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Hardy space

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In complex analysis, the Hardy spaces (or Hardy classes) are spaces of holomorphic functions on the unit disk or upper half plane. They were introduced by Frigyes Riesz (Riesz 1923), who named them after G. H. Hardy, because of the paper (Hardy 1915). In real analysis Hardy spaces are spaces of distributions on the real n-space , defined (in the sense of distributions) as boundary values of the holomorphic functions. are related to the Lp spaces.[1] For these Hardy spaces are subsets of spaces, while for the spaces have some undesirable properties, and the Hardy spaces are much better behaved. Hence, spaces can be considered extensions of spaces.[2]

Hardy spaces have a number of applications, both in mathematical analysis itself as well as in interdisciplinary areas such as control theory (e.g. methods) and scattering theory.

Definition

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On the unit disk

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The Hardy space for is the class of holomorphic functions on the open unit disk satisfying If then the equation coincides with the definition of the Hardy space p-norm, denoted by

The space H is defined as the vector space of bounded holomorphic functions on the disk, with the norm

For 0 < p ≤ q ≤ ∞, the class Hq is a subset of Hp, and the Hp-norm is increasing with p (it is a consequence of Hölder's inequality that the Lp-norm is increasing for probability measures, i.e. measures with total mass 1) (Rudin 1987, Def 17.7).

On the unit circle

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The Hardy spaces can also be viewed as closed vector subspaces of the complex Lp spaces on the unit circle . This connection is provided by the following theorem (Katznelson 1976, Thm 3.8): Given with , then the radial limit exists for almost every and such that [clarification needed] Denote by Hp(T) the vector subspace of Lp(T) consisting of all limit functions , when f varies in Hp, one then has that for p ≥ 1,(Katznelson 1976)

where the are the Fourier coefficients defined as The space Hp(T) is a closed subspace of Lp(T). Since Lp(T) is a Banach space (for 1 ≤ p ≤ ∞), so is Hp(T).

The above can be turned around. Given a function , with p ≥ 1, one can regain a (harmonic) function f on the unit disk by means of the Poisson kernel Pr:

and f belongs to Hp exactly when is in Hp(T). Supposing that is in Hp(T), i.e., has Fourier coefficients (an)nZ with an = 0 for every n < 0, then the associated holomorphic function f of Hp is given by In applications, those functions with vanishing negative Fourier coefficients are commonly interpreted as the causal solutions. For example, the Hardy space H2 consists of functions whose mean square value remains bounded as from below. Thus, the space H2 is seen to sit naturally inside L2 space, and is represented by infinite sequences indexed by N; whereas L2 consists of bi-infinite sequences indexed by Z.

On the upper half plane

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The Hardy space on the upper half-plane is defined to be the space of holomorphic functions on with bounded norm, given by The corresponding is defined as functions of bounded norm, with the norm given by The unit disk is isomorphic to the upper half-plane by means of a Möbius transformation. For example, let denote the Möbius transformation Then the linear operator defined by is an isometric isomorphism of Hardy spaces.

A similair approach applies to, e.g., the right half-plane.

On the real vector space

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In analysis on the real vector space Rn, the Hardy space Hp (for 0 < p ≤ ∞) consists of tempered distributions f such that for some Schwartz function Φ with ∫Φ = 1, the maximal function

is in Lp(Rn), where ∗ is convolution and Φt(x) = t −nΦ(x / t). The Hp-quasinorm ||f ||Hp of a distribution f of Hp is defined to be the Lp norm of MΦf (this depends on the choice of Φ, but different choices of Schwartz functions Φ give equivalent norms). The Hp-quasinorm is a norm when p ≥ 1, but not when p < 1.

If 1 < p < ∞, the Hardy space Hp is the same vector space as Lp, with equivalent norm. When p = 1, the Hardy space H1 is a proper subspace of L1. One can find sequences in H1 that are bounded in L1 but unbounded in H1, for example on the line

The L1 and H1 norms are not equivalent on H1, and H1 is not closed in L1. The dual of H1 is the space BMO of functions of bounded mean oscillation. The space BMO contains unbounded functions (proving again that H1 is not closed in L1).

If p < 1 then the Hardy space Hp has elements that are not functions, and its dual is the homogeneous Lipschitz space of order n(1/p − 1). When p < 1, the Hp-quasinorm is not a norm, as it is not subadditive. The pth power ||f ||Hpp is subadditive for p < 1 and so defines a metric on the Hardy space Hp, which defines the topology and makes Hp into a complete metric space.

Atomic decomposition

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When 0 < p ≤ 1, a bounded measurable function f of compact support is in the Hardy space Hp if and only if all its moments

whose order i1+ ... +in is at most n(1/p − 1), vanish. For example, the integral of f must vanish in order that fHp, 0 < p ≤ 1, and as long as p > n / (n+1) this is also sufficient.

If in addition f has support in some ball B and is bounded by |B|−1/p then f is called an Hp-atom (here |B| denotes the Euclidean volume of B in Rn). The Hp-quasinorm of an arbitrary Hp-atom is bounded by a constant depending only on p and on the Schwartz function Φ.

When 0 < p ≤ 1, any element f of Hp has an atomic decomposition as a convergent infinite combination of Hp-atoms,

where the aj are Hp-atoms and the cj are scalars.

On the line for example, the difference of Dirac distributions f = δ1−δ0 can be represented as a series of Haar functions, convergent in Hp-quasinorm when 1/2 < p < 1 (on the circle, the corresponding representation is valid for 0 < p < 1, but on the line, Haar functions do not belong to Hp when p ≤ 1/2 because their maximal function is equivalent at infinity to a x−2 for some a ≠ 0).

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Real-variable techniques, mainly associated to the study of real Hardy spaces defined on Rn, are also used in the simpler framework of the circle. It is a common practice to allow for complex functions (or distributions) in these "real" spaces. The definition that follows does not distinguish between real or complex case.

Let Pr denote the Poisson kernel on the unit circle T. For a distribution f on the unit circle, set

where the star indicates convolution between the distribution f and the function ePr(θ) on the circle. Namely, (fPr)(e) is the result of the action of f on the C-function defined on the unit circle by

For 0 < p < ∞, the real Hardy space Hp(T) consists of distributions f such that M f  is in Lp(T).

The function F defined on the unit disk by F(re) = (fPr)(e) is harmonic, and M f  is the radial maximal function of F. When M f  belongs to Lp(T) and p ≥ 1, the distribution f  "is" a function in Lp(T), namely the boundary value of F. For p ≥ 1, the real Hardy space Hp(T) is a subset of Lp(T).

Conjugate function

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To every real trigonometric polynomial u on the unit circle, one associates the real conjugate polynomial v such that u + iv extends to a holomorphic function in the unit disk,

This mapping uv extends to a bounded linear operator H on Lp(T), when 1 < p < ∞ (up to a scalar multiple, it is the Hilbert transform on the unit circle), and H also maps L1(T) to weak-L1(T). When 1 ≤ p < ∞, the following are equivalent for a real valued integrable function f on the unit circle:

  • the function f is the real part of some function gHp(T)
  • the function f and its conjugate H(f) belong to Lp(T)
  • the radial maximal function M f  belongs to Lp(T).

When 1 < p < ∞, H(f) belongs to Lp(T) when fLp(T), hence the real Hardy space Hp(T) coincides with Lp(T) in this case. For p = 1, the real Hardy space H1(T) is a proper subspace of L1(T).

The case of p = ∞ was excluded from the definition of real Hardy spaces, because the maximal function M f  of an L function is always bounded, and because it is not desirable that real-H be equal to L. However, the two following properties are equivalent for a real valued function f

  • the function f  is the real part of some function gH(T)
  • the function f  and its conjugate H(f) belong to L(T).

For 0 < p < 1

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When 0 < p < 1, a function F in Hp cannot be reconstructed from the real part of its boundary limit function on the circle, because of the lack of convexity of Lp in this case. Convexity fails but a kind of "complex convexity" remains, namely the fact that z → |z|q is subharmonic for every q > 0. As a consequence, if

is in Hp, it can be shown that cn = O(n1/p–1). It follows that the Fourier series

converges in the sense of distributions to a distribution f on the unit circle, and F(re) =(f ∗ Pr)(θ). The function FHp can be reconstructed from the real distribution Re(f) on the circle, because the Taylor coefficients cn of F can be computed from the Fourier coefficients of Re(f).

Distributions on the circle are general enough for handling Hardy spaces when p < 1. Distributions that are not functions do occur, as is seen with functions F(z) = (1−z)N (for |z| < 1), that belong to Hp when 0 < N p < 1 (and N an integer ≥ 1).

A real distribution on the circle belongs to real-Hp(T) iff it is the boundary value of the real part of some FHp. A Dirac distribution δx, at any point x of the unit circle, belongs to real-Hp(T) for every p < 1; derivatives δ′x belong when p < 1/2, second derivatives δ′′x when p < 1/3, and so on.

Beurling factorization

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For 0 < p ≤ ∞, every non-zero function f in Hp can be written as the product f = Gh where G is an outer function and h is an inner function, as defined below (Rudin 1987, Thm 17.17). This "Beurling factorization" allows the Hardy space to be completely characterized by the spaces of inner and outer functions.[3][4]

One says that G(z)[clarification needed] is an outer (exterior) function if it takes the form

for some complex number c with |c| = 1, and some positive measurable function on the unit circle such that is integrable on the circle. In particular, when is integrable on the circle, G is in H1 because the above takes the form of the Poisson kernel (Rudin 1987, Thm 17.16). This implies that

for almost every θ.

One says that h is an inner (interior) function if and only if |h| ≤ 1 on the unit disk and the limit

exists for almost all θ and its modulus is equal to 1 a.e. In particular, h is in H.[clarification needed] The inner function can be further factored into a form involving a Blaschke product.

The function f, decomposed as f = Gh,[clarification needed] is in Hp if and only if φ belongs to Lp(T), where φ is the positive function in the representation of the outer function G.

Let G be an outer function represented as above from a function φ on the circle. Replacing φ by φα, α > 0, a family (Gα) of outer functions is obtained, with the properties:

G1 = G, Gα+β = Gα Gβ  and |Gα| = |G|α almost everywhere on the circle.

It follows that whenever 0 < p, q, r < ∞ and 1/r = 1/p + 1/q, every function f in Hr can be expressed as the product of a function in Hp and a function in Hq. For example: every function in H1 is the product of two functions in H2; every function in Hp, p < 1, can be expressed as product of several functions in some Hq, q > 1.

Martingale Hp

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Let (Mn)n≥0 be a martingale on some probability space (Ω, Σ, P), with respect to an increasing sequence of σ-fields (Σn)n≥0. Assume for simplicity that Σ is equal to the σ-field generated by the sequence (Σn)n≥0. The maximal function of the martingale is defined by

Let 1 ≤ p < ∞. The martingale (Mn)n≥0 belongs to martingale-Hp when M*Lp.

If M*Lp, the martingale (Mn)n≥0 is bounded in Lp; hence it converges almost surely to some function f by the martingale convergence theorem. Moreover, Mn converges to f in Lp-norm by the dominated convergence theorem; hence Mn can be expressed as conditional expectation of f on Σn. It is thus possible to identify martingale-Hp with the subspace of Lp(Ω, Σ, P) consisting of those f such that the martingale

belongs to martingale-Hp.

Doob's maximal inequality implies that martingale-Hp coincides with Lp(Ω, Σ, P) when 1 < p < ∞. The interesting space is martingale-H1, whose dual is martingale-BMO (Garsia 1973).

The Burkholder–Gundy inequalities (when p > 1) and the Burgess Davis inequality (when p = 1) relate the Lp-norm of the maximal function to that of the square function of the martingale

Martingale-Hp can be defined by saying that S(f)∈ Lp (Garsia 1973).

Martingales with continuous time parameter can also be considered. A direct link with the classical theory is obtained via the complex Brownian motion (Bt) in the complex plane, starting from the point z = 0 at time t = 0. Let τ denote the hitting time of the unit circle. For every holomorphic function F in the unit disk,

is a martingale, that belongs to martingale-Hp iff F ∈ Hp (Burkholder, Gundy & Silverstein 1971).

Example

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In this example, Ω = [0, 1] and Σn is the finite field generated by the dyadic partition of [0, 1] into 2n intervals of length 2n, for every n ≥ 0. If a function f on [0, 1] is represented by its expansion on the Haar system (hk)

then the martingale-H1 norm of f can be defined by the L1 norm of the square function

This space, sometimes denoted by H1(δ), is isomorphic to the classical real H1 space on the circle (Müller 2005). The Haar system is an unconditional basis for H1(δ).

See also

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Notes

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  1. ^ Folland 2001.
  2. ^ Stein & Murphy 1993, p. 88.
  3. ^ Beurling, Arne (1948). "On two problems concerning linear transformations in Hilbert space". Acta Mathematica. 81: 239–255. doi:10.1007/BF02395019.
  4. ^ Voichick, Michael; Zalcman, Lawrence (1965). "Inner and outer functions on Riemann surfaces". Proceedings of the American Mathematical Society. 16 (6): 1200–1204. doi:10.1090/S0002-9939-1965-0183883-1.

References

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