1 Introduction
One of the most challenging problems in fractal geometry is to understand how a stationary measure distributes mass when the underlying iterated function system (IFS) is overlapping. The exact overlaps conjecture and the study of Bernoulli convolutions are two particular instances of this problem (see [Reference Hochman28, Reference Hochman29, Reference Rapaport44, Reference Rapaport and Varju45, Reference Shmerkin47, Reference Varju50, Reference Varju51] and the references therein). In this paper, we show that for self-conformal and self-similar measures (defined in §2), it is possible to disintegrate them over a family of measures for which we have lots of control over how mass is distributed. Our main result is the following statement.
Theorem 1.1. Let
$\mu $
be a non-atomic self-conformal measure on
$\mathbb {R}^{d}$
. Then there exist a probability space
$(\Omega ,\mathcal {A},\mathbb {P})$
and a family of measures
$\{\mu _{\omega }\}_{\omega \in \Omega }$
such that the following properties are satisfied.
-
(1)
$\mu =\int \mu _{\omega }\, d\mathbb {P}(\omega )$
. -
(2) (Doubling) There exists
$C_{1}>0$
such that for any
$\omega \in \Omega , x\in \mathrm {supp}(\mu _{\omega })$
and
$r>0$
we have
$\mu _{\omega }(B(x,2r))\leq C_{1}\mu _{\omega }(B(x,r)).$
-
(3) (Uniformly non-concentrated on balls) There exist
$C_{2},\alpha>0$
such that for any
${\omega \in \Omega }$
,
$x\in \mathrm {supp}(\mu _{\omega }), y\in \mathbb {R}^{d}, 0<r\leq 1$
and
$\epsilon>0$
we have
$\mu _{\omega }(B(y,\epsilon r)\cap B(x,r))\leq C_{2}\epsilon ^{\alpha }\mu _{\omega }(B(x,r)).$
Moreover, if we also assume that
$\mu $
is an affinely irreducible self-similar measure, then the
$\{\mu _{\omega \}_{\omega \in \Omega }}$
also satisfy the following property.
-
(4) (Uniformly affinely non-concentrated) There exist
$C_{3},\alpha>0$
such that for any
$\omega \in \Omega $
,
$x\in \mathrm {supp}(\mu _{\omega }),$
affine subspace
$W<\mathbb {R}^{d}, 0<r\leq 1$
and
$\epsilon>0$
we have
$\mu _{\omega }(W^{(\epsilon r)}\cap B(x,r))\leq C_{3}\epsilon ^{\alpha }\mu _{\omega }(B(x,r)).$
Precise definitions for the objects appearing in this theorem are given in §2. We merely state at this point that given an affine subspace
$W<\mathbb {R}^{d}$
and
$\epsilon>0,$
we let
$W^{(\epsilon )}$
denote the
$\epsilon $
neighbourhood of W. The
$\mu _{\omega }$
appearing in Theorem 1.1 also satisfy a form of dynamical invariance reminiscent of that satisfied by stationary measures (see (2.2)). A similar result was obtained in [Reference Algom, Rodriguez Hertz and Wang3] where it was shown that it was possible to disintegrate non-atomic self-conformal measures in
$\mathbb {R}$
into a family of measures so that property
$(2)$
is satisfied. It is reasonable to expect that property
$(4)$
also holds for self-conformal measures under suitable irreducibility assumptions. What makes our method of proof fail in this context is that unlike contractions in a self-similar IFS, a contraction in a self-conformal IFS does not necessarily map an affine subspace of
$\mathbb {R}^{d}$
to an affine subspace of
$\mathbb {R}^{d}$
.
The measures
$\mu _{\omega }$
appearing in Theorem 1.1 have many of the properties possessed by self-conformal or self-similar measures when the underlying IFS satisfies the strong separation condition. When the underlying IFS only satisfies the open set condition, or satisfies no separation assumption at all, then these doubling and non-concentration properties do not necessarily hold. We refer the reader to [Reference Yang, Yuan and Zhang53] and the references therein for a detailed discussion of when the doubling property holds for these measures. Section 4 of this paper includes an explicit example of an affinely irreducible self-similar measure coming from an IFS satisfying the open set condition that does not satisfy property
$(4)$
. Given the above, we see that Theorem 1.1 provides a connecting bridge between the more complicated case of overlapping IFSs and the simpler case when the underlying IFS satisfies the strong separation condition. Indeed, if a property is known to hold for
$\mu $
-almost every x under the assumption that the underlying IFS satisfies the strong separation condition, then it reasonable to expect that Theorem 1.1 would provide a route to showing that this property holds for
$\mu $
-almost every x without this assumption. In the next section we will show how this strategy can be implemented to prove results on the Diophantine properties of self-conformal and self-similar measures. This strategy was previously applied in [Reference Algom, Baker and Shmerkin2] to prove results on normal numbers in fractal sets. We conclude this introductory section by highlighting that a disintegration of the form provided by Theorem 1.1 can be used, in conjunction with results from [Reference Khalil33], to prove an
$L^{2}$
-flattening result for the disintegrated measure. We do not include a proof of this fact as such a result is already known for the self-conformal and self-similar measures we are interested in (see [Reference Baker, Khalil and Sahlsten11] for details).
1.1 Diophantine approximation
One of the main motivations behind Theorem 1.1 comes from applications to Diophantine approximation. In this section we detail two such applications.
1.1.1
$\Psi $
-well-approximable vectors
At its core, Diophantine approximation is concerned with approximating elements of
$\mathbb {R}^{d}$
with rational vectors. A standard framework for this problem is as follows. Given a decreasing function
$\Psi :\mathbb {N}\to (0,\infty )$
, let
(i.m. stands for infinitely many). We will always assume that
$\Psi $
is decreasing. Much is known about the Lebesgue measure of the sets
$W(\Psi )$
(see, for instance, [Reference Aistleitner, Borda and Hauke1, Reference Beresnevich, Bernik, Dodson and Velani14, Reference Harman27, Reference Khintchine35, Reference Koukoulopoulos and Maynard40] and the references therein). Once a result has been established for the Lebesgue measure, it is a natural and well-studied problem to show that the analogous statement holds for a fractal measure. This problem has attracted significant attention recently (see [Reference Allen, Baker, Chow and Yu5, Reference Allen, Chow and Yu6, Reference Baker8, Reference Baker9, Reference Broderick, Fishman and Reich16–Reference Bugeaud and Durand18, Reference Das, Fishman, Simmons and Urbański21–Reference Datta and Jana23, Reference Fishman, Merrill and Simmons25, Reference Khalil and Luethi34, Reference Kleinbock, Lindenstrauss and Weiss37, Reference Levesley, Salp and Velani41, Reference Mahler42, Reference Simmons and Weiss48, Reference Tan, Wang and Wu49, Reference Weiss52, Reference Yu54] and the references therein). We do not attempt to give an exhaustive overview of this topic but instead recap a few results to properly contextualize our work. A measure is said to be extremal if it gives zero measure to the very well-approximable vectors (see [Reference Kleinbock, Lindenstrauss and Weiss37] for a definition). Much of the work on this topic was initially concerned with proving that fractal measures are extremal. In [Reference Kleinbock, Lindenstrauss and Weiss37] Kleinbock, Lindenstrauss and Weiss introduced the notion of a friendly measure and showed that any friendly measure is extremal. We do not give the definition of a friendly measure (see [Reference Kleinbock, Lindenstrauss and Weiss37] for a definition), but merely state that the natural Hausdorff measure restricted to a self-similar set coming from an IFS satisfying the open set condition is friendly provided the self-similar set is not contained in an affine subspace. More recently, following on from work of Khalil and Luethi [Reference Khalil and Luethi34], Bénard, He and Zhang [Reference Bénard, He and Zhang13] proved that an analogue of a well-known theorem due to Khintchine holds for any non-atomic self-similar measure in
$\mathbb {R}$
. We finish this discussion by giving a more detailed account of a result due to Pollington and Velani [Reference Pollington and Velani43] which is particularly important to us. They proved the following statement.
Theorem 1.2. Let
$\mu $
be a compactly supported measure on
$\mathbb {R}^{d}$
. Suppose that there exist
$C_1,C_2,\alpha>0$
such that the following properties are satisfied.
-
(1) For any
$x\in \mathrm {supp}(\mu )$
and
$r>0$
we have
$\mu (B(x,2r))\leq C_{1}\mu (B(x,r))$
. -
(2) For any
$x\in \mathrm {supp}(\mu ),$
affine subspace
$W<\mathbb {R}^{d}$
,
$0\leq r \leq 1$
and
$\epsilon>0$
we have
$\mu (W^{(\epsilon r)}\cap B(x,r))\leq C_{2}\epsilon ^{\alpha }\mu (B(x,r))$
.
Then
$\mu (W(\Psi ))=0$
for any
$\Psi $
satisfying
$\sum _{n=1}^{\infty }n^{\alpha ({(d+1)}/{d}) -1}\Psi (n)^{\alpha }<\infty .$
The significance of this theorem is that it allows us to make a stronger conclusion than extremality. In particular, it can be applied to show that
$\mu (W(\Psi ))=0$
for suitable measures where
$\Psi :\mathbb {N}\to (0,\infty )$
is of the form
$\Psi (n)= n^{-({(d+1)}/{d})}(\log n)^{-\beta }.$
Pollington and Velani applied Theorem 1.2 to show that its conclusion holds for the natural Hausdorff measure on a self-similar set when the open set condition is satisfied and the self-similar set is not contained in an affine subspace. The only genuine obstacle to the conclusion of Theorem 1.2 is for the measure to be supported on an affine subspace. In that case it can be shown that the conclusion of this theorem may be false. The conclusion of Theorem 1.2 should hold more generally for self-conformal and self-similar measures with no separation assumptions. The following result which follows from Theorems 1.1 and 1.2 shows that this is indeed the case.
Theorem 1.3. The following statements are true.
-
(1) Let
$\mu $
be a self-conformal measure in
$\mathbb {R}$
. Then there exists
$\alpha>0$
such that
$\mu (W(\Psi ))=0$
for any
$\Psi :\mathbb {N}\to (0,\infty )$
satisfying
$\sum _{n=1}^{\infty }n^{2\alpha -1}\Psi (n)^{\alpha }<\infty .$
-
(2) Let
$\mu $
be an affinely irreducible self-similar measure in
$\mathbb {R}^{d}$
. Then there exists
$\alpha>0$
such that
$\mu (W(\Psi ))=0$
for any
$\Psi :\mathbb {N}\to (0,\infty )$
satisfying
$\sum _{n=1}^{\infty }n^{\alpha ({d+1}/{d}) -1} \Psi (n)^{\alpha }<\infty .$
1.1.2 Singular vectors
A vector
$(x_1,\ldots ,x_d)\in \mathbb {R}^d$
is said to be singular if for every
$c>0$
the system of inequalities
has an integer solution for all
$t>0$
sufficiently large. Here we let
$\|\cdot \|$
denote the distance to the nearest integer. We let
$\mathbf {Sing}_{d}$
denote the set of singular vectors in
$\mathbb {R}^{d}$
. It was shown in [Reference Davenport and Schmidt24] that
$\mathbf {Sing}_{d}$
has zero Lebesgue measure. An argument due to Khintchine shows that in
$\mathbb {R}$
we have
$\mathbf {Sing}_{1}=\mathbb {Q}$
[Reference Khintchine36]. Recently, Cheung and Chevallier [Reference Cheung and Chevallier20] showed that
$\dim _{H}(\mathbf {Sing}_{d})=d^{2}/{(d+1)}$
for all
$d\geq 2$
. For more on singular vectors we refer the reader to [Reference Beresnevich, Guan, Marnat, Ramirez and Velani15, Reference Cheung19, Reference Khalil32, Reference Kleinbock, Moshchevitin and Weiss38]. For our purposes we will need the following result due to Kleinbock and Weiss [Reference Kleinbock and Weiss39].
Theorem 1.4. Let
$\mu $
be a friendly measure on
$\mathbb {R}^{d}$
. Then
$\mu (\mathbf {Sing}_{d})=0$
.
Kleinbock and Weiss used this result to show that the natural Hausdorff measure restricted to a self-similar set coming from an IFS satisfying the open set condition gives zero mass to
$\mathbf {Sing}_{d}$
provided the self-similar set is not contained in an affine subspace. We emphasize that we have not defined what it means for a measure to be friendly (see [Reference Kleinbock, Lindenstrauss and Weiss37] for a definition). We merely remark that if a measure satisfies the assumptions of Theorem 1.2 then it is friendly. The conclusion
$\mu (\mathbf {Sing}_{d})=0$
should hold for a more general family of fractal measures. The only genuine obstruction is for the measure to be supported on an affine subspace. The following statement follows from Theorems 1.1 and 1.4 and shows that this is the case.
Theorem 1.5. Let
$\mu $
be an affinely irreducible self-similar measure on
$\mathbb {R}^{d}$
. Then
$\mu (\mathbf {Sing}_{d})=0$
.
Proof. Let
$\{\mu _{\omega }\}_{\omega \in \Omega }$
be as in Theorem 1.1. Properties
$(2)$
and
$(4)$
of that theorem imply that each
$\mu _{\omega }$
is a friendly measure. Now apply Theorem 1.4 to each
$\mu _{\omega }$
and use the fact that
$\mu =\int \mu _{\omega }\, d\mathbb {P}(\omega )$
to conclude our result.
Theorems 1.1 and 1.4 imply an analogous statement for self-conformal measures when
$d=1$
. However, by the aforementioned result of Khintchine in this case
$\mathbf {Sing}_{1}=\mathbb {Q}$
, so this result holds trivially.
2 Preliminaries
In this section we will introduce some notation, collect some useful results from fractal geometry, and provide a general framework for our disintegration technique.
2.1 Notation
Given a set S and
$f,g:S\to (0,\infty )$
, we write
$f\ll g$
if there exists
$C>0$
such that
$f(s)\leq Cg(s)$
for all
$s\in S$
. We write
$f\asymp g$
if
$f\ll g$
and
$g\ll f$
. Given an alphabet
$\mathcal {A}$
, we let
$\mathcal {A}^*=\bigcup _{n=1}^{\infty }\mathcal {A}^{n}$
denote the set of finite words with entries in
$\mathcal {A}$
. Given two finite words
$\mathbf {a},\mathbf {b}\in \mathcal {A}^{*}$
, we let
$\mathbf {a}\wedge \mathbf {b}$
denote the maximal common prefix of
$\mathbf {a}$
and
$\mathbf {b}$
. If no such prefix exists we define
$\mathbf {a}\wedge \mathbf {b}$
to be the empty word. We denote the length of a finite word
$\mathbf {a}\in \mathcal {A}^*$
by
$|\mathbf {a}|.$
Given
$a\in \mathcal {A}$
and
$n\in \mathbb {N}$
, we let
$a^{n}=\overbrace {a\cdots a}^{\times n}.$
2.2 Fractal geometry
Let
$Y\subset \mathbb {R}^{d}$
be a closed set. A map
$\varphi :Y\to Y$
is called a contraction if there exists
$r\in (0,1)$
such that
$\|\varphi (x)-\varphi (y)\|\leq r\|x-y\|$
for all
$x,y\in Y$
. Here
$\|\cdot \|$
denotes the Euclidean norm on
$\mathbb {R}^{d}$
. An IFS on Y is a finite set of contractions acting on Y. We will often suppress Y from our discussion and simply speak of an iterated function system or IFS. A well-known result due to Hutchinson [Reference Hutchinson30] states that for any IFS
$\Phi =\{\varphi _{a}\}_{a\in \mathcal {A}}$
there exists a unique non-empty compact set
$X\subset \mathbb {R}^{d}$
satisfying
We call X the invariant set of the IFS. We will always assume that two of the contractions in our IFS have distinct fixed points. This ensures that the invariant set is non-trivial. When an IFS
$\Phi $
consists of similarities we say that it is a self-similar IFS and the invariant set is a self-similar set. In the special case where each contraction in our IFS is
$C^{1+\alpha }$
and angle preserving we will say that the IFS is self-conformal. By angle preserving, we mean that for all
$a\in \mathcal {A}$
,
$x\in Y,$
and
$y\in \mathbb {R}^{d}$
we have
$\|\varphi _{a}'(x)y\|=\|\varphi _{a}'(x)\|\cdot \|y\|$
. We will say that a self-similar IFS is affinely irreducible if there does not exist an affine subspace in
$\mathbb {R}^{d}$
that is preserved by each element of the IFS. This is equivalent to the property that the invariant set is not contained in an affine subspace of
$\mathbb {R}^d$
. Given
$\mathbf {a}=(a_1,\ldots ,a_n)\in \mathcal {A}^{*}$
, we let
$\varphi _{\mathbf {a}}=\varphi _{a_1}\circ \cdots \circ \varphi _{a_n}$
.
Given an IFS
$\Phi =\{\varphi _{a}\}_{a\in \mathcal {A}}$
and a probability vector
$\mathbf {p}=(p_{a})_{a\in \mathcal {A}}$
(
$\mathbf {p} $
is a probability vector if
$\sum _{a\in \mathcal {A}} p_a=1$
and
$p_{a}>0$
for all
$a\in \mathcal {A}$
), there exists a unique Borel probability measure
$\mu $
satisfying
$\mu =\sum _{a\in \mathcal {A}}p_{a}\varphi _{a}\mu $
where
$\varphi _{a}\mu $
is the pushforward of
$\mu $
under
$\varphi _{a}$
. We call
$\mu $
the stationary measure corresponding to
$\Phi $
and
$\mathbf {p}$
. It is a consequence of our underlying assumptions that the invariant set is non-trivial that
$\mu $
is always non-atomic. When
$\Phi $
consists of similarities we will say that
$\mu $
is the self-similar measure corresponding to
$\Phi $
and
$\mathbf {p}$
. Similarly, when
$\Phi $
is a self-conformal IFS we will say that
$\mu $
is the self-conformal measure corresponding to
$\Phi $
and
$\mathbf {p}$
. We will say that a self-similar measure is affinely irreducible if the underlying self-similar IFS is affinely irreducible.
We finish this section by stating the following lemma that records some useful properties of self-conformal IFSs. For a proof of this lemma see [Reference Angelevska, Käenmäki and Troscheit7, Lemma 6.1].
Lemma 2.1. Let
$\Phi $
be a self-conformal IFS. Then for any
$x,y\in Y$
and
$\mathbf {a}\in \mathcal {A}^{*}$
we have
Moreover, for any
$\mathbf {a},\mathbf {b}\in \mathcal {A}^{*}$
we have
2.3 A general disintegration framework
In this section we will provide a general framework for disintegrating stationary measures. The ideas appearing in this section have their origins in a paper of Galicer et al. [Reference Galicer, Saglietti, Shmerkin and Yavicoli26]. These ideas have been used to study the absolute continuity of self-similar measures [Reference Käenmäki and Orponen31, Reference Saglietti, Shmerkin and Solomyak46], normal numbers in fractal sets [Reference Algom, Baker and Shmerkin2], and problems related to the Fourier decay of stationary measures [Reference Algom, Rodriguez Hertz and Wang3, Reference Algom, Rodriguez Hertz and Wang4, Reference Baker and Banaji10–Reference Baker and Sahlsten12].
Suppose we are given an IFS
$\Phi =\{\varphi _{a}\}_{a\in \mathcal {A}}$
and a probability vector
$\mathbf {p}$
. Let
$\mathcal {A}_{1},\ldots , \mathcal {A}_{k}\subset \mathcal {A}$
be a collection of non-empty subsets of
$\mathcal {A}$
satisfying
$\bigcup _{i=1}^{k}\mathcal {A}_{i}=\mathcal {A}$
. We emphasize that we do not assume that
$\mathcal {A}_{i}\cap \mathcal {A}_{j}=\emptyset $
for
$i\neq j$
. We let
$I=\{1,\ldots , k\}$
and
$\Omega =I^{\mathbb {N}}$
. We let
$\sigma :\Omega \to \Omega $
denote the usual left shift map, that is,
$\sigma ((i_n))=(i_{n+1})$
for all
$(i_n)\in \Omega $
. We define a probability vector
$\mathbf {q}=(q_i)_{i=1}^{k}$
according to the rule
$$ \begin{align*} q_{i}=\sum_{a\in \mathcal{A}_{i}}\frac{p_{a}}{\#\{j\in I: a\in \mathcal{A}_{j}\}} \end{align*} $$
for each
$i\in I$
. We let
$\mathbb {P}$
denote the infinite product measure on
$\Omega $
corresponding to
$\mathbf {q}$
. Note that
$\mathbb {P}$
is
$\sigma $
-invariant. For each
$i\in I$
we define a probability vector
$\mathbf {q}_{i}=(q_{a}^{i})_{a\in \mathcal {A}_{i}}$
according to the rule
$$ \begin{align*} q_{a}^{i}=\frac{1}{q_{i}}\frac{p_{a}}{\#\{j\in I: a\in \mathcal{A}_{j}\}} \end{align*} $$
for each
$i\in \mathcal {A}_{i}$
. Given
$\omega =(i_n)\in \Omega $
, we let
$\Sigma _{\omega }=\prod _{n=1}^{\infty }\mathcal {A}_{i_n}$
and
$m_{\omega }=\prod _{n=1}^{\infty }\mathbf {q}_{i_n}.$
We emphasize that for all
$\omega \in \Omega $
the support of
$m_{\omega }$
is
$\Sigma _{\omega }$
. Given
$\omega \in \Omega $
, we also let
${\Pi _{\omega }:\Sigma _{\omega }\to \mathbb {R}^{d}}$
be given by
Here
$\mathbf {x}$
is any vector in the domain of our IFS. For each
$\omega \in \Omega $
we let
$X_{\omega }=\Pi _{\omega }(\Sigma _{\omega })$
. It follows from the definition that
$X_{\omega }$
satisfies a form of dynamical invariance which resembles that satisfied by invariant sets:
$$ \begin{align} X_{\omega}=\bigcup_{a\in \mathcal{A}_{i_1}}\varphi_{a}(X_{\sigma(\omega)}). \end{align} $$
Moreover, iterating (2.1), we have the following relation for all
$\omega \in \Omega $
and
$n\in \mathbb {N}$
:
$$ \begin{align*} X_{\omega}=\bigcup_{\mathbf{a}\in \prod_{j=1}^{n}\mathcal{A}_{i_j}}\varphi_{\mathbf{a}}(X_{\sigma^{n}\omega}). \end{align*} $$
Last of all, we define
$\mu _{\omega }=\Pi _{\omega }m_{\omega }$
. It follows immediately from the definition of
$\mu _{\omega }$
that we have the following relation which resembles that satisfied by stationary measures:
$$ \begin{align} \mu_{\omega}=\sum_{a\in \mathcal{A}_{i_1}}q_{a}^{i_1}\varphi_{a}\mu_{\sigma(\omega)}. \end{align} $$
Iterating (2.2), we have the following relation for all
$\omega \in \Omega $
and
$n\in \mathbb {N}$
:
$$ \begin{align*}\mu_{\omega}=\sum_{\mathbf{a}\in \prod_{j=1}^{n}\mathcal{A}_{i_j}}\prod_{j=1}^{n}q_{a_j}^{i_j}\cdot \varphi_{\mathbf{a}}\mu_{\sigma^{n}\omega}.\end{align*} $$
The following result shows that the above framework always gives a disintegration of a stationary measure.
Proposition 2.2. Let
$\mu $
be the stationary measure for an IFS
$\{\varphi _{a}\}_{a\in \mathcal {A}}$
and a probability vector
$\mathbf {p}$
. Let
$\mathcal {A}_{1},\ldots ,\mathcal {A}_{k}\subset \mathcal {A}$
satisfy
$\bigcup _{i=1}^{k}\mathcal {A}_{i}=\mathcal {A}$
. Then for the family of measures
$\{\mu _{\omega }\}_{\omega \in \Omega }$
defined above, we have the following disintegration of
$\mu $
:
Various versions of Proposition 2.2 appear in the literature (see [Reference Algom, Baker and Shmerkin2, Reference Baker and Banaji10, Reference Galicer, Saglietti, Shmerkin and Yavicoli26, Reference Saglietti, Shmerkin and Solomyak46], for instance). The proof of this proposition is a minor adaptation of the arguments appearing in these papers and is therefore omitted. Our proof of Theorem 1.1 will rely upon a careful choice of
$\mathcal {A}_{1},\ldots ,\mathcal {A}_{k}.$
3 Proof of Theorem 1.1
In this section we will prove Theorem 1.1. We first present the proof for self-conformal IFSs as it is the simplest and it will serve as a warm-up for the more demanding arguments required for affinely irreducible self-similar measures.
3.1 Proof of Theorem 1.1 for self-conformal measures
Let us fix a self-conformal IFS
$\Phi $
and a probability vector
$\mathbf {p}$
. We let X denote the invariant set of
$\Phi $
. Appealing to our underlying assumption that the IFS is non-trivial, we can assert that there exist
$N\in \mathbb {N}$
and
$a_1,a_2\in \mathcal {A}$
such that
$\varphi _{a_1^{N}}(X)\cap \varphi _{a_{2}^{N}}(X)=\emptyset .$
Replacing N with a potentially larger integer, we can guarantee that the following property also holds. For any
$\mathbf {a}\in \mathcal {A}^{N}$
, either
${\varphi _{\mathbf {a}}(X)\cap \varphi _{a_{1}^{N}}(X)=\emptyset }$
or
$\varphi _{\mathbf {a}}(X)\cap \varphi _{a_{2}^{N}}(X)=\emptyset .$
It follows from the above, and the well-known fact that any stationary measure for an IFS can be realized as a stationary measure for an iterate of an IFS, that after relabelling digits there is no loss of generality in assuming that the following lemma holds.
Lemma 3.1. There exist
$a_{1},a_{2}\in \mathcal {A}$
such that for any
$a\in \mathcal {A}$
either
$\varphi _{a}(X)\cap \varphi _{a_1}(X)=\emptyset $
or
$\varphi _{a}(X)\cap \varphi _{a_2}(X)=\emptyset .$
We are now in a position to define our subsets of
$\mathcal {A}$
so that we can perform our disintegration. For each
$a\in \mathcal {A}$
let
$\mathcal {A}_{a}=\{a,a_i\}$
where
$a_i\in \{a_1,a_2\}$
has been chosen so that
This is permissible by Lemma 3.1. We will show that Theorem 1.1 holds for the
$\Omega $
,
$\mathbb {P}$
, and
$\{\mu _{\omega }\}_{\omega \in \Omega }$
corresponding to
$\{\mathcal {A}_{a}\}_{a\in \mathcal {A}}$
coming from Proposition 2.2. We emphasize that in this context
$\Omega =\mathcal {A}^{\mathbb {N}}$
. At this point it is instructive to highlight an ambiguity in our notation. Elements of
$\mathcal {A}$
are being used to encode two objects. They encode contractions in our IFS, as is standard. They also encode the sets with which we perform our disintegration, that is, the sets
$\mathcal {A}_1,\ldots , \mathcal {A}_k$
(using the terminology of §2). Thus, to help with our exposition, when an element of
$\mathcal {A}$
is being used to encode a contraction we will denote it by a, and when an element of
$\mathcal {A}$
is being used to encode a subset of
$\mathcal {A}$
we will denote it by b. Elements of
$\Omega $
will be denoted by
$(b_n)_{n=1}^{\infty }.$
We now make several straightforward observations that follow from the construction of the sets
$\{\mathcal {A}_{b}\}_{b\in \mathcal {A}}$
. There exists
$c_{1}>0$
such that for any
$(b_n)\in \Omega ,$
if
$a,a'\in \mathcal {A}_{b_1}$
are distinct then
This equation has the important consequence that there exist constants
$c_{2},c_{3}>0$
such that for all
$\omega \in \Omega $
we have
Combining (3.3) with Lemma 2.1 implies that for any
$\omega \in \Omega $
and
$\mathbf {a}\in \mathcal {A}^{*}$
we have
It also follows from the definition of
$\mu _{\omega }$
and (3.1) that for any
$\omega =(b_n)\in \Omega $
and
$(a_1,\ldots a_n)\in \prod _{j=1}^{n}\mathcal {A}_{b_j}$
we have
$$ \begin{align} \mu_{\omega}(\varphi_{a_1,\ldots, a_n}(X_{\sigma^{n}\omega}))=\prod_{j=1}^{n}q_{a_j}^{b_j}. \end{align} $$
Moreover, since each
$\mathcal {A}_{b}$
contains at least two elements and our probability vector
$\mathbf {p}$
is strictly positive, it follows that
satisfy
We will also require the following lemmas.
Lemma 3.2. For all
$(b_n)\in \Omega $
and
$\mathbf {a},\mathbf {a}^{\prime }\in \bigcup _{n=1}^{\infty }\prod _{j=1}^{n}\mathcal {A}_{b_{j}}$
such that
$\mathbf {a}$
is not a prefix of
$\mathbf {a}'$
and
$\mathbf {a}^{\prime }$
is not a prefix of
$\mathbf {a},$
we have
Proof. Since
$\varphi _{\mathbf {a}}(X),\varphi _{\mathbf {a}}^{\prime }(X)\subset \varphi _{|\mathbf {a}\wedge \mathbf {a}^{\prime }|}(X)$
for all
$\mathbf {a},\mathbf {a}^{\prime }\in \mathcal {A}^*$
we trivially have
We now focus on proving an inequality in the opposite direction. Let
$\mathbf {a}=(a_n),\mathbf {a}^{\prime }=(a_{n}^{\prime })\in \bigcup _{n=1}^{\infty }\prod _{j=1}^{n}\mathcal {A}_{b_j}$
satisfy the assumptions of the lemma. Let us also assume that they have a common prefix, that is,
$\mathbf {a}\wedge \mathbf {a}^{\prime }$
exists. The case where
$\mathbf {a}\wedge \mathbf {a}'$
is the empty word follows immediately from (3.2). Let
$x_{\mathbf {a}},x_{\mathbf {a}}^{\prime }$
be such that
$d(\varphi _{\mathbf {a}}(X),\varphi _{\mathbf {a}^{\prime }}(X))=\|x_{\mathbf {a}}-x_{\mathbf {a}^{\prime }}\|.$
These points have to exist by compactness. There exist
$\tilde {x}_{\mathbf {a}}\in \varphi _{a_{|\mathbf {a}\wedge \mathbf {a}^{\prime }|+1}}(X)$
and
$\tilde {x}_{\mathbf {a}^{\prime }}\in \varphi _{a_{|\mathbf {a}\wedge \mathbf {a}^{\prime }|+1}^{\prime }}(X)$
such that
$\varphi _{\mathbf {a}\wedge \mathbf {a}^{\prime }}(\tilde {x}_{\mathbf {a}})=x_{\mathbf {a}}$
and
$\varphi _{\mathbf {a}\wedge \mathbf {a}^{\prime }}(\tilde {x}_{\mathbf {a}^{\prime }})=x_{\mathbf {a}^{\prime }}.$
Since
$a_{|\mathbf {a}\wedge \mathbf {a}^{\prime }|+1}\neq a_{|\mathbf {a}\wedge \mathbf {a}^{\prime }|+1}^{\prime },$
it follows from (3.2) that
$\|\tilde {x}_{\mathbf {a}}-\tilde {x}_{\mathbf {a}^{\prime }}\|\geq c_{1}$
. Using this inequality together with Lemma 2.1 yields
Lemma 3.3. There exists
$M\in \mathbb {N}$
such that for any
$\omega \in \Omega , r\in (0,c_{1}/2)$
and
$x\in X_{\omega }$
there exist
$(a_n)\in \Sigma _{\omega }$
and
$N_1,N_{2}\in \mathbb {N}$
satisfying:
-
(1)
$0<N_{2}-N_{1}\leq M$
; -
(2) Diam
$(\varphi _{a_1\cdots a_{N_1}}(X_{\sigma ^{N_1}\omega }))\asymp $
Diam
$(\varphi _{a_1\cdots a_{N_2}}(X_{\sigma ^{N_2}\omega }))\asymp r$
; -
(3)
$B(x,2r)\cap X_{\omega }\subset \varphi _{a_1\cdots a_{N_1}}(X_{\sigma ^{N_{1}}\omega })$
; -
(4)
$\varphi _{a_1\cdots a_{N_2}}(X_{\sigma ^{N_{2}}\omega })\subset B(x,r)$
.
Proof. Let
$\omega =(b_n)$
, r and x be as in the statement of our lemma. Since
$x\in X_{\omega }$
there exists
$(a_n)\in \Sigma _{\omega }$
such that
$\Pi _{\omega }((a_n))=x$
. For the rest of our proof this
$(a_n)$
is fixed. We let
and
It follows from (2.1), (3.2) and our assumption
$r\in (0,c_1/2)$
that
$N_{1}$
is well defined. It is a consequence of (2.1) that
$N_{1}<N_{2}$
. The third and fourth properties in the statement of our lemma follow immediately for this choice of
$N_1$
and
$N_2$
. It remains to show that
$N_{2}-N_{1}$
can be uniformly bounded from above and that the second statement holds.
We focus on proving the second property holds, namely,
Since
$\varphi _{a_1\cdots a_{N_2}}(X_{\sigma ^{N_2}\omega })\subset \varphi _{a_1\cdots a_{N_1}}(X_{\sigma ^{N_1}\omega })$
by (2.1), it will suffice to show that
Let
$N_{3}=\min \{n\in \mathbb {N}: \varphi _{a_1\cdots a_{n}}(X)\subset B(x,r) \}.$
Since
$X_{\omega }\subset X$
for any
$\omega \in \Omega $
it follows from the definition that
$N_{2}\geq N_{3}.$
Appealing to well-known properties of self-conformal IFSs, it can be shown that the sequence
$(\mathrm {Diam}(\varphi _{a_1\cdots a_{n}}(X)))_{n=1}^{\infty }$
satisfies
for all
$n\in \mathbb {N}$
for some
$\kappa \in (0,1)$
that does not depend upon
$(a_n)$
. Using this property together with the fact that
$\Pi _{\omega }((a_n))=x$
, it follows that
$\mathrm {Diam}(\varphi _{a_1\cdots a_{N_{3}}}(X))\gg r$
. Combining this with (3.4) then implies that
We have
$N_{2}\leq N_{3}$
so
$\varphi _{a_1\cdots a_{N_{3}}}(X_{\sigma ^{N_{3}}\omega })\subset \varphi _{a_1\cdots a_{N_{2}}}(X_{\sigma ^{N_{2}}\omega })$
by (2.1). Therefore,
$\mathrm {Diam}(\varphi _{a_1\cdots a_{N_{2}}}(X_{\sigma ^{N_{2}}\omega }))\geq \mathrm {Diam}(\varphi _{a_1\cdots a_{N_{3}}}(X_{\sigma ^{N_{3}}\omega })).$
Thus, the above implies that
and we have proved the first part of (3.10).
We now focus on the second inequality in (3.10). It follows from the definition of
$N_{1}$
and (2.1) that there exist distinct
$a,a'\in \mathcal {A}_{b_{N_1+1}}$
such that
Therefore,
Since
$X_{\omega }\subset X$
for all
$\omega \in \Omega $
, this now implies that
By Lemma 3.2 this implies that
Since
for all
$\omega \in \Omega ,$
this in turn implies that
Thus, we have established the second part of (3.10). As previously remarked, this together with (3.11) implies (3.9). Thus, the second property in the statement of our lemma holds.
We now focus on establishing the uniform upper bound for
$N_2 - N_1$
. By (3.4) we have
and
Combining these equations with our second property and Lemma 2.1, we have
$$ \begin{align*} 1\asymp \frac{r}{r}\asymp \frac{\mathrm{Diam}(\varphi_{a_1\cdots a_{N_2}}(X_{\sigma^{N_2}\omega}))}{\mathrm{Diam}(\varphi_{a_1\cdots a_{N_1}}(X_{\sigma^{N_1}\omega}))}\asymp\frac{\mathrm{Diam}(\varphi_{a_1\cdots a_{N_2}}(X))}{\mathrm{Diam}(\varphi_{a_1\cdots a_{N_1}}(X))}\asymp \mathrm{Diam}(\varphi_{a_{N_1+1}\cdots a_{N_2}}(X)).\end{align*} $$
Since
$\mathrm {Diam}(\varphi _{a_{N_1+1}\cdots a_{N_2}}(X))\ll \gamma ^{N_2-N_1}$
for some
$\gamma \in (0,1)$
it follows that
$1\ll \gamma ^{N_2-N_1}$
. Hence
$N_{2}-N_{1}$
must be uniformly bounded from above.
We now give our proof of Theorem 1.1 for self-conformal measures.
Proof of Theorem 1.1 for self-conformal measures
Statement
$(1)$
of this theorem is the content of Proposition 2.2. Let us now focus on statement
$(2)$
. Let
$\omega =(b_n)\in \Omega , x\in \mathrm {supp}(\mu _{\omega })$
and
$0<r\leq c_{1}/2$
. We emphasize that to establish statement
$(2)$
it suffices to consider r in this interval. Applying Lemma 3.3, we can assert that there exist two words
$\mathbf {a},\mathbf {a}'$
such that
$\mathbf {a}$
is a prefix of
$\mathbf {a}', |\mathbf {a}'|-|\mathbf {a}|\ll 1,$
and
Therefore, by (3.5) we have
$$ \begin{align*}\mu_{\omega}(B(x,2r))\leq \mu_{\omega}(\varphi_{\mathbf{a}}(X_{\sigma^{|\mathbf{a}|}\omega}))=\prod_{j=1}^{|\mathbf{a}|}q_{a_j}^{b_{j}} \end{align*} $$
and
$$ \begin{align*}\prod_{j=1}^{|\mathbf{a}'|}q_{a_{j}'}^{b_{j}}= \mu_{\omega}(\varphi_{\mathbf{a}'}(X_{\sigma^{|\mathbf{a}'|}\omega}))\leq \mu_{\omega}(B(x,r)). \end{align*} $$
Now using these inequalities together with the facts that
$\mathbf {a}$
is a prefix of
$\mathbf {a}'$
and
${|\mathbf {a}'|-|\mathbf {a}|\ll 1}$
, we have
$$ \begin{align*} \frac{\mu_{\omega}(B(x,2r))}{\mu_{\omega}(B(x,r))}\ll \frac{\prod_{j=1}^{|\mathbf{a}|}q_{a_{j}}^{b_{j}}}{\prod_{j=1}^{|\mathbf{a}'|}q_{a_{j}'}^{b_{j}}}& =\bigg(\prod_{j=|\mathbf{a}|+1}^{|\mathbf{a}'|}q_{a_{j}'}^{b_{j}}\bigg)^{-1}\leq q_{\min}^{-(|\mathbf{a}'|-|\mathbf{a}|)}\ll 1. \end{align*} $$
In the final inequality we used (3.6). Thus,
$\mu (B(x,2r))\ll \mu (B(x,r))$
and statement
$(2)$
follows.
We now turn our attention to statement
$(3)$
of our theorem. Let
$(b_n)\in \Omega $
,
$x\in \mathrm {supp}(\mu _{\omega })$
,
$y\in \mathbb {R}^{d}$
,
$0<r<c_{1}$
and
$0<\epsilon <1$
. We emphasize that there is no loss of generality in restricting to
$0<r<c_{1}$
and
$0<\epsilon <1$
. We may also assume without loss of generality that
$y\in \mathrm {supp}(\mu _{\omega })$
and that
$B(y,\epsilon r)\subset B(x,r).$
This final reduction is permissible because of the doubling property guaranteed by the already established statement
$(2)$
.
By Lemma 3.3 there exist
$\mathbf {a},\mathbf {a}'\in \bigcup _{n=1}^{\infty }\prod _{j=1}^{n}\mathcal {A}_{b_j}$
such that:
-
•
$\mathrm {Diam}(\varphi _{\mathbf {a}}(X_{\sigma ^{|\mathbf {a}|}\omega }))\asymp r$
; -
•
$\mathrm {Diam}(\varphi _{\mathbf {a}^{\prime }}(X_{\sigma ^{|\mathbf {b}|}\omega }))\asymp \epsilon r$
; -
•
$B(x,r)\cap X_{\omega }\subset \varphi _{\mathbf {a}}(X_{\sigma ^{|\mathbf {a}|}\omega })$
; -
•
$\varphi _{\mathbf {a}^{\prime }}(X_{\sigma ^{|\mathbf {a}^{\prime }|}\omega })\subset B(y,\epsilon r)$
.
The analysis given in the proof of statement
$(2)$
also yields the following properties of
$\mathbf {a}$
and
$\mathbf {a}^{\prime }$
:
and
It follows from the inclusions
$B(y,\epsilon r)\subset B(x,r)$
and
$B(x,r)\cap X_{\omega }\subset \varphi _{\mathbf {a}}(X_{\sigma ^{|\mathbf {a}|}\omega })$
that
$\mathbf {a}$
must be a prefix of
$\mathbf {a}^{\prime }$
. As a consequence of this fact, the above, (3.4), and Lemma 2.1, we have that
$$ \begin{align} \epsilon \asymp \frac{\epsilon r}{r}\asymp \frac{\mathrm{Diam}(\varphi_{\mathbf{a}^{\prime}}(X_{\sigma^{|\mathbf{a}^{\prime}|}\omega}))}{\mathrm{Diam}(\varphi_{\mathbf{a}}(X_{\sigma^{|\mathbf{a}|}\omega}))}\asymp \frac{\mathrm{Diam}(\varphi_{\mathbf{a}^{\prime}}(X))}{\mathrm{Diam}(\varphi_{\mathbf{a}}(X))}\asymp \mathrm{Diam}(\varphi_{a_{|\mathbf{a}|+1}^{\prime}\cdots a_{|\mathbf{a}^{\prime}|}^{\prime}}(X)). \end{align} $$
Appealing to well-known properties of self-conformal IFSs, it can be shown that there exist
$\gamma ,c_1\in (0,1)$
such that
$\mathrm {Diam}(\varphi _{\mathbf {a}}(X))\geq c\gamma ^{|\mathbf {a}|}$
for all
$\mathbf {a}\in \mathcal {A}^{*}$
. Substituting this inequality into (3.15) implies that there exist
$c_{2},c_{3}>0$
such that
We now observe that
$$ \begin{align*} \frac{\mu_{\omega}(B(y,\epsilon r)\cap B(x,r))}{\mu_{\omega}(B(x, r))}\stackrel{({3.13}),\, ({3.14})}{\asymp} \frac{\mu_{\omega}(\varphi_{\mathbf{a}^{\prime}}(X_{\sigma^{|\mathbf{a}^{\prime}|}\omega}))}{\mu_{\omega}(\varphi_{\mathbf{a}}(X_{\sigma^{|\mathbf{a}|}\omega}))} & \stackrel{({3.5})}{=}\bigg(\prod_{j=1}^{|\mathbf{a}^{\prime}|}q_{a_{j}^{\prime}}^{b_{j}}\bigg)\cdot \bigg(\prod_{j=1}^{|\mathbf{a}|}q_{a_{j}}^{b_{j}}\bigg)^{-1} \\&\kern5pt =\prod_{j=|\mathbf{a}|+1}^{|\mathbf{a}^{\prime}|}q_{a_{j}'}^{b_{j}} \\&\kern4pt \leq q_{\max}^{|\mathbf{a}^{\prime}|-|\mathbf{a}|} \\& \stackrel{({3.16})}{\ll} q_{\max}^{-c_{2}\log \epsilon} \\&\kern5pt =\epsilon^{\alpha} \end{align*} $$
where
$\alpha =-c_{2}\log q_{\max }.$
In the second equality we have used that
$\mathbf {a}$
is a prefix of
$\mathbf {a}'$
. The fact that
$\alpha>0$
follows from (3.6). Thus, statement
$(3)$
holds and our proof is complete.
3.2 Proof of Theorem 1.1 for affinely irreducible self-similar measures
Throughout this section we fix an affinely irreducible self-similar IFS
$\Phi $
and a probability vector
$\mathbf {p}$
. We begin by making some simplifications that are permissible because of our affinely irreducible assumption.
Suppose that for all
$n\in \mathbb {N}$
there exists an affine subspace
$W_{n}<\mathbb {R}^{d}$
such that our self-similar set X satisfies
$X\subset W_{n}^{(1/n)}$
. Then, appealing to a compactness argument, there must exist an affine subspace
$W<\mathbb {R}^{d}$
such that
$X\subset W$
. This contradicts our affinely irreducible assumption, and so there must exist
$\epsilon _{0}>0$
such that for any affine subspace
$W<\mathbb {R}^{d}$
we have
$X\setminus W^{(\epsilon _0)}\neq \emptyset .$
Replacing
$\epsilon _0$
with a potentially smaller constant, it follows that there exist
$x_1,\ldots , x_{n}\in X$
such that the following properties are satisfied.
-
•
$B(x_i,\epsilon _0)\cap B(x_j, \epsilon _0)=\emptyset $
for
$i\neq j$
. -
• For any
$x\in X$
there exists
$1\leq i\leq n$
such that
$B(x_i,\epsilon _{0})\subset B(x,3\epsilon _{0})$
. -
• For any affine subspace
$W{\kern-1pt}<{\kern-1pt}\mathbb {R}^{d}$
there exists
$1{\kern-1pt}\leq{\kern-1pt} i{\kern-1pt}\leq{\kern-1pt} n$
such that
${B(x_i,\epsilon _0){\kern-1pt}\cap{\kern-1pt} W^{(\epsilon _0)}=\emptyset }$
.
Now using the self-similar structure of X, these properties imply that there exist
$N\in \mathbb {N}$
and
$\mathbf {a}_1,\ldots ,\mathbf {a}_n\in \mathcal {A}^{N}$
such that the following statements hold.
-
•
$\varphi _{\mathbf {a}_i}(X)\cap \varphi _{\mathbf {a}_j}(X)=\emptyset $
for
$i\neq j$
. -
• For any
$x\in X$
there exists
$1\leq i\leq n$
such that
$\varphi _{\mathbf {a}_{i}}(X)\subset B(x,3\epsilon _{0})$
. -
• For any affine subspace
$W<\mathbb {R}^{d}$
there exists
$1\leq i\leq n$
such that
$\varphi _{\mathbf {a}_i}(X)\cap W^{(\epsilon _0)}=\emptyset $
.
Now replacing N with a larger integer if necessary, and
$\epsilon _0>0$
with a potentially smaller quantity if necessary, the above implies that there exist
$N\in \mathbb {N}$
and
$\mathbf {a}_{1},\ldots \mathbf {a}_{n}$
such that the following properties are satisfied.
-
• For any
$\mathbf {a}\in \mathcal {A}^{2N}$
there exists
$1\leq i\leq n$
such that
$$ \begin{align*} \varphi_{\mathbf{a}}(X)\cap \bigcup_{j=1}^{n}\varphi_{\mathbf{a}_{i}\mathbf{a}_{j}}(X)=\emptyset. \end{align*} $$
-
• For any
$1\leq i\leq n$
we have
$\varphi _{\mathbf {a}_{i}\mathbf {a}_{j}}(X)\cap \varphi _{\mathbf {a}_{i}\mathbf {a}_{j^{\prime }}}(X)=\emptyset $
for
$j\neq j^{\prime }$
. -
• For any affine subspace
$W<\mathbb {R}^{d}$
and
$1\leq i\leq n,$
there exists
$1\leq j\leq n$
such that
$\varphi _{\mathbf {a}_i\mathbf {a}_j}(X)\cap W^{(\epsilon _0)}=\emptyset $
.
To derive the third property listed above, we have relied upon the fact that our contractions are similarities and therefore map affine subspaces to affine subspaces and contract distances in a uniform way.
It is clear now that after iterating our IFS and relabelling the digits, we can assume without loss of generality that the following lemma holds.
Lemma 3.4. There exist
$n\in \mathbb {N}, \{a_{1,1},\ldots , a_{n,1}\},\ldots , \{a_{1,n},\ldots , a_{n,n}\}\subset \mathcal {A}$
and
$\epsilon _0>0$
such that the following properties are satisfied.
-
• For any
$a\in \mathcal {A}$
there exists
$1\leq i\leq n$
such that
$$ \begin{align*}\varphi_{a}(X)\cap \bigcup_{j=1}^{n}\varphi_{a_{j,i}}(X)=\emptyset. \end{align*} $$
-
• For any
$1\leq i\leq n$
we have
$\varphi _{a_{j,i}}(X)\cap \varphi _{a_{j^{\prime },i}}(X)=\emptyset $
for
$j\neq j^{\prime }$
. -
• For any affine subspace
$W<\mathbb {R}^{d}$
and
$1\leq i\leq n,$
there exists
$1\leq j\leq n$
such that
$\varphi _{a_{j,i}}(X)\cap W^{(\epsilon _0)}=\emptyset $
.
For each
$a\in \mathcal {A}$
we let
$\mathcal {A}_{a}=\{a,a_{1,i},\ldots a_{n,i}\}$
where
$\{a_{1,i},\ldots a_{n,i}\}$
is one of the subsets listed in Lemma 3.4 and has been chosen so that
$$ \begin{align*}\varphi_{a}(X)\cap \bigcup_{j=1}^{n}\varphi_{a_{j,i}}(X)=\emptyset.\end{align*} $$
As in the proof of Theorem 1.1, an ambiguity in our notation arises. Elements of
$\mathcal {A}$
encode contractions in our IFS and the sets with which we perform our disintegration. To help with our exposition, when an element of
$\mathcal {A}$
is being used to encode a contraction we will denote it by a, and when an element of
$\mathcal {A}$
is being used to encode a subset of
$\mathcal {A}$
we will denote it by b.
It follows from the above that there exists
$c_{1}>0$
such that for any
$b\in \mathcal {A},$
if
$a,a'\in \mathcal {A}_{b}$
are distinct then
and
It follows now from the definition of
$\mu _{\omega }$
and (3.18) that for any
$\omega =(b_n)\in \Omega $
and
$(a_1,\ldots a_n)\in \prod _{j=1}^{n}\mathcal {A}_{b_j},$
we have
$$ \begin{align} \mu_{\omega}(\varphi_{a_1,\ldots, a_n}(X_{\sigma^{n}\omega}))=\prod_{j=1}^{n}q_{a_j}^{b_j}. \end{align} $$
As in the proof of Theorem 1.1, since each
$\mathcal {A}_{b}$
contains at least two elements and our probability vector
$\mathbf {p}$
is strictly positive, it follows that
satisfy
We now show that the desired properties hold for the
$\Omega $
,
$\mathbb {P}$
and
$\{\mu _{\omega }\}_{\omega }$
coming from Proposition 2.2 for this choice of
$\{\mathcal {A}_{b}\}_{b\in \mathcal {A}}.$
The first step is the following proposition which uniformly bounds how much mass a
$\mu _{\omega }$
can give to a neighbourhood of an affine subspace.
Proposition 3.5. There exist
$C,\alpha>0$
such that for any
$\omega \in \Omega , W<\mathbb {R}^{d}$
and
$\epsilon>0$
we have
$\mu _{\omega }(W^{(\epsilon )})\leq C\epsilon ^{\alpha }.$
Proof. We begin by remarking that to prove our proposition it suffices to consider
$\epsilon < \epsilon _{0}$
where
$\epsilon _{0}$
is as above. Let
$$ \begin{align*} r_{\min}:=\min_{a\in \mathcal{A}}\min_{x,y\in\mathbb{R}^{d},\, x\neq y}\bigg\{\frac{\|\varphi_{a}(x)-\varphi_{a}(y)\|}{\|x-y\|}\bigg\}. \end{align*} $$
Since our IFS consists of similarities we must have
$r_{\min }>0$
. Our proof will rely upon showing that for any
$\omega \in \Omega $
,
$\epsilon <\epsilon _{0}$
and
$W<\mathbb {R}^{d}$
there exists an affine subspace
$W_{1}<\mathbb {R}^{d}$
such that
As such, let
$\omega =(b_n)\in \Omega , W<\mathbb {R}^{d}$
and
$\epsilon <\epsilon _{0}$
. Then by (2.2) we have
$$ \begin{align*} \mu_{\omega}(W^{(\epsilon)})=\sum_{a\in \mathcal{A}_{b_1}}q^{b_1}_{a}\varphi_{a}\mu_{\sigma \omega}(W^{(\epsilon)}). \end{align*} $$
By Lemma 3.4 there must exist
$a\in \mathcal {A}_{b_1}$
such that
$W^{(\epsilon )}\cap \varphi _{a}(X)=\emptyset .$
Since
$\mathrm {supp}( \varphi _{a}\mu _{\sigma \omega })\subset \varphi _{a}(X)$
it follows that
$\varphi _{a}\mu _{\sigma \omega }(W^{(\epsilon )})=0$
for some
$a\in \mathcal {A}_{b_{1}}$
. Consequently, if we choose
$a^{*}\in \mathcal {A}_{b_{1}}$
for which
$\varphi _{a^*}\mu _{\sigma \omega }(W^{(\epsilon )})=\max _{a\in \mathcal {A}_{b_1}}\{\varphi _{a}\mu _{\sigma \omega }(W^{(\epsilon )})\},$
we have
Finally, using the fact that our IFS consists of similarities, we have
for some
$W_{1}<\mathbb {R}^d$
. Therefore,
Combining (3.22) and (3.23) implies (3.21).
Equipped with (3.21), we can now finish our proof. Let
$\omega \in \Omega $
,
$W<\mathbb {R}^{d}$
and
$\epsilon <\epsilon _{0}$
be arbitrary. Let
$M\in \mathbb {N}$
be the unique integer satisfying
Repeatedly applying (3.21) yields a sequence of affine subspaces
$W_{1},W_{2},\ldots ,W_{M}$
such that
$$ \begin{align*} & \mu_{\omega}(W^{(\epsilon)})\leq (1-q_{\min})\mu_{\sigma \omega}(W_{1}^{(\epsilon r_{\min}^{-1})})\\ & \quad \leq \cdots \leq (1-q_{\min})^{M}\mu_{\sigma^{M} \omega}(W_{M}^{(\epsilon r_{\min}^{-M})})\leq (1-q_{\min})^{M}. \end{align*} $$
Thus,
$\mu _{\omega }(W^{(\epsilon )})\leq (1-q_{\min })^{M}$
. Combining this inequality with (3.24) yields
for
$\alpha = ({(\log (1-q_{\min }))}/{(\log r_{\min })}).$
Thus, our result holds.
Duplicating the arguments given in the proof of Lemma 3.3, it is possible to show that the following analogous statement holds for the sets
$\{\mathcal {A}_{b}\}_{b\in \mathcal {A}}$
defined in this section. In this lemma
$c_{1}$
is as in (3.17).
Lemma 3.6. There exists
$M\in \mathbb {N}$
such that for any
$\omega \in \Omega , r\in (0,c_{1}/2)$
and
$x\in X_{\omega }$
there exist
$(a_n)\in \Sigma _{\omega }$
and
$N_1,N_{2}\in \mathbb {N}$
satisfying:
-
(1)
$0<N_{2}-N_{1}\leq M$
; -
(2) Diam
$(\varphi _{a_1\cdots a_{N_1}}(X_{\sigma ^{N_1}\omega }))\asymp $
Diam
$(\varphi _{a_1\cdots a_{N_2}}(X_{\sigma ^{N_2}\omega }))\asymp r$
; -
(3)
$B(x,2r)\cap X_{\omega }\subset \varphi _{a_1\cdots a_{N_1}}(X_{\sigma ^{N_{1}}\omega })$
; -
(4)
$\varphi _{a_1\cdots a_{N_2}}(X_{\sigma ^{N_2}\omega })\subset B(x,r)$
.
Equipped with Proposition 3.5 and Lemma 3.6, we can now prove the remaining case of Theorem 1.1.
Proof of Theorem 1.1 for affinely irreducible self-similar measures
Statement
$(1)$
of this theorem holds because of Proposition 2.2. Statement
$(2)$
follows from an analogous argument to that used in our earlier proof in the self-conformal case where we appeal to (3.19) and Lemma 3.6 instead of (3.5) and Lemma 3.3. As such we omit this argument. We now focus on statement
$(4)$
. Notice that statement
$(3)$
follows from statement
$(4)$
. Fix
$\omega =(b_n)\in \Omega $
,
$x\in \mathrm {supp}(\mu _{\omega }),$
an affine subspace
$W<\mathbb {R}^{d}, r\in (0,c_1/2)$
and
$\epsilon \in (0,1)$
. It suffices to consider r and
$\epsilon $
contained in this restricted domain.
It follows from an application of Lemma 3.6, and the arguments used in the proof of Theorem 1.1, that there exists
$D>0$
depending only on our IFS and
$\mathbf {a}\in \bigcup _{n=1}^{\infty }\prod _{j=1}^{n}\mathcal {A}_{b_j}$
such that
$$ \begin{align} \kern-7pt \prod_{j=1}^{|\mathbf{a}|}r_{a_j}\geq \frac{r}{D} \end{align} $$
and
In (3.26) we have adopted the standard notation that for
$a\in \mathcal {A}$
we let
$r_{a}\in (0,1)$
be such that
$\|\varphi _{a}(x)-\varphi _{a}(y)\|=r_{a}\|x-y\|$
for all
$x,y\in \mathbb {R}^{d}$
.
We now observe the following:
$$ \begin{align*} \mu_{\omega}(W^{(\epsilon r)}\cap B(x,r))&\stackrel{({2.2})}{=}\sum_{\mathbf{a}'\in \prod_{j=1}^{|\mathbf{a}|}\mathcal{A}_{b_{j}}}\prod_{j=1}^{|\mathbf{a}|}q_{a_{j}}^{b_{j}}\cdot \varphi_{\mathbf{a}'}\mu_{\sigma^{|\mathbf{a}|}\omega}(W^{(\epsilon r)}\cap B(x,r))\\&\kern-2pt\stackrel{({3.25})}{=}\prod_{j=1}^{|\mathbf{a}|}q_{a_{j}}^{b_{j}}\cdot \varphi_{\mathbf{a}}\mu_{\sigma^{|\mathbf{a}|}\omega}(W^{(\epsilon r)}\cap B(x,r))\\&\kern3pt\leq \prod_{j=1}^{|\mathbf{a}|}q_{a_{j}}^{b_{j}}\cdot \varphi_{\mathbf{a}}\mu_{\sigma^{|\mathbf{a}|}\omega}(W^{(\epsilon r)})\\&\kern3pt\leq \prod_{j=1}^{|\mathbf{a}|}q_{a_{j}}^{b_{j}}\cdot \mu_{\sigma^{|\mathbf{a}|}\omega}(W_{1}^{(D\epsilon )}). \end{align*} $$
Here
$W_{1}=\varphi _{\mathbf {a}}^{-1}(W)$
, and in the final line we have used (3.26). To conclude the second equality in the above we also used that
$\varphi _{\mathbf {a}'}(X_{\sigma ^{|\mathbf {a}|}\omega })\cap \varphi _{\mathbf {a}'}(X_{\sigma ^{|\mathbf {a}|}\omega })=\emptyset $
for distinct
$\mathbf {a}',\mathbf {a}"\in \prod _{j=1}^{|\mathbf {a}|}\mathcal {A}_{b_{j}}.$
Now applying Proposition 3.5, (3.19) and (3.27), we have
$$ \begin{align*} \mu_{\omega}(W^{(\epsilon r)}\cap B(x,r))\ll \prod_{j=1}^{|\mathbf{a}|}q_{a_{j}}^{b_{j}}\cdot \epsilon^{\alpha}=\epsilon^{\alpha}\mu_{\omega}(\varphi_{\mathbf{a}}(X_{\sigma^{|\mathbf{a}|}\omega}))\ll \epsilon^{\alpha}\mu_{\omega}(B(x,r)). \end{align*} $$
Thus, statement
$(4)$
holds and our proof is complete.
4 An example
In this section we give an example of an affinely irreducible self-similar measure coming from an IFS that satisfies the open set condition, for which there exist no
$C,\alpha>0$
such for any
$x\in \mathrm {supp}(\mu )$
, affine subspace
$W<\mathbb {R}^{d}$
,
$0< r\leq 1$
and
$\epsilon>0$
we have
We do not know whether this example is well known, but as several colleagues have asked us to explain it to them we have decided to include it here.
Let
$\Phi =\{\varphi _{\mathbf {a}}(x)=({(x_i+a_{i})}/{2})_{i=1}^{d}\}_{\mathbf {a}=(a_1,\ldots ,a_{d})\in \{0,1\}^{d}}$
. In this case the invariant set is
$[0,1]^{d}$
. It is easy to check that this IFS satisfies the open set condition and is affinely irreducible. For simplicity, let
$\varphi _{0}=\varphi _{(0,\ldots ,0)}$
and
$\varphi _{1}=\varphi _{(1,0,\ldots , 0)}$
. Let
$\mathbf {p}=(p_{\mathbf {a}})_{\mathbf {a}\in \{0,1\}^{d}}$
be a probability vector such that
$p_{0}:=p_{(0,\ldots ,0)}< p_{(1,0,\ldots ,0)}=:p_{1}$
and let
$\mu $
be the corresponding self-similar measure. Since
$p_{0}<p_{1}$
we have
${(\log p_{0})}/{(\log p_{1})}>1$
. This inequality should be borne in mind in what follows. For each
$n\in \mathbb {N}$
let
$$ \begin{align*} x_{n}=\bigg(\frac{1}{2}+\frac{1}{2^{n+1}}-\frac{1}{2^{\lfloor {n \log p_0}/{\log p_1}\rfloor+1}},0,\ldots, 0 \bigg),\quad r_{n}=\frac{1}{2^{n+1}}+\frac{1}{2^{\lfloor {n \log p_0}/{\log p_1}\rfloor+1}} \end{align*} $$
and
$$ \begin{align*} W_{n}=\bigg\{(x_{1},\ldots,x_{d}):x_{1}=\frac{1}{2}-\frac{1}{2^{\lfloor {n \log p_0}/{\log p_1}\rfloor+1}}\bigg\}. \end{align*} $$
Then by a simple geometric argument it can be shown that there exists
$L\in \mathbb {N}$
such that for any
$n\in \mathbb {N}$
sufficiently large we have
and
Using the well-known property of this
$\mu $
that
$(\varphi _{\mathbf {a}_{1}}\circ \cdots \circ \varphi _{\mathbf {a}_m})((0,1)^{d})=(\varphi _{\mathbf {a}_{1}}\circ \cdots \circ \varphi _{\mathbf {a}_m})([0,1]^{d})=\prod _{i=1}^{m} p_{\mathbf {a}_{i}}$
for any
$(\mathbf {a}_{1},\ldots , \mathbf {a}_{m}),$
these inclusions imply that
and
Observing now that
$B(x_{n},r_{n})\cap W_{n}^{(2^{-\lfloor {n \log p_0}/{\log p_1} \rfloor -1})} =B(x_{n},r_{n})\cap \{(x_{1},\ldots ,x_{d}: x_{1}< \tfrac 12)\},$
it follows from the above that
Define the sequence
$(\epsilon _{n})$
implicitly via the equation
$\epsilon _{n}r_{n}=2^{-\lfloor {n \log p_0}/{\log p_1}\rfloor -1}$
for all
$n\in \mathbb {N}$
. Then it is a consequence of our assumption that
$p_{0}<p_{1}$
that
$\epsilon _{n}\to 0$
as
$n\to \infty $
. Summarizing the above, our
$(x_{n}), (W_{n}), (\epsilon _{n})$
and
$(r_{n})$
satisfy
$\mu (B(x_{n},r_{n})\cap W_{n}^{(\epsilon _{n}r_{n})})\gg \mu (B(x_{n},r_{n})).$
Thus, there can exist no
$C,\alpha>0$
such for any
$x\in \mathrm {supp}(\mu )$
, affine subspace
$W<\mathbb {R}^{d}$
,
$0< r\leq 1$
and
$\epsilon>0$
we have
$\mu (W^{(\epsilon r)}\cap B(x,r))\leq C\epsilon ^{\alpha }\mu (B(x,r)).$
Acknowledgements
The author was supported by an EPSRC New Investigator Award (EP/W003880/1). We thank the anonymous referee for their feedback.