\in X. Then, by Fubini’s theorem, we will get that the measure of the set of (x,t)(x,t) failing (1) is small.

Here are the details. Fix ρ>0\rho>0; we will show that the measure of the desired set is at least 1ρ1-\rho for nn sufficiently large. First, let σ\sigma be so small that for any ϕ,ψAut(I,m)\phi,\psi\in\operatorname{Aut}(I,m),

dA(ϕ,ψ)<σimpliesm{t:π(ϕt)=π(ψt)}>1ρ/2.d_{A}(\phi,\psi)<\sigma\quad\text{implies}\quad m\left\{t:\pi(\phi t)=\pi(\psi t)\right\}>1-\rho/2.

This is possible because

{t:π(ϕt)π(ψt)}(ϕ1[0,1/2)ψ1[0,1/2))(ϕ1[1/2,1]ψ1[1/2,1]).\{t:\pi(\phi t)\neq\pi(\psi t)\}\ \subseteq\ (\phi^{-1}[0,1/2)\,\triangle\,\psi^{-1}[0,1/2))\cup(\phi^{-1}[1/2,1]\,\triangle\,\psi^{-1}[1/2,1]).

Then, from the definition of the cocycle topology, we have

μ{xX:dA(βg(n)(x),αg(x))<σfor all gF} 1as n.\mu\left\{x\in X:d_{A}\left(\beta^{(n)}_{g}(x),\alpha_{g}(x)\right)<\sigma\quad\text{for all $g\in F$}\right\}\ \to\ 1\qquad\text{as $n\to\infty$}.

Let nn be large enough so that the above is larger than 1ρ/21-\rho/2. Then, by Fubini’s theorem, we have

(μ×m){(x,t):Q¯Tβ(n),F(x,t)=Q¯Tα,F(x,t)}\displaystyle(\mu\times m)\left\{(x,t):\overline{Q}_{T_{\beta^{(n)}},F}(x,t)\ =\ \overline{Q}_{T_{\alpha},F}(x,t)\right\}
=\displaystyle=\ m{t:π(βg(n)(x)t)=π(αg(x)t)for all gF}𝑑μ(x).\displaystyle\int m\left\{t:\pi\left(\beta^{(n)}_{g}(x)t\right)=\pi\left(\alpha_{g}(x)t\right)\quad\text{for all $g\in F$}\right\}\,d\mu(x).

We have arranged things so that the integrand above is >1ρ/2>1-\rho/2 on a set of xx of μ\mu-measure >1ρ/2>1-\rho/2, so the integral is at least (1ρ/2)(1ρ/2)>1ρ(1-\rho/2)(1-\rho/2)>1-\rho as desired. ∎

Lemma 3.3.

For any finite FGF\subseteq G and any L>0L>0, {αCo(X):cov(Q¯,Tα,F,μ×m)>L}\{\alpha\in\operatorname{Co}(X):\operatorname{cov}(\overline{Q},T_{\alpha},F,\mu\times m)>L\} is open in Co(X)\operatorname{Co}(X).

Proof.

Suppose β(n)\beta^{(n)} is a sequence of cocycles converging to α\alpha and satisfying cov(Q¯,Tβ(n),F,μ×m)L\operatorname{cov}(\overline{Q},T_{\beta^{(n)}},F,\mu\times m)\leq L for all nn. We will show that cov(Q¯,Tα,F,μ×m)L\operatorname{cov}(\overline{Q},T_{\alpha},F,\mu\times m)\leq L as well. The covering number cov(Q¯,Tβ(n),F,μ×m)\operatorname{cov}(\overline{Q},T_{\beta^{(n)}},F,\mu\times m) is a quantity which really depends only on the measure (Q¯Tβ(n),F)(μ×m)Prob({0,1}F)\left(\overline{Q}_{T_{\beta^{(n)}},F}\right)_{*}(\mu\times m)\in\operatorname{Prob}\left(\{0,1\}^{F}\right), which we now call νn\nu_{n} for short. The assumption that cov(Q¯,Tβ(n),F,μ×m)L\operatorname{cov}(\overline{Q},T_{\beta^{(n)}},F,\mu\times m)\leq L for all nn says that for each nn, there is a collection of LL words w1(n),,wL(n){0,1}Fw_{1}^{(n)},\dots,w_{L}^{(n)}\in\{0,1\}^{F} such that the Hamming balls of radius ϵ\epsilon centered at these words cover a set of νn\nu_{n}-measure at least 1ϵ1-\epsilon. Since {0,1}F\{0,1\}^{F} is a finite set, there are only finitely many possibilities for the collection (w1(n),,wL(n))(w_{1}^{(n)},\dots,w_{L}^{(n)}). Therefore by passing to a subsequence and relabeling we may assume that there is a fixed collection of words w1,,wLw_{1},\dots,w_{L} with the property that if we let BiB_{i} be the Hamming ball of radius ϵ\epsilon centered at wiw_{i}, then νn(i=1LBi)1ϵ\nu_{n}\left(\bigcup_{i=1}^{L}B_{i}\right)\geq 1-\epsilon for every nn.

Now, by Lemma 3.2, the map Q¯Tβ(n),F\overline{Q}_{T_{\beta^{(n)}},F} agrees with Q¯Tα,F\overline{Q}_{T_{\alpha},F} on a set of measure converging to 11 as nn\to\infty. This implies that the measures νn\nu_{n} converge in the total variation norm on Prob({0,1}F)\operatorname{Prob}\left(\{0,1\}^{F}\right) to ν:=(Q¯Tα,F)(μ×m)\nu:=\left(\overline{Q}_{T_{\alpha},F}\right)_{*}(\mu\times m). Since νn(i=1LBi)1ϵ\nu_{n}\left(\bigcup_{i=1}^{L}B_{i}\right)\geq 1-\epsilon for every nn, we conclude that ν(i=1LBi)1ϵ\nu\left(\bigcup_{i=1}^{L}B_{i}\right)\geq 1-\epsilon also, which implies that cov(Q¯,Tα,F,μ×m)L\operatorname{cov}(\overline{Q},T_{\alpha},F,\mu\times m)\leq L as desired. ∎

Define 𝒰N:={αCo(X):cov(Q¯,Tα,Fn,μ×m)>2an for some n>N}\mathcal{U}_{N}:=\{\alpha\in\operatorname{Co}(X):\operatorname{cov}(\overline{Q},T_{\alpha},F_{n},\mu\times m)>2a_{n}\text{ for some $n>N$}\}. By Lemma 3.3, each 𝒰N\mathcal{U}_{N} is a union of open sets and therefore open. Also, N𝒰N\bigcap_{N}\mathcal{U}_{N} is exactly the set of αCo(X)\alpha\in\operatorname{Co}(X) satisfying cov(Q¯,Tα,Fn,μ×m)>2an\operatorname{cov}(\overline{Q},T_{\alpha},F_{n},\mu\times m)>2a_{n} infinitely often. Therefore, by the Baire category theorem, in order to prove Theorem 3.1 it suffices to prove

Proposition 3.4.

For each NN, 𝒰N\mathcal{U}_{N} is dense in Co(X)\operatorname{Co}(X).

The proof of this proposition is the content of the next section.

4. Proof of Proposition 3.4

4.1. Setup

Let NN be fixed and let α0\alpha_{0} be an arbitrary cocycle. Consider an arbitrary neighborhood of α0\alpha_{0} determined by a finite set FGF\subseteq G and η>0\eta>0. We can assume without loss of generality that ηϵ=1/100\eta\ll\epsilon=1/100. We will produce a new cocycle α𝒰N\alpha\in\mathcal{U}_{N} such that there is a set XX^{\prime} of measure 1η\geq 1-\eta on which αf(x)=(α0)f(x)\alpha_{f}(x)=(\alpha_{0})_{f}(x) for all fFf\in F. The construction of such an α\alpha is based on the fact that the orbit equivalence relation RR is hyperfinite.

Theorem 4.1 (​​[CFW81, Theorem 10]).

There is an increasing sequence of equivalence relations RnX×XR_{n}\subseteq X\times X such that

  • each RnR_{n} is measurable as a subset of X×XX\times X,

  • every cell of every RnR_{n} is finite, and

  • Rn\bigcup R_{n} agrees μ\mu-a.e. with RR.

Fix such a sequence (Rn)(R_{n}) and for xXx\in X, write Rn(x)R_{n}(x) to denote the cell of RnR_{n} that contains xx.

Lemma 4.2.

There exists an m1m_{1} such that μ{xX:TFxRm1(x)}>1η\mu\{x\in X:T^{F}x\subseteq R_{m_{1}}(x)\}>1-\eta.

Proof.

Almost every xx satisfies TGx=mRm(x)T^{G}x=\bigcup_{m}R_{m}(x), so in particular, for μ\mu-a.e. xx, there is an mxm_{x} such that TFxRm(x)T^{F}x\subseteq R_{m}(x) for all mmxm\geq m_{x}. Letting X={xX:mx}X_{\ell}=\{x\in X:m_{x}\leq\ell\}, we see that the sets XX_{\ell} are increasing and exhaust almost all of XX. Therefore we can pick m1m_{1} so that μ(Xm1)>1η\mu(X_{m_{1}})>1-\eta. ∎

Now we drop R1,,Rm11R_{1},\dots,R_{m_{1}-1} from the sequence and assume that m1=1m_{1}=1.

Lemma 4.3.

There exists a KK such that μ{x:|R1(x)|K}>1η\mu\{x:|R_{1}(x)|\leq K\}>1-\eta.

Proof.

Every R1R_{1}-cell is finite, so if we define Xk={xX:|R1(x)|k}X_{k}=\{x\in X:|R_{1}(x)|\leq k\}, then the XkX_{k} are increasing and exhaust all of XX. So we pick KK so that μ(XK)>1η\mu(X_{K})>1-\eta. ∎

Continue to use the notation XK={xX:|R1(x)|K}X_{K}=\{x\in X:|R_{1}(x)|\leq K\}.

Lemma 4.4.

For all nn sufficiently large, μ{xX:|(TFnx)XK||Fn|>12η}>1η\mu\{x\in X:\frac{|(T^{F_{n}}x)\cap X_{K}|}{|F_{n}|}>1-2\eta\}>1-\eta.

Proof.

We have |(TFnx)XK|=fFn1XK(Tfx)|(T^{F_{n}}x)\cap X_{K}|=\sum_{f\in F_{n}}1_{X_{K}}(T^{f}x). By the mean ergodic theorem, we get

|(TFnx)XK||Fn|μ(XK)> 1ηin probability as n.\frac{|(T^{F_{n}}x)\cap X_{K}|}{|F_{n}|}\ \to\ \mu(X_{K})\ >\ 1-\eta\qquad\text{in probability as $n\to\infty$.}

Therefore, in particular, μ{xX:|(TFnx)XK||Fn|>12η}1\mu\left\{x\in X:\frac{|(T^{F_{n}}x)\cap X_{K}|}{|F_{n}|}>1-2\eta\right\}\to 1 as nn\to\infty, so this measure is >1η>1-\eta for all nn sufficiently large. ∎

From now on, let nn be a fixed number that is large enough so that the above lemma holds, n>Nn>N, and 12exp(18K2|Fn|)>2an\frac{1}{2}\exp\left(\frac{1}{8K^{2}}\cdot|F_{n}|\right)>2a_{n}. This is possible because (an)(a_{n}) is assumed to be subexponential in |Fn||F_{n}|. The relevance of the final condition will appear at the end.

Lemma 4.5.

There is an m2m_{2} such that μ{xX:TFnxRm2(x)}>1η\mu\{x\in X:T^{F_{n}}x\subseteq R_{m_{2}}(x)\}>1-\eta.

Proof.

Same proof as Lemma 4.2. ∎

Again, drop R2,,Rm21R_{2},\dots,R_{m_{2}-1} from the sequence of partitions and assume m2=2m_{2}=2.

4.2. Construction of the perturbed cocycle

Let (Rn)(R_{n}) be the relabeled sequence of equivalence relations from the previous section. The following measure theoretic fact is well known. Recall that two partitions PP and PP^{\prime} of II are said to be independent with respect to mm if m(EE)=m(E)m(E)m(E\cap E^{\prime})=m(E)m(E^{\prime}) for any EPE\in P, EPE^{\prime}\in P^{\prime}.

Lemma 4.6.

Let PP and PP^{\prime} be two finite partitions of II. Then there exists a φAut(I,m)\varphi\in\operatorname{Aut}(I,m) such that PP and φ1P\varphi^{-1}P^{\prime} are independent with respect to mm.

Proposition 4.7.

For any α0Co(X)\alpha_{0}\in\operatorname{Co}(X), there is an αCo(X)\alpha\in\operatorname{Co}(X) such that

  1. (1)

    αg(x)=(α0)g(x)\alpha_{g}(x)=(\alpha_{0})_{g}(x) whenever (x,Tgx)R1(x,T^{g}x)\in R_{1}, and

  2. (2)

    for μ\mu-a.e. xx, the following holds. If CC is an R1R_{1}-cell contained in R2(x)R_{2}(x), consider the map YC:tQ¯Tα,{g:TgxC}(x,t)Y_{C}:t\mapsto\overline{Q}_{T_{\alpha},\{g:T^{g}x\in C\}}(x,t) as a random variable on the underlying space (I,m)(I,m). Then as CC ranges over all such R1R_{1}-cells, the random variables YCY_{C} are independent.

Proof.

We give here only an intuitive sketch of the proof and leave the full details to Appendix A. It is more convenient to adopt the perspective of a cocycle as a map α:RAut(I,m)\alpha:R\to\operatorname{Aut}(I,m) satisfying the condition α(x,z)=α(y,z)α(x,y)\alpha(x,z)=\alpha(y,z)\circ\alpha(x,y).

Step 1. For (x,y)R1(x,y)\in R_{1}, let α(x,y)=α0(x,y)\alpha(x,y)=\alpha_{0}(x,y).

Step 2. Fix an R2R_{2}-cell C¯\overline{C}. Enumerate by {C1,,Ck}\{C_{1},\dots,C_{k}\} all of the R1R_{1}-cells contained in C¯\overline{C} and choose from each a representative xiCix_{i}\in C_{i}.

Step 3. Let π\pi denote the partition {[0,1/2),[1/2,1]}\{[0,1/2),[1/2,1]\} of II. Define α(x1,x2)\alpha(x_{1},x_{2}) to be an element of Aut(I,m)\operatorname{Aut}(I,m) such that

yC1α(x1,y)1πandα(x1,x2)1(yC2α(x2,y)1π)\bigvee_{y\in C_{1}}\alpha(x_{1},y)^{-1}\pi\qquad\text{and}\qquad\alpha(x_{1},x_{2})^{-1}\left(\bigvee_{y\in C_{2}}\alpha(x_{2},y)^{-1}\pi\right)

are independent. These expressions are well defined because α\alpha has already been defined on R1R_{1} and we use Lemma 4.6 to guarantee that such an element of Aut(I,m)\operatorname{Aut}(I,m) exists.

Step 4. There is now a unique way to extend the definition of α\alpha to (C1C2)×(C1C2)(C_{1}\cup C_{2})\times(C_{1}\cup C_{2}) that is consistent with the cocycle conditition. For arbitrary y1C1,y2C2y_{1}\in C_{1},y_{2}\in C_{2}, define

α(y1,y2)\displaystyle\alpha(y_{1},y_{2})\ =α(x2,y2)α(x1,x2)α(y1,x1)and\displaystyle=\ \alpha(x_{2},y_{2})\circ\alpha(x_{1},x_{2})\circ\alpha(y_{1},x_{1})\qquad\text{and}
α(y2,y1)\displaystyle\alpha(y_{2},y_{1})\ =α(y1,y2)1.\displaystyle=\ \alpha(y_{1},y_{2})^{-1}.

The middle term in the first equation was defined in the previous step and the outer two terms were defined in step 1.

Step 5. Extend the definition of α\alpha to the rest of the CiC_{i} inductively, making each cell independent of all the previous ones. Suppose α\alpha has been defined on (C1Cj)×(C1Cj)\left(C_{1}\cup\dots\cup C_{j}\right)\times\left(C_{1}\cup\dots\cup C_{j}\right). Using Lemma 4.6 again, define α(x1,xj+1)\alpha(x_{1},x_{j+1}) to be an element of Aut(I,m)\operatorname{Aut}(I,m) such that

yC1Cjα(x1,y)1πandα(x1,xj+1)1(yCj+1α(xj+1,y)1π)\bigvee_{y\in C_{1}\cup\dots\cup C_{j}}\alpha(x_{1},y)^{-1}\pi\qquad\text{and}\qquad\alpha(x_{1},x_{j+1})^{-1}\left(\bigvee_{y\in C_{j+1}}\alpha(x_{j+1},y)^{-1}\pi\right)

are independent. Then, just as in step 4, there is a unique way to extend the definition of α\alpha to all of (C1Cj+1)×(C1Cj+1)(C_{1}\cup\dots\cup C_{j+1})\times(C_{1}\cup\dots\cup C_{j+1}). At the end of this process, α\alpha has been defined on all of C¯×C¯\overline{C}\times\overline{C}. This was done for an arbitrary R2R_{2}-cell C¯\overline{C}, so now α\alpha is defined on R2R_{2}.

Step 6. For each N2N\geq 2, extend the definition of α\alpha from RNR_{N} to RN+1R_{N+1} with the same procedure, but there is no need to set up any independence. Instead, every time there is a choice for how to define α\alpha between two of the cell representatives, just take it to be the identity. This defines α\alpha on N1RN\bigcup_{N\geq 1}R_{N}, which is equal mod μ\mu to the full orbit equivalence relation, so α\alpha is a well defined cocycle.

Now we verify the two claimed properties of α\alpha. Property (1) is immediate from step 1 of the construction. To check property (2), fix xx and let CjC_{j} be any of the R1R_{1}-cells contained in R2(x)R_{2}(x). Note that the name Q¯Tα,{g:TgxCj}(x,t)\overline{Q}_{T_{\alpha},\{g:T^{g}x\in C_{j}\}}(x,t) records the data Q¯(Tαg(x,t))=Q¯(Tgx,αg(x)t)=π(αg(x)t)\overline{Q}(T^{g}_{\alpha}(x,t))=\overline{Q}(T^{g}x,\alpha_{g}(x)t)=\pi(\alpha_{g}(x)t) for all gg such that TgxCjT^{g}x\in C_{j}, which, by switching to the other notation is the same data as π(α(x,y)t)\pi(\alpha(x,y)t) for yCjy\in C_{j}. So, the set of tt for which Q¯Tα,{g:TgxCj}(x,t)\overline{Q}_{T_{\alpha},\{g:T^{g}x\in C_{j}\}}(x,t) is equal to a particular word is given by a corresponding particular cell of the partition yCjα(x,y)1π=α(x,x1)1(yCjα(x1,y)1π)\bigvee_{y\in C_{j}}\alpha(x,y)^{-1}\pi=\alpha(x,x_{1})^{-1}\left(\bigvee_{y\in C_{j}}\alpha(x_{1},y)^{-1}\pi\right). The construction of α\alpha was defined exactly so that the partitions yCjα(x1,y)1π\bigvee_{y\in C_{j}}\alpha(x_{1},y)^{-1}\pi are all independent and the names Q¯Tα,{g:Tgxj}(x,t)\overline{Q}_{T_{\alpha},\{g:T^{g}x\in_{j}\}}(x,t) are determined by these independent partitions pulled back by the fixed mm-preserving map α(x,x1)\alpha(x,x_{1}), so they are also independent.

The reason this is only a sketch is because it is not clear that the construction described here can be done in a way so that the resulting α\alpha is a measurable function. To do it properly requires a slightly different approach; see Appendix A for full details. ∎

Letting X~={xX:TFxR1(x)}\widetilde{X}=\{x\in X:T^{F}x\subseteq R_{1}(x)\}, this construction guarantees that αf(x)=(α0)f(x)\alpha_{f}(x)=(\alpha_{0})_{f}(x) for all fF,xX~f\in F,x\in\widetilde{X}. By Lemma 4.2, μ(X~)>1η\mu(\widetilde{X})>1-\eta, so this shows that α\alpha is in the (F,η)(F,\eta)-neighborhood of α0\alpha_{0}.

4.3. Estimating the size of Hamming balls

Let α\alpha be the cocycle constructed in the previous section. We will estimate the (μ×m)(\mu\times m)-measure of (Q¯,Tα,Fn)(\overline{Q},T_{\alpha},F_{n})-Hamming balls in order to get a lower bound for the covering number. The following formulation of Hoeffding’s inequality will be quite useful [Ver18, Theorem 2.2.6].

Theorem 4.8.

Let Y1,,YY_{1},\dots,Y_{\ell} be independent random variables such that each Yi[0,K]Y_{i}\in[0,K] almost surely. Let a=𝔼[Yi]a=\mathbb{E}\left[\sum Y_{i}\right]. Then for any t>0t>0,

(i=1Yi<at)exp(2t2K2).\mathbb{P}\left(\sum_{i=1}^{\ell}Y_{i}<a-t\right)\ \leq\ \exp\left(-\frac{2t^{2}}{K^{2}\ell}\right).

Let X0={xX:|(TFnx)XK||Fn|>12η and TFnxR2(x)}X_{0}=\left\{x\in X:\frac{|(T^{F_{n}}x)\cap X_{K}|}{|F_{n}|}>1-2\eta\text{ and }T^{F_{n}}x\subseteq R_{2}(x)\right\}. By Lemmas 4.4 and 4.5, μ(X0)>12η\mu(X_{0})>1-2\eta. Also write μ×m=mx𝑑μ(x)\mu\times m=\int m_{x}\,d\mu(x), where mx=δx×mm_{x}=\delta_{x}\times m.

Proposition 4.9.

For any (x,t)X0×I(x,t)\in X_{0}\times I,

(2) mx(BHam(Q¯,Tα,Fn,(x,t),ϵ))exp(18K2|Fn|).m_{x}\left(B_{\operatorname{Ham}}(\overline{Q},T_{\alpha},F_{n},(x,t),\epsilon)\right)\ \leq\ \exp\left(-\frac{1}{8K^{2}}\cdot|F_{n}|\right).
Proof.

Let 𝒞\mathcal{C} be the collection of R1R_{1}-cells CC that meet TFnxT^{F_{n}}x and satisfy |C|K|C|\leq K. For each C𝒞C\in\mathcal{C}, let FC={fFn:TfxC}F_{C}=\{f\in F_{n}:T^{f}x\in C\}. Define

Y(t)=|Fn|dFn(Q¯Tα,Fn(x,t),Q¯Tα,Fn(x,t))=fFn1Q¯(Tαf(x,t))Q¯(Tαf(x,t)),Y(t^{\prime})\ =\ |F_{n}|\cdot d_{F_{n}}\left(\overline{Q}_{T_{\alpha},F_{n}}(x,t),\overline{Q}_{T_{\alpha},F_{n}}(x,t^{\prime})\right)\ =\ \sum_{f\in F_{n}}1_{\overline{Q}(T_{\alpha}^{f}(x,t))\neq\overline{Q}(T_{\alpha}^{f}(x,t^{\prime}))},

and for each C𝒞C\in\mathcal{C}, define

YC(t)=fFC1Q¯(Tαf(x,t))Q¯(Tαf(x,t)).Y_{C}(t^{\prime})\ =\ \sum_{f\in F_{C}}1_{\overline{Q}(T_{\alpha}^{f}(x,t))\neq\overline{Q}(T_{\alpha}^{f}(x,t^{\prime}))}.

Then we have

Y(t)C𝒞YC(t),Y(t^{\prime})\ \geq\ \sum_{C\in\mathcal{C}}Y_{C}(t^{\prime}),

so to get an upper bound for mx(BHam(Q¯,Tα,Fn,(x,t),ϵ))=m{t:Y(t)<ϵ|Fn|}m_{x}\left(B_{\operatorname{Ham}}(\overline{Q},T_{\alpha},F_{n},(x,t),\epsilon)\right)=m\left\{t^{\prime}:Y(t^{\prime})<\epsilon|F_{n}|\right\}, it is sufficient to control m{t:C𝒞YC(t)<ϵ|Fn|}m\left\{t^{\prime}:\sum_{C\in\mathcal{C}}Y_{C}(t^{\prime})<\epsilon|F_{n}|\right\}.

View each YC(t)Y_{C}(t^{\prime}) as a random variable on the underlying probability space (I,m)(I,m). Our construction of the cocycle α\alpha guarantees that the collection of names Q¯Tα,FC(x,t)\overline{Q}_{T_{\alpha},F_{C}}(x,t^{\prime}) as CC ranges over all of the R1R_{1}-cells contained in R2(x)R_{2}(x) is an independent collection. Therefore, in particular, the YCY_{C} for C𝒞C\in\mathcal{C} are independent (the assumption that xX0x\in X_{0} guarantees that all C𝒞C\in\mathcal{C} are contained in R2(x)R_{2}(x)).

We also have that each YC[0,K]Y_{C}\in[0,K] and the expectation of the sum is

a\displaystyle a\ :=C𝒞YC(t)𝑑m(t)=C𝒞fFC1Q¯(Tαf(x,t))Q¯(Tαf(x,t))𝑑m(t)=C𝒞12|FC|\displaystyle:=\ \sum_{C\in\mathcal{C}}\int Y_{C}(t^{\prime})\,dm(t^{\prime})\ =\ \sum_{C\in\mathcal{C}}\sum_{f\in F_{C}}\int 1_{\overline{Q}(T_{\alpha}^{f}(x,t))\neq\overline{Q}(T_{\alpha}^{f}(x,t^{\prime}))}\,dm(t^{\prime})\ =\ \sum_{C\in\mathcal{C}}\frac{1}{2}|F_{C}|
=12C𝒞|C(TFnx)|>12(12η)|Fn|,\displaystyle=\ \frac{1}{2}\sum_{C\in\mathcal{C}}|C\cap(T^{F_{n}}x)|\ >\ \frac{1}{2}(1-2\eta)|F_{n}|,

where the final inequality is true because xX0x\in X_{0}. So, we can apply Theorem 4.8 with t=aϵ|Fn|t=a-\epsilon|F_{n}| to conclude

m{t:C𝒞YC(t)<ϵ|Fn|}\displaystyle m\left\{t^{\prime}:\sum_{C\in\mathcal{C}}Y_{C}(t^{\prime})<\epsilon|F_{n}|\right\}\ exp(2t2K2|𝒞|)exp(2(1/2ηϵ)2|Fn|2K2|Fn|)\displaystyle\leq\ \exp\left(\frac{-2t^{2}}{K^{2}|\mathcal{C}|}\right)\ \leq\ \exp\left(\frac{-2(1/2-\eta-\epsilon)^{2}|F_{n}|^{2}}{K^{2}|F_{n}|}\right)
exp(18K2|Fn|).\displaystyle\leq\ \exp\left(-\frac{1}{8K^{2}}\cdot|F_{n}|\right).

The final inequality holds because ϵ=1/100\epsilon=1/100 and ηϵ\eta\ll\epsilon is small enough so that 1/2ηϵ>1/41/2-\eta-\epsilon>1/4. ∎

Corollary 4.10.

Let yX0y\in X_{0}. If BB is any (Q¯,Tα,Fn)(\overline{Q},T_{\alpha},F_{n})-Hamming ball of radius ϵ\epsilon, then my(B)exp(18K2|Fn|)m_{y}(B)\leq\exp\left(-\frac{1}{8K^{2}}\cdot|F_{n}|\right).

Proof.

If BB does not meet the fiber above yy, then obviously my(B)=0m_{y}(B)=0. So assume (y,s)B(y,s)\in B for some sIs\in I. Then applying the triangle inequality in the space ({0,1}Fn,dFn)(\{0,1\}^{F_{n}},d_{F_{n}}) shows that BBHam(Q¯,Tα,Fn,(y,s),2ϵ)B\subseteq B_{\operatorname{Ham}}(\overline{Q},T_{\alpha},F_{n},(y,s),2\epsilon). Now apply Proposition 4.9 with 2ϵ2\epsilon in place of ϵ\epsilon. The proof goes through exactly the same and we get the same constant 1/8K21/8K^{2} in the final estimate because ϵ\epsilon and η\eta are small enough so that 1/2η2ϵ1/2-\eta-2\epsilon is still >1/4>1/4. ∎

Corollary 4.11.

We have cov(Q¯,Tα,Fn,μ×m)12exp(18K2|Fn|)\operatorname{cov}(\overline{Q},T_{\alpha},F_{n},\mu\times m)\geq\frac{1}{2}\exp(\frac{1}{8K^{2}}\cdot|F_{n}|).

Proof.

Let {Bi}i=1\{B_{i}\}_{i=1}^{\ell} be a collection of (Q¯,Tα,Fn)(\overline{Q},T_{\alpha},F_{n})-Hamming balls of radius ϵ\epsilon such that

(μ×m)(Bi)> 1ϵ.(\mu\times m)\left(\bigcup B_{i}\right)\ >\ 1-\epsilon.

Then

1ϵ\displaystyle 1-\epsilon\ <(μ×m)(Bi)=(μ×m)(Bi(X0×I))+(μ×m)(Bi(X0c×I))\displaystyle<\ (\mu\times m)\left(\bigcup B_{i}\right)\ =\ (\mu\times m)\left(\bigcup B_{i}\cap(X_{0}\times I)\right)+(\mu\times m)\left(\bigcup B_{i}\cap(X_{0}^{c}\times I)\right)
<i=1(μ×m)(Bi(X0×I))+(μ×m)(X0c×I)\displaystyle<\ \sum_{i=1}^{\ell}(\mu\times m)(B_{i}\cap(X_{0}\times I))+(\mu\times m)(X_{0}^{c}\times I)
<i=1yX0my(Bi)𝑑μ(y)+2η\displaystyle<\ \sum_{i=1}^{\ell}\int_{y\in X_{0}}m_{y}(B_{i})\,d\mu(y)+2\eta
<exp(18K2|Fn|)+2η,\displaystyle<\ \ell\cdot\exp\left(-\frac{1}{8K^{2}}\cdot|F_{n}|\right)+2\eta,

implying that >(1ϵ2η)exp(18K2|Fn|)>(1/2)exp(18K2|Fn|)\ell>(1-\epsilon-2\eta)\exp\left(\frac{1}{8K^{2}}\cdot|F_{n}|\right)>(1/2)\exp\left(\frac{1}{8K^{2}}\cdot|F_{n}|\right). ∎

Our choice of nn at the beginning now guarantees that cov(Q¯,Tα,Fn,μ×m)12exp(18K2|Fn|)>2an\operatorname{cov}(\overline{Q},T_{\alpha},F_{n},\mu\times m)\geq\frac{1}{2}\exp(\frac{1}{8K^{2}}\cdot|F_{n}|)>2a_{n}, showing that α𝒰N\alpha\in\mathcal{U}_{N} as desired. This completes the proof of Proposition 3.4.

Appendix A Measurability of the perturbed cocycle

In this section, we give a more careful proof of Proposition 4.7 that addresses the issue of measurability. We will need to use at some point the following measurable selector theorem [Fre06, Proposition 433F].

Theorem A.1.

Let (Ω1,1)(\Omega_{1},\mathcal{F}_{1}) and (Ω2,2)(\Omega_{2},\mathcal{F}_{2}) be standard Borel spaces. Let \mathbb{P} be a probability measure on (Ω1,1)(\Omega_{1},\mathcal{F}_{1}) and suppose that f:Ω2Ω1f:\Omega_{2}\to\Omega_{1} is measurable and surjective. Then there exists a measurable selector g:Ω1Ω2g:\Omega_{1}\to\Omega_{2} which is defined \mathbb{P}-a.e. (meaning g(ω)f1(ω)g(\omega)\in f^{-1}(\omega) for \mathbb{P}-a.e. ωΩ1\omega\in\Omega_{1}).

Given xXx\in X, there is a natural bijection between TGxT^{G}x and GG because TT is a free action. We can also identify subsets – if ETGxE\subseteq T^{G}x, then we will write E~:={gG:TgxE}\widetilde{E}:=\{g\in G:T^{g}x\in E\}. Note that this set depends on the “base point” xx. If xx and yy are two points in the same GG-orbit, then the set E~\widetilde{E} based at xx is a translate of the same set based at yy. It will always be clear from context what the intended base point is.

Definition A.2.

A pattern in GG is a pair (H,𝒞)(H,\mathscr{C}), where HH is a finite subset of GG and 𝒞\mathscr{C} is a partition of HH.

Definition A.3.

For xXx\in X, define patn(x)\operatorname{pat}_{n}(x) to be the pattern (H,𝒞)(H,\mathscr{C}), where H=Rn(x)~H=\widetilde{R_{n}(x)} and 𝒞\mathscr{C} is the partition of HH into the sets C~\widetilde{C} where CC ranges over all of the Rn1R_{n-1}-cells contained in Rn(x)R_{n}(x).

Lemma A.4.

patn(x)\operatorname{pat}_{n}(x) is a measurable function of xx.

Proof.

Because there are only countably many possible patterns, it is enough to fix a pattern (H,𝒞)(H,\mathscr{C}) and show that {x:patn(x)=(H,𝒞)}\{x:\operatorname{pat}_{n}(x)=(H,\mathscr{C})\} is measurable. Enumerate 𝒞={C1,,Ck}\mathscr{C}=\{C_{1},\dots,C_{k}\}. Saying that patn(x)=(H,𝒞)\operatorname{pat}_{n}(x)=(H,\mathscr{C}) is the same as saying that THx=Rn(x)T^{H}x=R_{n}(x) and each TCixT^{C_{i}}x is a cell of Rn1R_{n-1}. We can express the set of xx satisfying this as

(i=1kg,hCi{x:(Tgx,Thx)Rn1}(g,h)G2(Ci×Ci){x:(Tgx,Thx)Rn1})\displaystyle\left(\bigcap_{i=1}^{k}\bigcap_{g,h\in C_{i}}\{x:(T^{g}x,T^{h}x)\in R_{n-1}\}\quad\cap\quad\bigcap_{(g,h)\in G^{2}\setminus\bigcup(C_{i}\times C_{i})}\{x:(T^{g}x,T^{h}x)\not\in R_{n-1}\}\right)\quad\cap
(gH{x:(x,Tgx)Rn}gH{x:(x,Tgx)Rn}).\displaystyle\left(\bigcap_{g\in H}\{x:(x,T^{g}x)\in R_{n}\}\quad\cap\quad\bigcap_{g\not\in H}\{x:(x,T^{g}x)\not\in R_{n}\}\right).

Because each RnR_{n} is a measurable set and each TgT^{g} is a measurable map, this whole thing is measurable. ∎

For each pattern (H,𝒞)(H,\mathscr{C}), let XH,𝒞(n)={xX:patn(x)=(H,𝒞)}X_{H,\mathscr{C}}^{(n)}\ =\ \{x\in X:\operatorname{pat}_{n}(x)=(H,\mathscr{C})\}. We will define our cocycle α\alpha inductively on the equivalence relations RnR_{n}. For each nn, the sets XH,𝒞(n)X_{H,\mathscr{C}}^{(n)} partition XX into countably many measurable sets, so it will be enough to define α\alpha measurably on each XH,𝒞(n)X_{H,\mathscr{C}}^{(n)}. At this point, fix a pattern (H,𝒞)(H,\mathscr{C}), fix n=2n=2, and write XH,𝒞X_{H,\mathscr{C}} instead of XH,𝒞(2)X_{H,\mathscr{C}}^{(2)}. Define

Ω2H,𝒞\displaystyle\Omega_{2}^{H,\mathscr{C}}\ ={ψ:H×HAut(I,m):ψ(h1,h3)=ψ(h2,h3)ψ(h1,h2)for allh1,h2,h3H},\displaystyle=\ \left\{\psi:H\times H\to\operatorname{Aut}(I,m):\psi(h_{1},h_{3})=\psi(h_{2},h_{3})\circ\psi(h_{1},h_{2})\ \text{for all}\ h_{1},h_{2},h_{3}\in H\right\},
Ω1H,𝒞\displaystyle\Omega_{1}^{H,\mathscr{C}}\ ={σ:C𝒞C×CAut(I,m):σ(g1,g3)=σ(g2,g3)σ(g1,g2)for allg1,g2,g3G},\displaystyle=\ \left\{\sigma:\bigcup_{C\in\mathscr{C}}C\times C\to\operatorname{Aut}(I,m):\sigma(g_{1},g_{3})=\sigma(g_{2},g_{3})\circ\sigma(g_{1},g_{2})\ \text{for all}\ g_{1},g_{2},g_{3}\in G\right\},
Ω2H,𝒞,ind\displaystyle\Omega_{2}^{H,\mathscr{C},\text{ind}}\ ={ψΩ2H,𝒞:ψis (H,𝒞)-independent},\displaystyle=\ \left\{\psi\in\Omega_{2}^{H,\mathscr{C}}:\psi\ \text{is $(H,\mathscr{C})$-independent}\right\},

where ψΩ2H,𝒞\psi\in\Omega_{2}^{H,\mathscr{C}} is said to be (H,𝒞)(H,\mathscr{C})-independent if for any fixed h0Hh_{0}\in H, the partitions

hCψ(h0,h)1π\bigvee_{h\in C}\psi(h_{0},h)^{-1}\pi

as CC ranges over 𝒞\mathscr{C} are independent with respect to mm.

Proposition A.5.

For every σΩ1H,𝒞\sigma\in\Omega_{1}^{H,\mathscr{C}}, there is some ψΩ2H,𝒞,ind\psi\in\Omega_{2}^{H,\mathscr{C},\text{ind}} that extends σ\sigma.

Proof.

The idea is exactly the same as the construction described in steps 3-5 in the sketched proof of Proposition 4.7, but we write it out here also for completeness.

Enumerate 𝒞={C1,,Ck}\mathscr{C}=\{C_{1},\dots,C_{k}\} and for each ii fix an element giCig_{i}\in C_{i}. First, obviously we will define ψ=σ\psi=\sigma on each Ci×CiC_{i}\times C_{i}. Next, define ψ(g1,g2)\psi(g_{1},g_{2}) to be an element of Aut(I,m)\operatorname{Aut}(I,m) such that

gC1σ(g1,g)1πandψ(g1,g2)1(gC2σ(g2,g)1π)\bigvee_{g\in C_{1}}\sigma(g_{1},g)^{-1}\pi\qquad\text{and}\qquad\psi(g_{1},g_{2})^{-1}\left(\bigvee_{g\in C_{2}}\sigma(g_{2},g)^{-1}\pi\right)

are independent. Then, define ψ\psi on all of (C1C2)×(C1C2)(C_{1}\cup C_{2})\times(C_{1}\cup C_{2}) by setting

ψ(h1,h2)\displaystyle\psi(h_{1},h_{2})\ =σ(g2,h2)ψ(g1,g2)σ(h1,g1)and\displaystyle=\ \sigma(g_{2},h_{2})\circ\psi(g_{1},g_{2})\circ\sigma(h_{1},g_{1})\qquad\text{and}
ψ(h2,h1)\displaystyle\psi(h_{2},h_{1})\ =ψ(h1,h2)1\displaystyle=\ \psi(h_{1},h_{2})^{-1}

for any h1C1,h2C2h_{1}\in C_{1},h_{2}\in C_{2}. Continue this definition inductively, making each new step independent of all the steps that came before it. If ψ\psi has been defined on (C1Cj)×(C1Cj)\left(C_{1}\cup\dots\cup C_{j}\right)\times\left(C_{1}\cup\dots\cup C_{j}\right), then define ψ(g1,gj+1)\psi(g_{1},g_{j+1}) to be an element of Aut(I,m)\operatorname{Aut}(I,m) such that

gC1Cjψ(g1,g)1πandψ(g1,gj+1)1(gCj+1σ(gj+1,g)1π)\bigvee_{g\in C_{1}\cup\dots\cup C_{j}}\psi(g_{1},g)^{-1}\pi\qquad\text{and}\qquad\psi(g_{1},g_{j+1})^{-1}\left(\bigvee_{g^{\prime}\in C_{j+1}}\sigma(g_{j+1},g^{\prime})^{-1}\pi\right)

are independent. Then extend the definition of ψ\psi to all of (C1Cj+1)×(C1Cj+1)(C_{1}\cup\dots\cup C_{j+1})\times(C_{1}\cup\dots\cup C_{j+1}) in the exact same way.

At the end of this process, ψ\psi has been defined on (C1Ck)×(C1Ck)=H×H(C_{1}\cup\cdots\cup C_{k})\times(C_{1}\cup\cdots\cup C_{k})=H\times H, and it satisfies the cocycle condition by construction. To verify that it also satisfies the independence condition, notice that the construction has guaranteed that

hCψ(g1,h)1π\bigvee_{h\in C}\psi(g_{1},h)^{-1}\pi

are independent partitions as CC ranges over 𝒞\mathscr{C}. To get the same conclusion for an arbitrary base point h0h_{0}, pull everything back by the fixed map ψ(h0,g1)\psi(h_{0},g_{1}). Because this map is measure preserving, pulling back all of the partitions by it preserves their independence. ∎

Now we would like to take this information about cocycles defined on patterns and use it to produce cocycles defined on the actual space XX. Define the map σH,𝒞:XH,𝒞Ω1H,𝒞\sigma^{H,\mathscr{C}}:X_{H,\mathscr{C}}\to\Omega_{1}^{H,\mathscr{C}} by σxH,𝒞(g1,g2):=α0(Tg1x,Tg2x)\sigma^{H,\mathscr{C}}_{x}(g_{1},g_{2}):=\alpha_{0}(T^{g_{1}}x,T^{g_{2}}x). Note that this is a measurable map because α0\alpha_{0} is a measurable cocycle.

By Theorem A.1 applied to the measure =(σH,𝒞)(μ(|XH,𝒞))Prob(Ω1H,𝒞)\mathbb{P}=(\sigma^{H,\mathscr{C}})_{*}(\mu(\cdot\,|\,X_{H,\mathscr{C}}))\in\operatorname{Prob}(\Omega_{1}^{H,\mathscr{C}}), we get a measurable map EH,𝒞:Ω1H,𝒞Ω2H,𝒞,indE^{H,\mathscr{C}}:\Omega_{1}^{H,\mathscr{C}}\to\Omega_{2}^{H,\mathscr{C},\text{ind}} defined \mathbb{P}-a.e. such that EH,𝒞(σ)E^{H,\mathscr{C}}(\sigma) extends σ\sigma. Denote the composition EH,𝒞σH,𝒞E^{H,\mathscr{C}}\circ\sigma^{H,\mathscr{C}} by ψH,𝒞\psi^{H,\mathscr{C}} and write the image of xx under this map as ψxH,𝒞\psi^{H,\mathscr{C}}_{x}. To summarize, for every pattern (H,𝒞)(H,\mathscr{C}), there is a measurable map ψH,𝒞:XH,𝒞Ω2H,𝒞,ind\psi^{H,\mathscr{C}}:X_{H,\mathscr{C}}\to\Omega_{2}^{H,\mathscr{C},\text{ind}} defined μ\mu-a.e. with the property that ψxH,𝒞\psi^{H,\mathscr{C}}_{x} extends σxH,𝒞\sigma^{H,\mathscr{C}}_{x}.

It is now natural to define our desired cocycle α\alpha on the equivalence relation R2R_{2} by the formula α(x,Tgx):=ψxpat2(x)(e,g)\alpha(x,T^{g}x):=\psi^{\operatorname{pat}_{2}(x)}_{x}(e,g). It is then immediate to verify the two properties of α\alpha claimed in the statement of Proposition 4.7. The fact that α\alpha agrees with α0\alpha_{0} on R1R_{1} follows from the fact that ψH,𝒞\psi_{H,\mathscr{C}} extends σH,𝒞\sigma^{H,\mathscr{C}} and the claimed independence property of α\alpha translates directly from the independence property that the ψxH,𝒞\psi^{H,\mathscr{C}}_{x} were constructed to have (see also the discussion after step 6 in the sketched proof of Proposition 4.7). Also, α\alpha is measurable because for each fixed gg, the map xα(x,Tgx)x\mapsto\alpha(x,T^{g}x) is simply a composition of other maps already determined to be measurable. The only problem is that α\alpha, when defined in this way, need not satisfy the cocycle condition. To see why, observe that the cocycle condition α(x,Thx)=α(Tgx,Thx)α(x,Tgx)\alpha(x,T^{h}x)=\alpha(T^{g}x,T^{h}x)\circ\alpha(x,T^{g}x) is equivalent to the condition

(3) ψxpat2(x)(e,h)=ψTgxpat2(Tgx)(e,hg1)ψxpat2(x)(e,g).\psi_{x}^{\operatorname{pat}_{2}(x)}(e,h)\ =\ \psi_{T^{g}x}^{\operatorname{pat}_{2}(T^{g}x)}(e,hg^{-1})\circ\psi_{x}^{\operatorname{pat}_{2}(x)}(e,g).

But in defining the maps ψH,𝒞\psi^{H,\mathscr{C}}, we have simply applied Theorem A.1 arbitrarily to each pattern separately, so ψpat2(x)\psi^{\operatorname{pat}_{2}(x)} and ψpat2(Tgx)\psi^{\operatorname{pat}_{2}(T^{g}x)} have nothing to do with each other. However, we can fix this problem with a little extra work, and once we do, we will have defined α:R2Aut(I,m)\alpha:R_{2}\to\operatorname{Aut}(I,m) with all of the desired properties.

Start by declaring two patterns equivalent if they are translates of each other, and fix a choice of one pattern from each equivalence class. Since there are only countably many patterns in total, there is no need to worry about how to make this choice. For each representative pattern (H0,𝒞0)(H_{0},\mathscr{C}_{0}), apply Theorem A.1 arbitrarily to get a map ψH0,𝒞0\psi^{H_{0},\mathscr{C}_{0}}. This does not cause any problems because two patterns that are not translates of each other can not appear in the same orbit (this follows from the easy fact that pat2(Tgx)=g1pat2(x)\operatorname{pat}_{2}(T^{g}x)=g^{-1}\cdot\operatorname{pat}_{2}(x)), so it doesn’t matter that their ψ\psi maps are not coordinated with each other. For convenience, let us denote the representative of the equivalence class of pat2(x)\operatorname{pat}_{2}(x) by rp(x)\operatorname{rp}(x). Now for every xXx\in X, let g(x)g^{*}(x) be the unique element of GG with the property that pat2(Tg(x)x)=rp(x)\operatorname{pat}_{2}(T^{g^{*}(x)}x)=\operatorname{rp}(x). Notice that the maps gg^{*} and rp\operatorname{rp} are both constant on each subset XH,𝒞X_{H,\mathscr{C}} and are therefore measurable.

Now for an arbitrary pattern (H,𝒞)(H,\mathscr{C}) and xXH,𝒞x\in X_{H,\mathscr{C}}, we define the map ψH,𝒞\psi^{H,\mathscr{C}} by

ψxH,𝒞(g,h):=ψTg(x)xrp(x)(gg(x)1,hg(x)1).\psi_{x}^{H,\mathscr{C}}(g,h)\ :=\ \psi_{T^{g^{*}(x)}x}^{\operatorname{rp}(x)}(g\cdot g^{*}(x)^{-1},h\cdot g^{*}(x)^{-1}).

Notice that this is still just a composition of measurable functions, so ψH,𝒞\psi^{H,\mathscr{C}} is measurable. All that remains is to verify that this definition satisfies (3). The right hand side of (3) is

ψTg(Tgx)Tgxrp(Tgx)(eg(Tgx)1,hg1g(Tgx)1)ψTg(x)xrp(x)(eg(x)1,gg(x)1)\displaystyle\psi_{T^{g^{*}(T^{g}x)}T^{g}x}^{\operatorname{rp}(T^{g}x)}(eg^{*}(T^{g}x)^{-1},hg^{-1}g^{*}(T^{g}x)^{-1})\ \circ\ \psi_{T^{g^{*}(x)}x}^{\operatorname{rp}(x)}(eg^{*}(x)^{-1},gg^{*}(x)^{-1})
=\displaystyle=\ ψTg(x)g1Tgxrp(x)((g(x)g1)1,hg1(g(x)g1)1)ψTg(x)xrp(x)(g(x)1,gg(x)1)\displaystyle\psi_{T^{g^{*}(x)g^{-1}}T^{g}x}^{\operatorname{rp}(x)}((g^{*}(x)g^{-1})^{-1},hg^{-1}(g^{*}(x)g^{-1})^{-1})\ \circ\ \ \psi_{T^{g^{*}(x)}x}^{\operatorname{rp}(x)}(g^{*}(x)^{-1},gg^{*}(x)^{-1})
=\displaystyle=\ ψTg(x)xrp(x)(gg(x)1,hg(x)1)ψTg(x)xrp(x)(g(x)1,gg(x)1)\displaystyle\psi_{T^{g^{*}(x)}x}^{\operatorname{rp}(x)}(gg^{*}(x)^{-1},hg^{*}(x)^{-1})\ \circ\ \psi_{T^{g^{*}(x)}x}^{\operatorname{rp}(x)}(g^{*}(x)^{-1},gg^{*}(x)^{-1})
=\displaystyle=\ ψTg(x)xrp(x)(g(x)1,hg(x)1),\displaystyle\psi_{T^{g^{*}(x)}x}^{\operatorname{rp}(x)}(g^{*}(x)^{-1},hg^{*}(x)^{-1}),

which is by definition equal to the left hand side of (3) as desired.

This, together with the discussion surrounding (3), shows that if we construct the maps ψH,𝒞\psi^{H,\mathscr{C}} in this way, then making the definition α(x,Tgx)=ψxpat2(x)(e,g)\alpha(x,T^{g}x)=\psi_{x}^{\operatorname{pat}_{2}(x)}(e,g) gives us a true measurable cocycle with all of the desired properties. Finally, to extend the definition of α\alpha to RnR_{n} with n3n\geq 3, repeat the exact same process, except it is even easier because there is no need to force any independence. The maps ψH,𝒞\psi^{H,\mathscr{C}} only need to be measurable selections into the space Ω2H,𝒞\Omega_{2}^{H,\mathscr{C}}, and then everything else proceeds in exactly the same way.

References

  • [AGTW21] Tim Austin, Eli Glasner, Jean-Paul Thouvenot, and Benjamin Weiss. An ergodic system is dominant exactly when it has positive entropy. arXiv:2112.03800, 2021.
  • [CFW81] Alain Connes, Jacob Feldman, and Benjamin Weiss. An amenable equivalence relation is generated by a single transformation. Ergodic Theory Dynam. Systems, 1(4):431–450, 1981.
  • [Fre06] D. H. Fremlin. Measure theory. Vol. 4. Torres Fremlin, Colchester, 2006. Topological measure spaces. Part I, II, Corrected second printing of the 2003 original.
  • [Gla03] Eli Glasner. Ergodic theory via joinings, volume 101 of Mathematical Surveys and Monographs. American Mathematical Society, Providence, RI, 2003.
  • [GTW21] E. Glasner, J.-P. Thouvenot, and B. Weiss. On some generic classes of ergodic measure preserving transformations. Trans. Moscow Math. Soc., 82:15–36, 2021.
  • [Kec10] Alexander S. Kechris. Global aspects of ergodic group actions, volume 160 of Mathematical Surveys and Monographs. American Mathematical Society, Providence, RI, 2010.
  • [KT97] Anatole Katok and Jean-Paul Thouvenot. Slow entropy type invariants and smooth realization of commuting measure-preserving transformations. Ann. Inst. H. Poincaré Probab. Statist., 33(3):323–338, 1997.
  • [MO85] Jean Moulin Ollagnier. Ergodic theory and statistical mechanics, volume 1115 of Lecture Notes in Mathematics. Springer-Verlag, Berlin, 1985.
  • [Orn70] Donald Ornstein. Bernoulli shifts with the same entropy are isomorphic. Advances in Math., 4:337–352, 1970.
  • [Ros88] A. Rosenthal. Finite uniform generators for ergodic, finite entropy, free actions of amenable groups. Probab. Theory Related Fields, 77(2):147–166, 1988.
  • [Sew19] Brandon Seward. Krieger’s finite generator theorem for actions of countable groups I. Invent. Math., 215(1):265–310, 2019.
  • [Ver18] Roman Vershynin. High-dimensional probability, volume 47 of Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge University Press, Cambridge, 2018. An introduction with applications in data science, With a foreword by Sara van de Geer.