Summability and speed of convergence in an ergodic theorem
Leonardo Colzani, Bianca M. Gariboldi, Alessandro Monguzzi

TL;DR
This paper investigates how quickly weighted averages of functions along irrational rotations on tori converge to the integral, showing that certain weights can accelerate convergence beyond the standard rate.
Contribution
It introduces new estimates for the convergence speed of weighted ergodic averages, considering both metric and deterministic cases, and relates these rates to Fourier transforms and Diophantine properties.
Findings
Weighted means can converge faster than standard averages.
Convergence speed depends on Fourier transform of weights and function smoothness.
Diophantine properties influence deterministic convergence rates.
Abstract
Given an irrational vector in , a continuous function on the torus and suitable weights such that , we estimate the speed of convergence to the integral of the weighted sum as . Whereas for the arithmetic means the speed of convergence is never faster than , for other means such speed can be accelerated. We estimate the speed of convergence in two theorems with different flavor. The first result is a metric one, and it provides an estimate of the speed of convergence in terms of the Fourier transform of the weights and the smoothness of the function which holds for almost every . The second result is a deterministic…
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Taxonomy
TopicsMathematical Dynamics and Fractals · Advanced Banach Space Theory · Analytic Number Theory Research
Summability and speed of convergence
in an ergodic theorem
Leonardo Colzani
Dipartimento di Matematica, Università degli Studi di Milano Bicocca, via Roberto Cozzi 55, Milano, Italy)
,
Bianca Gariboldi
Dipartimento di Ingegneria Gestionale, dell’Informazione e della Produzione, Università degli Studi di Bergamo, Viale Marconi 5, Dalmine BG, Italy
and
Alessandro Monguzzi
Dipartimento di Ingegneria Gestionale, dell’Informazione e della Produzione, Università degli Studi di Bergamo, Viale Marconi 5, Dalmine BG, Italy
Abstract.
Given an irrational vector in , a continuous function on the torus and suitable weights such that , we estimate the speed of convergence to the integral of the weighted sum as . Whereas for the arithmetic means the speed of convergence is never faster than , for other means such speed can be accelerated. We estimate the speed of convergence in two theorems with different flavor. The first result is a metric one, and it provides an estimate of the speed of convergence in terms of the Fourier transform of the weights and the smoothness of the function which holds for almost every . The second result is a deterministic one, and the speed of convergence is estimated also in terms of the Diophantine properties of the given irrational vector .
Key words and phrases:
Kronecker sequences, Weyl sums, Ergodic theorem
2010 Mathematics Subject Classification:
37A44, 37A46, 42B08
The authors are members of GNAMPA - Istituto Nazionale di Alta Matematica (INdAM). The third author is partially supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “2nd Call for H.F.R.I. Research Projects to support Faculty Members & Researchers” (Project Number: 73342).
1. Introduction
The motivation for this work comes from an attempt to estimate the speed of convergence in a classical ergodic theorem which we now describe. There are several results in the literature concerning this problem and here we only cite a few.
A classical result of L. Kronecker states that if is an irrational vector, that is, if are linearly independent over the rationals, then the sequence is dense in the torus . This implies that for every continuous nonconstant function on the torus the sequence does not have a limit as . Another classical result obtained independently by P. Bohl, W. Sierpinski and H. Weyl states that the sequence is uniformly distributed in the torus, and the arithmetic means of the sequence converge to the integral of the function,
[TABLE]
For such classical facts we refer the reader, for instance, to [16] and [23, Chapter 6]. The map is a measure preserving ergodic transformation whenever is an irrational vector and the above results are particular cases of classical ergodic theorems. It is known that no general statement can be made about the rate of convergence in these theorems. In [13] and [15] it is proved that if is a measure preserving ergodic transformation of the interval and if is a positive sequence converging to 0, then there exists a continuous function such that, for almost every , one has
[TABLE]
Confirming a conjecture of Erdös and Szüs, in [14] and in [18] it is proved that if is the characteristic function of an interval , with , then the quantity
[TABLE]
is bounded in if and only if for some integers and . Therefore, for a characteristic function the speed of convergence is the exception, not the rule. For multidimensional analogues of such results see [10, 11].
In [12] it is proved that if is a continuously differentiable function on with Lipschitz continuous and with , then, for every , one has
[TABLE]
It is also proved that if , hence is continuous as a function on the torus , but the derivative may have a jump discontinuity, then, for almost every , one has
[TABLE]
Observe that a discontinuous function cannot have an absolutely convergent Fourier expansion. On the other hand, the assumptions and Lipschitz continuous in imply that . More generally, if is Hölder continuous with exponent , then . In [6] it is proved that if is a van der Corput sequence on the interval and if the Fourier coefficients of the function have decay for some , then
[TABLE]
In [1] it is proved that the expected speed of convergence of Weyl sums of continuous, or, more generally, square integrable functions, is slightly less than . More precisely, they proved that if is square integrable and if then, for almost every , one has
[TABLE]
They also proved that the exponent is best possible and that there exist continuous functions such that, for almost every , one has
[TABLE]
In conclusion, the rate of convergence of the means to the integral can be arbitrarily slow and it is also quite easy to see that this rate of convergence cannot be faster than ; see the proof of Corollary LABEL:C-1. The goal in this paper is to show that, with suitable smoothness assumptions on the function , the speed of summability of the divergent sequence can be improved if instead of the arithmetic means one considers smoother means such as, for instance,
[TABLE]
See [7] and [24] for references about summation methods. Let us now fix some notations for what follows. Denote by the distance of a real number to the nearest integer, that is, . Functions on the torus are identified with periodic functions on with period . The Fourier transform and the Fourier expansion of an integrable function on the torus are defined respectively by
[TABLE]
The Sobolev space , , is the space of distributions on defined by the norm
[TABLE]
In what follows denotes a complex valued function of the positive integer variable and the integer variable , with the property that for every the function has bounded support, and that
[TABLE]
The weighted discrepancy associated to the weights and to the Kronecker sequence , with , or equivalently with , is defined by
[TABLE]
An example to keep in mind is
[TABLE]
where is a suitable bounded function with compact support. In this case is roughly the size of the support of the function . The assumption of compact support could be weakened assuming a suitably fast decay at infinity.
Our first main result is related to the results in [4, 5] and it reads as follows.
Theorem 1.1**.**
Let be the operator defined as above, with satisfying (1). Assume the following.
There exist constants and such that for every and every one has
[TABLE]
The function is in the Sobolev class , with if , and if .
Then, for almost every there exists a positive constant such that for every positive integer one has
[TABLE]
Observe that if the assumption holds true with an exponent , then it also holds true for every . If the function has a degree of smoothness with , then one cannot guarantee a speed of convergence , but at least one can guarantee a speed for every with .
The above result is a metric one and it holds true for almost every . Our second main result is a deterministic one and it holds for a specific .
Theorem 1.2**.**
Let be the operator defined as above with satisfying (1). Assume the following.
There exist constants and such that for every positive integer and every one has
[TABLE]
The vector is irrational and there exist constants and such that for every .
Finally assume that and set
[TABLE]
Then there exists a positive constant such that for every function in the Sobolev space and every positive integer one has
[TABLE]
Observe that both Theorem 1.1 and Theorem 1.2 guarantee a speed of convergence , up to some possible logarithmic transgressions, but the smoothness assumptions on the functions in these theorems are different. The index of smoothness in Theorem 1.1 is allowed to be smaller than the index in Theorem 1.2. On the other hand the conclusion in Theorem 1.1 holds for almost every , with depending on the given function one is considering, whereas in Theorem 1.2 the vector is independent of the function. Anyhow, both theorems are essentially sharp. The following theorem shows that in Theorem 1.1 and in Theorem 1.2 the speed of convergence cannot be accelerated for every nonconstant function, provided that the assumption can be reversed.
Theorem 1.3**.**
Set
[TABLE]
Then, for every function , every and every one has
[TABLE]
In particular, if for a set of of measure , then for a set of of measure ; see Lemma 2.1.
Notice that in this theorem the smoothness index of the function plays no role. Nonetheless, some smoothness is necessary. Indeed, since the Sobolev space contains unbounded functions, it easily follows that the smoothness assumption in Theorem 1.1 and Theorem 1.2 is necessary.
Theorem 1.4**.**
There exists a function in the Sobolev space such that for every irrational vector and every one has
[TABLE]
Moreover, if the sequence is non-negative, then the above discrepancy is infinite for every .
The following theorem shows that the index in Theorem 1.1 is sharp, provided that the assumption in the theorem can be reversed.
Theorem 1.5**.**
Assume that for an infinite sequence of ’s there exists such that
[TABLE]
If then there exists a function in the Sobolev space such that, for every , one has
[TABLE]
There exists a function in the Sobolev space such that, for almost every , one has
[TABLE]
To conclude, the above results may have continuous analogues where the discrete means are replaced by continuous means,
[TABLE]
We plan to investigate such operator in future works.
In the next section we provide the proofs of our main theorems, whereas in Section 3 we conclude with some final remarks.
2. Proofs of the main results
To prove Theorem 1.1 we need an elementary lemma.
Lemma 2.1**.**
If is a periodic locally integrable function on , then, for every , one has
[TABLE]
More precisely, if is a measurable function on , then, for every , the functions , , and , , have the same distribution function. Namely, for every ,
[TABLE]
Proof.
By periodicity and a change of variables, for every non-zero integer and real number , one has
[TABLE]
Hence, setting with and , and , one obtains
[TABLE]
The distribution functions of and are seen to be equal by applying the above identity to the characteristic function of the upper level set . ∎
We now prove our first main result.
Proof of Theorem 1.1.
First observe that for every one has
[TABLE]
The first factor is the Sobolev norm of , whereas the second series converges provided that . In particular, for and one sees that the Fourier expansion of converges absolutely. This fact and the compact support of assure the pointwise identity
[TABLE]
Hence, thanks to , one has
[TABLE]
In order to show that the constants are finite for almost every it suffices to show that the series defining these constants converges absolutely for almost every . By the previous lemma the functions are in for every with norm independent of ,
[TABLE]
If , then the functions the functions are integrable and the series
[TABLE]
converges provided that
[TABLE]
As observed before, this holds true if .
If , then , and, by the inequality , the series
[TABLE]
converges for almost every and in the quasinorm provided that
[TABLE]
As observed at the beginning of the proof this happens for every whenever , from which one obtains . ∎
A key ingredient in the proof of Theorem 1.2 is a classical result in Diophantine approximation. Let be an irrational number. If the sequence is well-distributed in as it is distributed the sequence , then one can guess that
[TABLE]
Under suitable Diophantine assumptions on the above conjectured estimate is correct. The following lemma is a variant of known results (see e.g. **[17, Chapter 3]**).
Lemma 2.2**.**
Assume that is an irrational vector, that is, are linearly independent over the rationals, and assume that there exist constants and such that for every . Then there exists a positive constant such that, for every ,
[TABLE]
Proof.
By the assumptions and , the interval does not contain any term of the sequence . Moreover, for every integer such that the interval contains at most one term of such sequence. Indeed, if there are two terms in the interval, then there are integer points with , and integers and such that
[TABLE]
The signum is minus if and approximate the nearest integers and both from above or both from below, the signum is plus if one approximation is from above and the other from below. Hence,
[TABLE]
But , and this contradicts the assumption . Notice that the number of intervals ’s is of the order of , whereas the number of integer points in the punctured ball is about , and recall also that . Observe that one has the worst estimate when the terms of the sequence are concentrated in the the first intervals. In conclusion,
[TABLE]
∎
Proof of Theorem 1.2.
As in the proof of Theorem 1.1 one has the pointwise identity
[TABLE]
Hence, by Cauchy’s inequality and assumption , one has the estimate
[TABLE]
By Lemma 2.2, for every positive integer one has
[TABLE]
For , the choice if or if gives
[TABLE]
Observe that if , then . If , the choice if or if gives
[TABLE]
Observe that if , then . For the last case , the choice if or if gives
[TABLE]
Collecting the above estimates one obtains that
[TABLE]
∎
Proof Theorem 1.3.
Recall that the Fourier coefficients are bounded by the norm of the function, so that
[TABLE]
Therefore,
[TABLE]
∎
The proof of Theorem 1.4 is straightforward. We include a proof for the sake of completeness.
Proof of Theorem 1.4.
It suffices to recall that the Sobolev space contains unbounded functions. If is unbounded in just one point and if is an irrational vector, or if the weights are non-negative and is arbitrary, then in the sum the possible infinite terms do not cancel. Hence
[TABLE]
An explicit example of function in unbounded in a neighborhood of the origin and bounded elsewhere is given by the series
[TABLE]
∎
The following lemma is a main ingredient in the proof of Theorem 1.5.
Lemma 2.3**.**
If , then, for every , one has
[TABLE]
If , then, for almost every , one has
[TABLE]
Proof.
It is a classical result of Dirichlet in Diophantine approximation that for every vector and every positive integer there exists in with for every , and with . See e.g. [19, Chapter II, Theorem 1E]. Since , it follows that in the series we are interested in there are infinitely many terms larger than , and the series diverges.
It is a classical result of Khintchine in dimension one, and of Groshev in dimension , that for almost every vector there exists infinitely many such that . See e.g. [19, Chapter III, Theorem 3A] and [2, 20]. Hence, for almost every there are infinitely many terms larger than in the given series, so that such series diverges. ∎
Proof of Theorem 1.5.
Observe that if then , and this case is already covered by Theorem 1.4. In order to prove , define
[TABLE]
The norm of this function in the Sobolev space is
[TABLE]
Hence, this function is in if and only if , that is, if and only if .
Let us estimate with ,
[TABLE]
Then, by part of Lemma 2.3 , it follows that, for every , one has
[TABLE]
The proof of is similar. Define
[TABLE]
If this function is in the Sobolev space , and
[TABLE]
Then, by part of Lemma 2.3, it follows that, for almost every , one has
[TABLE]
∎
At last, we prove Theorem LABEL:T-6.
Proof of Theorem LABEL:T-6.
Let be a subset of of cardinality , and let
[TABLE]
Then . Moreover, for the ’s in the theorem and under the assumption that for every ,
[TABLE]
Hence, if one has
[TABLE]
Letting , it follows that the family of operators is not uniformly bounded from into . Therefore, by the resonance theorem of Banach and Steinhaus, there exists a function such that
[TABLE]
∎
We conclude the section proving the corollaries.
Proof of Corollary LABEL:C-1.
Recall that, as observed in the introduction, if the theorems apply with an exponent , then they also apply with every . The choice of gives
[TABLE]
Up to a factor one recognizes the Dirichlet kernel and easily verifies that
[TABLE]
Hence Theorem 1.1 and Theorem 1.2 apply with . In order to prove that the speed of convergence cannot be accelerated one can apply Theorem 1.3. However, there is also a more elementary and general argument that applies to every nonconstant function . Assume that there exists a pair such that
[TABLE]
Then the triangle inequality gives a contradiction,
[TABLE]
∎
Proof of Corollary LABEL:C-2.
In this case we have
[TABLE]
Up to a factor one recognizes the Fejér kernel, and checks that Theorem 1.1 and Theorem 1.2 apply with . To prove that the speed of convergence cannot be accelerated observe that
[TABLE]
If , then . If is rational, then takes a finite number of values for , hence . If is irrational then, by Kronecker’s theorem, . The conclusion follows from Theorem 1.3. ∎
Proof of Corollary LABEL:C-3.
The function is related to the Bochner–Riesz kernel. Recall the integral representation of Bessel functions,
[TABLE]
The Poisson summation formula gives the series expansion
[TABLE]
See [22, Chapter 4, Theorem 4.15 and Chapter 7, Theorem 2.4]. Observe that the use of the Poisson summation formula is legitimate since both above series are absolutely and uniformly convergent (see [21, Lemmas 4 and 5]). Also recall that the Bessel function has the asymptotic expansions
[TABLE]
Assume for simplicity that . Then the above sum has a main term of the form
[TABLE]
The remainder is the sum over all ’s with and it can be estimated as
[TABLE]
The main term can be estimated from above by
[TABLE]
Observe that the estimates of the main term dominate the remainder. Also notice that
[TABLE]
In conclusion,
[TABLE]
Hence, Theorem 1.1 and Theorem 1.2 apply with . To apply Theorem 1.3 let us show that there exist and such that for every in a set of measure one has . Observe that
[TABLE]
Again assume that is not an integer for every . The asymptotic expansion of Bessel functions gives
[TABLE]
Let . Then for every such that one has
[TABLE]
In conclusion, if is suitably small, for every suitable large one has
[TABLE]
Moreover, if is irrational, by Kronecker’s theorem,
[TABLE]
Hence for every . ∎
Proof of Corollary LABEL:C-4.
One has
[TABLE]
Up to a normalizing factor one recognizes the de la Vallée Poussin kernel, which is similar to the heat kernel. Indeed, when ,
[TABLE]
It follows that, for every , there exists such that
[TABLE]
Hence, Theorem 1.1 and Theorem 1.2 apply with replaced by . ∎
Proof of Corollary LABEL:C-5.
The fact that the speed of convergence is the best possible in the Sobolev space is proved in [3]. The fact that one can actually obtain such speed of convergence, up to some small transgression, follows from Theorem 1.2 with suitable combinations of , and . Let , with a smooth compactly supported bounded function satisfying . Then, for every there exists such that
[TABLE]
for every positive integer . To see this set
[TABLE]
Since is smooth with compact support, by iterated integration by parts, one has
[TABLE]
Hence, for every there exists such that
[TABLE]
By the Poisson summation formula,
[TABLE]
It follows that, for every ,
[TABLE]
Hence, for this assumption in Theorem 1.2 holds with arbitrary , and for fixed and one can chose a that optimizes the estimates in Theorem 1.2. In particular, if one can choose , whereas if one can choose . ∎
3. Concluding remarks
Remark 3.1*.*
The above corollaries show that the assumptions in Theorem 1.1 and Theorem 1.2 are not void. We now show that the assumptions in in Theorem 1.5 and Theorem LABEL:T-6 are not void as well. Let us prove that for every there exists a positive weight which satisfies (1), with the property that has compact support for every , and with the property that there exist constants and such that for every one has
[TABLE]
Let be a positive integer, and let
[TABLE]
[TABLE]
It is easily verified that is a trigonometric polynomial of degree . Hence, the convolution is a trigonometric polynomial as well. From the inequalities one deduces that
[TABLE]
It follows that there exist constants such that for every one has
[TABLE]
In order to estimate from below, observe that for every ,
[TABLE]
In order to estimate from above, observe that for every ,
[TABLE]
Moreover, if then
[TABLE]
Hence, if then for some positive constants and independent of and for every one has
[TABLE]
Finally, define as the Fourier transform of ,
[TABLE]
Remark 3.2*.*
Observe that we cannot apply Theorem 1.5 and Theorem LABEL:T-6 to Corollary LABEL:C-1 and Corollary LABEL:C-2, since in these corollaries vanishes in many points. However, the ranges of indexes of the Sobolev class in Corollary LABEL:C-1, and in Corollary LABEL:C-2 at least in dimension one, seem to be essentially sharp as well. In Corollary LABEL:C-1 with the assumption in Theorem 1.1 becomes . As already observed, this assumption is necessary since the Sobolev spaces with contain unbounded functions. In Corollary LABEL:C-2 with the assumption becomes . At least, in dimension one can prove that this range is essentially sharp, in the sense that it cannot be replaced by any index . Indeed, for every there exists a function such that
[TABLE]
for almost every . In order to show that this is true, observe that
[TABLE]
In Petersen [18] it is proved that if the following are equivalent:
- (i)
(mod 1); 2. (ii)
.
It is easy to verify that (ii) is also equivalent to
- (iii)
.
Let be an algebraic number and set
[TABLE]
Such a function belongs to for every . Since for every transcendental number condition (i) does not holds, then (iii) does not hold as well. This is exactly what we wanted to prove thanks to (2) and the fact that almost every is a transcendental number.
Remark 3.3*.*
It is curious to compare the above results on the speed of convergence in ergodic theorems with the approximation properties of Fourier series. Whereas our results suggest that stronger summation methods guarantee faster convergence, the approximation properties of partial sums and Féjer means of Fourier series seem to go in the opposite direction. Assume and denote by and the partial sums and the arithmetic means of the partial sums of the Fourier expansion of a function ,
[TABLE]
The partial sums may not converge, but the approximation is close to optimal. Indeed, if denotes the operator norm of the partial sums, the Lebesgue constant, if denotes the best approximation in the supremum norm of with trigonometric polynomials of degree at most , and if is the trigonometric polynomial of best approximation, then
[TABLE]
Finally, the means always converge, but the approximation is never better than ,
[TABLE]
In particular, the partial sums may converge faster than the Féjer means.
4. Appendix
In this appendix we deal with logarithmic means. Such means are defined by the weights
[TABLE]
and the associated logarithmic discrepancy is
[TABLE]
See **[7, Section 2.2]** for references about these means and discrepancy. Although Theorem 1.1 and Theorem 1.2 do not immediately apply in this setting, due to the fact that the assumption on the kernels is not satisfied, the proofs can be adapted to obtain some analogues of the above results.
Theorem 4.1**.**
If the function has an absolutely convergent Fourier expansion, , then, for almost every , there exists a positive constant such that, for every positive integer , one has
[TABLE]
Theorem 4.2**.**
If is not a Liouville vector, that is, if there exist positive constants and such that for every , then there exists a positive constant , such that for every positive integer ,
[TABLE]
In particular, the above theorems apply to functions in Sobolev classes with . The main ingredient in the proofs of both theorems is an estimate for the kernels .
Lemma 4.3**.**
For every ,
[TABLE]
Moreover, if is large enough and if , the reverse inequality holds true as well.
Proof.
A direct and explicit proof goes as follows. The inequality is obvious. In order to prove the other inequality it suffices to assume that and . An integration by parts gives
[TABLE]
The inequalities imply that
[TABLE]
from which an estimate for the term is immediately obtained. In order to estimate one can separately consider the sum where the index varies in the set and the sum where the index varies in the set . The latter set is empty if . Otherwise, there is a uniform bound. Indeed,
[TABLE]
The inequality implies that also the sum over the is uniformly bounded. Indeed,
[TABLE]
In order to estimate the last term , one considers separately the sum over the set of indexes and the sum over the set of indexes . The sum over this latter set is uniformly bounded,
[TABLE]
The sum over the indexes is bounded by
[TABLE]
Notice that if , then the reverse inequality holds true,
[TABLE]
∎
Proof of Theorem 4.1.
As in the proof of Theorem 1.1,
[TABLE]
Hence, by Lemma 4.3,
[TABLE]
And, by Lemma 2.1,
[TABLE]
Finally, . ∎
Proof of Theorem 4.2.
As in the proof of Theorem 4.1, under the Diophantine assumption ,
[TABLE]
∎
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