Abstract
A central role in the variational principle of the measure preserving transformations is played by the topological pressure. We introduce subadditive pre-image topological pressure and pre-image measure-theoretic entropy properly for the random bundle transformations on a class of measurable subsets. On the basis of these notions, we are able to complete the subadditive pre-image variational principle under relatively weak conditions for the bundle random dynamical systems.
1. Introduction
The topological pressure and variational principle play an important role in statistical mechanics, ergodic theory, and dynamical systems [,,,,,,,]. The classical topological pressure for a single potential was first presented by Ruelle [] for expansive maps. Falconer [] introduced the topological pressure for a subadditive sequence of potentials on mixing repellers. Cao [] extended this notion to general compact dynamical systems. The topological pressure for nonadditive sequences of potentials has proved to be a valuable tool in the study of multifractal formalism in dimension theory, especially for non-conformal dynamical systems [,,]. In random dynamical systems (RDS), the earlier work on topological pressure for a single potential was due to Ledrappier [] and Bogenschütz []. Kifer [] generalized this notion to general bundle RDS and set up the corresponding variational principle. Using the topological pressure for a single potential, Gundlach [] derived the uniqueness of equilibrium states for a large class of functions, and recently Feng [] studied the multifractal structure of disintegrations of Gibbs measures.
The pre-image structure of a map has been studied by many authors [,,,,,,,,,]. Cheng and Newhouse et al. [] defined a new version of pre-image measure-theoretic and topological entropies and obtained a variational principle for entropy. Zeng [] presented the notion of pre-image topological pressure for a single potential f and established a pre-image variational principle as
where is the pre-image measure-theoretic entropy, is the set of T-invariant measures on the compact metric space X. Zhu [,] formulated the notions in the whole space analogous to those in the deterministic case, and deduced the variational principles for the random pre-image topological entropy and pre-image topological pressure as follows:
and for ,
where is the set of -invariant measures on .
The subadditive topological pressure has been proven to be essential to estimate the lower bound of the Hausdorff dimension of non-conformal repellers in the deterministic dynamical systems []. Thus, it should be asked if there exists a random version of pre-image thermodynamic formalism for subadditive sequences of potentials, which might have some potential applications in the study of multifractal analysis of non-conformal random dynamical systems.
In this paper, we present the notion of subadditive pre-image topological pressure for continuous random dynamical systems. By restricting the pressure function being not , we set up the variational principle as
where is the limit function of the subadditive potentials with respect to the invariant measure . As for the case of , the subadditive pre-image topological pressure is tightly relative to the limit function , which is also for all invariant measure . Our result generalizes Zhu’s notion of entropy to the pressure on a class of measurable subsets for the general bundle RDS. In particular, if we consider the special case, i.e., consists of only one point, , and the additive function sequence, then our result contains Zeng’s deterministic pre-image variational principle. We adopt Ledrappier and Walters’ method for decomposing the measure on each fiber instead of Cheng and Zeng’s approach for using the upper semi-continuous decomposition of the space in the deterministic case. Our method generalizes Kifer’s proof of the standard additive bundle random variational principle, which is a generalization of Misiurewicz’s elegant proof for the (non-relative) variational principle [].
This paper is organized as follows. In Section 2, we give the main needed definitions and results related to the pre-image measure-theoretic entropy for the bundle RDS. In Section 3, we introduce the notion of subadditive pre-image topological pressure and give the power rule for the pressure function. In Section 4, we state and prove the subadditive pre-image variational principle. Conclusions are presented in the final section.
2. Pre-Image Measure-Theoretic Entropy
is a probability space together with an invertible -preserving transformation , where is assumed to be complete, countably generated and separated points. is a compact metric space together with the Borel -algebra . A set is measurable with respect to the product -algebra and such that the fibers , , are compact. A continuous bundle random dynamical system (RDS) over is generated by map with iterates , , so that the map is measurable and the map is continuous for -almost all (a.a) . The map defined by is called the skew product transformation. For more details please refer to [].
Denote , where is the space of probability measures on having the marginal on . Any on can be disintegrated as (see []), where are regular conditional probabilities with respect to the -algebra formed by all sets with . denotes the set of -invariant measures . is -invariant if and only if the disintegrations of satisfy -a.s. []. is a finite measurable partition of , and , where , is a partition of . For each , denote , . Similarly, denote , .
For , the conditional entropy of given the -algebra is defined as usual (See Kifer []) by
where is the conditional probability of the set given .
The pre-image measure-theoretic (relativized) entropy of the RDS T with respect to is defined by the formula
where
and the supremum is taken over all finite or countable measurable partitions of with finite conditional entropy . It should be noted that the supremum in the Equation (2) can be taken only over partitions of into sets of the form , where is a partition of X into measurable sets, so that (See [,,] for detail). The existence of the limit (3) follows from the formula and the standard subadditive argument (cf. Kifer Theorem II.1.1 in []).
It should be noted that the pre-image measure-theoretic entropy defined here is on a class of measurable subsets of instead of Zhu’s on the whole space . In [], Zhu gave the fiberwise expression for this notion, which can be seen as a generalization of Kifer’s []. For the above measurable subset , we gave a similar fiberwise expression in Proposition 1 in []. For the completeness, we give the proof as follows.
Proposition 1.
Proof.
Note that for any and where and , is the projection of into , we have
where . Therefore,
Hence, for any finite measurable partition of , we have
where denotes the standard conditional information function. Thus,
Since for any , then
Dividing by n and letting , we obtain the Equation (4). □
Furthermore, through a rigorous investigation, all results with respect to the pre-image measure-theoretic entropy hold in our case by using the methods in []. In the sequel, we will use these results directly and not give these proofs since it seems that there is no different from the arguments in [] except changing the symbols and restricting to the measurable subset .
3. Subadditive Pre-Image Topological Pressure
Denote , for each , we always assume that is measurable with respect to the product -algebra . For each , -almost all (a.a) , and denote . By the continuity of RDS T and Theorem III.30 in [], it is not hard to see that is also measurable. Since for each , is compact in , this means (See Chaper III in []) that the mapping is measurable with respect to the Borel -algebra induced by the Hausdorff topology on the space and that the distance function is measurable in for each .
For each , a family of metrics on is defined as
where is the identity map. It is not hard to see that, for each and , the set belongs to the product -algebra (See Proposition III.13 in []). Since, for each , and a real number a, the set is measurable with respect to this product -algebra, then depends measurably on .
For each and , a set is said to be -separated if , implies . Similarly, for a compact subset , is called to be -separated for K if , implies .
Due to the compactness, there exists a small natural number such that for every -separated F. Moreover, there always exists a maximal -separated set F in the sense that, for every with , the set is not -separated anymore. In particular, this is also true for any compact subset K in , and we let be the small natural number such that for every -separated set F of K.
For each measurable in and continuous in function f on , let
and be the space of such functions f with and identify f and g provided , then is a Banach space with the norm .
Let be a sequence functions on such that each is measurable in and continuous in x on . These functions are measurable in in view of Lemma III.14 from []. is called subadditive if for any and ,
If and this inequality holds, then a simple calculation indicates that each . In the following, we always assume satisfying these conditions.
For any -invariant measure , denote
Existence of the limit follows from the well-known subadditive argument. If we denote for any , then . Most of the above mentioned in this section can be found in references [,]. We list them here for completeness.
For assumed as above, , , with , and an -separated set E of such that , denote
where E is taken over all -separated sets of in . For , we set for all n and , and then the function is well-defined. In the sequel, we always assume that, for each and , . Alternatively, we can assume that the map is a surjection for each . Clearly, the above supremum can be taken only over all maximal -separated sets.
The following auxiliary result, which relies on Kifer’s work [] restricted on compact subset and nonrandom positive number , provides basic measurability properties needed in what follows. We prove the additive case in Lemma 2 in []. By replacing by and f by , respectively, we make a little change and give a similar argument for the subadditive case as follows.
Lemma 1.
Suppose that is measurable for each as above, then, for any , and a nonrandom small positive number ϵ, the function is measurable in ω, and for any , there exists a family of maximal -separated sets satisfying
and depending measurably on ω in the sense that , which also means that the mapping is measurable with respect to the Borel σ-algebra induced by the Hausdorff topology on the of compact subsets of X. In particular, the supremum in the definition of can be taken only over measurable in ω families of -separated sets.
Proof.
Fix . For set
Observe that , where is the product -algebra on the product of q copies of X. This follows from Theorem III.30 in [] since
is the distance function on ; and, if denotes the product of q copies of , then
is measurable in for each . Next, define measurable functions , on by . Then,
By the continuity of the RDS T, each is a closed subset of , and so it is compact. Clearly, and as , in particular, .
Let be the largest cardinality of all -separated set in and set . By Theorem III.23 in [], it follows that
where is the projection of to , and so is measurable in . Now,
and so is measurable in as well. Since for all , it follows that as , and so for all k large enough (depending on n and ). By Lemma III.39 in [], each function
is measurable, and so both functions and are measurable.
For each constant , the set
belongs to . Hence,
Set
Obverse that are compact sets and as . The sets
are, clearly, measurable, and the sets , with are measurable, disjoint and . Thus (see Theorem III.30 in []), the multifunction defined by for is measurable, and it admits a measurable selection which is measurable map such that for all . Let be the multifunction form to q-point subsets of X defined by . Then, is a multifunction assigning to each a maximal -separated set in for which the Equation (5) holds true.
For any open set, , denote which is an open set of . Then, clearly,
Define the random variable by for all and set ; then,
Hence, is measurable multifunction which assigns to each a maximal -separated set for which Equation (5) holds true and Lemma 1 follows since is arbitrary. □
For the function sequence assumed as above and any positive number , , if , then we can set
It should be noted that, though we set , in fact, only those points such that acts in the function .
The subadditive pre-image (relativized) topological pressure of the function sequence for the bundle RDS T is defined as
and the limit exists since is monotone in and, in fact, equal .
Remark 1.
If we let and consider the whole product space in this definition, then it is the pre-image topological entropy for the bundle RDS T defined by Zhu [] through the separated set:
where is the largest cardinality of an -separated set of .
Remark 2.
If the measure space Ω consists of the single point, i.e., , and the function sequence is the trivial one, namely, , for each n, which is the special additive case for the subadditive function sequence, then it is not difficult to see that the above definition is just the pre-image topological pressure defined by Zeng [] in the deterministic dynamical systems.
For a given , if we replace by and consider the bundle RDS defined by , i.e. , then the subadditive pre-image topological pressure has the following power rule.
Lemma 2.
Let T be a continuous bundle RDS on and Φ be a subadditive sequence of potentials. Then, for any , .
Proof.
Let , and . If E is an -separated set of for , then E is also an -separated set of for T. Since ,
Hence,
Therefore, .
Since is continuous, then for any , some small exists such that with implies . For any positive integer n, one can find some integer l such that . Notice that any -separated set for T is also -separate for . By the subadditivity of , and . Then, for ,
Since , so . Let , , so , then by the definition of , it is not hard to see that
If , then . Hence, we obtain and complete the proof. □
4. Subadditive Pre-Image Variational Principle
In this section, we are concerned with the variational principle for the subadditive pre-image topological pressure.
We first give a variational inequality among the subadditive pre-image topological pressure, the pre-image measure-theoretic entropy and the subadditive potential with respect to the invariant measures.
Theorem 1.
Let T be a continuous bundle RDS on and be subadditive. Then, for each with ,
Proof.
Let , , , be a finite measurable partition of X, and be a positive number with . Denote by , , the corresponding partition of . By the regularity of , we can find compact sets , such that
where . Let be the partition of , where . Then, by the proof of Theorem 4 of Zhu [] and Lemma II. 1.3 of Kifer [], the following inequality holds (see [] for details),
where (respectively by ) denotes the partition of into sets (respectively by ).
For each , denote be the partition of into points, and be the -algebra generated by . Obviously, and so . Set
then .
Let be the decomposition of relative to the partition . By the continuity of T, we can choose the measures so that for each y (See []). Therefore,
For each and with , denote
and let be the point in such that . Then, by the well-known inequality (See [])
where each is a real number, and , we have
Let be the open cover set of X, and be the Lebesgue number for . Then, for every , is the open cover of and is a Lebesgue number of . If D is another element of with such that , then and are in the same element of , say . Hence, for each C, there are at most elements D of such that
Now, an -separated set can be constructed, which satisfies
For this purpose, we first select the point such that
then select the second point such that
the third point such that
continue this process, a finite step m can complete this selection since is finite. Let . Obviously is an -separated set. By the above analysis, for each step, we delete at most elements of , so the inequality (10) holds.
Using the inequality (8), (9) and (10), we have
By our assumed integrable condition, integrating this inequality against and letting , dividing by n and passing to , by Proposition 1, the equality (6) and , we get
Hence, following from the inequality (7),
By the arbitrariness of and , it follows that
Since (see Proposition 4 in []), the same arguments as above applied to in place of T; then, by , we obtain
Using Lemma 2, dividing by n and letting , we conclude that
□
The following lemma is necessary in the proof of Proposition 2. It is a generalization of Cao’s result [] for the deterministic case and is proved in [] as follows.
Lemma 3.
For a sequence probability measures in , where and , if is some subsequence of natural numbers such that ; then, for any ,
In particular, the left part is no more than .
Proof.
For and , by the subadditivity of ,
where denotes the integer part of a.
Summing over j and dividing by k,
Since and , where , integrating this inequality, then by ,
where , since, for any ,
Dividing by n and letting , we get
Observing that , which follows from , we have
Replacing n by in Equation (12), dividing by and passing to , then Equation (16) follows by Equation (13). Letting , then the result holds. □
For the subadditive sequences of potentials, by constructing a maximal invariant measure, one can set up a relationship between the subadditive pre-image topological pressure and the pre-image measure-theoretic entropy on continuous bundle random dynamical systems.
Proposition 2.
Let T be a continuous bundle RDS on and be subadditive. If , there exists some with satisfying
Proof.
Choose some small positive nonrandom with . By Lemma 1, we can also choose a positive integer sequence , , and points for each such that
Fix and employ Lemma 1 in order to choose a measurable in family of maximal -separated sets such that
Next, define probability measures on via their measurable disintegrations
so that , and set
Then, by Lemma 2.1 (i)–(ii) in [], we can choose a subsequence such that . Without losing the generality, we still assume that .
Next, choose a partition of X with and such that and for all , where ∂ denotes the boundary. Set , . Since each element of contains at most one element of , by the inequality (14), we have
For , let denotes the subcollection of consisting of -null sets. For any -algebra of subsets of , there is an enlarged -algebra defined by if and only if there are sets such that and . The -algebra is simply the standard -completion of . Denote -algebra for all . Since for each , we have that . Let , then and for all .
Similarly, let denote the subcollection of consisting of -null sets. Define and . Clearly, , and for all . As a similar proof in Proposition 4, for any finite partition of , we have
Note that is supported on , the canonical system of conditional measures induced by on the measurable partition reduces to a single measure on the set , which we may identify with . Moreover, since each can be expressed as the disjoint union , where and , since is supported on elements of , then . Hence, for any finite partition , we have
Let , where , then is a partition of and . Integrating in the Equation (15) against , then by Equations (16) and (17), we obtain the inequality
Considering such that and let denote the integer part of for all . Then, clearly, for each s,
where .
Since , taking into account the subadditivity of conditional entropy (see Section 2.1 in []), it follows that
Summing this inequality over , we get
where the second inequality, as in Kifer’s works [], relies on the general property of conditional entropy of partition which holds for any finite partition , -algebra , probability measures , and probability vector , in view of the convexity of in the same way as in the unconditional case (cf. [] (pp.183 and 188)). This together with the Equation (18) yields
Diving by , passing to the , taking into account Lemma 3 and using the inequality 10 in [] in the case of the measurable set , i.e.,
we get that
then since . Dividing by q and letting , we have
Letting , we have and complete the proof of Proposition 2. □
It follows directly from Theorem 1 and Proposition 2 that the desired subadditive pre-image variational principle holds.
Theorem 2.
Let T be a continuous bundle RDS on , be subadditive. If , then
Remark 3.
In fact, is equivalent to for all invariant measure . Obviously, if , then, by , . Thus, the restricted condition in the above theorem is only used in the oppositive direction .
5. Conclusions
In this paper, we set up a variational principle for subadditive pre-image topological pressure for continuous bundle random dynamical systems. The topological pressure herein is proved under mild restriction to be the supremum of the sum of the pre-image measure-theoretic entropy and Lyapunov exponent of the subadditive potentials over the set of invariant measures in the continuous bundle random dynamical systems. For the whole product space as a measurable set and the zero potential, the variational principle reduces to the maximal entropy principle for the general random dynamical systems. Moreover, for the trivial base space with a single point adhering to the additive potentials, it is just the pre-image variational principle in the deterministic environment. The method we adopt is still in the framework of Misiurewicz’s perfect proof of the classical variational principle. The result obtained generalizes the extant ones to a more general continuous bundle random dynamical systems and might be useful for the study of dimension estimates on non-conformal random dynamical systems.
Author Contributions
All authors have contributed in equal amount to the paper. All authors have read and agreed to the published version of the manuscript.
Funding
The research is supported by the National Natural Science Foundation of China (Grant No. 11471114) and Undergraduate Training Program for Innovation and Entrepreneurship (Grant No. X19189).
Acknowledgments
We would like to thank the references for their constructive comments and valuable suggestions.
Conflicts of Interest
The authors declare no conflict of interest.
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