Singular stationary measures for random piecewise affine interval homeomorphisms
Krzysztof Bara\'nski, Adam \'Spiewak

TL;DR
This paper demonstrates that certain random systems of two piecewise affine interval homeomorphisms have singular stationary measures, addressing conjectures and questions about their absolute continuity in the context of semigroups of circle homeomorphisms.
Contribution
It provides the first proof of singular stationary measures for specific random piecewise affine systems, partially confirming a conjecture and advancing understanding of measure regularity.
Findings
Stationary measures are singular for some random systems of two piecewise affine homeomorphisms.
Addresses a conjecture by Alsedà and Misiurewicz regarding measure singularity.
Contributes to the question of absolute continuity of stationary measures in semigroups of circle homeomorphisms.
Abstract
We show that the stationary measure for some random systems of two piecewise affine homeomorphisms of the interval is singular, verifying partially a conjecture by Alsed\`a and Misiurewicz and contributing to a question of Navas on the absolute continuity of stationary measures, considered in the setup of semigroups of piecewise affine circle homeomorphisms. We focus on the case of resonant boundary derivatives.
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.
Singular stationary measures for random piecewise affine interval homeomorphisms
Krzysztof Barański
Institute of Mathematics, University of Warsaw, ul. Banacha 2, 02-097 Warszawa, Poland
and
Adam Śpiewak
Institute of Mathematics, University of Warsaw, ul. Banacha 2, 02-097 Warszawa, Poland
Dedicated to Lluís Alsedà on his 65th birthday and Michał Misiurewicz on his 70th birthday
Abstract.
We show that the stationary measure for some random systems of two piecewise affine homeomorphisms of the interval is singular, verifying partially a conjecture by Alsedà and Misiurewicz and contributing to a question of Navas on the absolute continuity of stationary measures, considered in the setup of semigroups of piecewise affine circle homeomorphisms. We focus on the case of resonant boundary derivatives.
2010 Mathematics Subject Classification:
Primary 37E05, 37E10, 37H10, 37H15.
Supported by the National Science Centre, Poland, grant no 2018/31/B/ST1/02495.
1. Introduction
For the last forty years there has been an intensive interest in the study of non-autonomous real one-dimensional dynamical systems, especially in the context of the theory of groups of smooth diffeomorphisms acting on the unit circle (see e.g. [Ghy01, Nav11] and the references therein). In a probabilistic approach, such a system equipped with an appropriate probability distribution generates in a natural way a Markov process on the circle (see e.g. [Arn98, Kif86] as general references on random dynamical systems).
Recently, a continuously growing interest in random dynamics has led to an intensive study of random systems given by groups or semigroups of one-dimensional non-smooth maps, for instance interval or circle homeomorphisms (see e.g. [AM14, SZ16, GH16, GH17, Mal17, GS17]). In this paper we consider the properties of stationary measures for a certain class of such systems.
Let , , be homeomorphisms of a -dimensional compact manifold (the closed interval or the unit circle). Such a system of maps generates a semigroup consisting of iterates for , . Let be a probability vector. A Borel probability measure on is called stationary, if
[TABLE]
for every Borel set . The Krylov–Bogolyubov Theorem shows that such a measure always exists (but is non-necessarily unique). However, in most cases little is known about its properties. Assuming some regularity of the system (e.g. forward and backward non-singularity of the transformations) and the uniqueness of the stationary measure, which occur for a wide class of systems (see e.g. [DKN07]), we know that the stationary measure is either absolutely continuous or singular with respect to the Lebesgue measure. Determining which of the two possibilities occur is a well-known problem, especially in the context of groups of smooth diffeomorphisms acting on the circle (see e.g. [Nav17, Question 18]). Up to now, an answer has been given only in some particular cases. For instance, a conjecture by Y. Guivarc’h, V. Kaimanovich and F. Ledrappier (see [DKN09, Conjecture 1.21] states that for a finitely generated subgroup of acting smoothly on the circle, the stationary measure is singular. The conjecture was proved by Y. Guivarc’h and Y. Le Jan in [GLJ90] for non-cocompact subgroups and by B. Deroin, V. Kleptsyn and A. Navas in [DKN09] for some minimal actions of the Thompson group and subgroups of by -diffeomorphisms. On the other hand, the absolute continuity of the stationary measure was proved to hold for a number of random systems of non-homeomorphic maps of the interval (usually expanding at least at average), see e.g. [Pel84, Buz00, AS14].
Let us note that the question of determining singularity or absolute continuity of the stationary measure is non-trivial even in the apparently simple case of two contracting similarities of the unit interval , given by , for . Then the unique stationary measure for the probability vector is called the symmetric Bernoulli convolution and is always either singular or absolutely continuous. It is known (see [Shm14]) that the set of parameters for which is singular has Hausdorff dimension zero, and the only known values of “singular” parameters are the reciprocals of the Pisot numbers, as proved in [Erd39]. It is a long-standing open question whether these are the only examples of singular Bernoulli convolutions. Despite many results in this direction, a complete answer is still unknown and stimulates an active research. See e.g. [PSS00, Var16] for comprehensive surveys on the subject.
In this paper we consider a random system of two piecewise affine orientation-preserving homeomorphisms of the circle with a unique common fixed point. We look at it as a system of two piecewise affine increasing homeomorphisms , of the interval . We assume that , for , each has one point of non-differentiability and for . See Definition 2.1 and Figure 1 for a precise description. Since systems of this type were introduced in [AM14] by Alsedà and Misiurewicz, we call them Alsedà–Misiurewicz systems, or AM-systems.
We consider as a random system with given probabilities , where , . Formally, it means that defines a step skew product
[TABLE]
where and is shift on the space of infinite one-sided sequences of two symbols , with the Bernoulli probability distribution given by (see Section 3). However, in this paper we are mainly interested in the behaviour of the system in the phase space , studying trajectories of points under , i.e. for .
Note that on the intervals and the system is equivalent, respectively, to two (typically different and non-symmetric) one-dimensional random walks, which are glued in a continuous way. This makes such systems interesting from a probabilistic point of view and we believe they can serve as models for many stochastic phenomena which appear in random one-dimensional dynamics.
The behaviour of an AM-system depends on the values of the Lyapunov exponents at the interval endpoints, i.e.
[TABLE]
For instance, if , are negative, then the endpoints of the interval are attracting in average, so a typical trajectory converges to one of them, which can give rise to two intermingled basins for the step skew product (see e.g. [Kan94, BM08, GH17]). In this paper we assume that the Lyapunov exponents are positive. Then for almost all paths , any two trajectories defined by converge to each other, i.e. as for . This phenomenon is called synchronization (see e.g. [Ant84, Bax89, PRK01, KV14]). Moreover, apart from purely atomic stationary measures supported at the common fixed points [math] and , there exists a (unique) stationary measure on such that . In this paper we study the properties of the measure , which we call the stationary measure for the AM-system.
In [AM14] L. Alsedà and M. Misiurewicz showed that for some parameters of an AM-system the stationary measure is equal to the Lebesgue measure and conjectured that should be singular for typical parameters. In this paper we provide a precise condition under which the stationary measure is equal to the Lebesgue measure (Theorem 2.4) and verify the conjecture on singularity for some set of parameters, showing that for a class of AM-systems with resonant boundary derivatives (i.e. with ) the measure is indeed singular and supported on an exceptional minimal set, which is a Cantor set of dimension smaller than . See Theorem 2.10 for details. We also determine the value of the Hausdorff dimension of in the case (see Theorem 2.12). Furthermore, we present an interesting example of an AM-system with a singular stationary measure of full support (Theorem 2.16). Finally, we show that the considered systems with the same resonance are topologically conjugate (Theorem 2.15).
To our knowledge, these are the first examples of singular stationary measures for non-expanding random systems generated by semigroups of homeomorphisms of the circle of that type. The fact that the maps are piecewise affine is especially interesting, since such systems are studied intensively and often serve as models for smooth systems (see e.g. [Nav17, Questions 12 and 16]). In a forthcoming paper [BS19] we prove that the stationary for an AM-system is singular and has Hausdorff dimension smaller than for an open set of parameters, including also non-resonant cases.
Notice that in the resonant case mentioned above, the stationary measure is supported on an exceptional minimal set (i.e. invariant Cantor sets where the systems is minimal), while in the non-resonant one, its support is equal to the entire interval (see Proposition 2.6). It should be noted that the properties of exceptional minimal sets are a well-known subject of interest, especially in the context of the groups of diffeomorphisms. For instance, a conjecture of Ghys and Sullivan says that exceptional minimal sets for groups of -diffeomorphisms have Lebesgue measure zero. The hypothesis has been recently verified by B. Deroin, V. Kleptsyn and A. Navas [DKN18] for real-analytic diffeomorphisms, while the question remains open in the smooth case. Our paper contributes to the study of such sets for piecewise-linear systems.
The plan of the paper is as follows. In Section 2 we describe the AM-systems and state the results of the paper in a precise way. Section 3 contains preliminaries, while Section 4 is devoted to the proofs of the minor results and Theorem 2.4. The proofs of the main results (Theorems 2.10 and 2.12) are split into Section 5 (case ) and Section 6 (case ). Sections 7 and 8 contain, respectively, the proofs of Theorems 2.15 and 2.16.
Acknowledgement**.**
We thank Balázs Bárány, Michał Misiurewicz, Károly Simon and Anna Zdunik for useful discussions.
2. Main results
We begin with a precise description of an Alsedà–Misiurewicz system.
Definition 2.1**.**
An AM-system is the system of increasing homeomorphisms of the interval of the form
[TABLE]
where , and
[TABLE]
See Figure 1.
We consider an AM-system as a random system with probabilities , where , .
Definition 2.2**.**
The Lyapunov exponents of an AM-system with probabilities are defined as
[TABLE]
It is known (see [AM14, GH16, GH17]) that if the Lyapunov exponents are positive, then there exists a unique stationary measure without atoms at the endpoints of , i.e. a Borel probability measure on , such that
[TABLE]
with . For details, see Theorem 3.6. Throughout the paper, by a stationary measure for an AM-system with positive Lyapunov exponents we will mean the measure . It is known that if the Lyapunov exponents are positive, then the measure is non-atomic and is either absolutely continuous or singular with respect to the Lebesgue measure (see Propositions 3.10 and 3.11).
Definition 2.3**.**
We say that an AM-system is of:
- –
disjoint type, if the intervals , are disjoint, i.e. ,
- –
border type, if the intervals , touch each other, i.e. ,
- –
overlapping type, if the intervals , overlap, i.e. .
See Figure 2.
Note that in the case (which will be assumed in most of the paper, see Lemma 4.1), the system is of
- –
disjoint type, if , are disjoint,
- –
border type, if ,
- –
overlapping type, if , overlap.
In [AM14, Theorem 6.1] Alsedà and Misiurewicz showed that if , , , , then the measure is the Lebesgue measure on . The first result of our paper, presented below, gives an exact condition for an AM-system to have a stationary Lebesgue measure.
Theorem 2.4**.**
Let be an AM-system with probabilities , such that the Lyapunov exponents are positive. Then the stationary measure is the Lebesgue measure on if and only if the system is of border type and
[TABLE]
In this case we also have .
In [AM14] the authors conjectured that the stationary measure for an AM-system with positive Lyapunov exponents is typically singular. The main result of this paper verifies this conjecture for some set of the system parameters. First, we split the AM-systems into two kinds: resonant and non-resonant, which have different kinds of behaviour.
Definition 2.5**.**
We say that that an AM-system with probabilities exhibits a resonance at the point [math], if
[TABLE]
More precisely, a -resonance at [math] occurs for if
[TABLE]
which is equivalent to for some and also to .
Analogously, a -resonance at occurs if
[TABLE]
Without loss of generality, we always assume that are relatively prime.
We will show that in the resonant case the (topological) support of the stationary measure for some parameters is a Cantor set in of Hausdorff dimension smaller than (see Theorems 2.10 and 2.12). A different situation occurs in the non-resonant case, as shown in the following proposition (for the proof see Proposition 4.3 and Corollary 4.5).
Proposition 2.6**.**
If an AM-system with positive Lyapunov exponents has no resonance at one of the endpoints , then it is minimal in and the support of is equal to .
Before stating the main results of this paper, we need to present some definitions. Let
[TABLE]
be the symmetry of with respect to its center.
Definition 2.7**.**
An AM-system is called symmetric, if .
Obviously, a system is symmetric if and only if and . It is straightforward that for symmetric systems we have and . Moreover, for symmetric systems the existence of -resonance at [math] is equivalent to the existence of -resonance at . Note also that if a symmetric systems exhibits -resonance, then the condition is equivalent to the positivity of the exponents for (see the proof of Lemma 4.1).
Definition 2.8**.**
For an AM-system of disjoint type, we call the interval the central interval of the system .
Definition 2.9**.**
Let and . We say that a trajectory jumps over the central interval at the time , for , if and are in different components of the complement of the central interval in .
The main results of this paper shows the singularity of the stationary measure for some symmetric AM-systems of disjoint type, which exhibit a resonance.
Theorem 2.10**.**
Let be a symmetric AM-system of disjoint type with positive Lyapunov exponents. If the system exhibits -resonance for some relatively prime , , and satisfies , where
[TABLE]
and is the unique solution of the equation , then the stationary measure is singular with
[TABLE]
where denotes the topological support of . Moreover, is a nowhere dense perfect set consisting of all limit points of trajectories of any point under , which jump over the central interval infinitely many times.
Remark 2.11**.**
The condition is equivalent to and implies that the system is of disjoint type. In the case it holds for all systems of disjoint type.
In the case we give a more precise description of the measure .
Theorem 2.12**.**
Let be a symmetric AM-system of disjoint type with probabilities , such that the Lyapunov exponents are positive. If the system exhibits -resonance for some , then
[TABLE]
where is defined as above and are, respectively, the unique solutions of the equations
[TABLE]
In particular, if , then
[TABLE]
Remark 2.13**.**
Under the assumptions of Theorem 2.10, if or , , then the stationary measure is a countable sum of (geometrically) similar copies, with disjoint supports, of a self-similar measure of an iterated function system with the Strong Separation Condition. In the case this iterated function system consists of maps, while in the case , it is infinite. See Propositions 5.14 and 6.15.
Remark 2.14**.**
For every and and probability vector with , the assumptions of Theorem 2.12 are fulfilled for some AM-system with and probabilities . In particular, the theorem gives examples of AM-systems with for arbitrary .
The next result shows that the considered resonant systems are uniquely determined (up to topological conjugacy) by their resonance data.
Theorem 2.15**.**
Let , be symmetric AM-systems of disjoint type. If both system exhibit -resonance for some relatively prime , , and satisfy , then they are topologically conjugated, i.e. there exists an increasing homeomorphism such that
[TABLE]
The last result shows that there exist symmetric resonant AM-systems with singular stationary measure of full support.
Theorem 2.16**.**
If a symmetric AM-system with probabilities and positive Lyapunov exponents exhibits -resonance and satisfies , with defined as above, then is singular with
[TABLE]
Note that in this case the condition is equivalent to
[TABLE]
which gives .
Remark 2.17**.**
The resonance was chosen because the proof is relatively short in this case. Similar arguments work also for some other values of the resonance with .
3. Preliminaries
Notation*.*
We write . For we set
[TABLE]
For , we use the notation
[TABLE]
The convex hull of a set is denoted by . We write for the length of an interval . The symbol denotes the Lebesgue measure. By (resp. ) we denote the Hausdorff (resp. box) dimension. The Hausdorff dimension of a Borel measure in is defined as
[TABLE]
Throughout this section we assume that , , are piecewise increasing homeomorphisms of the interval , such that , and for , .
For a set we define
[TABLE]
and, inductively,
[TABLE]
for .
Definition 3.1**.**
Suppose for some . We say that the system is (forward) minimal in , if the union of forward trajectories under of every point in is dense in , i.e. for every and every non-empty open subset of there exist , , such that .
Let be a probability vector, i.e. and . We consider the symbolic space
[TABLE]
equipped with the Bernoulli measure
[TABLE]
where is the probability distribution on given by , .
We study as the random systems of maps, given by the step skew product
[TABLE]
where and is the left-side shift, i.e. .
Let be the space of all Borel probability measures on . For we denote by the topological support of , i.e. the intersection of all closed sets in of full measure .
Definition 3.2**.**
A measure is called a stationary measure of the system with probabilities , if
[TABLE]
Definition 3.3**.**
The Markov (or transfer) operator is defined as
[TABLE]
Analogously, the transfer operator is defined as
[TABLE]
It is clear that the stationary measures of the system with probabilities coincide with the fixed points of the transfer operator , while the stationary densities (densities of stationary measures with respect to the Lebesgue measure) are the fixed points of the transfer operator .
Proposition 3.4**.**
Suppose that for some and the system is minimal in . If is a stationary measure for the system and , then .
The proof of this proposition is standard and can found e.g. in [DKN07, Lemme 5.1] or [GS17, Lemma 2].
Note that since the maps fix the endpoints of the interval, the Dirac measures at [math] and are stationary for any probabilities . If we assume that the endpoints are repelling in average, then there exists a stationary measure with no atoms at . More precisely, we have the following.
Definition 3.5**.**
Assuming , , the Lyapunov exponents of the system with probabilities are defined as
[TABLE]
Theorem 3.6** ([GH16, Proposition 4.1], [GH17, Lemmas 3.2–3.4]).**
If , then there exists a unique probability stationary measure for the system with probabilities , such that . Moreover, there exist positive constants such that for every , and for
[TABLE]
we have and .
Remark 3.7**.**
Actually, in [GH16, GH17] the theorem was proved for systems of -diffeomorphisms, but the proof goes through if we only assume that the map are smooth in some neighbourhoods of .
Remark 3.8**.**
The uniqueness of the stationary measure implies
[TABLE]
Remark 3.9**.**
The measure is an -invariant measure on . Moreover, there is a Borel probability measure on , where , invariant with respect to the (extended) step skew product, which is associated to in a unique way (see [Arn98, GH17]).
It is well-known (see e.g. [DF66, Theorem 2.5]) that whenever the operator preserves absolute continuity and singularity of measures (with respect to the Lebesgue measure) and the stationary measure is unique, then it is of pure type (i.e. is either absolutely continuous or singular with respect to the Lebesgue measure). It is easy to see that the same holds for the measure from Theorem 3.6. Hence, we have the following.
Proposition 3.10**.**
The stationary measure is either absolutely continuous or singular with respect to the Lebesgue measure.
Another standard fact is that cannot have atoms.
Proposition 3.11**.**
The stationary measure is non-atomic.
Proof.
The proof follows [GS17, proof of Lemma 2] (see also [DKN07, Lemme 5.1]). By Theorem 3.6, has no atoms at . Suppose there exists an atom in and take such that . Then, by the definition of stationary measure, for every and, consequently, for every . Since has no fixed points in , the trajectory is strictly monotonic and thus infinite, which contradicts the finiteness of . ∎
The following lemma is useful in determining singularity of the measure.
Lemma 3.12**.**
If is non-empty, closed as a subset of , and , then and . Consequently, if there exists such a set of Lebesgue measure [math], then is singular.
Proof.
Take . Since , the Dirac measure at is in for sufficiently small , so by Remark 3.8 we have
[TABLE]
Since
[TABLE]
the measures have topological support in , which is contained in , as . Since and , we have and . ∎
4. Preliminary results and proof of Theorem 2.4
In this section we prove Theorem 2.4 together with other preliminary results on the AM-systems. We begin with the following observation.
Lemma 4.1**.**
Let be an AM-system. If the Lyapunov exponents are positive for the probabilities , then . In particular, holds if the system is symmetric and exhibits a -resonance for , .
Proof.
The inequality can be written as
[TABLE]
which is equivalent to
[TABLE]
By the positivity of the Lyapunov exponents for ,
[TABLE]
so
[TABLE]
which gives (1). As already noted, if the system is symmetric and exhibits a -resonance for , then the assumption on the positivity of the Lyapunov exponents for is satisfied. Indeed, in this case we have and , so
[TABLE]
for . ∎
The following lemma is used in the proof of Theorem 2.4.
Lemma 4.2**.**
If an AM-system with probabilities is of border type and , then . Conversely, if
[TABLE]
then the AM-system with probabilities is of border type.
Proof.
An elementary calculation shows that the system is of border type if and only if
[TABLE]
which is equivalent to
[TABLE]
Suppose that the system is of border type and
[TABLE]
Then
[TABLE]
so by (2),
[TABLE]
which gives
[TABLE]
Conversely, suppose
[TABLE]
Then
[TABLE]
which gives (2). ∎
The following proposition, which gives the first part of Proposition 2.6, is essentially proved in [Ily10, Lemma 3] and [GH17, Proposition 2.1] (formally, in the case of diffeomorphisms). For completeness, we present the proof suited to our setup.
Proposition 4.3**.**
If an AM-system has no resonance at one of the endpoints , then it is minimal in .
Proof.
To fix notation, assume that the system has no resonance at [math] (in the other case the proof is analogous). Choose . Since both families of intervals , , and , , cover , it is sufficient to prove that for every , where
[TABLE]
with some chosen and every there exist and such that
[TABLE]
To show (3), we choose so that and let
[TABLE]
Since we assume that has no resonance at [math], we have . Hence, for any and we can find such that
[TABLE]
As
[TABLE]
(4) implies
[TABLE]
if is chosen sufficiently small. In particular,
[TABLE]
Since , we have . Moreover, (5) implies for , which gives . This together with (5) shows (3) and ends the proof. ∎
Assume now that an AM-system with probabilities has positive Lyapunov exponents, which is equivalent to
[TABLE]
Then, by Theorem 3.6, there exists a unique probability stationary measure for the system, such that . By Propositions 3.10 and 3.11, we have the following.
Proposition 4.4**.**
The stationary measure is non-atomic. Moreover, it is either absolutely continuous or singular with respect to the Lebesgue measure.
Propositions 3.4 and 4.3 imply the following corollary, which completes the proof of Proposition 2.6.
Corollary 4.5**.**
If the system has no resonance at one of the endpoints , then .
We end the section by proving Theorem 2.4.
Proof of Theorem 2.4.
The transfer operator on has the form
[TABLE]
The measure is the Lebesgue measure if and only if
[TABLE]
for the constant unity function . If the system is of border type, then
[TABLE]
so (6) is equivalent to
[TABLE]
Conversely, if (6) holds, then applying it to points close to the endpoints of we get (7). To end the proof, it is enough to use Lemma 4.2. ∎
Remark 4.6**.**
As noted in the introduction, for the case , , , , Theorem 2.4 was proved in [AM14, Theorem 6.1].
5. Proofs of Theorems 2.10 (case ) and 2.12.
In Theorems 2.10 and 2.12 we consider a symmetric AM-system of disjoint type with probabilities , positive Lyapunov exponents and a -resonance for some relatively prime , . In this section we prove the results in the case . The proof is divided into several parts concerning consecutive assertions of the theorems.
Preliminaries
By assumption, , , so the maps have the form
[TABLE]
where and
[TABLE]
Note that (see Lemma 4.1) and . The assumption that the system is of disjoint type, i.e. the condition , is equivalent to
[TABLE]
and also to . For the function , we have , , for and for , where . This implies that on has a unique zero , i.e.
[TABLE]
and the condition is equivalent to (8) (this shows Remark 2.11 in the case ).
Since the system is symmetric, in fact we have
[TABLE]
A simple computation shows that the condition of the positivity of the Lyapunov exponents is equivalent to
[TABLE]
Note that the above considerations prove Remark 2.14.
Construction of the set
Now we construct a set which will be shown later to be the support of the measure in . Our strategy is the following. First, we construct a family of disjoint closed intervals , , with the union being forward-invariant under . The disjointness of follows from the assumption that the system is of disjoint type. We check that the intervals are mapped by into with separation gaps, i.e. are disjoint subsets of (see Lemma 5.1 and Figure 3). Further iterates of these images and their similar copies generate an infinite collection of disjoint Cantor sets, whose union is fully invariant and minimal under the action of (see Proposition 5.10). As we wish to calculate the dimension of , it is convenient to describe as the union of the attractor of a self-similar iterated function system on and its similar copies. Moreover, as the successive levels of the Cantor set are produced during jumps over the central interval, we obtain a characterization of in terms of limit points of trajectories jumping over the central interval infinitely many times (see Proposition 5.9).
Let
[TABLE]
and for define
[TABLE]
The following lemma is elementary and describes the combinatorics of the intervals .
Lemma 5.1**.**
The following statements hold.
- (a)
* for .* 2. (b)
The sets , are pairwise disjoint and situated in in the increasing order with respect to . 3. (c)
, , , . In particular,
[TABLE] 4. (d)
* for , , for .* 5. (e)
* for , , for .*
See Figure 3.
Proof.
The assertion (a) follows directly from the definition of . To show (b), we first check . This is equivalent to
[TABLE]
which boils down to (8). By (9), . The rest of the assertion (b) follows directly from the above facts and the definition of .
The assertions (c)–(e) are easy consequences of the definition of , the symmetry of the system and the fact
[TABLE]
which follows from the definition of .
∎
Let
[TABLE]
Note that Lemma 5.1 implies . More precisely, for every and we have
[TABLE]
Lemma 5.2**.**
For every there exists , , such that .
Proof.
Enumerate the components of by , , such that is the gap between and for , is the gap between and , and is the gap between and for . Take . Since the system is symmetric, we can assume , . Then to prove the lemma it is enough to notice that by Lemma 5.1, we have . ∎
Consider the maps
[TABLE]
Note that
[TABLE]
for . Obviously, the maps are contracting similarities with .
Let
[TABLE]
be the limit set of the iterated function system generated by on . Recall that it is the unique non-empty compact set in satisfying
[TABLE]
(see e.g. [Fal03, Theorem 9.1]). For define
[TABLE]
Obviously, are pairwise disjoint compact sets and . Furthermore, for , let
[TABLE]
where for we set , . Since , for every and an infinite sequence the segments , , form a nested sequence of sets, such that
[TABLE]
so
[TABLE]
for a point and
[TABLE]
Description of trajectories
Lemma 5.1 and (11) imply immediately the following.
Lemma 5.3**.**
For , , ,
[TABLE]
and
[TABLE]
The following lemmas characterize trajectories jumping over the central interval. The first one follows directly from Lemma 5.1.
Lemma 5.4**.**
The following statements hold.
- (a)
If a trajectory , for , jumps over the central interval at the time , for , then .
- (b)
A trajectory , for , jumps over the central interval at the time , for , if and only if
[TABLE]
In particular, for given and , for all the trajectories jump over the central interval at the same times.
For such that , define
[TABLE]
Note that for some , , and, by Lemma 5.1,
[TABLE]
for . In particular, this implies
[TABLE]
for such that . By Lemma 5.3,
[TABLE]
for , .
Lemma 5.5**.**
A trajectory of a point , , does not jump over the central interval at any time , for some , if and only if
[TABLE]
for such that and .
Proof.
If a trajectory of does not jump over the central interval at any time , then by Lemmas 5.1 and 5.4,
[TABLE]
for such that . Therefore, by (12). The other implication follows directly from Lemmas 5.1 and 5.4. ∎
Define
[TABLE]
setting
[TABLE]
We have for some , . Moreover, by (11) and (12),
[TABLE]
while Lemma 5.3 and (13) imply
[TABLE]
for , .
Lemma 5.6**.**
A trajectory of a point jumps over the central interval at the time , for some , if and only if
[TABLE]
for some .
Proof.
Follows directly from Lemmas 5.4, 5.5 and the definitions of the maps , . ∎
Lemma 5.7**.**
A trajectory of a point , , jumps over the central interval exactly at the times , for some , , if and only if
[TABLE]
for some and , where when is even and when is odd. Moreover, in this case we have
[TABLE]
and
[TABLE]
Proof.
Follows directly from Lemmas 5.5 and 5.6, and (12), (13), (14), (15). ∎
Definition 5.8**.**
For let be the set of limit points of all trajectories of under , which jump over the central interval infinitely many times, i.e.
[TABLE]
Proposition 5.9**.**
For every ,
[TABLE]
Proof.
First, we prove for . By Lemma 5.4(a), we can assume . Take . Then , where and the trajectory jumps over the central interval infinitely many times. By Lemma 5.7, we have
[TABLE]
for some , , , where as . Since as , , we have . In this way we have showed .
Now we prove for . By Lemma 5.2, we can assume , . Since the system is symmetric, we can assume . Take . Then for some , . Let
[TABLE]
and note that . Define
[TABLE]
for even . Then is well-defined on . Using (13) and (15) inductively, we see
[TABLE]
for every even . Since as and , the trajectory defined by has as a limit point and, by Lemma 5.7, jumps over the central interval infinitely many times. This shows .
Take now and define
[TABLE]
and
[TABLE]
for even . Then, arguing as previously, we see that
[TABLE]
for even , the trajectory defined by has as its limit point and jumps over the central interval infinitely many times. This implies . ∎
Proposition 5.10**.**
We have
[TABLE]
Moreover, the system is minimal in .
Proof.
The first assertion follows directly from Lemma 5.3, while Proposition 5.9 implies minimality. ∎
Singularity of
Proposition 5.11**.**
We have
[TABLE]
Proof.
By Proposition 5.10, we have . Moreover, is closed in . Hence, Lemma 3.12 implies and . On the other hand, the system is minimal in by Proposition 5.10, so Proposition 3.4 gives . ∎
Proposition 5.12**.**
[TABLE]
where is the unique solution of the equation .
Proof.
By definition, the maps , , are contractions and
[TABLE]
Using (8), we check that for . Consequently, is an iterated function system of contracting similarities with scales , respectively, satisfying the Strong Separation Condition, i.e. , , are pairwise disjoint. Therefore, its limit set is a Cantor set and its Hausdorff (and box) dimension is equal to the unique positive number satisfying
[TABLE]
(see e.g. [Fal03, Theorem 9.3]). This equation is equivalent to for . Hence,
[TABLE]
Since , , are disjoint similar copies of , we have , as the Hausdorff dimension is countably stable, see e.g. [Fal03, Section 3.2]. To see note that , where and is given as . Since is Lipschitz and , we obtain .
The condition (8), equivalent to , implies . ∎
Propositions 5.11 and 5.12 imply the following.
Corollary 5.13**.**
The measure is singular with .
Dimension of
To determine the exact form of , consider the coding map for the IFS on given by
[TABLE]
where and is any point from . Note that is a homeomorphism, since the IFS satisfies the strong separation condition. It follows that is homeomorphic to with the topology defined as the product of the discrete topology on and the standard (product) topology on . The homeomorphism is given by
[TABLE]
Let be the lifts by of , , respectively, i.e.
[TABLE]
Lemma 5.3 implies
[TABLE]
Due to (16), there is a one-to-one correspondence between stationary probability measures for the system on with probabilities and for the system with probabilities , both considered on the -algebra of Borel sets. Since there is a unique stationary probability measure for on , there is also a unique stationary probability measure for . Moreover, .
Now we determine the structure of the measure .
Proposition 5.14**.**
There exist numbers and probabilistic vectors , , such that , where are the unique solutions of the equations
[TABLE]
respectively, and
[TABLE]
where
[TABLE]
* is a probability measure on given by*
[TABLE]
and is the Dirac measure at .
Proof.
Let
[TABLE]
Since are convex, , and, by (10), , the function has a unique zero in , which determines the values of , . Suppose that satisfy
[TABLE]
Then the measure
[TABLE]
for as in Proposition 5.14 is a probability measure on . Let
[TABLE]
for , and be the cylinders in . By definition,
[TABLE]
Now we prove that for some choice of the constants satisfying (18) the measure is stationary for with probabilities . Note that to show that is stationary, it is enough to check
[TABLE]
for , even and , because the corresponding cylinders generate the -algebra of Borel sets in . By (17),
[TABLE]
Using this together with (19), we check that (20) for even (split into four cases: , , , , respectively) is equivalent to the following system of equations:
[TABLE]
(where we write instead of ).
Now we solve the system (21) together with (18). The first two equations of (21) agree with the definitions of , . Substituting them, respectively, into the third and fourth ones, we obtain
[TABLE]
Summing this over and using the second and third equation of (18), we have
[TABLE]
and substituting the second and first equation of (21) respectively, we arrive at a single equation
[TABLE]
which together with the first equation of (18) gives
[TABLE]
Using (22), we finally obtain
[TABLE]
The numbers satisfy (21) and (18). In this way we showed that the system of equations (21) and (18) has a unique solution for which the measure is stationary. By the uniqueness of such a measure, we have . ∎
Finally, we determine the Hausdorff dimension of the measure . Since for by Proposition 5.14, we have
[TABLE]
Note that the measure , supported on the Cantor set , is bi-Lipschitz isomorphic (after normalization) to the measure , which (after normalization) is the self-similar measure for the iterated function system with probabilities . It is well-known (see e.g. [Edg98, Theorem 5.2.5]) that the Hausdorff dimension of such a measure is equal to the ratio of the entropy of the measure and its Lyapunov exponent, i.e.
[TABLE]
6. Proof of Theorem 2.10. Case
Preliminaries
In Theorem 2.10 we consider a symmetric AM-system of disjoint type with probabilities , positive Lyapunov exponents and a -resonance for some relatively prime , . In this section we deal with the case . Our approach is similar to the case , however the combinatorics of the obtained system of intervals is more complicated and produces Cantor sets which are attractors for infinite iterated function systems.
We have
[TABLE]
where , , and
[TABLE]
In particular, we have
[TABLE]
A direct computation gives
[TABLE]
We assume that the system is of disjoint type, which is equivalent to
[TABLE]
and also (by symmetry) to
[TABLE]
Hence, since the system is symmetric, we have
[TABLE]
Consider the function , . We have , , and has exactly one zero in . This implies that on has a unique zero , i.e.
[TABLE]
and the assumption is equivalent to
[TABLE]
and also to
[TABLE]
In particular, this shows that the condition implies that the system is of disjoint type, which proves Remark 2.11.
Finally, notice that the positivity of the Lyapunov exponents of the system is equivalent to
[TABLE]
Construction of the set
Let us define the basic intervals in the same manner as in the case , i.e.
[TABLE]
and note that by (25),
[TABLE]
For let
[TABLE]
Let us now explain briefly the differences compared to the case . Unlike previously, the union is no longer forward-invariant under . More precisely, , but is situated between and , inside a larger interval (see Lemma 6.3 and Figure 5). Therefore, our first step is extending the family to a larger family consisting of similar copies of intervals and their further iterates which are not contained in the intervals obtained in previous steps of the construction (see Figures 4 and 5). As a result, we obtain a forward-invariant family of intervals, which has infinitely many elements inside each of the (disjoint) intervals . As before, we iterate the intervals from this family to produce a fully invariant and minimal union of disjoint Cantor sets. The corresponding iterated function system on is generated by the action of on the interval , which maps some of the intervals into . This infinite IFS has a Cantor attractor , which is copied inside each of the intervals to form a suitable invariant minimal set .
Let
[TABLE]
and note that
[TABLE]
As previously, consider the maps
[TABLE]
for . Recall that are orientation-reversing contracting similarities with and .
Lemma 6.1**.**
We have
[TABLE]
Moreover, , , are pairwise disjoint.
Proof.
By definition,
[TABLE]
It is obvious that for and for . The inequality for boils down to (24), while for is equivalent to . For it is enough to have (as and ). By (24) this can be reduced to which is obviously true, since . This proves the first assertion. To show , it is enough to notice that holds due to (23). To check the disjointness of , we notice that the inequality , , is equivalent to (24). ∎
For let
[TABLE]
We will denote the elements of by , where , , , with the convention that for is the empty sequence.
For define
[TABLE]
Note that this notation is compatible with our previous definition of for . Furthermore, for let
[TABLE]
The following lemmas describe the combinatorics of the intervals .
Lemma 6.2**.**
The following statements hold.
- a
, for , , .
- b
The segments , , are pairwise disjoint.
- c
For , the segments , , are pairwise disjoint subsets of .
- d
For , we have , for and , for . In particular,
[TABLE]
- e
*Let . Then for *resp. , the segments , , are situated in in the increasing resp. decreasing order with respect to , to the left resp. right of .
- f
*Let , for . Then for and even or and odd *resp. and odd or and even , the segments , are situated in in the increasing resp. decreasing order with respect to , between and if , and between and if .
- g
, , , .
Proof.
The assertion (a) is straightforward. To show (b), it is enough to use (26) and check for (and use the symmetry of the system). By a direct computation, the latter inequality is equivalent to (24). By symmetry and the definition of and , showing (c)–(f) we can assume . First, we prove (c). Since , Lemma 6.1 implies for . To show the disjointness of , suppose that for some distinct . We can assume . Applying suitable sequence of inverses of maps to both segments, we can suppose or . In the first case we have a contradiction with the last assertion of Lemma 6.1, while the second case contradicts with the first assertion of it. This proves (c). The first part of (d) is straightforward. Together with (c), it shows the second part. The assertion (e) follows from (c) and the fact . The first part of (f) holds by a direct checking. In turn, together with the fact that the maps reverse the orientation and , it proves the second part by induction. The assertion (g) is straightforward. ∎
The following lemma is a direct consequence of the definition of the maps and Lemma 6.2. See Figure 5.
Lemma 6.3**.**
We have
[TABLE]
Moreover, for , we have:
[TABLE]
Analogously,
[TABLE]
In particular, Lemma 6.3 implies . More precisely, for every and ,
[TABLE]
Let
[TABLE]
We will denote the elements of by , , where in the case , in the case and , with the convention that for is the empty sequence. Note that
[TABLE]
For define the maps
[TABLE]
on the interval . By Lemma 6.1,
[TABLE]
so the family is a countable infinite iterated function system of contractions in satisfying for any sequence of mutually distinct elements of . Moreover, the definition of implies
[TABLE]
This together with Lemma 6.1 implies that , , are pairwise disjoint. Similarly as before, we are interested in the limit set of this system. As the family is infinite, there are two limit sets one can consider:
[TABLE]
and its closure
[TABLE]
It is easy to see that they satisfy
[TABLE]
(see e.g. [MU96, Section 2]). As our goal is to find the minimal attractor of the system (which equals also the support of ), we will focus on the . However, we will use the set in the proof of Proposition 6.14, as it is better suited for calculating the Hausdorff dimension.
For let
[TABLE]
where we write
[TABLE]
Obviously, for and . Furthermore, for and let
[TABLE]
(for the set is equal to ). As , for , we have
[TABLE]
so
[TABLE]
for a point and
[TABLE]
Description of trajectories
Lemma 6.3 implies the following.
Lemma 6.4**.**
For , and , we have:
[TABLE]
[TABLE]
and
[TABLE]
[TABLE]
The next lemma follows directly from Lemma 6.3.
Lemma 6.5**.**
The following statements hold.
- (a)
If a trajectory , for , jumps over the central interval at the time , for , then .
- (b)
A trajectory , for , jumps over the central interval at the time , for , if and only if
[TABLE]
In particular, for given and , for all the trajectories jump over the central interval at the same times.
Since are relatively prime, there exist such that . Let
[TABLE]
Then
[TABLE]
For such that , define
[TABLE]
We have for some , , and, by Lemma 6.3,
[TABLE]
for . In particular, this implies
[TABLE]
for such that . By Lemma 6.4,
[TABLE]
for , , .
Lemma 6.6**.**
For every there exists , , such that .
Proof.
If for (resp. ), then it is enough to notice that by Lemma 6.3, we have (resp. ). Suppose . Enumerate the components of by , , such that is the gap between and for , is the gap between and , and is the gap between and for . Since the system is symmetric, we can assume , . Then, by Lemma 6.3, we have . ∎
Define
[TABLE]
by
[TABLE]
Note that for some , . By (28), we have
[TABLE]
[TABLE]
for , , .
Define also
[TABLE]
by
[TABLE]
Again, for some , . By (28) and (30),
[TABLE]
[TABLE]
for , , , .
We introduce the following notation. For we set (resp. ) if (resp. ). We also write and set , .
For , such that and is even, or and is odd, define
[TABLE]
by
[TABLE]
for
[TABLE]
respectively. Note that in the case the definition of agrees with the previous one. We have for some , .
[TABLE]
for . In particular, this gives
[TABLE]
for suitable . Moreover, (29), (31) and (33) imply
[TABLE]
for , .
Lemma 6.7**.**
A trajectory of a point , , does not jump over the central interval at any time , for some , if and only if
[TABLE]
for such that , where and is even, or and is odd.
Proof.
If a trajectory of does not jump over the central interval at any time , then by Lemmas 6.3 and 6.5,
[TABLE]
where such that and is even, or and is odd. Consequently, is defined on and is an increasing affine homeomorphism from onto itself, so it is identity. Therefore, . The other implication follows from Lemmas 6.3 and 6.5 and the definitions of the maps .
∎
Define, for ,
[TABLE]
setting
[TABLE]
Note that for some , . By Lemma 6.3 and (34), we have
[TABLE]
[TABLE]
for , .
Lemma 6.8**.**
A trajectory of a point jumps over the central interval at the time , for some , if and only if one of the four following possibilities:
[TABLE]
holds for some .
Proof.
Follows directly from Lemma 6.5.
∎
Lemma 6.9**.**
A trajectory of a point , , jumps over the central interval exactly at the times , for some , , if and only if
[TABLE]
for some , where , , are defined by backward induction as
[TABLE]
and
[TABLE]
with such that and is even, or and is odd. Moreover, in this case we have
[TABLE]
and
[TABLE]
where , .
Proof.
The definitions of , and the conditions for imply that all the considered maps are well-defined. The assertions of the lemma follow directly from Lemmas 6.7 and 6.8, and (34), (35), (36), (37). ∎
Lemma 6.10**.**
For every , and , there exists a map
[TABLE]
such that for some , and any trajectory of defined by jumps over the central interval at the times , for some .
Proof.
Since the system is symmetric, we can assume .
Let
[TABLE]
and
[TABLE]
Define by
[TABLE]
We have
[TABLE]
Furthermore, define , by
[TABLE]
By the definition of , we have
[TABLE]
Note that if and only if is even. Therefore, as we obtain
[TABLE]
where (resp. ) if (resp. ). This together with (38) implies
[TABLE]
Moreover, by the definition of , we have and is even, or and is odd. This implies that if we define
[TABLE]
then by Lemma 6.9 (with replaced by ), is well-defined on and for some , . Moreover, any trajectory of defined by jumps over the central interval at the times , for some . By (35) and (37),
[TABLE]
∎
Proposition 6.11**.**
For every ,
[TABLE]
Proof.
First, we prove for . By Lemma 6.5(a), we can assume . Take . We have , where and the trajectory jumps over the central interval infinitely many times. By Lemma 6.9,
[TABLE]
for some and , where as . Moreover, as and . Hence, , which shows .
Now we prove for . By Lemma 6.6, we can assume for some . Take . Then for some and , . Using Lemma 6.10, define inductively
[TABLE]
By Lemma 6.10, the trajectory of under defined by is well-defined and jumps over the central interval infinitely many times. Moreover,
[TABLE]
so
[TABLE]
as , since . Hence, is a limit point of this trajectory.
Take now . Then, by Lemma 6.10, we see
[TABLE]
for , the trajectory defined by
[TABLE]
jumps over the central interval infinitely many times and has as its limit point. Hence, .
∎
Proposition 6.12**.**
We have
[TABLE]
Moreover, the system is minimal in .
Proof.
The first assertion follows directly from Lemma 6.4, while Proposition 6.11 implies minimality. ∎
Singularity of
Proposition 6.13**.**
We have
[TABLE]
Proof.
Similarly as for the case , it is enough to use Proposition 6.12. ∎
Proposition 6.14**.**
[TABLE]
where is the unique solution of the equation .
Proof.
Our first goal is to determine the dimension of . We begin with calculating the dimension of the defined in (27). Recall that is an iterated function system of contracting similarities on , satisfying the Strong Separation Condition. It is well-known (see e.g. [MU96, Theorem 3.15]) that for such systems is equal to the (unique) zero of the topological pressure function
[TABLE]
provided the system is regular (i.e. zero of the pressure function exists). Since are affine, we have
[TABLE]
provided , which is equivalent to . Since by Lemma 6.1, , are pairwise disjoint subset of , we have for . It follows that for , where is the unique solution of the equation . Moreover, the condition is equivalent to
[TABLE]
which is the same as (24). Since is strictly decreasing and continuous whenever it is finite (see [MU96]) and , we see that there exists such that . By (39), we have , so
[TABLE]
We will prove now that , i.e. taking the closure does not increase the Hausdorff dimension of . To that end, let be the “asymptotic boundary” of the system , i.e. the set of all limit points of sequences , where and consists of mutually distinct elements of . It follows from [MU96, Lemma 2.1] that
[TABLE]
As the above sum is countable and the transformations are bi-Lipschitz, we obtain
[TABLE]
Using Lemmas 6.1 and 6.2, it is easy to see that
[TABLE]
where is the limit set of the iterated function system on . By Lemma 6.1, this system satisfies the Strong Separation Condition, so its box and Hausdorff dimension are both equal to the unique solution of the equation . As noted above, we have , hence . By Lemma 6.2, the sets , , are disjoint similar copies of , so . To end the proof, note that \Lambda\setminus\bigcup_{{\bf j}\in\mathcal{J}}\Lambda_{\bf j}=\bigcup_{j>0}\big{(}\rho^{j}K\cup\mathcal{I}(\rho^{j}K)\big{)}, hence
[TABLE]
Finally, this implies . ∎
The following proposition gives some information about the structure of the measure in the case of equal probabilities .
Proposition 6.15**.**
Suppose . Then for , , , we have
[TABLE]
for
[TABLE]
where , , moreover resp. are real resp. non-real roots of the polynomial of moduli smaller than and
[TABLE]
Proof.
Let for and define for as in the proposition. Note that the assumption and the uniqueness of imply (recall that for )
[TABLE]
Furthermore, by Lemma 6.3 and the stationarity of , for every fixed we have
[TABLE]
for every , . This defines a linear difference equation with characteristic polynomial . It is well-known (see e.g. [Ela05]) that a solution of such an equation has the form
[TABLE]
, where resp. are real resp. non-real roots of the characteristic polynomial and , . Since , in fact we take into account only the roots of moduli smaller than . This proves that has the form described in the proposition.
To show , note that by Lemma 6.3 and the stationarity of ,
[TABLE]
which together with Proposition 6.13 implies
[TABLE]
Let for , , . Since the family of sets generates the -algebra of Borel sets in , extends to a Borel probability measure on . Therefore, by the uniqueness of the stationary measure, to prove the proposition it is sufficient to check that is stationary. It is enough to verify
[TABLE]
By Lemma 6.4, for , we have
[TABLE]
By (40) and (42), the statement (41) is equivalent to the systems of equations
[TABLE]
where and . The second equation is equivalent to the definition of and the remaining ones hold due to (40), (42) for , and the fact that is stationary.
∎
7. Proof of Theorem 2.15
Let and be the sets constructed in Section 5 (in the case ) or Section 6 (in the case ) for the systems and , respectively. Following the notation used in these sections, we have
[TABLE]
in the case and
[TABLE]
in the case . We define the conjugating homeomorphism setting
[TABLE]
in the case and
[TABLE]
in the case (with a unique continuous extension to ). By the definition of , the map is an increasing homeomorphism between and , while Lemmas 5.3 and 6.4 imply that it conjugates to . It is easy to see that can be extended to an increasing homeomorphism of conjugating to , such that is affine on each component of . For completeness, below we present a detailed construction for the case , leaving the case to the reader.
From the considerations preceding Proposition 5.14, it follows that and are both conjugated to the system acting on . Hence, there exists a homeomorphism conjugating on to on . We claim that can be extended in a continuous and equivariant manner to the interval . To show this, we describe the structure of the complement of in .
Like in the proof of Lemma 5.2, let
[TABLE]
and for define
[TABLE]
By Lemma 5.1, the following statements hold.
- (a)
for . 2. (b)
The sets , , are pairwise disjoint and together with , , form a partition of , where is the gap between and for , is the gap between and , and is the gap between and for . 3. (c)
for , , for . 4. (d)
for , , for .
For , define
[TABLE]
Note that are the gaps between cylinders of the first order for the iterated function system on . More precisely, together with form a partition of , and are situated in the order
[TABLE]
For , and , , define
[TABLE]
where , for , which agrees with the previous definition for . Note that for a fixed , the collection of disjoint intervals forms the complement of the Cantor set and
[TABLE]
with the union being disjoint. We can carry the same construction for the system , yielding a decomposition
[TABLE]
for analogously defined . By Lemma 5.1, for ,
[TABLE]
and for , , , ,
[TABLE]
We can now extend to an increasing homeomorphism of as follows: on , we define to be the unique affine increasing homeomorphism such that and on , , , , we set to be the unique affine increasing homeomorphism such that . Finally, we set . It is easy to see that is a homeomorphism of . Using and we see that
[TABLE]
Since and are both affine and increasing on each of the above intervals, we have on each of them.
8. Proof of Theorem 2.16
We consider a symmetric AM-system with probabilities and positive Lyapunov exponents, which exhibits -resonance and satisfies . The latter condition is equivalent to
[TABLE]
and to . Note that this implies , so the system is of disjoint type (see the beginning of the proof of Theorem 2.10 in the case ).
Define segments , as in the case . We have
[TABLE]
so the segments have pairwise disjoint interiors, each two consecutive intervals (according to the order in ) have a common endpoint and . Similarly, defining maps and intervals , as in the case and proceeding as in the proofs of Lemmas 6.1 and 6.2, we check that for each , the intervals , are contained in , have disjoint interiors and satisfy . Analogously, we can define maps , , intervals and sets in the same way as in the case . The maps form an iterated function system in , such that the intervals have disjoint interiors and . Hence, and the pressure (39) satisfies . The combinatorics of the intervals is the same as in the case , so Lemmas 6.3 and 6.4 and Propositions 6.11 and 6.12 still hold. We have for and .
By Theorem 3.6, there exists a unique stationary measure , and Proposition 6.12 implies . By Proposition 3.11, the measure is non-atomic. Hence, the measure of the endpoints of the intervals is zero. In particular, Proposition 6.15 holds in this case with the same proof.
The above facts show that is a countable iterated function system of contracting similarities on satisfying the Open Set Condition, with the attractor . By Proposition 6.15, the probability measure
[TABLE]
is the self-similar measure for this system with probabilities , .
To prove Theorem 2.16, we show . Since by Proposition 6.15, the measure is a countable linear combination of and its similar copies , , it is sufficient to show . Let
[TABLE]
be the entropy of . The proof splits into two cases depending whether is finite or infinite. To shorten the proof, we do not determine which case actually takes place, but we consider both possibilities.
Suppose first that is infinite. Then we have , where is the unique solution of the equation (see the proof of Proposition 6.14). This fact follows from [BJ18, Proposition 3.1], which is based on [KPW01, Theorem 4.1]. Actually, the mentioned results in [BJ18, KPW01] are formulated for a more specific class of iterated function systems, but the proofs are valid in the general case of self-similar systems on the interval.
Suppose now that is finite. Recall that the self-similar iterated function system on is regular with the attractor . In particular, the normalized Lebesgue measure is the Gibbs and equilibrium state for the geometrical potential in dimension and also the -conformal measure for this system on (see [MU03, Section 4.4]). Moreover, the Lyapunov exponent
[TABLE]
of the measure is finite, since (similarly as in (39)) by the definition of the set in the considered case,
[TABLE]
In such a situation [MU03, Theorem 4.4.7] (see also [HMU02, Theorem 4.6]) asserts that either the self-similar measure is equal to or . Therefore, to end the proof of the theorem, it is sufficient to show .
Suppose . Then
[TABLE]
for . Consider the characteristic polynomial from Proposition 6.15. In the considered case it has the form
[TABLE]
Computing the derivatives, we check that the polynomial has a unique real root , while has a unique real root . By Viete’s formulas for these polynomials, the remaining non-real roots of have moduli greater than . Therefore, Proposition 6.15 implies that for and ,
[TABLE]
for some . Since , we have .
[TABLE]
where . This implies for , which gives
[TABLE]
We have . Moreover, because , . If , then by (45) and the definition of ,
[TABLE]
which is impossible since . Hence, and we can write
[TABLE]
which implies and makes a contradiction. This ends the proof of Theorem 2.16.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1[AM 14] Lluís Alsedà and Michał Misiurewicz, Random interval homeomorphisms , Publ. Mat. 58 (2014), no. suppl., 15–36. MR 3211824
- 2[Ant 84] Vadim A. Antonov, Modeling of processes of cyclic evolution type. Synchronization by a random signal , Vestnik Leningrad. Univ. Mat. Mekh. Astronom. (1984), no. vyp. 2, 67–76. MR 756386
- 3[Arn 98] Ludwig Arnold, Random dynamical systems , Springer Monographs in Mathematics, Springer-Verlag, Berlin, 1998. MR 1723992
- 4[AS 14] Vitor Araujo and Javier Solano, Absolutely continuous invariant measures for random non-uniformly expanding maps , Math. Z. 277 (2014), no. 3-4, 1199–1235. MR 3229987
- 5[Bax 89] Peter H. Baxendale, Lyapunov exponents and relative entropy for a stochastic flow of diffeomorphisms , Probab. Theory Related Fields 81 (1989), no. 4, 521–554. MR 995809
- 6[BJ 18] Simon Baker and Natalia Jurga, Maximising Bernoulli measures and dimension gaps for countable branched systems , preprint ar Xiv:1802.07585, 2018.
- 7[BM 08] Araceli Bonifant and John Milnor, Schwarzian derivatives and cylinder maps , Holomorphic dynamics and renormalization, Fields Inst. Commun., vol. 53, Amer. Math. Soc., Providence, RI, 2008, pp. 1–21. MR 2477416
- 8[BS 19] Krzysztof Barański and Adam Śpiewak, On the dimension of stationary measures for random interval homeomorphisms , in preparation, 2019.
