A generalization of Hardy’s operator and an asymptotic Müntz-Szász Theorem
1 Overview
In this note we shall give a novel proof that Hardy’s Operator , defined on by the formula,
is bounded. This new proof relies only on algebra together with the observation that the monomial functions are eigenvectors for . Specifically, for each ,
(1.1) |
Always intrigued by results in analysis whose proofs rely mainly on algebra, the new proof of Hardy’s Inequality prompts the authors to propose the following definition.
Definition 1.2.
We say that is a monomial operator if is a bounded operator on and there exist a number and a sequence of scalars such that for all ,
(1.3) |
We shall call the number in (1.3) the order of . It can be any complex number with non-negative real part, though in all our examples it will be a natural number. In addition to , a monomial operator of order , other examples of monomial operators are the multiplication operator that sends a function to the function , and the Volterra operator , the operator given by
Both and are of order .
For we shall use to denote the closed subspace of of functions that are on .
Definition 1.4.
We shall say that a bounded operator is vanishing preserving if for every in .
In this note we shall prove the following result.
Theorem 1.5.
If is a monomial operator, then is vanishing preserving.
Why might such a theorem be true? If is a monomial operator, and is a polynomial that vanishes at to some high order , then also vanishes to order at least . So if one thinks of vanishing on as an extreme case of vanishing to high order, one might believe that monomial operators preserve this property.
Our proof of Theorem 1.5 relies on a new type of Müntz-Szász Theorem, wherein the monomial sequence is allowed to drift. This may be more interesting than the theorem itself!
2 Hardy’s Inequality
For a continuous function on consider the continuous function on defined by the formula
(2.1) |
Noting that as , and , the following question arises:
How does behave near 0? |
Invoking the Mean Value Theorem for Integrals yields that for each , there exists such that . Thus,
(2.2) |
so that in particular, is bounded near 0. More delicately, if we apply the MVT to the function , we obtain the estimate
(2.3) |
which implies that as . Therefore, if we agree to extend the definition of at the point by setting , then our observations imply the following proposition.
Proposition 2.4.
If is a continuous function on , then is a continuous function on . Furthermore,
(2.5) |
Hardy [5] was the first to study the local behavior of at for functions equipped with norms other than the supremum norm. His result when specialized to , the Hilbert space of square integrable Lesbesgue measurable functions on , is as follows.
Proposition 2.6.
(Hardy’s Inequality in ) If is a measurable function on , then is a measurable function on , and
(2.7) |
A linear operator on a normed vector space is called bounded111It is a straightforward exercise to show that a linear operator is bounded if and only if it is continuous. if there is some constant so that
(2.8) |
The infimum of all for which (2.8) holds is called the norm of , and written . Using this terminology, (2.7) says .
3 Hilbert Space distance formula
Let be vectors in a hilbert space . We may associate to these vectors their Gram matrix, i.e., the matrix defined by
An often used application is the following elegant formula for the distance to the span of .
Theorem 3.1.
(Hilbert Space Distance Formula) If is a Hilbert space, , and are linearly independent, then
(3.2) |
Proof.
Write , where is in the span of and is perpendicular to the span. Then .
We can write
Since is in the span of , we have
Moreover, is a matrix whose first row is . Therefore
Combining these observations, we get (3.2). ∎
4 A Hilbert space proof of Hardy’s Inequality
The key step in our proof is the following lemma.
Lemma 4.1.
An Identity for
Proof.
It suffices to show for a polynomial, since the polynomials are dense in . If
then
Likewise, as
Hence
∎
5 An asymptotic Müntz-Szász Theorem
Let be a subset of the non-negative integers. When is the linear span of the monomials dense? The Müntz-Szász Theorem, proved by Müntz [6] and Szász [7], answers this question in both and , the continuous functions on . The answer is basically the same in both cases, but the constant function plays a special role in , since it cannot be approximated by any polynomial that vanishes at (which all the other monomials do).
Theorem 5.1.
(Müntz-Szász Theorem) (i) The linear span of is dense in if and only if
(5.2) |
(ii) The linear span of is dense in if and only if and (5.2) holds.
What happens if the approximants come from a set of linear combinations of monomials that is losing as well as gaining members? Fix an increasing sequence of natural numbers and for each define
For each let denote the fraction of the non-negative integers less than or equal to that do not lie in , i.e.,
Finally, with this setup, let
(5.3) |
We wish to characterize (Theorem 5.12 below). We shall follow Müntz’s original proof of Theorem 5.1 [6]. His argument involved an ingenious calculation using Theorem 3.1 and the following venerable formula of Cauchy [3].
Theorem 5.4.
(The Cauchy Determinant Formula) If is the Cauchy matrix defined by the formula
where for all and , , then
We need two more auxiliary results.
Proposition 5.5.
(Baby Brodskii-Donoghue Theorem) Let be a closed subspace of that is invariant under both and . Then for some between and .
Proof.
Note that the constant function 1 has the unique representation in ,
(5.6) |
where and . The fact that is invariant, implies that whenever is a polynomial222Note that it is also true that whenever is a polynomial, since is self-adjoint., it follows that whenever is a polynomial. But then for all polynomials which implies that
(5.7) |
For a Lesbesgue measurable set we let denote the characteristic function of , i.e., the function defined by
We observe that (5.6) and (5.7) imply that there exists a partition of into two measurable sets and such that and . We define a parameter by setting
(5.8) |
Notice that with this definition, we have that
(5.9) |
Since , we have . Also, recall that . Therefore, using (5.9) we see that . In light of (5.6), this implies , which in turn, implies via (5.8) that
(5.10) |
As and whenever is a polynomial, it follows immediately from (5.10) and the fact that the polynomials are dense in both and , that
Hence, we have that both and , so that , as was to be proved. ∎
We call Proposition 5.5 the Baby Brodskii-Donoghue Theorem because Brodskii and Donoghue independently proved the far deeper fact that the only closed invariant subspaces of are [2, 4]. The operator has other invariant subspaces. Indeed the ideas in the preceding proof can be adapted to show that the invariant subspaces of are the spaces , where is any measurable subset of .
Lemma 5.11.
If is as in (5.3), then there exists such that .
Proof.
Theorem 5.12.
(Asymptotic Müntz-Szász Theorem) Let , let , and let If
then
Proof.
6 The Bernstein Conundrum: Asymptotic Müntz-Szász Theorem for
The Müntz-Szász Theorem can be deduced from the version. What about the asymptotic version? Let be as in Section 5, and let be
(6.1) |
where in this section all distances are with respect to the supremum norm333This means ..
One way to prove the Weierstraß approximation theorem is to use the Bernstein polynomials. For each , these are the polynomials defined by
Bernstein proved in 1912 [1] that for every continuous function , the polynomials
(6.2) |
converge uniformly on to .
As the lowest order term in is , if vanished on and one used the Bernstein formula (6.2) to approximate it, the corresponding polynomial would lie in the span of which is in . So one immediately gets that contains all the continuous functions that vanish on .
This construction seems natural, and could lead one to suspect that should be the functions that vanish on . However, Theorem 6.3 shows this is incorrect.
Theorem 6.3.
(Asymptotic Müntz-Szász Theorem, Continuous Case) If
then
Proof.
As the supremum norm is larger than the norm, we have
For the reverse inclusion, notice that it follows from Cauchy-Schwarz that the Volterra operator is a bounded linear map from into . (Indeed, if , we get that satisfies a Hölder continuity condition of order .)
Let be a function that vanishes on . Then , where . By Theorem 5.12, there are polynomials that converge in to . Then converges in to , so is in . As is closed, and the functions that vanish on are dense in the continuous ones, we get
∎
Question 6.4.
Can one prove Theorem 6.3 directly using Bernstein approximation?
7 Proof of Theorem 1.5
Proof.
Assume that is a monomial operator of order , let , and fix . We wish to prove that .
Choose an increasing sequence of natural numbers such that
By Theorem 5.12, there exists a sequence of polynomials where for each , has the form
and such that
As is bounded,
Also, as is a monomial operator of order , for each , has the form
For any , multiplication by is a bounded invertible map from to itself. Therefore
converges, as , to some function , which by Theorem 5.12 is in . So , and lies in in . ∎
References
- [1] Serge Bernstein. Démonstration du théorème de Weierstrass fondée sur le calcul des probabilités. Comm. Kharkov Math. Soc, 13:1–2, 1912.
- [2] M. S. Brodskii. On a problem of I. M. Gelfand. Uspehi Mat. Nauk (N.S.), 12(2(74)):129–132, 1957.
- [3] Augustin Louis Cauchy. Exercices d’analyse et de physique mathématique. Vol. 2. Bachelier, Paris, 1841.
- [4] W. F. Donoghue, Jr. The lattice of invariant subspaces of a completely continuous quasi-nilpotent transformation. Pacific J. Math., 7:1031–1035, 1957.
- [5] G. H. Hardy. Note on a theorem of Hilbert. Math. Z., 6(3-4):314–317, 1920.
- [6] Chaim Herman Müntz. Über den Approximationssatz von Weierstrass. In H.A. Schwartz Festschrift, pages 303–312. Berlin, 1914.
- [7] Otto Szász. Über die Approximation stetiger Funktionen durch lineare Aggregate von Potenzen. Math. Ann., 77(4):482–496, 1916.