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Littlewood-Paley square-function equivalence on Lp for 1<p<infinity

Statement

Assume Countable Choice (The Axiom of Countable Choice (ACω)). Let n≥1, fix the partition and operators of The inhomogeneous dyadic frequency partition and its Littlewood-Paley operators, and let S be the square function of The Littlewood-Paley square function.

  1. For every 1<p<∞ there are constants 0<cp≤Cp<∞, depending only on n, p and the fixed cutoff, such that every f∈S(Rn) satisfies cp∥f∥Lp≤∥Sf∥Lp≤Cp∥f∥Lp; in particular Sf∈Lp for Schwartz f.
  2. (Extension to Lp.) For every f∈Lp(Rn;C) and every sequence fk∈S(Rn) with fk→f in Lp, the sequence Sfk is Cauchy in Lp; its limit, written Sf, is independent of the approximating sequence, satisfies the same two-sided estimate with the constants of part 1, and is the unique continuous extension of the Schwartz assignment. Moreover the increasing sequence SNf=(∑j<N∣Δjf∣2)1/2 of convolution representatives converges to Sf in Lp and almost everywhere, so Sf=(∑j≥0∣Δjf∣2)1/2 almost everywhere.

Only 1<p<∞ is claimed.

Facts & Assumptions

Given: the fixed partition, operators and kernels of The inhomogeneous dyadic frequency partition and its Littlewood-Paley operators; the square function S and its truncations SN, SF of The Littlewood-Paley square function; a real 1<p<∞ with conjugate p′; the finite partial symbols mt,N=∑j<Nεj(t)φj for t∈[0,1).

[F1]

Rademacher randomisation: for every 0<q<∞ there are 0<cq≤Cq<∞, depending only on q, such that for every finite F, every f∈S and every x, cqSFf(x)≤(∫01∣∑j∈Fεj(t)Δjf(x)∣qdt)1/q≤CqSFf(x), and for each t the random sum equals Tmt,Ff; integrating in x gives cqq∥SFf∥qq≤∫01∥Tmt,Ff∥qqdt≤Cqq∥SFf∥qq (Rademacher randomisation turns dyadic square functions into random signed multipliers, Khintchine's inequality for finite Rademacher sums).

[F2]

Uniform signed-sum bounds: for every sequence ∣cj∣≤1 the symbol ∑jcjφj is a Mihlin symbol with constants independent of the coefficients, and for 1<q<∞ one has ∥T∑jcjφjf∥q≤Cn,ψmax⁡(q,(q−1)−1)∥f∥q; in particular the bound applies to every truncation symbol mt,N and is uniform in t,N (Random signed dyadic sums have uniform Mihlin and Lp multiplier bounds, Dyadic pieces are uniformly Mihlin multipliers and uniformly Lp-bounded).

[F3]

Reproducing formula: for f,g∈S with ∥Sf∥p<∞ and ∥S~g∥p′<∞ the series ∑j⟨Δjf,Δ~jg⟩ converges absolutely to ⟨f,g⟩ and ∑j∣⟨Δjf,Δ~jg⟩∣≤∫Sf S~g (The Littlewood-Paley reproducing formula in tempered distributions).

[F4]

Holder's inequality and the finite ℓ2 reverse-triangle inequality ∣SNu−SNv∣≤SN(u−v); its limit gives ∣Su−Sv∣≤S(u−v) wherever Su and Sv are finite (Complex Holder, Minkowski, and the quotient norm, The Littlewood-Paley square function).

[F5]

Integration and limit tools: Tonelli for nonnegative product-measurable integrands, monotone convergence for increasing sequences, dominated convergence in Lp, completeness of Lp together with almost everywhere convergence of a subsequence, density of smooth compactly supported functions in Lp for finite p, and the duality formula ∥h∥p=sup⁡{∣∫hg∣:∥g∥p′≤1} (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product, Monotone convergence for the integral, Dominated convergence, Complex Lp completeness and almost-everywhere subsequences, Complex finite-simple and smooth compact-support density for finite p, The Lp norm is the supremum of pairings against unit Lq functions).

Proof

technique · direct
1.1F1F2F5algebra

Upper bound for Schwartz functions. Let f∈S and N≥0. The lower pointwise Khintchine bound of [F1] with q=p gives SNf(x)≤cp−1(∫01∣∑j<Nεj(t)Δjf(x)∣pdt)1/p; raising to the p-th power, integrating in x, and applying Tonelli (the integrand is nonnegative and product-measurable by [F1]) gives ∥SNf∥pp≤cp−p∫01∥Tmt,Nf∥ppdt≤cp−p(Cn,ψmax⁡(p,(p−1)−1))p∥f∥pp, where the last inequality is the uniform signed-sum bound [F2] applied at each t to the truncation symbols. Since SNf↑Sf pointwise, monotone convergence [F5] gives ∥Sf∥p≤Cp∥f∥p with Cp:=cp−1Cn,ψmax⁡(p,(p−1)−1); in particular Sf∈Lp. The same computation for any finite set F in place of {0,…,N−1} gives ∥SFf∥p≤Cp∥f∥p.

2.1F5step 1.1algebra

Companion upper bound. Since φ~j=φj−1+φj+φj+1 and the multiplier map is linear in the symbol, Δ~jf=Δj−1f+Δjf+Δj+1f (with Δ−1:=0); hence ∣Δ~jf∣2≤3(∣Δj−1f∣2+∣Δjf∣2+∣Δj+1f∣2) pointwise, and summing over j∈F gives S~Ff≤3SF′f with the finite set F′={j−1,j,j+1:j∈F}∩{0,1,2,… }. By step 1.1 applied to F′, ∥S~Ff∥p≤3Cp∥f∥p; letting F increase to all indices and using monotone convergence for S~Ff↑S~f gives ∥S~f∥p≤3Cp∥f∥p.

2.2F4F5step 1.1algebra

Extension to Lp. For u,v∈S the pointwise inequality ∣Su−Sv∣≤S(u−v) of [F4] and step 1.1 give ∥Su−Sv∥p≤Cp∥u−v∥p; hence u↦Su is Lipschitz on the dense subspace S of Lp, and for any f∈Lp and any fk∈S with fk→f the sequence Sfk is Cauchy in Lp. By completeness of Lp [F5] it has a limit F, which is independent of the approximating sequence: if f~k is another such sequence, the interleaved sequence f1,f~1,f2,f~2,… also converges to f in Lp and its image is Cauchy, so the two limits agree. This assignment is the unique continuous extension of the Schwartz square function, by the same Lipschitz bound.

3.1F3F4F5step 1.1step 2.1algebra

Lower bound for Schwartz functions. Let f∈S. By steps 1.1 and 2.1, ∥Sf∥p<∞ and, for every g∈S, ∥S~g∥p′<∞; the reproducing formula [F3] therefore gives ⟨f,g⟩=∑j⟨Δjf,Δ~jg⟩ with ∑j∣⟨Δjf,Δ~jg⟩∣≤∫Sf S~g. By the pointwise Cauchy-Schwarz inequality and Holder [F4], ∫Sf S~g≤∥Sf∥p∥S~g∥p′≤3Cp′∥Sf∥p∥g∥p′. Hence ∣⟨f,g⟩∣≤3Cp′∥Sf∥p∥g∥p′ first for all g∈S and then, by density of S in Lp′ and continuity of the pairing, for all g∈Lp′; taking the supremum over ∥g∥p′≤1 and using the duality formula [F5] gives ∥f∥p≤3Cp′∥Sf∥p. This is the lower bound of part 1 with cp:=(3Cp′)−1.

4.1F2F4F5step 1.1step 2.2step 3.1algebra

Identification with the pointwise square function. For fixed N, [F2] and the finite reverse-triangle inequality give ∥SNu−SNv∥p≤∑j<N∥Δj(u−v)∥p≤NBp∥u−v∥p for all u,v∈Lp, where Bp is a uniform bound for the pieces. Therefore SN is continuous on Lp, and approximation by Schwartz functions passes the bound of step 1.1 to ∥SNf∥p≤Cp∥f∥p for every f∈Lp, uniformly in N. Monotone convergence [F5] gives ∥Sf∥p≤Cp∥f∥p for the increasing pointwise limit, so Sf is finite almost everywhere. Since ∣Sf−SNf∣p≤(Sf)p, dominated convergence [F5] gives SNf→Sf in Lp, as well as pointwise. Passing the finite reverse-triangle inequality to the limit gives ∣Su−Sv∣≤S(u−v) almost everywhere and hence ∥Su−Sv∥p≤Cp∥u−v∥p on all of Lp. In particular, for fk∈S with fk→f, Sfk→Sf in Lp, identifying this function with the extension of step 2.2. Taking limits in steps 1.1 and 3.1 gives the two-sided estimate for f.

5.1step 1.1step 2.1step 2.2step 3.1step 4.1∎

Conclusion. Steps 1.1 and 3.1 prove part 1, and steps 2.2 and 4.1 prove part 2: the Cauchy property and independence of the approximating sequence, the identification of the extension with the increasing pointwise square function both in Lp and almost everywhere, and the inherited two-sided estimate.

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