Box dimension of stable sub-slices of fractal graphs over Anosov diffeomorphisms
Abstract
We consider fractal graphs invariant by a skew product of the form where , is a function, and is an Anosov diffeomorphism of admitting distinct eigenvalues with respective eigenvectors forming a basis of . We note that the stable sub-slices can give information of the fractal structure of the graph that is not captured by the box dimension of the graph. Using the results of Kaplan, Mallet-Paret, and Yorke [6], we exhibit conditions on the skew product that ensure the box dimension of the graph is smaller than the sum of the box dimensions of its stable/unstable sub-slices. We prove that these conditions hold for generic functions .
1 Introduction
Fractal geometry, as a branch of mathematics, provides mathematical tools to understand fractals. It was inspired by the classical example of the Weierstrass function of a continuous but everywhere non-differentiable function (see Falconer [3] for more details). Though the structure of fractal sets can be really complicated, it is still possible to study their fractal properties, and concepts such as dimension (either box or Hausdorff) help the understanding of their structure. Fractal sets appear naturally in hyperbolic dynamics as important examples of hyperbolic sets, such as the classical examples of Smale’s horseshoe and the solenoid (among others). The hyperbolic dynamics, and especially the stable/unstable manifolds, can help us to calculate fractal properties of hyperbolic fractal sets. Indeed, the Hausdorff dimension of hyperbolic basic sets of surfaces is calculated in McCluskey and Manning [8] as the sum of the Hausdorff dimension of its stable and unstable slices at any point of the set (these are the intersections of the local stable/unstable manifolds with the hyperbolic set). Extend this result to higher dimensional (and non-conformal) hyperbolic sets seems to be a really difficult problem that is not explored enough in the literature. The lack of regularity on the stable/unstable holonomies and the possible difference between Hausdorff and box dimensions are difficulties that appear in this scenario. Two results in this direction are important to be noted: in the first, Hasselblatt and Schmeling [5] prove that the ideas of McCluskey and Manning [8] can be applied to the solenoid and conjecture that the dimension (either box or Hausdorff) of any hyperbolic set should be the sum of the dimension of their stable/unstable slices; in the second, Kaplan, Mallet-Paret, and Yorke [6] calculate the box dimension of fractal graphs invariant by a skew product over the cat map on using Fourier analysis of quasi-periodic functions, which are quite distinct techniques and will be explained in Section 2.4 of this paper. It is also noted in [6] that their techniques can be used to calculate the box dimension of fractal graphs over higher-dimensional linear Anosov diffeomorphisms of (see Theorem C in [6]). The argument is similar to the case of using the strongest stable eigenvalue of the base hyperbolic matrix to control the sizes of boxes covering the graph. One thing we observe and explore in this paper is that the other stable directions do not influence on the box dimension of the graph, but the associated stable/unstable slices can be either smooth or fractal, depending on the relation between the eigenvalues and the contraction rate of the skew product on the fibers. Thus, the box dimension of the graph does not give a full description of the fractal directions of these graphs. This motivates our study of fractal dimensions of stable sub-slices that we now describe.
2 Kaplan, Mallet-Paret, and Yorke techniques
In this section, we define the basic concepts of fractal geometry and hyperbolic dynamics that will be used in this article and explain the techniques of Kaplan, Mallet-Paret, and Yorke [6] to calculate the box dimension of the graph invariant by .
2.1 Box dimension
Definition 2.1.
Consider a non-empty totally bounded subset of a metric space and for each let be the smallest number of sets of diameter at most which union covers X. We define the lower box dimension of as
and the upper box dimension of as
If they are equal, this is the box dimension of , and we write .
The following proposition exhibits an easy way to calculate the box dimension of a set and will be used a few times in the arguments.
Proposition 2.2.
If there are positive constants and such that
then .
Proof.
We just need to note the following inequalities:
Then follows by letting in the last inequalities. ∎
In the special case that is the graph of a continuous function , Proposition 2.2 can be applied to calculate the box dimension considering similar inequalities for the variation of the function defined by
Proposition 2.3.
If there are , , such that
for every interval with length, then
Proof.
Given , let
where is the smaller integer greater than . For each , let
and for each , let
Consider the set
and let
The set covers with sets of diameter , so

Note that and that by hypothesis
It follows that
and, hence,
for some positive constant . Also note that
since any set of diameter intercepts no more than 9 distinct sets of the form . By hypothesis we have
and since we similarly have and
it follows that
for some positive constant . Thus,
and Proposition 2.2 ensures that . ∎
The essence of the proof above is that the number of intervals of size needed to cover the domain are proportional to and on each of these intervals the number of intervals of size needed to cover the image is, by hypothesis, proportional to , so the number of squares of size needed to cover the graph is proportional to . This can also be done for a -variable function with the only difference being that the number of -cubes needed to cover the domain is proportional to . Then we can state the following result.
Proposition 2.4.
If is a function satisfying the same hypothesis as in Proposition 2.3, then
A formal proof is omitted since it is similar with the proof of Proposition 2.3 with the only adaptation explained above.
2.2 Hyperbolic Sets and Stable/Unstable Manifolds
Definition 2.5 (Hyperbolic set).
Let be a Riemannian manifold, be an open set, and be a smooth embedding. A compact invariant subset is called a hyperbolic set if the tangent bundle over splits as and there exist constants and such that and for every .
The Stable Manifold Theorem ensures that if is small enough, then the sets
are embedded disks tangent to and , respectively. In particular, there is a local product structure close to any : there exists and a map
where and , defined by
Thus, for each , the map defines a homeomorphism between the product
and (for some ). The sets in this product are called the local stable and local unstable slices of at . If the map is bi-Lipschitz, then the dimension of equals the sum of the dimensions of the stable and the unstable slices at any point, since Hausdorff and box dimensions are preserved by bi-Lipschitz functions. This fact is used by McCluskey and Manning [8] to calculate the Hausdorff dimension of two dimensional horseshoes.
Theorem 2.6 (Theorem 2 of [8]).
Let be a axiom A diffeomorphism of a surface, and be a basic set of . Then the Hausdorff dimension of is the sum of the Hausdorff dimension of the stable and unstable slices of any . Also the Hausdorff dimension varies continuously with .
For hyperbolic sets on manifolds of higher dimensions, the map is always Hölder continuous but not necessarily Lipschitz (see Shub [9]). Thus, it is really difficult to compute the dimension in this case. Hasselblatt and Schmeling [5] stated the following conjecture:
Conjecture 2.7.
The fractal dimension of a hyperbolic set is (at least generically or under mild hypotheses) the sum of those of its stable and unstable slices, where “fractal” can mean either Hausdorff or upper box dimension.
They prove this conjecture for the Smale Solenoid, that is a hyperbolic set on a manifold of dimension three (see [5] for more details). We hope we have motivated the importance of the stable/unstable slices and the calculus of their dimensions, and finish this sub-section.
2.3 The graph of a skew product and its sub-slices
Following Kaplan et al. [6] we consider the skew product , where is the -torus, defined by
where is a linear Anosov diffeomorphism, , and is a smooth function. This skew-product has an attractor that can be seen as a graph over (see [6]) such that any point in the attractor satisfies
For simplicity, consider the function defined by
(1) |
Thus, , and since is a linear Anosov diffeomorphism, the box dimensions of the graphs of and are the same. Assume that has distinct eigenvalues and that the respective eigenvectors form a basis of . Write points of on this basis as and write on this basis as
At any point of the graph , each direction gives a slice of the graph given by the graph of the function given by
(with sufficiently small). These slices are called the sub-slices of the graph at the point . If denotes the space spanned by all the eigenvectors whose respective eigenvalues have modulus smaller than 1, and denotes the space spanned by all the eigenvectors whose respective eigenvalues have modulus bigger than 1, then the slices of the graph given by and are exactly the stable and the unstable slices defined in the previous sub-section. In this paper we discuss how to calculate the box dimension of each sub-slice of the graph. The case we deal in this subsection is when the absolute value of the eigenvalue is bigger than the contraction rate of the skew product. The following proposition ensures that the box dimensions of these sub-slices equal one.
Proposition 2.8.
If then is a function of and is bounded independent of .
Proof.
The following function is the candidate for the derivative of on in the direction :
Let us prove it is, indeed, the case. For each , let
Note that is converges uniformly to because is bounded and . Therefore
The notation means that we are integrating as a function of one variable where varies only on the coordinate . We hope this does not cause confusion with the number that is fixed on the point we consider at the beginning. On the other hand we have
because is bounded and it follows that
So we have that , and, hence,
∎
The function being in the direction implies that the slice given by the graph of is a curve and, hence, has box dimension one. We end this subsection noting that this applies to all unstable sub-slices since, in this case, the eigenvalues have modulus bigger than 1, while .
2.4 Box dimension for the stable slice in
In this section, we consider the case , that is, the skew product is of the form
In this case, at any point of the graph there is only one stable slice and we discuss how to calculate its box dimension following Kaplan et al. [6]. This will be used in Section 3 to calculate the box dimension of all stable sub-slices in the higher-dimensional case associated to directions with . Using the notation of the previous subsection, when the hyperbolic matrix has two eigenvalues and . If is the eigenvector associated to , then the stable slice at any point is given by the graph of the function defined by
Letting , the stable slice is given by the graph of the function
The following theorem calculates the box dimension of this stable slice:
Theorem 2.9 (Theorem A in [6]).
Let
where and and assume that
(2) |
for some real numbers . Then either is , and hence , or
Actually, the conclusion holds for every function that is quasi-periodic and satisfies hypothesis (H1) (see Definitions 2.10 and 2.11). In this subsection, we explain the proof of this statement. First, we recall the necessary definitions and explain their consequences.
Definition 2.10.
A function is called almost periodic if for every there is such that any real interval of length contains a number satisfying
Even though is not periodic it is possible to define a formal Fourier series (see Corduneanu [2]) such that
where
There is only a countable set of such that .111Notice that if was periodic this definition would coincide with the standard definition of Fourier Series. The main idea to prove Theorem 2.9 is to formally consider
(3) |
that contains the function but also the negative part of the series. Ignoring the fact that the function may not be well defined, if we try to calculate its Fourier series coefficients we get:
Regardless of the lack of rigor in the calculation above, all that is truly necessary is that
(4) |
converges. The Hypothesis (H1) of Kaplan et al. [6] gives a sufficient condition to ensure this convergence.
Definition 2.11.
We say that an almost periodic function satisfies the hypothesis (H1) if
(H1) |
where and are its Fourier Coefficients.
Lemma 2.12.
If is an almost periodic function satisfying , , and , then the series converges.
Proof.
Given and , let , notice that , and since we have , so
Thus, Hypothesis (H1) ensures that
If , then consider such that and note that
where , so we are in the previous case. ∎
Although this condition may appear to be too technical, Kaplan et al. [6] proved that if is a function then will satisfy (H1) (see Proposition 3.3 for our version in higher dimensions). So now that is well defined, there are two possible cases: either 1) for every , and in this case hypothesis (H1) ensures that as shown in Proposition 2.2 from Kaplan et al. [6], and, hence, that
This ensures that is by a similar argument as in Proposition 2.8 (see Lemma 2.1 in [6]); or 2) there is a Fourier coefficient and it can be used to ensure the existence of such that
for every interval with small enough. Indeed, the following proposition is the main step in proving this.
Proposition 2.13 (Proposition 2.5 in [6]).
Given a continuous real function , let
where , and is a positive integer. Then
where .
Kaplan et al. [6] use this proposition for any translation of the form , since the variation of on equals the variation of on , so they can cover any interval of the domain. Using Lemma 2.6 and Lemma 2.7 in [6] they shown that for large enough there is such that
Setting as and using Proposition 2.13 we obtain
whenever . For the upper bound the fact that and are bounded let us obtain such that
if is small enough (see Proposition 2.9 in [6]). Then Proposition 2.3 ensures that
After calculating the box dimensions of the stable and unstable slices, it is possible to calculate the box dimension of the graph of . We expand some details in the proof given in [6].
Theorem 2.14 (Theorem B in [6]).
If is and , then either is nowhere differentiable and
or is and .
Proof.
Recall that restricted to the unstable manifold is a function (see Proposition 2.8) and when all Fourier coefficients of are null, is , so in this case is and . If there exists a non-zero Fourier coefficient of , then there exist , as in the proof of Theorem 2.9, and given by Proposition 2.8, such that
if is sufficiently small. If and , then the above inequalities ensure that
that is equivalent to
that, in turn, implies
if . Proposition 2.4 ensures that
∎
3 Fractal structure of the graph and its sub-slices
In this section, we consider the case , where is a linear Anosov diffeomorphism with distinct eigenvalues satisfying
and such that the respective eigenvectors form a basis of .
3.1 Box dimension for the stable slices in
In Proposition 2.8 we proved that if then the box dimension of the graph of is 1. When , the function can be written in the form of the function in Theorem 2.9. Indeed, letting
it follows that
Thus, the argument of subsection 2.4 can also be applied for , using the function
associated to as in (3), and we obtain the following theorem.
Theorem 3.1.
If is a function, almost periodic, and satisfies the hypothesis , then either all the Fourier coefficients of are zero, is , and , or there is at least one non-zero Fourier coefficient of and
The hypothesis on are satisfied with enough regularity on . Indeed, will be almost periodic as long as is continuous and the Hypothesis (H1) is satisfied when is . This is proved in the next results but analogous results in the case are announced in [6].
Lemma 3.2.
If is uniformly continuous, then is almost periodic.
Proof.
Given , because is uniformly continuous, there is such that
Let be a parametrization of the stable manifold on the direction of . Since is linear, parametrizes an orbit of a linear flow on the Torus , that is a recurrent flow without singularities. Thus, if , we can consider the smaller satisfying: and such that there exists with . We let and call it the first-return time of to . Let
and note that . Every interval of length contains satisfying
since for every implies the existence of such that
contradicting the definition of . Now given , by linearity we have
and this implies that for each interval of length , there is such that
Hence,
for every . Since this can be done for each , the proof is complete. ∎
Proposition 3.3.
If is , then is almost periodic and satisfies for every .
Proof.
As is periodic and , the Fourier Series of is convergent, let
Because is , we have that there is a positive such that
Indeed, the coefficient of are and they are all limited (see Corduneanu [2]) therefore
because we have
and so
With this the Fourier series of can be written as
(5) |
where . Thus, using the Cauchy-Schwarz inequality and the one above,
This converges because (see Bromwich [1]222This fact is proved for the double sum, but also works for any finite number sum.). ∎
The following is a direct corollary of the above results.
Theorem 3.4.
If is a function and , then either all the Fourier coefficients of are zero, is , and , or there is at least one non-zero Fourier coefficient of and
This calculates the box dimension of all stable sub-slices of the graph.
3.2 Dimension of the graph and dimension of the sub-slices
In this subsection, we discuss how to calculate the dimension of the graph using the dimension of the sub-slices calculated in the previous section and compare the dimension of the graph with the sum of the dimensions of its sub-slices. We obtain sufficient conditions that ensure the dimension of the graph is smaller than the sum of the dimension of the sub-slices (see Theorem 3.6). This means that there exist fractal structure in each sub-slice that is not captured by the box dimension of the graph. The box dimension of the graph in the case can be calculated as in Theorem C of Kaplan et al. [6]. Indeed, if and there is such that , then the variation of is proportional to the variation of and so
The above number is also the Lyapunov dimension of the (see Frederickson et al. [4] for more details), and it is conjectured that this is usually the case for an attractor.333You can find more results in this direction in Ledrappier [7]. If for every and , we can try to see if there is fractal dimension for the sub-slice by seeing if there is such . If this is the case, then
and if not, we can repeat the argument till the sub-slice as long as . The idea is that the variation of and the variation of the sub-slice with the highest variation are proportional to the same value, while the sub-slice with the highest variation is given by the smallest admitting a .
Theorem 3.5.
If is , with , and there is with , then
where . If for every and every , then is and .
Proof.
For each , let
and if let . Consider the cube , so we have that for each there are positive constants such that
Since
and
it follows that
Note that for every . Indeed, this is clear if , and otherwise, and
Thus, if is small enough such that
then
So by the Proposition 2.4 we have
∎
It is interesting that the only fractal structure captured by the box dimension of the graph is the one given by the sub-slice . Thus, if there are more fractal sub-slices for , then the sum of the box dimensions of the sub-slices will be greater than the box dimension of the graph.
Theorem 3.6.
If is , with , and there exist and with , then
3.3 Examples and generic conditions
In this subsection, we prove that the hypothesis on Theorem 3.6 about the existence of two distinct with and is always satisfied if we choose correctly the function . Actually, we prove that it is possible to choose such that this holds for every and that the set of functions satisfying this is generic in the topology. We begin with an explicit example illustrating Theorem 3.6.
Example 3.7.
Let A be the following hyperbolic matrix
The characteristic polynomial is given by
This polynomial has three distinct real positive roots, which are the eigenvalues of , and satisfy

Moreover, if is an eigenvalue of , then
that is, is an eigenvector associated to . For each let . For each , let , and
(6) |
Proposition 3.8.
In the coordinate system given by , if
where is any function, then for each we have
Proof.
This stands from the fact that the Fourier coefficient is the only non zero coefficient of . Indeed, it is known that
and
Therefore,
is non zero if, and only if, , and in this case, . By Definition (4) it follows that
∎
Thus, if , then
and, hence,
If , then
Indeed, if , then
and, hence,
and if , then is and .
Now we return to the general case where is any linear Anosov diffeomorphism of the Torus as in the beginning of this section.
Theorem 3.9.
If with , then there is a function satisfying: for each there exists such that . Moreover, the set of functions satisfying this is an open and dense subset in (in the topology).
Proof.
The first part of this Theorem follows the idea of Proposition 3.8. If is any function, let be the set of such that for every . For each , the function
satisfies for every (by Proposition 3.8). Also, if , it satisfies for some . Letting we obtain that is approximated by functions satisfying: for each there exists such that . Because of the relation (5) we have that the Fourier coefficients of depend continuously on the Fourier coefficients of and so also varies continuously with . This concludes the proof. ∎
We conclude noting that for a generic function the box dimension of a stable sub-slice will depend only if or . In the first case the dimension is one and in the second is .
Corollary 3.10.
If is a generic function and for some , then
Acknowledgments. Bernardo Carvalho was supported by Progetto di Eccellenza MatMod@TOV grant number PRIN 2017S35EHN, by CNPq grant number 405916/2018-3, and Rafael Pereira was also supported by Fapemig grant number APQ-00036-22.
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B. Carvalho
Dipartimento di Matematica,
Università degli Studi di Roma Tor Vergata
Via Cracovia n.50 - 00133
Roma - RM, Italy
R. C. Pereira
Departamento de Matemática,
Universidade Federal de Minas Gerais - UFMG
Av. Antônio Carlos, 6627 - Campus Pampulha
Belo Horizonte - MG, Brazil.