How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Littlewood-Paley square-function equivalence on Lp for 1<p<infinity
Statement
Assume Countable Choice (The Axiom of Countable Choice ()). Let , fix the partition and operators of The inhomogeneous dyadic frequency partition and its Littlewood-Paley operators, and let be the square function of The Littlewood-Paley square function.
- For every there are constants , depending only on , and the fixed cutoff, such that every satisfies in particular for Schwartz .
- (Extension to .) For every and every sequence with in , the sequence is Cauchy in ; its limit, written , 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 of convolution representatives converges to in and almost everywhere, so almost everywhere.
Only 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 and its truncations , of The Littlewood-Paley square function; a real with conjugate ; the finite partial symbols for .
Rademacher randomisation: for every there are , depending only on , such that for every finite , every and every , , and for each the random sum equals ; integrating in gives (Rademacher randomisation turns dyadic square functions into random signed multipliers, Khintchine's inequality for finite Rademacher sums).
Uniform signed-sum bounds: for every sequence the symbol is a Mihlin symbol with constants independent of the coefficients, and for one has ; in particular the bound applies to every truncation symbol and is uniform in (Random signed dyadic sums have uniform Mihlin and Lp multiplier bounds, Dyadic pieces are uniformly Mihlin multipliers and uniformly Lp-bounded).
Reproducing formula: for with and the series converges absolutely to and (The Littlewood-Paley reproducing formula in tempered distributions).
Holder's inequality and the finite reverse-triangle inequality ; its limit gives wherever and are finite (Complex Holder, Minkowski, and the quotient norm, The Littlewood-Paley square function).
Integration and limit tools: Tonelli for nonnegative product-measurable integrands, monotone convergence for increasing sequences, dominated convergence in , completeness of together with almost everywhere convergence of a subsequence, density of smooth compactly supported functions in for finite , and the duality formula (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 norm is the supremum of pairings against unit functions).
Proof
Upper bound for Schwartz functions. Let and . The lower pointwise Khintchine bound of [F1] with gives ; raising to the -th power, integrating in , and applying Tonelli (the integrand is nonnegative and product-measurable by [F1]) gives , where the last inequality is the uniform signed-sum bound [F2] applied at each to the truncation symbols. Since pointwise, monotone convergence [F5] gives with ; in particular . The same computation for any finite set in place of gives .
Companion upper bound. Since and the multiplier map is linear in the symbol, (with ); hence pointwise, and summing over gives with the finite set . By step 1.1 applied to , ; letting increase to all indices and using monotone convergence for gives .
Extension to . For the pointwise inequality of [F4] and step 1.1 give ; hence is Lipschitz on the dense subspace of , and for any and any with the sequence is Cauchy in . By completeness of [F5] it has a limit , which is independent of the approximating sequence: if is another such sequence, the interleaved sequence also converges to in 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.
Lower bound for Schwartz functions. Let . By steps 1.1 and 2.1, and, for every , ; the reproducing formula [F3] therefore gives with . By the pointwise Cauchy-Schwarz inequality and Holder [F4], . Hence first for all and then, by density of in and continuity of the pairing, for all ; taking the supremum over and using the duality formula [F5] gives . This is the lower bound of part 1 with .
Identification with the pointwise square function. For fixed , [F2] and the finite reverse-triangle inequality give for all , where is a uniform bound for the pieces. Therefore is continuous on , and approximation by Schwartz functions passes the bound of step 1.1 to for every , uniformly in . Monotone convergence [F5] gives for the increasing pointwise limit, so is finite almost everywhere. Since , dominated convergence [F5] gives in , as well as pointwise. Passing the finite reverse-triangle inequality to the limit gives almost everywhere and hence on all of . In particular, for with , in , 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 .
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 and almost everywhere, and the inherited two-sided estimate.
Depends on
- Khintchine's inequality for finite Rademacher sums
- The inhomogeneous dyadic frequency partition and its Littlewood-Paley operators
- Dyadic pieces are uniformly Mihlin multipliers and uniformly Lp-bounded
- The Littlewood-Paley square function
- Rademacher randomisation turns dyadic square functions into random signed multipliers
- Random signed dyadic sums have uniform Mihlin and Lp multiplier bounds
- The Littlewood-Paley reproducing formula in tempered distributions
- The $L^p$ norm is the supremum of pairings against unit $L^q$ functions
- Complex finite-simple and smooth compact-support density for finite p
- Complex Lp completeness and almost-everywhere subsequences
- Dominated convergence
- Monotone convergence for the integral
- Tonelli's theorem for nonnegative measurable functions on a sigma-finite product
- Complex Holder, Minkowski, and the quotient norm
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
Used by
Dependency tree · two levels
89 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Terence Tao, Math 247A Lecture Notes 4 (UCLA, Fall 2006) (standard reference, not scraped)
- Loukas Grafakos, Classical Fourier Analysis, 3rd ed. (Springer GTM 249) (standard reference, not scraped)
- Mark Williams, Notes on Harmonic Analysis (January 11, 2022) (standard reference, not scraped)