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Maximal-function characterisations of real Hardy spaces

Statement

Assume Countable Choice. Let n≥1, 0<p<∞ and let φ∈S(Rn) with ∫φ≠0. Then there is N0(n,p,φ)<∞, depending only on n, p and the fixed kernel φ, such that for every N≥N0(n,p,φ) and every f∈S′(Rn) the following assertions are equivalent:

  1. Mφ0f∈Lp(Rn);
  2. Mφ∗,af∈Lp(Rn) for some a≥1 (equivalently, for every a≥1);
  3. MNf∈Lp(Rn).

Here Mφ0f, Mφ∗,af are the maximal functions of Radial and nontangential maximal functions of a tempered distribution and MN is the grand maximal function of Grand maximal test class of order N and the grand maximal function. Moreover the extended quantities ∥Mφ0f∥Lp, ∥Mφ∗,af∥Lp and ∥MNf∥Lp are finite exactly on the common set of f satisfying 1-3, and on that set they are equivalent: ∥Mφ0f∥Lp≤∥Mφ∗,af∥Lp≤(1+a)NPN(φ)∥MNf∥Lp,∥MNf∥Lp≤C∥Mφ0f∥Lp, with C=C(n,p,N,φ)<∞ depending only on n,p,N and finitely many Schwartz seminorms of φ together with quantitative nonvanishing data for φ^ near zero (as used in the deconvolution lemma). Consequently the space Hp(Rn) of The real Hardy space Hp defined by a radial maximal function does not depend on the choice of admissible φ, and for each admissible φ the grand maximal function may be used to define the same space with an equivalent quasi-norm for every order N≥N0(n,p,φ); for two admissible kernels φ,ψ the two radial definitions agree because both are equivalent to MN for every N≥max⁡(N0(n,p,φ),N0(n,p,ψ)). The recorded admissible thresholds of the sources are N≥⌊n/p⌋+1 for the nontangential class FN with derivatives through N+1 [DKKP], N>1+n/p for the radial class BN with derivatives through N [MSV, section 1, p. 16, for 0<p≤1], and N>n/p+n+1 [CUW], stated there for the grand maximal functions normalised by the test classes of those papers; the proof below uses an unspecified finite N0(n,p,φ) that is at least as large as the order thresholds consumed by the finitely many comparison estimates for the fixed kernel φ (the deconvolution constants of the comparison lemmas depend on the kernel, so the order threshold asserted here depends on φ as well as on n and p), and the existence of such a finite threshold is what is asserted.

Facts & Assumptions

Given: Countable Choice, n≥1, 0<p<∞, φ∈S with ∫φ≠0, f∈S′, and a fixed order N.

[F1]

Pointwise domination by the grand maximal function: Mφ0f≤Mφ∗,1f≤2NPN(φ)MNf and Mφ∗,af≤(1+a)NPN(φ)MNf for every a≥1, provided N is the order of the grand maximal function (The grand maximal function dominates every admissible radial and nontangential maximal function).

[F2]

Tangential comparison: for 0<q<p and T=n/q, ∥Mφ,Tf∥Lp≤Cn,p,q∥Mφ∗,1f∥Lp (The tangential maximal function is controlled by the aperture-one nontangential maximal function in Lp).

[F3]

Grand dominated by tangential: for every T>0 there are N2(n,φ,T) and C0 with MNf≤C0Mφ,Tf whenever N≥N2 (The grand maximal function is pointwise dominated by a tangential maximal function).

[F4]

Good-set estimates: assertion 5 of Truncated maximal functions: finiteness, comparison estimates and the good-set bound uses the extended centered average M~ of that item for general nonnegative Borel inputs. When Mφ0f∈Lp and q0=p/2, the input (Mφ0f)q0 belongs to L2⊂Lloc1, so M~=M and the standard maximal operator can be used. Assertions 1-4 of the same lemma provide the truncated functions Mφ,jϵ,L and their finiteness, grand/tangential comparison, tangential/aperture-one comparison and good-set bound.

[F5]

Hardy-Littlewood boundedness: ∥Mg∥Lr≤Cn,r∥g∥Lr for 1<r<∞ (The centered maximal operator is bounded on Lp(Rn) for 1<p<∞).

[F6]

The maximal functions are Borel measurable, so all Lp expressions are meaningful with values in [0,∞] (Measurability and lower semicontinuity of the smooth maximal functions).

[F7]

L2(Rn)⊂Lloc1(Rn): on each compact K, Holder gives ∫K∣g∣≤λ(K)1/2∥g∥2, and compact sets have finite measure because they are bounded (Holder's inequality for integrals, including the endpoint cases, Lebesgue measure is sigma-finite, and every metrically bounded subset of Rn has finite outer measure).

[F8]

If nonnegative measurable functions hm increase pointwise to h, then their integrals increase to ∫h by the monotone convergence theorem (Monotone convergence for the integral).

Proof technique: a priori good-set argument, then removal of the a priori finiteness by truncation, then the pointwise domination for the converse.

Proof

technique · direct
1.1F1F2F3F4F5F6F7algebra

A priori estimate. Assume Mφ∗,1f∈Lp and let q0=p/2, T=2n/p, so that T=n/q0 and q0<p. Let N2=N2(n,φ,T) and C0=C0(n,φ,T) be the constants of [F3], let CT=Cn,p,q0 be the norm constant from [F2], and let CH=Cn,21/q0 be the powered Hardy-Littlewood constant from [F5] at r=2. Put C1=C0CT and λ=21/pC1, so that ∥MNf∥Lp≤C1∥Mφ∗,1f∥Lp by [F2], [F3] for every N≥N2. Let N3=N3(n,φ,q0,λ) be the threshold of [F4, assertion 5]; fix N≥max⁡(N2,N3) and let C4=C4(n,φ,q0,λ,N) be the constant of [F4, assertion 5] at this order. Set F={x:MNf(x)≤λMφ∗,1f(x)}. On Fc one has Mφ∗,1f≤λ−1MNf pointwise, hence ∥Mφ∗,1f χFc∥Lpp≤λ−p∥MNf∥Lpp≤(C1/λ)p∥Mφ∗,1f∥Lpp=12∥Mφ∗,1f∥Lpp. On F, [F4, assertion 5] gives Mφ∗,1f≤C4M~((Mφ0f)q0)1/q0 at every point at which Mφ∗,1f is finite, hence almost everywhere. Since [F1] gives Mφ0f≤Mφ∗,1f, we have (Mφ0f)q0∈L2; [F7] gives its local integrability and hence M~=M on this input. Integrating, ∥Mφ∗,1f χF∥Lp≤C4∥M((Mφ0f)q0)1/q0∥Lp=C4∥M((Mφ0f)q0)∥Lp/q01/q0≤C4CH∥(Mφ0f)q0∥Lp/q01/q0=C4CH∥Mφ0f∥Lp by [F5] with r=p/q0=2>1. Combining the two pieces, ∥Mφ∗,1f∥Lpp≤(C4CH)p∥Mφ0f∥Lpp+12∥Mφ∗,1f∥Lpp, so ∥Mφ∗,1f∥Lp≤21/pC4CH∥Mφ0f∥Lp; this is the a priori estimate, with a constant independent of f at each fixed order N≥max⁡(N2,N3).

2.1F4F5F6F7F8step 1.1algebra

Finiteness of Mφ∗,1f when Mφ0f∈Lp. Let f be arbitrary with Mφ0f∈Lp. Choose L≥L0(f,n,φ,p) as in assertion 1 of [F4] for the fixed exponent p of the theorem and then N′=N′(n,φ,T,L) as in assertions 2-4 of [F4], where T=2n/p and q0=p/2 are as above (note that N′ may be much larger than the theorem's fixed N; it is used only to prove finiteness). With 0<ϵ≤1/2 set M1=Mφ,1ϵ,Lf, M0=Mφ,0ϵ,Lf, MT=Mφ,Tϵ,Lf, MG=MN′ϵ,Lf and Fϵ={x:MG(x)<λM1(x)} with λ=21/pC1′, C1′=C1′(n,φ,T,L) the product of the constants in assertions 2 and 3 of [F4]. Assertion 1 of [F4] gives ∥M1∥Lp<∞. On Fϵc one has M1≤λ−1MG, so ∥M1χFϵc∥Lpp≤λ−p∥MG∥Lpp≤(C1′/λ)p∥M1∥Lpp=12∥M1∥Lpp. On Fϵ, assertion 4 of [F4] gives M1≤C3M~((Mφ0f)q0)1/q0 with C3=C3(n,φ,q0,T,L,λ,N′). Since (Mφ0f)q0∈L2, [F7] gives M~=M on this input; integrating as in step 1.1 and using [F5] gives ∥M1χFϵ∥Lp≤C′′∥Mφ0f∥Lp with C′′ independent of ϵ (but depending on the fixed L and hence on f). Hence ∥Mφ,1ϵ,Lf∥Lp≤21/pC′′∥Mφ0f∥Lp for every 0<ϵ≤1/2. Take ϵm=1/(m+2) for m≥0. Then the weights tL/(t+ϵm+ϵm∣y∣)L increase pointwise to 1 and the ranges 0<t<1/ϵm increase to (0,∞). For each fixed witness (t,y), eventually t<1/ϵm and its weight tends to 1, so Mφ,1ϵm,Lf↗Mφ∗,1f pointwise. By [F8], monotone convergence gives ∥Mφ∗,1f∥Lp≤21/pC′′∥Mφ0f∥Lp<∞.

3.1step 1.1step 2.1F2F3F5algebra

The implication 1⇒3 and the norm bound. Let f satisfy 1. By step 2.1, Mφ∗,1f∈Lp, so the a priori estimate of step 1.1 applies at every order N≥N0(n,p,φ):=max⁡(N2(n,φ,2n/p), N3(n,φ,p/2,21/pC1)) and gives ∥Mφ∗,1f∥Lp≤C∥Mφ0f∥Lp with C=21/pC4(n,φ,p/2,21/pC1,N)CH independent of f, where CH=Cn,21/q0 is the constant from [F5] at r=2; then [F2], [F3] give ∥MNf∥Lp≤C1∥Mφ∗,1f∥Lp≤C1C∥Mφ0f∥Lp for the same orders N≥N0(n,p,φ), since the estimates of steps 1.1 and 2.1 hold with the stated constants for every such N. Thus 1 implies 3 for every N≥N0(n,p,φ), with the stated norm bound.

4.1step 3.1F1F6∎

The remaining implications. If 3 holds, then [F1] gives Mφ0f≤2NPN(φ)MNf∈Lp and Mφ∗,af≤(1+a)NPN(φ)MNf∈Lp for every a≥1, so 3 implies 1 and 2 for every aperture, with the displayed bounds (the first inequality ∥M0∥≤∥M∗,a∥ is pointwise since Mφ0f≤Mφ∗,af). If 2 holds for some a, then Mφ0f≤Mφ∗,af∈Lp pointwise, so 2 implies 1. Hence all three assertions are equivalent, the quantities are finite exactly on the common set, and the displayed equivalence of extended norms holds with constants depending only on n,p,N and the kernel data used in the deconvolution comparison and in PN(φ). The last sentence about the kernel-independence of Hp follows by applying the equivalence to two admissible kernels φ,ψ and a common order N≥max⁡(N0(n,p,φ),N0(n,p,ψ)). This proves the theorem.

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