Alphabeta Math
TheoremStatement: Literature-sourcedProof: AI-adaptedPipeline-generatedprecheck passjudge pass (gpt-6.1-sol)audited 2026-10-02
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.

The Marcel Riesz conjugate-function theorem on the circle

Statement

Assume Countable Choice and the conventions of Period-one Fourier coefficients, partial sums, and convolution on the torus on the torus T=R/Z with normalized Haar measure m, so that m(T)=1: characters ek(x)=e2πikx, Fourier coefficients f^(k)=∫01f(t)e−2πikt dt, trigonometric polynomials as finite complex linear combinations of characters, and C the conjugate function of Conjugate function on the circle, with Cf^(k)=−isgn⁡(k)f^(k) and sgn⁡(0)=0.

  1. For every 1<p<∞ the operator C extends uniquely from the trigonometric polynomials to a bounded complex-linear operator Cp:Lp(T;C)→Lp(T;C), and the extensions are mutually consistent: Cpf=Cqf almost everywhere for every f∈Lp(T;C)∩Lq(T;C).
  2. Constants lie in the kernel: Cp1=0 for every 1<p<∞.
  3. No compatible endpoint extension exists: there is no bounded operator U:L1(T;C)→L1(T;C) with Up=Cp for every trigonometric polynomial p, and no bounded operator V:L∞(T;C)→L∞(T;C) with Vp=Cp for every trigonometric polynomial p. The failure is of strong-type boundedness; assertions about weak type (1,1), maximal truncations or a bounded mean-oscillation range are not made here.

Facts & Assumptions

Given: Countable Choice; the torus T=R/Z with normalized Haar measure m; the conjugate function C on trigonometric polynomials, Cf^(k)=−isgn⁡(k)f^(k).

[F1]

On trigonometric polynomials C is complex-linear, kills constants and preserves real-valuedness; the characters satisfy eaeb=ea+b and a trigonometric polynomial has only finitely many nonzero Fourier coefficients. Conjugate function on the circle Period-one Fourier coefficients, partial sums, and convolution on the torus

[F2]

For every real mean-zero trigonometric polynomial g one has (Cg)2=g2+2C(gCg). The periodic conjugate square identity for real mean-zero polynomials

[F3]

Parseval: for f,g∈L2(T;C), ∥f∥22=∑k∣f^(k)∣2 and ⟨f,g⟩=∫Tfg‾ dm=∑kf^(k)g^(k)‾, the sums being finite-subset-net limits whose value is also the limit of the symmetric partial sums ∑∣k∣≤N. The Parseval identity for Fourier series

[F4]

Hölder and Minkowski for complex Lp: for conjugate exponents and complex measurable functions, the integral of a product is bounded by the product of the norms, and the norm of a sum by the sum of the norms. Complex Holder, Minkowski, and the quotient norm

[F5]

Cesàro means: σNf=f∗FN; for 1≤p<∞ and f∈Lp(T;C) one has ∥σNf−f∥p→0; for continuous one-periodic f one has sup⁡x∣σNf(x)−f(x)∣→0. Cesaro and Abel means of a Fourier series Fejer means converge in L^p for 1 <= p < infinity Fejer means converge uniformly for continuous periodic functions

[F6]

The Fejér kernel satisfies FN≥0 and ∫01FN=1. The Fejer kernel is a positive approximate identity

[F7]

For one-period integrable f, SNf(x)=∫01f(x−t)DN(t) dt at every x, where DN is real-valued, even and ∫01DN=1. Fourier partial sums are Dirichlet convolutions Dirichlet and Fejer kernels

[F8]

On the continuous periodic functions with the supremum norm, ∥SN:C(T)→C(T)∥=∫01∣DN(t)∣ dt, and for N≥1 this number is at least 13πlog⁡(N+1). Fourier partial-sum operator norm equals the Lebesgue constant

[F9]

For every measure space and 1≤p≤∞ the complex space Lp is complete. Complex Lp completeness and almost-everywhere subsequences

[F10]

Riesz–Thorin: a complex-linear map defined on the complex finite simple functions with finite-measure support which is bounded with constants M0,M1 between Lp0→Lq0 and Lp1→Lq1, 1≤pi<∞, 1<qi<∞, extends uniquely to a bounded operator Lpθ→Lqθ with norm at most M01−θM1θ. Riesz-Thorin interpolation theorem

[F11]

For a finite measure space and 1<p<∞, every bounded complex-linear functional on Lp is integration against a unique h∈Lq with the bilinear pairing, and the norms agree. Complex Lp duality from real Lp duality

[F12]

Norm recovery: for 1≤p<∞ (and p=1 only for sigma-finite measures, which includes T), ∥f∥p=sup⁡{∣∫fg dm∣:∥g∥q≤1}. The Lp norm is the supremum of pairings against unit Lq functions

[F13]

On a finite measure space, ∥f∥p≤m(X)1/p−1/r∥f∥r for 1≤p<r<∞ and ∥f∥p≤m(X)1/p∥f∥∞. Finite-measure Lr includes into Lp for p<r

[F14]

Tonelli/Fubini for L1 functions on sigma-finite product spaces. Fubini's theorem for L^1 functions on a sigma-finite product

Proof

technique · direct
1.1F1F3givenalgebra

Let g be a real mean-zero trigonometric polynomial. By [F3] and the coefficient rule of [F1], ∥Cg∥22=∑k∣Cg^(k)∣2=∑k≠0∣g^(k)∣2=∑k∣g^(k)∣2=∥g∥22, where g^(0)=0 is used in the middle equality; again by [F1], Cg is real-valued with Cg^(0)=0, so Cg is real with zero mean. Moreover [F3] with the coefficient rule gives ∫Tg Cg=∑kg^(k)Cg^(k)‾=i∑ksgn⁡(k)∣g^(k)∣2, which is i times the real number ∑ksgn⁡(k)∣g^(k)∣2; since g Cg is real-valued, its integral is real, so ∫Tg Cg=0 and g Cg is a real mean-zero trigonometric polynomial.

1.2F1givenalgebra

For a trigonometric polynomial h put P+h:=∑k≥0h^(k)ek, and for a∈Z put Mah:=eah. Then P+ is complex-linear, (Mah) ^(k)=h^(k−a) for every k, and for every trigonometric polynomial h and every N≥1 one has SNh=M−NP+MNh−MN+1P+M−(N+1)h. Indeed the definitions and eaeb=ea+b of [F1] give (M−NP+MNh) ^(k)=1{k≥−N}h^(k) and (MN+1P+M−(N+1)h) ^(k)=1{k≥N+1}h^(k) for every k, and subtracting gives 1{∣k∣≤N}h^(k)=SNh^(k) for every k, which identifies the two trigonometric polynomials.

1.3F7F14givenalgebra

For f∈L1(T) and g∈L∞(T), ∫T(SNf)g dm=∫Tf(SNg) dm. Indeed [F7] gives SNf(x)=∫01f(x−t)DN(t) dt and SNg(s)=∫01g(s−u)DN(u) du with DN real and even, so the double integral of ∣f(x−t)DN(t)g(x)∣ is at most ∥f∥1∥g∥∞∥DN∥∞<∞ and [F14] applies; the substitution s=x−t and evenness of DN turn ∫ ⁣ ⁣∫f(x−t)DN(t)g(x) dt dx into ∫f(s)(∫DN(s−x)g(x) dx)ds=∫f(s)SNg(s) ds.

1.4F5F6givenalgebra

For f∈L1(T), each σjf is a trigonometric polynomial with ∥σjf∥1≤∥f∥1 and ∥σjf−f∥1→0; for f∈L∞(T), each σjf is a trigonometric polynomial with ∥σjf∥∞≤∥f∥∞ and ∥σjf−f∥1→0. This is [F5] with p=1 together with [F6]: from Fj≥0 and ∫01Fj=1 one gets ∣σjf∣=∣f∗Fj∣≤∣f∣∗Fj, hence ∥σjf∥1≤∥f∥1 and, for f∈L∞, ∣σjf(x)∣≤∥f∥∞ for every x.

1.5F7givenalgebra

For g∈L1(T) and every real x one has ∣SNg(x)∣≤∥DN∥∞∥g∥1 by [F7], hence ∥SNg∥∞≤∥DN∥∞∥g∥1: on the unit ball of L1, every SN is bounded by ∥DN∥∞.

2.1step 1.1F2F4givenalgebra

Put Am:=sup⁡{∥Cg∥2m/∥g∥2m:g a real mean-zero trigonometric polynomial, g≠0}. Then A1=1 by 1.1, and Am+1≤Am+Am2+1≤2Am+1 for every m≥1, so every Am is finite. Indeed fix m, put p:=2m and let g≠0 be real with zero mean; the square identity [F2], the identification of g Cg as a real mean-zero trigonometric polynomial in 1.1, and the definition of Am give ∥Cg∥2p2=∥(Cg)2∥p≤∥g∥2p2+2∥C(gCg)∥p≤∥g∥2p2+2Am∥g Cg∥p, while [F4] applied with exponents 2,2 to the functions ∣g∣p and ∣Cg∣p gives ∥g Cg∥p≤∥g∥2p∥Cg∥2p. Dividing by ∥g∥2p2>0 and writing u:=∥Cg∥2p/∥g∥2p≥0 yields u2≤1+2Amu, hence u≤Am+Am2+1; taking the supremum over g gives the recursion.

2.2step 1.2step 1.4step 1.5givenalgebra

Suppose a bounded linear V:L∞(T)→L∞(T) satisfies Vp=Cp for every trigonometric polynomial p; put M:=∥V∥ and Af:=12((∫Tf dm)1+f+iVf) for f∈L∞. Then ∥A∥L∞→L∞≤1+12M and Ap=P+p for every trigonometric polynomial p, by 1.2: the multiplier of 12(f+iVf) is 1 on positive frequencies, 0 on negative frequencies and 1/2 at zero, and the half-mean term supplies the remaining 1/2 at zero. For h∈L∞ with ∥h∥∞≤1 let hj:=σjh: by 1.4 these are trigonometric polynomials with ∥hj∥∞≤1 and ∥hj−h∥1→0, and 1.2 gives SNhj=M−NAMNhj−MN+1AM−(N+1)hj because M±ahj is again a trigonometric polynomial on which A acts as P+. Hence ∥SNhj∥∞≤2∥A∥L∞→L∞∥hj∥∞≤2+M, while 1.5 with ∥hj−h∥1→0 gives ∥SNhj−SNh∥∞→0, so ∥SNh∥∞≤2+M. Therefore ∥SN∥L∞→L∞≤2+M for every N, and in particular the continuous functions give ∥SN∥C→C≤2+M.

2.3step 1.3step 1.4F5F6F8givenalgebra

By [F8], ∥SN:C(T)→C(T)∥=∫01∣DN∣≥13πlog⁡(N+1) for every N≥1. Write LN:=∫01∣DN∣. Given δ>0, choose a continuous one-periodic g with ∥g∥∞≤1 and ∥SNg∥∞≥LN−δ/2. Choose x0 with ∣SNg(x0)∣=∥SNg∥∞, let c have modulus one with cSNg(x0)=∣SNg(x0)∣ (take c=1 if this value is zero), and set ψj:=cFj(⋅−x0). Then ∥ψj∥1=1 by [F6], and ∫Tψj(SNg) dm=c σj(SNg)(x0)→∥SNg∥∞ because SNg is continuous and its Cesaro means converge uniformly by [F5]. By pairing symmetry from 1.3 and ∥g∥∞≤1, for all sufficiently large j we have ∥SNψj∥1≥∣∫T(SNψj)g dm∣=∣∫Tψj(SNg) dm∣≥∥SNg∥∞−δ/2≥LN−δ. Since ∥ψj∥1=1, this gives ∥SN∥L1→L1≥LN−δ for every δ>0, hence ∥SN∥L1→L1≥LN≥13πlog⁡(N+1).

3.1step 2.2step 1.2step 1.4step 1.5givenalgebra

Suppose a bounded linear U:L1(T)→L1(T) satisfies Up=Cp for every trigonometric polynomial p; put M:=∥U∥ and define A on L1 by the same formula Af:=12((∫Tf dm)1+f+iUf). Then ∥A∥L1→L1≤1+12M and Ap=P+p for every trigonometric polynomial p, by the frequency check in 2.2. For f∈L1 with ∥f∥1≤1 and its Cesàro means fj=σjf, which are trigonometric polynomials with ∥fj∥1≤1 by 1.4, identity 1.2 gives SNfj=M−NAMNfj−MN+1AM−(N+1)fj and hence ∥SNfj∥1≤2∥A∥L1→L1≤2+M; by 1.5, ∥SNfj−SNf∥1≤∥DN∥∞∥fj−f∥1→0, so ∥SNf∥1≤2+M. Therefore ∥SN∥L1→L1≤2+M for every N.

3.2step 2.2step 2.3given

No bounded V:L∞(T)→L∞(T) satisfies Vp=Cp on trigonometric polynomials: such a V would give ∥SN∥C→C≤2+∥V∥ for every N by 2.2, while ∥SN∥C→C≥13πlog⁡(N+1) grows without bound by 2.3, a contradiction for N large.

3.3step 2.1F4F5F9givenalgebra

For every m≥1 there is a finite constant Km with ∥Cf∥2m≤Km∥f∥2m for every complex trigonometric polynomial f: writing f=Re⁡f+iIm⁡f and applying 2.1 to the real mean-zero parts gives ∥C(Re⁡f)∥2m≤Am∥Re⁡f−Re⁡f‾∥2m≤2Am∥Re⁡f∥2m≤2Am∥f∥2m, and likewise for the imaginary part, so Km:=4Am works; here ∥Re⁡f−Re⁡f‾∥≤2∥Re⁡f∥ uses ∣Re⁡f‾∣≤∥Re⁡f∥1≤∥Re⁡f∥2m and [F4]. Since the trigonometric polynomials are dense in L2m(T;C) by [F5] and that space is complete by [F9], C therefore has a unique extension to a bounded complex-linear operator C(m) on L2m with ∥C(m)∥≤Km; uniqueness holds because two continuous extensions of one map agree on the dense polynomial core.

4.1step 3.1step 2.3given

No bounded U:L1(T)→L1(T) satisfies Up=Cp on trigonometric polynomials: such a U would give ∥SN∥L1→L1≤2+∥U∥ for every N by 3.1, while ∥SN∥L1→L1≥13πlog⁡(N+1) grows without bound by 2.3, a contradiction for N large.

4.2step 1.1step 3.3F1givenalgebra

For all f,g∈L2(T;C) one has ∫T(C(1)f)g dm=−∫Tf(C(1)g) dm for the bilinear pairing. Indeed, for trigonometric polynomials f,g the coefficient identity ∫T(Cf)g=∑kCf^(k)g^(−k) and the rule Cf^(k)=−isgn⁡(k)f^(k) of [F1] give ∫T(Cf)g=−i∑ksgn⁡(k)f^(k)g^(−k)=−∫Tf(Cg), since Cg^(−k)=−isgn⁡(−k)g^(−k)=isgn⁡(k)g^(−k); both pairings are bounded bilinear functionals on L2×L2 (bounded by ∥f∥2∥g∥2 times the norm of C(1)), and they agree on the dense polynomial core, so they agree everywhere.

4.3step 3.3F5F10F13givenalgebra

Let p∈[2,∞). If p=2k, set Cp:=C(k). Otherwise choose m≥1 with 2m<p<2m+1 and let T be C(1) restricted to the complex finite simple functions on T. For r=2m and r=2m+1, approximate a simple function h by trigonometric polynomials in Lr using [F5]; since r≥2 and m(T)=1, [F13] gives convergence in L2 as well. The extensions therefore satisfy C(1)h=C(m)h and C(1)h=C(m+1)h as L2 classes, so T has the endpoint bounds Km,Km+1. Applying [F10] gives an extension Cp with ∥Cp∥≤Km1−θKm+1θ, where 1p=1−θ2m+θ2m+1. It agrees with C on polynomials: uniformly approximate a polynomial P by finite simple functions hj; then Cphj=C(m+1)hj→C(m+1)P=CP in L2m+1, hence in Lp by [F13], while boundedness gives Cphj→CpP in Lp.

5.1step 4.2step 4.3F4F11F12givenalgebra

Let 1<p<2 and q:=pp−1>2, so that 4.3 gives a bounded operator Cq on Lq with norm Kq. For f∈Lp the formula Λf(ψ):=−∫Tf(Cqψ) dm defines a complex-linear functional on Lq, bounded by ∥Λf∥≤Kq∥f∥p because [F4] bounds ∣Λf(ψ)∣≤∥f∥p∥Cqψ∥q≤Kq∥f∥p∥ψ∥q; by [F11] there is a unique h∈Lp with Λf(ψ)=∫Tψh dm for all ψ∈Lq and ∥h∥p=∥Λf∥≤Kq∥f∥p. Put Cpf:=h: then Cp is complex-linear and bounded with ∥Cp∥≤Kq. It extends the polynomial core, because for a trigonometric polynomial f and any ψ∈Lq the defining identity, the consistency of 4.3 and the skew-adjointness of 4.2 give ∫T(Cpf)ψ dm=−∫Tf(Cqψ) dm=−∫Tf(C(1)ψ) dm=∫T(Cf)ψ dm, so Cpf=Cf by the norm recovery [F12] applied to the difference in Lp.

6.1step 3.2step 4.1step 4.3step 5.1F1F5F13given∎

Collecting: for every 1<p<∞ the operator Cp of 4.3 (for p≥2) and of 5.1 (for 1<p<2) is a bounded complex-linear extension of C to Lp(T;C), and it is the only such extension because trigonometric polynomials are dense in Lp for p<∞ and continuous extensions of one map agree on a dense set. If 1<p≤q<∞ and f∈Lp∩Lq, choose trigonometric polynomials ϕk→f in Lq using [F5]; [F13] gives convergence in Lp, and the bounded extensions agree on polynomials, so their images converge to the same Lp limit. Thus Cpf=Cqf. Also Cp1=0 because C kills constants by [F1]. By 3.2 there is no bounded compatible L∞ extension and by 4.1 no bounded compatible L1 extension. This proves all three assertions.

Depends on

Used by

Dependency tree · two levels

99 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