1. Introduction
The topological pressure with additive potential was introduced by Ruelle and Walters [
1,
2]. The topological pressure for subadditive sequence of continuous potentials was introduced by Falconer [
3] on mixing repellers. Cao et al. [
4] considered it on compact systems and established its corresponding variational principle. Ledrappier and Walters [
5] introduced a relative version of topological pressure in the field of the relativized ergodic theory. Bogenschütz [
6] defined the topological pressure for random transformations in the stationary case. Kifer [
7] proposed the notion of topological pressure for continuous bundle random transformations and established its variational principle. The topological pressure play a fundamental role in statistical mechanics, dimension theory [
8,
9,
10,
11,
12,
13] and in the study of complex properties of a random dynamical system [
14,
15,
16,
17,
18].
The topological pressure with zero potential reduces to the classical topological entropy. For the purpose of measuring the local complexity of compact dynamical systems at arbitrary small scales, Misiurewicz introduced topological tail entropy [
19] for continuous transformations. Downarowicz [
20,
21] established a maximal entropy principle for the topological tail entropy for homeomorphism. In terms of the essential partitions, Burguet [
22] proved the principle for continuous transformations. Ledrappier [
23] investigated the defect of upper semi-continuity of the metric entropy on the square of compact systems, presented a maximal entropy principle relating it with the topological tail entropy, and showed that topological tail entropy is invariant under the principal extension. The relative version of the tail entropy for continuous bundle random transformations was introduced by Kifer and Weiss [
24] and they deduced the consistence of the two entropy notions defined by open covers and spanning subsets.
Ma et al. set up a relative tail maximal entropy principle [
25] and a tail variational principle [
26] for continuous random transformations by introducing the relative tail entropy and pressure via open random covers, both of the two quantities are proved to be conserved under principal extensions. The notions defined there, via random covers, can enable ones to investigate different fibers under a natural but more complex cover way. For the nonadditive potentials case, the nonadditive thermodynamic formalisms are the powerful tools for the theory of multifractal analysis [
12,
27,
28,
29]. A natural question arises whether the tail variational principle still holds for the relative tail pressure associated with a sequence of subadditive random continuous potentials and whether this kind of tail pressure can be maintained by the action of principal extensions.
In this paper we introduce the relative tail pressure with subadditive potentials for continuous bundle random transformations via open random sets. The notion is a little different from that developed before [
24,
30] for the same cover of the fibers, which could make us consider various covers on different fibers. We investigate the product continuous bundle random dynamical system (RDS) generated by a given continuous bundle RDS and another continuous bundle RDS over the same probability space. A variational inequality is obtained for the relative tail pressure with subadditive potentials, which shows that the pressure of given continuous bundle RDS is an upper bound of the defect of the upper semi-continuity of the relative entropy and Lyapunov exponent of subadditive potentials in the product continuous bundle RDS. For the self-product of the given continuous bundle RDS, we establish a variational principle for the defined pressure by constructing a maximal invariant measure for the product continuous bundle RDS to ensure that the relative tail pressure may be attained. As for the trivial measure space, the relative tail pressure with the zero potential is just the topological tail entropy defined in Reference [
19] and the variational principle is the deterministic version of maximal entropy principle deduced by Ledrappier [
23]. It turns out that from this variational principle that the relative tail pressure with subadditive potentials is an invariant in the sense of the principal extension. The method we adopt is still in the framework of Misiurewicz’s elegant proof [
31].
Organization of the paper is as follows?We recall some basics of the relativized ergodic theory in
Section 2. The relative tail pressure with subadditive potentials is introduced in term of open random covers in
Section 3. In
Section 4, we give the power rule and a variational inequality for the relative tail pressure in the general product RDSs. In
Section 5, we state and prove the variational principle in the self-product RDSs for the relative tail pressure with the subadditive potentials and show that the defined pressure can be conserved under the consideration of the principal extension.
2. Relative Entropy
In this section, we recall some basic notions of the relative measure-theoretic entropies for bundle random transformations [
24,
26]. For a general theory of random dynamical systems, we refer to [
24,
32,
33].
Let be a probability space which is complete countably generated and be a -preserving transformation of this space. Let X be a compact metric space and be its Borel -algebra. Let be subset of which is measurable under the product -algebra and assume that the fibers are compact subsets of X. A continuous bundle random dynamical system (RDS) T over is generated by the mappings so that the map is measurable and the map is continuous for -almost all (a.a.) . The family is called a random transformation and each maps the fiber to . The map defined by is called the skew product transformation. Notice that , where for and .
Let be the space of probability measures on with the marginal on and . Denote by the space of all -invariant measures in .
Let
and
be a sub-
-algebra of
which is restricted on
and satisfies
. Let
be a finite or countable measurable partition of
, the relative entropy
of
is defined as
where
is the conditional entropy of
given
-algebra
and
.
The relative entropy of
is defined by the formula
where the supremum is taken over all finite or countable measurable partitions
of
with finite conditional entropy
. The defect of upper semi-continuity of the relative entropy
) is defined on
as
3. Relative Tail Pressure with Subadditive Potentials
Let
be a sequence of random continuous functions on
in
(see Reference [
34] for the detail).
is called subadditive if for any
and
,
For any
-invariant measure
, denote
The existence of the limit follows from the well-known subadditive argument. is called the Lyapunov exponent of with respect to . Denote by for any , then .
The map is called a (closed) random set if Q is measurable, where denotes the space of the (closed) subsets of X. The map is called an open random set if its complement is closed. Let be a finite or countable family of random sets and denote . is called a random cover of if for all . is called an open random cover if all random set U in are open. Let . We will denote by , the set of random covers, open random covers, respectively. A random cover is said to be finer than another random cover , written as , if each element of is a subset of some element of .
For each
and any non-empty set
, denote
where
belongs to the set of all random subcover of
. For
, let
For each , a standard argument shows that the sequence is subadditive.
By replacing the function
in Lemma 3.1 of Reference [
26] with
, one can easily get the following Lemma, which provides the basic measurable property needed. In fact, for any measurable function
g on
, this result also holds.
Lemma 1. The map from Ω to is measurable for each and .
-a.s. exists, which follows from the classical subadditive ergodic theorem (see Reference [
33,
35]). Let
Notice that
increase in
, a limit (finite or infinite) exists over the directed set
,
is said to be the relative conditional pressure of
with subadditive potentials
for random cover
. For the trivial
,
will be simply written as
. Since
decrease in
, another limit exists over
,
is said to be the relative tail pressure of
with subadditive potentials
. Obviously
.
4. Variational Inequality for Relative Tail Pressure
In this section we consider the relationship between the relative tail pressure, Lyapunov exponent with subadditive potentials and the relative entropy over the measurable subset of the product space .
We first give the power rules for the relative conditional pressure and relative tail pressure with subadditive potentials in the original continuous bundle RDS.
Proposition 1. Let Θ be a skew product transformation, Φ be subadditive and . Then for each .
Proof. Let
. Notice that
and then
Thus and the result holds. □
Proposition 2. Let Θ be a skew product transformation and Φ be subadditive. Then for each .
Proof. By Proposition 1,
where
belongs to the set of all random covers of
. Then
Since for each , then Then by taking infimum over all on this inequality. □
Consider another compact space
. Denote by
a measurable subset of
satisfying that the fibers
are compact. The continuous bundle RDS
S over
and the skew product transformation
on
can be defined similarly as in
Section 2.
Definition 1. A continuous bundle RDS T is called a factor of another continuous bundle RDS S if a family of continuous surjective maps exists, which satisfies the map being measurable and . The factor transformation π from to is defined as and the skew product system is said to be a factor of the skew product system .
We now take up the consideration of the measurable subset based on and with the product -algebra . Denote by and set . The continuous bundle RDS over can be defined as usual by the maps , which requires being measurable and being continuous in for -a.a. . The skew product transformation is defined as , which is generated by the two product transformations and .
Let , be the two natural projections with , , respectively. Then and are obviously two factor transformations. Let be the restriction of on and denote , and .
For the given the
algebra
, the relative entropy of
is then defined as
where
belongs to the set of all finite or countable measurable partitions of
satisfying
.
We need the following two important Lemmas. The first Lemma shows the upper semi-continuity of the conditional entropy, which can be found in many references, for instance [
5,
7]. The second one is Lemma 5 in [
26], which shows the intrinsic connection relating the relative entropy with the relative tail pressure even in the general additive case.
Lemma 2. Let be a finite measurable partition of . If with , , where , then Lemma 3. Let , and be two finite measurable partitions of . Then where .
For any given finite measurable partition of the original RDS, we give an inequality relating the relative conditional pressure with subadditive potentials and the relative entropy of the product RDS with respect to invariant measures.
Proposition 3. Let Γ be the skew product transformation on , and Φ be subadditive with . If is a finite measurable partition of , then Proof. Let
be a measurable partition of
,
and
. Let
be a measurable partition of
such that
and
be the open random cover of
generated by
(see [
26] for details). Denote by
the Lebesgue number of the open cover
for each
.
Fix
. Denote
where
and
. Choose one point
in
with
. For each pair of elements
in
,
implies that
and
are in the same element of
. Hence for each
, there exists at most
elements
of
satisfying
For each
, an
-separated set
satisfying the inequality
can be easily constructed in
as follows. Choose the first point
with
the second point
with
Choose the
mth point
such that
The process will cease at some finite step
l since
is finite. Let
.
is obviously an
-separated set and at most
elements of
are deleted for each step. The inequality (
1) holds.
It follows from Lemma 3 that
Let
be an open random cover of
satisfying
. Since each
cannot contain two or above elements in
, then
Since
and
, then
Let
be a refine sequence of finite measurable partitions such that
, then the inequality
follows from Lemma 1.6 in Reference [
33].
Observe that
where
is the usual relative entropy of
w.r.t. the partition
.
For each
, by Lemma 1.4 in Reference [
33],
Using
,
,
and
in the inequality (
2), by the above equalities (
3), (
4) and the power rules in Proposition 1, one can easily get
which completes the proof. □
The following theorem describes the variational inequality between the relative tail pressure with subadditive potentials, the defect of upper semi-continuity of the relative entropy function and Lyapunov exponent with subadditive potentials with respect to invariant measures.
Theorem 1. Let Γ be the skew product transformation on , . For subadditive potentials Φ with , one has .
Proof. Let
and
be finite. Let
be a refine finite measurable partition of
with
for each element
. Then by Proposition 3,
for each
and
. By Lemma 2, the upper semi-continuity of the conditional entropy implies that
By the arbitrariness of the partition , we have . □
5. Variational Principle for Relative Tail Pressure
In this section we investigate the variational principle between the defect of upper semi-continuity of the relative entropy function of the self-product RDSs and the relative tail pressure with subadditive potentials of the original RDS.
Denote by and . Let with be the skew product transformation on . Let be the natural projection from to with , i=1, 2, where .
We will use the following Lemma [
36] in the proof of Proposition 4. It is a random version of the result presented by Cao et al. [
4].
Lemma 4. Let be a sequence probability measures in , where and . Suppose that is a subsequence of with in . Then for each , Moreover, is an upper bound of the left limit superior.
For any given open random cover of the original RDS, the following construction of a maximal invariant measure sets up a relationship between the relative conditional pressure with subadditive potentials and the relative entropy of the self-product RDSs, which is essential for the argument of the variational principle.
Proposition 4. Let Θ be the skew product transformation on , Φ be subadditive and with . Then there exists some satisfying
- (i)
- (ii)
the support of is on .
Proof. Choose some with such that .
Fix
and
. Let
be an element in
with
and choose one point
. Let
be the Lebesgue number of the open cover
. Let
. There exists a maximal
-separated subset
with
in
, where
. Let
Notice that
is the subset of some element of
. It follows that
and we have
Let
be the probability measures of
such that their disintegrations satisfying
with
. Denote
It follows from Theorem 1.5.8 in Reference [
32] that the Krylov-Bogolyubov procedure for continuous bundle RDS guarantees that one can choose a subsequence
of
such that
converges towards some
.
We now show that satisfies the properties (i) and (ii).
For the first proposition, let . Let be a finite partition of into measurable subsets with and . Denote . Then since . Let .
Let , where and is the natural projection. It is abbreviated as for convenience in the sequel.
Since different elements of
belong to different elements of
,
It is not hard to verify that
For each
j with
, the section
can be separated into
subsection
, ⋯ and no more than
other positive integers. Then
Since the entropy function
is concave, then by summing over all
j,
we have
It follows the inequality (
7) that
Considering the selected subsequence
, by Lemmas 2 and 4, we have
By taking
, we have
Choose a refine sequence of
with
, and a refine sequence
with
, where each
is a finite measurable partition. Using Lemma l.6 in Reference [
33] we have
and the property (i) holds.
For the second proposition, we omit the argument since it is very similar to that of Proposition 4.2 in Reference [
26] and we complete the proof. □
We now show that the relative tail pressure with subadditive potentials of the original RDS could be reached by the defect of the upper semi-continuity of the relative entropy together with the Lyapunov exponent of the subadditive potentials with respect to some invariant measure of the self-product RDS.
Proposition 5. Let Θ be a skew product transformation on and Φ be subadditive with . There exists some with its support on and such that .
Proof. Let
. Denote by
. By Proposition 4, for each
, we can find some
with its support on
and satisfying the inequality
By ([
7] Lemma 2.1) the set of the limit points of the sequence of
is contained in
. Pick some limit point
m with
for some subsequence
of
, then
Notice that
and the sequence of open random covers
is refine, one has
Let
be any finite measurable partition of
, obviously,
then the two partitions
and
are the same except zero-measure sets. Notice that
a.s. for each
i,
. One has
and
. Hence
Since , then . By Theorem 1, the result holds. □
It follows directly from Theorem 1 and Proposition 5 that the desired variational principle holds.
Theorem 2. Let Θ be a skew product transformation on and Φ be subadditive with . Then Let be -algebra generated by the restriction of the product -algebra on and denote .
Definition 2. A skew product transformation Λ is called a principal extension of the skew product transformation Θ if the relative entropy vanishes for any measure m in .
The following theorem shows that the relative tail pressure with subadditive potentials is invariant under principal extensions. The proof is similar to Theorem 4.3 in Reference [
26] and we omit it.
Theorem 3. Let be two skew product transformations and Φ be subadditive with . If Λ is a principal extension of Θ, then , where π is the factor transformation between Λ and Θ and .