A family of stable diffusions
Fran\c{c}ois Ledrappier, Lin Shu

TL;DR
This paper studies a family of diffusions on negatively curved manifolds' tangent bundles, showing that as a parameter tends to negative infinity, the stationary measures converge to the uniform measure.
Contribution
It introduces a new family of leafwise diffusions on negatively curved manifolds and proves their stationary measures converge to the Lebesgue measure as the parameter goes to negative infinity.
Findings
Stationary measures converge to Lebesgue measure as λ→ -∞
The operator combines leafwise Laplacian and geodesic flow vector field
Unique stationary measure exists for each λ
Abstract
Consider a closed connected Riemannian manifold with negative curvature. The unit tangent bundle is foliated by the (weak) stable foliation of the geodesic flow. Let be the leafwise Laplacian for and let be the geodesic spray, i.e., the vector field that generates the geodesic flow. For each , the operator generates a diffusion for . We show that, as , the unique stationary probability measure for the leafwise diffusion of converges to the normalized Lebesgue measure on .
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMathematical Dynamics and Fractals · Geometric Analysis and Curvature Flows · Geometry and complex manifolds
A family of stable diffusions
François Ledrappier and Lin Shu
François Ledrappier, Sorbonne Université, UMR 8001, LPSM, Boîte Courrier 158, 4, Place Jussieu, 75252 PARIS cedex 05, France
Lin Shu, LMAM, School of Mathematical Sciences, Peking University, Beijing 100871, People’s Republic of China
Abstract.
Consider a closed connected Riemannian manifold with negative curvature. The unit tangent bundle is foliated by the (weak) stable foliation of the geodesic flow. Let be the leafwise Laplacian for and let be the geodesic spray, i.e., the vector field that generates the geodesic flow. For each , the operator generates a diffusion for . We show that, as , the unique stationary probability measure for the leafwise diffusion of converge to the normalized Liouville measure on .
Key words and phrases:
Harmonic measure, Liouville measure
2010 Mathematics Subject Classification:
37D40, 58J65
The second author was partially supported by NSFC (No.11331007 and No.11422104).
1. Statement of the result
Let be an -dimensional closed connected negatively curved Riemannian manifold. We shall study a class of probability measures on the unit tangent bundle which interpolates between the Burger-Roblin measure (whose transversal distribution in the weak unstable leaves is the same as the one for the maximal entropy measure of the geodesic flow) and the normalized Liouville measure.
Let be the the -invariant extension of to the universal cover space . The fundamental group acts on as isometries such that . Let be the geometric boundary of , i.e., the collection of equivalent classes of unit speed geodesic rays that remain a bounded distance apart. Since is negatively curved, there is a natural homeomorphism from to the unit sphere in the tangent space at , sending to the initial vector of the geodesic ray starting from in the equivalent class of ([EO73]). Hence we identify the unit tangent bundle with .
For each , its (weak) stable manifold for the geodesic flow on , denoted , is the collection of initial vectors of geodesic rays in the equivalent class of and can be identified with . The collection of form the stable foliation of . Extend the action of continuously to . Then can be identified with the quotient of under the diagonal action of . Since for , the collection of quotients of defines a lamination on , the so-called (weak) stable foliation of . The leaves of are discrete quotients of , which are naturally endowed with the Riemannian metric induced from . For , let be the leaf of containing . Then is a immersed submanifold of depending Hölder continuously on in the -topology ([Shu87]).
Let be a Markovian operator (i.e., ) on (the smooth functions on) with continuous coefficients. It is said to be subordinated to the stable foliation , if for every smooth function on , the value of at only depends on the restriction of to . A Borel probability measure on is called -harmonic if it satisfies
[TABLE]
for every smooth function on . Extend to be a -equivariant operator on , which we shall denote with the same symbol, and, for , let denote the laminated operator of on . Call weakly coercive, if its lifted leafwise operators , , are weakly coercive in the sense that there are a number (independent of ) and, for each , a positive -superharmonic function on (i.e., ). It is known that for a weakly coercive operator, there exists a unique harmonic measure ([Gar83], [Ham97]).
One classical example of weakly coercive operator is , the laminated Laplacian for , whose unique -harmonic measure is always referred to as the harmonic measure ([Gar83]). Many interesting open problems in dynamics are concerned with the relationship of the harmonic measure with the normalized Liouville measure and the normalized maximal entropy measure for the geodesic flow (Bowen-Margulis measure), and the applications of these relations to the characterizations of the locally symmetric property of the underlying space (see [Kat82, Sul83] and see also [Kai90, Led95, Yue94] for more descriptions).
In this paper, we are interested in the family , where is a real number and is the geodesic spray. Since is tangent to the stable manifold, the operators are subordinated to the stable foliation.
Let denote the volume entropy of :
[TABLE]
where is the ball of radius in and is the volume. The volume entropy coincides with the topological entropy of the geodesic flow on since has negative sectional curvature ([Man79]). For , the operator is weakly coercive ([Ham97]) and hence there is a unique -harmonic measure, which we will denote by .
Clearly, is the classical harmonic measure. When , tends to the Burger-Roblin measure the unique harmonic measure for the Laplacian subordinated to the strong stable foliation ([LS, Proposition 4.10], the uniqueness of such a measure is due to Kaimanovich ([Kai88])). When , the main result of this paper is:
Theorem 1.1**.**
Let be an -dimensional closed connected negatively curved Riemannian manifold. As , the -harmonic measure converge to the normalized Liouville measure on .
Roughly speaking, since the measure is -harmonic, it is also stationary for the operator (see Section 2 for a precise definition). In particular, any limit measure of the family as is invariant under the (reversed) geodesic flow. For a limit of random perturbations of a conservative Anosov flow, the convergence of the stationary measures to a SRB measure has been shown by several authors, in particular Kifer ([Kif74]), under the condition that the operator is hypoelliptic, so that the Markov kernels have a density with respect to Lebesgue on We cannot apply this to show Theorem 1.1 since in our case, the operators are subordinated to the stable foliation and the Markov kernels are singular. Another approach by Cowieson-Young ([CY05]) uses the variational principle from thermodynamical formalism and we show that such an approach can be used in our case in spite of the singularity of the Markov kernels. We shall show any limiting measure of (as ) satisfies Pesin entropy formula for the geodesic flow. Theorem 1.1 follows since the normalized Liouville measure on is indeed characterized by Pesin formula among invariant measures for the geodesic flow ([BR75]). More precisely, we will define a stochastic flow on a bigger space and consider a special stationary measure for that stochastic flow that projects to on . We then introduce a relative entropy like quantity for and show , the entropy of for the reversed geodesic flow, satisfies
[TABLE]
This can be done (see Proposition 3.2) along the lines of Cowieson-Young ([CY05]) and Kifer-Yomdin ([KY88]) for the upper semi-continuity of the relative entropy. To conclude Theorem 1.1, we verify that has a lower bound given by Pesin entropy integral for using the SRB like properties of (see Proposition 3.1) and their nice convergence property inherited from our stochastic flow system (see Proposition 2.7).
We arrange the paper as follows. In Section 2, we will give preliminaries on the properties of the -harmonic measures and the dynamics of the associated stochastic flows. In Section 3, we will introduce the random system to define and reveal its relation with Pesin entropy formula. The upper semi-continuity equality (1.1) will be shown in the final section.
2. Harmonic measure and stochastic flow
We begin with some basic understanding of the -harmonic measure () by analyzing the dynamics of its -invariant extension on , which is denoted by .
Consider the -equivariant extension of to , which we shall denote by the same symbol. It defines a Markovian family of probabilities on , the space of paths of (where ), equipped with the smallest -algebra for which the projections are measurable. Indeed, for , the laminated operator on can be regarded as an operator on with corresponding heat kernel functions , . Define
[TABLE]
where is the Dirac function at . Then the diffusion process on with infinitesimal operator is given by a Markovian family , where for every and every Borel set we have
[TABLE]
Proposition 2.1**.**
([Gar83, Ham97]) With the above notations, the following are true for .
- i)
The measure satisfies, for all with compact support,
[TABLE]
- ii)
The measure on is invariant under all the shift maps on , where for and .
- iii)
The measure can be expressed locally at as , where is a finite measure on without atoms and, for -almost every , is a positive function on satisfying the equation
[TABLE]
where we continue to use to denote the geodesic spray for .
Remark 2.2**.**
Let be any weak* limit of the probability measures on as and let be the -invariant extension of to . Clearly, Theorem 1.1 follows if we can show has absolutely continuous conditional measures on leafs . But this does not follow directly from equation (2.1) since the Harnack inequality used for each finite is worse and worse when goes to and hence we have less and less control of the density functions .
For Theorem 1.1, we will further explore the invariant dynamics of from the stochastic flow point of view and use it to establish the entropy formula for the limit measures.
We first recall some classical results from the theory of Stochastic Differential Equations (SDE). Let be a -dimensional Euclidean Brownian motion starting from the origin with the Euclidean Laplacian generator (so the covariance matrix is ) and let denote the corresponding Wiener space. Let , where are bounded vector fields on a smooth finite dimensional Riemannian manifold . The pair consists of a stochastic dynamical system (SDS) on and it is ( or ) if all are bounded ([Elw82]). An -valued semimartingale defined up to a stopping time is said to be a solution of the following Stratonovich SDE
[TABLE]
if for all ,
[TABLE]
The solution to (2.2) always exists and is essentially unique when all ’s are bounded ([Elw82]). Moreover, for almost all , the mapping
[TABLE]
has the following property.
Proposition 2.3**.**
([Elw82, Chapter VIII]) Let be a SDS on , where or . There is a version of the explosion time map , defined for , and a version of , defined when , such that if , then the following are true for each .
- i)
The set is open in .
- ii)
For almost all , and , we have the cocycle equality
[TABLE]
where is the shift transformation on :
[TABLE]
- iii)
The map is (or when ) and is a diffeomorphism onto an open subset of . Moreover, the map of into (or when ) mappings of is continuous.
- iv)
For , denote by the -th tangent map of . Then, for any , there is a bounded function , which depends on , and the bounds of , and such that , where is the -norm and denotes the -th covariant derivative and is the curvature tensor.
When , the solution process to (2.2) is said to be non-explosive. In this case, the maps induce a kind of semi-flow on , which we shall call the stochastic flow associated to the SDS or (2.2). A direct consequence of Proposition 2.3 is the following regularity of a one-parameter family of stochastic flows.
Corollary 2.4**.**
Let be a one-parameter family of SDS on with . Assume ’s are all on in the product differentiable structure. Then for any , and , is in the space of maps of .
Proof.
Let be the solution for the SDS . Then solves the new SDS on . The regularity in is a straightforward application of Proposition 2.3 by treating as a part of the initial value. ∎
Corollary 2.4 does not apply when we only have Hölder continuity of in . However, it is still possible to discuss the regularities of by using one criterion from Kolmogorov:
Proposition 2.5**.**
(cf. [Kun90, Theorem 1.4.1]) Let and let be a one parameter family of random processes on a complete metric space, where is some bounded -dimensional Euclidean domain. Suppose there are positive constants , with , and such that for all and ,
[TABLE]
then has a continuous modification with respect to the parameter .
Let , be arbitrary positive numbers less than . Then for any hypercube in , there exists a positive random variable with such that for any and ,
[TABLE]
Next, we consider and . Extend to be a -equivariant operator on , which we shall denote by the same symbol. Its associated leafwise diffusions can be visualized using the classical Eells-Elworthy-Malliavin construction.
Recall that, for we have identified the stable manifold with and endowed it with the Riemannian metric on . In the same way, we can identify an orthogonal frame in the tangent space with , where is an element in , the collection of the orthogonal frames in Set for the bundle of such stable orthogonal frames:
[TABLE]
We carry to all the Riemannian geometry from . In particular, if denotes the horizontal lift from to we can define the horizontal lift from to by for .
Let be an -dimensional Euclidean Brownian motion starting from the origin with the Euclidean Laplacian generator (and covariance matrix ) and let be the Wiener space. Set as the horizontal lift of to . We can realize the diffusion for as the projection to of the non-explosive solution process (the non-explosiveness follows since has Ricci curvature uniformly bounded from below) to the Stratonovich SDE on :
[TABLE]
Let be the natural projection and denote for the foliation of that projects on . Let be the space of homeomorphisms of that preserve the leaves of and are -diffeomorphisms along the leaves. We endow with the topology: are close if, for all , the -germs of and are uniformly close on compact sets and the -germs of and are uniformly close on compact sets.
Proposition 2.6**.**
With the above notations, for -a.e. , for all , , there exists such that the following hold true.
- i)
For all is a solution of the equation (2.3); in particular, for all , is measurable with respect to the -algebra generated by 2. ii)
For almost all all , . 3. iii)
For all , 4. iv)
The map is continuous in 5. v)
For fixed ,
[TABLE]
Proof.
Since both and are tangent to , the solution to (2.3) is constrained in . For fixed and , equation (2.3) can be seen as a SDE on and is solvable with infinite explosion time. Hence properties i) and ii) are given by Proposition 2.3. Property iii) follows from the uniqueness of the solution to (2.3). Considering as a parameter, we get the continuity of the solution in by Corollary 2.4. Considering as a parameter, the leaves of and , vary Hölder continuously with respect to . Hence, by a standard estimation using Burkholder inequality and Gronwall lemma and applying Proposition 2.5, we can obtain the continuity of the solution to (2.3) in , so that we can consider it as an element of . This shows iv). Finally we show v). Using a fundamental domain for the action of on , we may regard as a subset of . By the -equivariance property of the diffusion, we can restrict in the left hand side of (2.4) to . By continuity of in , the compactness of and Proposition 2.5, for (2.4), it suffices to show for each and ,
[TABLE]
This is an application of Proposition 2.3 iv) by using the SDE (2.3). ∎
Equation (2.3) for is the ordinary differential equation . Its solution is the extension of the reversed geodesic flow to by parallel transportation along the geodesics, and is called the reversed stable frame flow. Write for the probability measure on that is the distribution of in Proposition 2.6. Every element preserves each leaf and is a diffeomorphism along it. We write for the Jacobian determinant of the tangent map of at . For later use, we state a proposition concerning the limit behavior of when .
Proposition 2.7**.**
With the above notations, the following are true.
- i)
For -a.e. , all , as converge to in , in particular, converge to the time 1 map of the reversed stable frame flow.
- ii)
For any and positive integers,
[TABLE]
- iii)
For any ,
[TABLE]
- iv)
We have
[TABLE]
and the convergence is locally uniform in .
Proof.
The proof of continuity of the solution to (2.3) in Proposition 2.6 extends to . This shows i). When , . For ii), note that is finite by Proposition 2.6 v) (applied for ). Then is also finite by using the continuity in in the estimation of the expectation in (2.5) in the proof of Proposition 2.6 v). Similarly, we have the continuity in of the tangent maps (and their derivatives in ) of the solution to (2.3). Following Proposition 2.3 iv), it is easy to deduce from (2.3) the continuity in of the norm of the tangent maps and of the Jacobian of the first order tangent map. This shows iii) and iv). ∎
It follows from Proposition 2.6 i) and ii) that we can consider , as an independent product of the homeomorphisms and that we can apply the theory of independent random mappings. Let be the projection map from to . For any compactly supported function on , and any frame in the fiber , we have
[TABLE]
Let be the measure on that projects on on and such that the conditional measures on fibers of the projection map are proportional to the Lebesgue measure on -dimensional frames. The following is true.
Proposition 2.8**.**
The measure is stationary under , i.e., it satisfies, for any compactly supported function on ,
[TABLE]
Moreover, the conditional measures of with respect to the leaves of the foliation are absolutely continuous with respect to Lebesgue.
Proof.
The stationarity follows from relation (2.7), the stationarity of and the fact that the flow preserves the orthogonal group on the fibers ([CE86, Lemma 3.1]). The leaves of are made of whole fibers and project on the leaves of . The conditional measures on the leaves of are given by the extension by Lebesgue on the fibers of the conditional measures on the leaves of By Proposition 2.1 iii), they are therefore absolutely continuous. ∎
Let be the quotient of the map by the action of and let denote the corresponding quotient foliation of . Let be the space of homeomorphisms of that preserve the leaves of and are -diffeomorphisms along the leaves. We endow with the topology: are close if, for all , the -germs of and are uniformly close and the -germs of and are uniformly close. By Proposition 2.6 iii), we can consider as a probability measure on .
We define the measure on such that its -invariant extension to is . We see that is a probability measure that projects to on and is such that the conditional measures on fibers of are proportional to Lebesgue on -dimensional frames. As a consequence of Proposition 2.8, we have
Corollary 2.9**.**
The measure is stationary under , i.e., it satisfies, for any continuous function on ,
[TABLE]
Moreover, the conditional measures of with respect to the leaves of the foliation are absolutely continuous with respect to Lebesgue.
We are interested in the limit measures of ’s when goes to . Let be such a limit point and let be the probability measure on that projects to on and is such that the conditional measures on fibers of are proportional to the Lebesgue measure on -dimensional frames. Then is the limit of along the same subsequence. Let be the reversed stable frame flow. Then is invariant under . To show is Liouville, it suffices to show the conditional measures of on the leaves of are absolutely continuous with respect to Lebesgue. But this does not follow from Corollary 2.9 by the same reason that we mentioned in Remark 2.2. What we are going to do in the next section is to analyze the entropy related to the natural random dynamics for that arises in the stationarity relation (2.8).
3. Entropy of random mappings
We consider the action on of the random elements of with distribution Namely, let endowed with the product measures (with the convention that is the Dirac measure at ) and the shift transformation . On the space define the transformation by:
[TABLE]
For let be the stationary measure from Corollary 2.9 and for let be some weak* limit of as For the measure is invariant under the transformation
Let be a measurable partition of with finite or countably many elements. We assume . For , set and for , where denotes the join of partitions, i.e., the refinement of partitions by taking intersections. For , let denote the element of that contains . We define the entropy for as
[TABLE]
where
[TABLE]
For a formal definition of , we should use a measurable partition subordinated to (see Section 4 for details). But the value of does not depend on the choice of such a subordinated partition and is thus well-defined. Observe that
[TABLE]
Using the random Ruelle inequality (cf. [BB95, Kif86]), we obtain that is bounded independent of . Hence is finite. Note also that is absolutely continuous with respect to Lebesgue with a smooth density.
For the computation of , we can restrict the conditional measure to the local stable leaf for small enough. Recall that preserves each leaf and is a diffeomorphism along it. Write for the Jacobian determinant of the tangent map of at . We will conclude Theorem 1.1 from the following two propositions.
Proposition 3.1**.**
For ,
[TABLE]
Proposition 3.2**.**
Let be a sequence such that and converge to the probability measure as , and let be as above. Then
[TABLE]
The proofs of Proposition 3.1 and Proposition 3.2 use completely different techniques and will be presented in this section and the following section, respectively.
In the following, we shall use to denote the entropy of a measurable partition with respect to a measure of some space and use to denote the entropy of conditioned on some measurable partition , whenever these entropies are well-defined. We shall denote for the dimension of ; for , we shall write
[TABLE]
and for the Jacobian determinant of the tangent map of at . Clearly, we have for .
Proof of Theorem 1.1.
Let , be a sequence such that and converge to the probability measure as , and let be as above. Recall that is the time one map of the reversed frame flow on which is a compact isometric extension of the time one map of the reversed geodesic flow on Hence,
[TABLE]
On the other hand, we have:
[TABLE]
Assume Proposition 3.1 and Proposition 3.2 hold true. Then,
[TABLE]
where the last equality holds by Proposition 2.7 iii). Altogether, we obtain
[TABLE]
Note that is the central unstable foliation for , so that is the integral of the sum of the nonnegative exponents of for ; neither the direction of the flow nor the vertical directions tangent to the fibers provide positive exponents, so that is the integral of the sum of the positive exponents of for . By [BR75], is the normalized Liouville measure. ∎
3.1. Proof of Proposition 3.1
The deterministic diffeomorphism version estimation of (3.2) is standard using Pesin theory (cf. [Man83]). But this cannot be used directly since we are in the random and non-invertible case.
Clearly, Proposition 3.1 would follow if we can show the sample measures are SRB. This approach might work since in a similar context, Blumenthal-Young ([BY19]) showed the sample measures are SRB. We didn’t try that way since we don’t need that strong conclusion and the intuition for Proposition 3.1 is relatively simpler.
For a non-invertible endomorphism of a compact manifold preserving an absolutely continuous measure, the corresponding measure theoretical entropy is at least the integral of the logarithm of the Jacobian, which coincides with the so-called folding entropy (cf. [Rue96], [LS11]). Proposition 3.1 is intuitively a random conditional version of this phenomenon. But it might be subtle since we are considering the conditional measures and are in the random case. So we will give some details for the key steps.
We first recall some notations and results concerning Pesin local Lyapunov charts theory for random diffeomorphisms. In many places, we have to take invariant variables instead of constants since our system is invariant, but not necessarily ergodic in general.
Lemma 3.3**.**
([Ose68]) For each , there is a measurable with such that for there exist and, for , and a filtration
[TABLE]
with the following properties:
- i)
all of ’s depend measurably on ;
- ii)
* for ;*
- iii)
* and ;*
- iv)
.
Lemma 3.4**.**
(cf. [LQ95, Chapter III, Section 1]) For each , given a small enough positive -invariant function on , there is a positive function on such that for ,
[TABLE]
a positive constant and a sequence Euclidean metrics on such that for all ,
- i)
, where is the Riemannian norm on ;
- ii)
* is defined for with ;*
- iii)
* is and \|D^{(2)}{\bf F}_{(\underline{\varphi},u),n}\|^{\prime}_{(\underline{\varphi},u),n,n+1}<\kappa\big{(}(\underline{\varphi},u),n\big{)}, where by we mean the norm of the tangent map calculated using and ;*
- iv)
the map satisfies
[TABLE]
- v)
the map satisfies
[TABLE]
for all . Moreover, for , the spaces , , generate .
(Since elements of preserve the leaves of , Lemma 3.4 can be obtained as in [LQ95, Chapter III, Section 1]) using the natural auxiliary charts and Lemma 3.3.)
For Proposition 3.1, we shall follow Mañé ([Man83]) to give a local version of (3.2) for Bowen balls defined using the norms in Lemma 3.4 and then compare it with local entropy for special partitions. Note that we are in the non-invertible case, is not invariant (i.e., for , does not equal to in general). To overcome this deficiency, we will pick up a set with measure close to 1 and define modified Bowen balls associated to .
Let , be fixed. Choose as in Lemma 3.4. For any , we choose a measurable set with as follows. By the ergodicity of with respect to and the integrability property (2.6), for almost every ,
[TABLE]
For any , let
[TABLE]
Then there exists large such that
[TABLE]
Let be as in (3.4). For , set
[TABLE]
Choosing with and to be small enough, we can obtain a measurable set
[TABLE]
with measure greater than .
Let be as in (3.6). For almost all , it will return to under the iterations of the map for infinitely many times. Hence, for any such and ,
[TABLE]
is well-defined, where is the last non-negative time before or equal to with . For , such that and , let us define the modified random -Bowen ball (with respect to ) by
[TABLE]
where {\bf F}_{({\underline{\varphi}},u)}\big{|}_{k}:={\bf F}_{(\underline{\varphi},u),k-1}\circ\cdots\circ{\bf F}_{(\underline{\varphi},u),0}.
The following can be considered as a first step coarse local version of Proposition 3.1:
Lemma 3.5**.**
Let , , and be fixed. Choose as in Lemma 3.4. Let be as in (3.6). Then, there is a positive geometric constant such that, setting for almost all and all ,
[TABLE]
Proof.
The set is empty if Otherwise, by definition and Lemma 3.4 iv), is contained in the set of vectors such that
[TABLE]
where is the determinant of a linear mapping in the metrics and . By construction, and \kappa\big{(}\tau^{{\mathtt{N}}_{k}^{\rm A}}(\underline{\varphi},u),0\big{)}\leq\big{(}\frac{\eta}{l}\kappa_{0}\big{)}^{1/2}. Assume , i.e., . Then
[TABLE]
By chopping into pieces in between returning times and using (3.10), (3.11), we see that there exists a geometric constant such that the set is contained in the set of points such that
[TABLE]
It follows that, denoting the Lebesgue measure on ,
[TABLE]
where is a positive constant taking into account the regularity of the density for a fixed . It follows that, with our definition of
[TABLE]
Note that the partition is such that each element contains a ball with radius greater than some positive constant (see Section 4), we obtain some constant such that
[TABLE]
The estimation in (3.9) follows for small enough. ∎
By (3.5) and Lemma 3.4 i), we have
[TABLE]
So the estimation in (3.9) might be too coarse since is not a priori small compared with . But remains unchanged when we consider (3.9) for Bowen balls for any power of , hence it will not enter the lower bound estimation of entropy in (3.2).
More precisely, let be fixed. For , write
[TABLE]
Let
[TABLE]
The transformation can be identified with . We can use the same for as for , but now in (3.3) has to be changed into . So we have to choose so that Choose small enough that, if , the measurable set
[TABLE]
has measure greater than .
For almost all and , let denote the last non-negative time before or equal to such that . Similar to (3.7) and (3.8), we define
[TABLE]
and for , such that and , we define the *modified random -Bowen ball for (with respect to ) * by
[TABLE]
Then following the argument in Lemma 3.5, we obtain (observe that, by our choice of , has the same value as in Lemma 3.5)
Lemma 3.6**.**
Let , and be fixed. Let be as in (3.12) and let be as in Lemma 3.5. Then, for almost all and all ,
[TABLE]
Following Mañé ([Man83]) (see also [Thi92]), we can proceed to find partitions which have local entropy lower bound as in (3.13) in our non-invertible random setting.
Lemma 3.7**.**
Let , , be fixed. Let be as in (3.12) and let be as in Lemma 3.5. There exists a countable partition of with such that for almost all , we have and
[TABLE]
where . Consequently, for almost all ,
[TABLE]
Proof.
Clearly, (3.15) is a consequence of (3.14) and (3.13). Hence, it suffices to show (3.14). Let be as in (3.12). For , and , set
[TABLE]
By Lemma 3.4 i), we see that there exists some constant depending on the geometry of such that, for almost all and all ,
[TABLE]
Hence, to find a countable partition satisfying (3.14), it suffices to find a such that
[TABLE]
For each , let be the collection of points with as the first return time to with respect to the map . Recall that the local stable leaf depends continuously on and for each , we can choose in a continuous way a maximal separated set in . The cardinality of such sets satisfies for some . Using these points, we can further slice into such that for all , the intersection has diameter less than . The partition can be chosen to be
[TABLE]
Following [Man83], one checks that satisfies and (3.14). ∎
Proof of Proposition 3.1.
Let be fixed. In the following, we show, for every , there exists a finite measurable partition of satisfying
[TABLE]
Then, by definition of and (3.16),
[TABLE]
This concludes the proof of Proposition 3.1 since is arbitrary.
Let be such that . Let be small and let and be as in Lemma 3.7. Then for almost all , (3.15) holds true. Set
[TABLE]
For any , by our choice of in Section 4, it is true that (see Proposition 4.3)
[TABLE]
Hence, by Fatou Lemma,
[TABLE]
Since the function is integrable and , by using(3.15), we obtain, for small,
[TABLE]
Note that is such that and for any finite partition such that is finer than it,
[TABLE]
We can group the tail elements in together with some care to obtain a finite partition satisfying the requirement in (3.16). ∎
4. The proof of Proposition 3.2
Let be as in Proposition 3.2. To compare with , we first formulate the entropy (see (3.1)) in terms of some conditional entropy for the unconditional measure .
Let be a lamination of a compact metric space. A measurable partition is said to be subordinated to if its elements are bounded subsets of the leaves of with non-empty interiors in the topology of the leaf. We can construct a partition subordinated to by choosing a finite partition of into sufficiently small sets with non-empty interiors and subdivide each element of into the connected components of its intersection with the leaves. We may assume is such that each element contains a ball with radius greater than some positive constant. The partition is measurable if it is constructed as an intersection of an increasing family of finite partitions into measurable sets.
Let be a finite partition of and we assume that we have chosen as above and that refines . We may assume that the boundaries of the elements of and are all -negligible. The conditional measures in the definition of can be taken on any measurable finite partition chosen in the above way, so that
[TABLE]
Proving Proposition 3.2 amounts to proving that, if and as , then
[TABLE]
This is true, if we can show, for any , there are partitions and large, such that for all large enough,
[TABLE]
The first inequality in (4.1) can be achieved if we can find good for with being close to . So we will show the other two inequalities in (4.1) first.
We begin with the second inequality in (4.1), which is not trivial in our setting since the conditional entropy sequence is not necessarily a subadditive sequence in .
Lemma 4.1**.**
Given and as above, there exists a countable partition of such that the partition is finer than . Moreover, given , there are and such that if the diameters of the elements of are smaller than and if one can choose with
Proof.
For in the same leaf, write for the distance between and along their common leaf. For any , there are two constants and such that if and are on the same leaf and , then either or . We can ensure that as and that as Suppose and are in the same element of the partition and that and are in the same element of . If , in particular, as soon as , then and are in the same connected component of and thus in the same element of .
To obtain Lemma 4.1, it is therefore enough to take the partition of as follows: the projection on depends only on the first coordinate and is the partition where is one element of on each , we further cut into pieces of diameter smaller than .
The entropy of satisfies
[TABLE]
where is some constant depending on the geometry of . Given , we will have as soon as and the integral are sufficiently small. These two conditions can be realized by choosing small and close enough to . ∎
Proposition 4.2**.**
Given , there is and such that, for all , if the diameter of the elements of are smaller than and ,
[TABLE]
Proof.
Let be as in Lemma 4.1. Then we have that the mapping n\mapsto H_{\mu_{\rho}}\big{(}{{\mathcal{P}}}_{-n}\bigvee{{\mathcal{Q}}}_{-n}\big{|}{{\mathcal{R}}}\big{)} is subadditive. Indeed, for ,
[TABLE]
where and is defined in the same way. Moreover, by Lemma 4.1, the partition is finer than and the last term is smaller than H_{\mu_{\rho}}\big{(}{{\mathcal{P}}}_{-(n+n^{\prime})}^{-n}\bigvee{{\mathcal{Q}}}_{-(n+n^{\prime})}^{-n}\big{|}\tau^{-n}{{\mathcal{R}}}\big{)}. The desired subaddivity follows by invariance of under Hence (4.2) follows since
[TABLE]
∎
Proposition 4.3**.**
Let and let be as in Proposition 4.2. Then
[TABLE]
Proof.
Let be as in Lemma 4.1. Recall that
[TABLE]
Hence,
[TABLE]
∎
Next we show the last inequality in (4.1). For this, we first state the results extending to our context the classical results of [Bow72], [Yue94] and [Buz97] (compare with [CY05]).
For and , define the random -Bowen ball by
[TABLE]
The following notion was introduced by Bowen ([Bow72]) for a single map and by Cowieson-Young ([CY05]) in the random case. Since our mappings are smooth only along the foliation , we introduce a variant by restricting to the leaves Fix and a sequence . We denote for and the smallest number of random -Bowen balls needed to cover the random -Bowen ball . We then set
[TABLE]
The function is -invariant; we denote its -a.e. value.
The following three propositions (Proposition 4.4, Proposition 4.5 and Proposition 4.6) are proven in [CY05] for the global entropy with the additional hypotheses that are supported in a fixed neighborhood of in and that converge to as , in the sense that any neighborhood of has eventually full measure for In our case, we have two extensions of the argument in [CY05]: one is that the distributions are not supported on a neighbourhood of , but there is a tail; the other extension is that our mappings are not smooth everywhere, but only along the leaves of the foliation .
Proposition 4.4**.**
Given , let be as in Proposition 4.2. Assume that the diameters of the elements of are all smaller than Then, for all close enough to
[TABLE]
Proof.
Let be a fixed positive integer and set . Since
[TABLE]
we have
[TABLE]
Following [Bow72, Section 3], we obtain in our random setting that there is some positive constant which depends on the geometry of such that for any ,
[TABLE]
Using (4.3) and (4.5), we deduce that
[TABLE]
Letting and then , we obtain the inequality (4.4). ∎
Let be a fixed positive integer. We define for and ,
[TABLE]
the smallest number of balls needed to cover the ball,
[TABLE]
and the -a.e. value of
Proposition 4.5**.**
With the above notations, we have, for all
[TABLE]
Proof.
Observe that is a subset of , so we are going to cover with balls, arbitrarily small. Start with a cover of with balls with and fix big. Let . If for all then each ball is contained in and we take these balls in our cover of . Otherwise, assume, for instance, that , we find, for each at most points such that the union of the balls cover , where is some positive constant depending on the geometry of and denotes the smallest integer greater than . Working inductively, we see that
[TABLE]
It follows that for all
[TABLE]
Finally, we get, for all , all
[TABLE]
Since Proposition 4.5 follows by letting go to infinity. ∎
Proposition 4.6**.**
Fix small and . For all there is a positive constant such that, for all ,
[TABLE]
Proof.
Fix , a sequence and . Two points are said to be -separated if
[TABLE]
It is clear that is bounded from above by , the maximal cardinality of a set of -separated points in . Consider the mappings and their standard magnifications as explained in [CY05], page 1129. In particular, we have Using this, we can estimate by following almost verbatim the argument for the proof of Proposition 3 in [CY05] (which is based on the ‘Renormalization’ Theorem in [Yom87] and a telescoping construction in [Buz97]) and obtain some constant as in [CY05, Theorem 4] such that
[TABLE]
Since are independent, the ergodic theorem gives Proposition 4.6. ∎
Corollary 4.7**.**
For any , there exists such that if , then
[TABLE]
Proof.
Fix We choose large such that , where is defined in (2.6). Fix By (4.6), Therefore,
[TABLE]
Write, for , We have, using for ,
[TABLE]
We get by integrating with respect to
[TABLE]
where are defined in (2.6). Note that, by Proposition 2.7 ii),
[TABLE]
hence
[TABLE]
Since is arbitrary, the corollary follows. ∎
Proof of Proposition 3.2.
Fix We can choose the diameters of the elements of smaller than , where is a constant depending on the local geometry of the leaves so that the diameter of the elements of are smaller than and Corollary 4.7 applies. We can also ensure that these diameters are smaller than given by Proposition 4.2. We may assume that the boundaries of the elements of and are all -negligible.
By definition, We can choose and so that
[TABLE]
Consider now , such that and as . For -a.e. each element of the partition converge in the Hausdorff metric towards the corresponding element . Note that all these elements of , and the elements of have negligible boundaries. It follows that there exists such that for
[TABLE]
The second inequality holds because the partition is finer than . By Proposition 4.2, we have, by our choice of and as soon as
[TABLE]
where the second equality follows from Proposition 4.4. Finally, using all the above inequalities (i.e., (4.7), (4.8) and (4.9)) and Corollary 4.7, we find that
[TABLE]
Proposition 3.2 follows from the arbitrariness of ∎
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1[ Bow 72] R. Bowen, Entropy-expansive maps, Trans. Amer. Math. Soc. 164 (1972), 323–331.
- 2[ BB 95] J. Bahnmüller and T. Bogenschütz, A Margulis-Ruelle inequality for random dynamical systems, Arch. Math. 64 (1995), no. 3, 246–253.
- 3[ BR 75] R. Bowen and D. Ruelle, The ergodic theory of Axiom A flows, Invent. Math. 29 (1975), no. 3, 181–202.
- 4[ BY 19] A. Blumenthal and L.-S. Young, Equivalence of physical and SRB measures in random dynamical systems, Nonlinearity 32 (2019), no. 4, 1494–1524.
- 5[ Buz 97] J. Buzzi, Intrinsic ergodicity of smooth interval maps, Israel J. Math. 100 (1997), 125–161.
- 6[ CE 86] A. P. Carverhill and K. D. Elworthy, Lyapunov exponents for a stochastic analogue of the geodesic flow, Trans. Amer. Math. Soc. 295 (1986), no. 1, 85–105.
- 7[ CY 05] W. Cowieson and L.-S. Young, SRB measures as zero-noise limits, Ergod. Th. & Dynam. Sys. 25 (2005), no. 4, 1115–1138.
- 8[ EO 73] P. Eberlein and B. O’Neill, Visibility manifolds, Pacific J. Math. 46 (1973), 45–109.
