Alphabeta Math
ExampleConstruction: Literature-sourcedVerification: AI-adaptedPipeline-generated
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 method of continuity on a constant-coefficient one-dimensional path

Example

Assume Countable Choice and fix 0<α<1. Let Ω=(0,π), X:={u∈C2,α([0,π]):u(0)=u(π)=0}, Y:=C0,α([0,π]) and, for c>0 and t∈[0,1], Ltu:=−u′′−tc u. Then every Lt is a bounded operator X→Y, L0=−d2/dx2 is bijective, and the bijectivity set is I={t∈[0,1]:tc∉{k2:k≥1}}: for tc<1 the eigenfunction expansion u(x)=∑k≥1fkk2−tcsin⁡(kx),fk=2π∫0πf(x)sin⁡(kx) dx, converges absolutely and uniformly together with its first derivative, defines an element of X with Ltu=f and obeys the uniform bound ∥u∥C2,α≤C(1−tc)−1∥f∥C0,α, while at tc=k02 the kernel is spanned by sin⁡(k0x) and the range is the proper closed subspace {f:∫0πf(x)sin⁡(k0x) dx=0}. In this model one computes directly that I is open in [0,1], that I is relatively closed on every subinterval on which all the operators are injective, and that the uniform estimate fails on every interval that meets the spectrum.

Facts & Assumptions

Given: Countable Choice, 0<α<1, c>0, t∈[0,1], the spaces X={u∈C2,α([0,π]):u(0)=u(π)=0} and Y=C0,α([0,π]), and Ltu=−u′′−tcu.

[A1]

The only choice assumption is Countable Choice ACω; all series and subsequences below are countable and no further selection is made. (The Axiom of Countable Choice (ACω))

[F1]

The norms on X and Y are the usual ones: ∥u∥C2,α=sup⁡∣u∣+sup⁡∣u′∣+sup⁡∣u′′∣+[u′′]0,α and ∥f∥C0,α=sup⁡∣f∣+[f]0,α with [g]0,α=sup⁡x≠y∣g(x)−g(y)∣/∣x−y∣α. (Hölder spaces Ck,α, closure and interior scaled norms, and Ck,α domains)

[F2]

The functions ek(x):=sin⁡(kx), k≥1, satisfy ek(0)=ek(π)=0, −ek′′=k2ek, and ∫0πej(x)ek(x) dx=π2δjk; these are the classical eigenpairs of −d2/dx2 with Dirichlet conditions on (0,π). For the odd 2π-periodic extension F, translation by h gives ∥F(⋅+h)−F∥L1(−π,π)≤C([f]αhα+∥f∥∞h): away from endpoint jumps use Hölder continuity, and the jump-crossing strips have length O(h). With h=π/k, the exponential Fourier coefficient identity ∣eikh−1∣ ∣F^(k)∣≤(2π)−1∥F(⋅+h)−F∥1 gives ∣F^(k)∣≤Cα∥f∥C0,αk−α. The sine coefficients fk=2π∫0πf(x)sin⁡(kx) dx of an f∈C0,α([0,π]) satisfy ∣fk∣≤Cα∥f∥C0,αk−α, and Dini pointwise convergence criterion for Fourier series, after rescaling to period one, gives ∑k≥1fksin⁡(kx)=f(x) for every x∈(0,π) (the local Dini integral is bounded by C[f]α∫0δsα−1ds). The L2 convergence follows separately from Fourier series converge in mean square applied to the odd extension. (Hölder spaces Ck,α, closure and interior scaled norms, and Ck,α domains)

[F3]

If g∈C0([0,π]) then Sg(x):=−∫0x(x−s)g(s) ds+xπ∫0π(π−s)g(s) ds lies in C2([0,π]), vanishes at 0 and π, satisfies (Sg)′′=−g, and obeys ∥Sg∥C2≤C0∥g∥C0 with [Sg′′]0,α=[g]0,α for g∈Y; this is the explicit Dirichlet solution of the one-dimensional Poisson problem, obtained by differentiating twice under the integral sign.

[F4]

Uniform derivative limits: if uN:[0,π]→R is C1 for every N, uN converges at one point, and uN′→v uniformly, then uN→u uniformly for a differentiable u with u′=v; applied twice it gives: if uN→u uniformly, uN′→u′ uniformly and uN′′→u′′ uniformly, then u∈C2([0,π]) with those derivatives. (If continuously differentiable functions converge at one point and their derivatives converge uniformly on a closed interval, then the functions converge uniformly to a differentiable function whose derivative is the derivative limit)

[F5]

The abstract method-of-continuity theorem assumes a uniform a priori estimate and Countable Choice (The method of continuity for a uniformly estimated affine family of bounded operators).

[F6]

The global Schauder solvability theorem is the PDE-level version of the continuity argument (Global Schauder estimate and classical Dirichlet solvability by the continuity method).

[F7]

Classical derivatives agree with distributional derivatives under the assumed Countable Choice; distributional differentiation is continuous in the distribution topology (Distributional derivative, Distributional differentiation is continuous and commutes).

[F8]

On the bounded interval, L2 convergence implies local L1 convergence by Cauchy--Schwarz, and locally L1 convergence gives convergence of the associated regular distributions (Locally integrable functions embed in distributions).

[F9]

A distribution on the connected interval (0,π) whose derivative vanishes is a constant regular distribution; this result uses Countable Choice for the regular-distribution convention (A distribution with zero derivatives on a connected open set is constant).

Verification

technique · direct
1.1F1F3givenalgebraA1

The operators and the base point. For u∈X one has ∥Ltu∥C0,α≤∥u′′∥C0,α+tc∥u∥C0,α≤C(α,π)(1+c)∥u∥C2,α, so Lt maps X boundedly into Y for every t. For t=0, L0=−d2/dx2: if −u′′=0 with u(0)=u(π)=0 then u is affine and vanishes at both endpoints, so u=0 (injectivity); and for every f∈Y the explicit function Sf of [F3] satisfies −Sf′′=f, vanishes at the endpoints, and obeys ∥Sf∥C2,α≤C∥f∥C0,α, so L0Sf=f (surjectivity). Hence L0 is bijective.

1.2F2givenalgebra

The eigenvalue picture. By [F2], Ltek=(k2−tc)ek. For any u∈X, two integrations by parts, using u=ek=0 at both endpoints, give ∫0π(Ltu)ek=(k2−tc)∫0πuek. If Ltu=0, all sine coefficients of u vanish when tc is not a square; if tc=k02, all except the k0th vanish. Since u∈C0,α, the Fourier identity in [F2] then gives u=0 in the first case and u∈span⁡{ek0} in the second. Thus Lt is injective exactly off the displayed spectrum, and its kernel at a spectral parameter is exactly span⁡{ek0}.

1.3F2F4givenalgebra

The Fourier solution away from resonance, including the coercive range. Fix f∈Y. If tc=k02, assume fk0=0 and set ck0=0; for every k∈J:={k≥1:k2≠tc} set ck=fk/(k2−tc). In the non-resonant case this defines every ck. In either case m:=inf⁡k∈J∣k2−tc∣/k2>0, because the ratios tend to 1 and none of the finitely many remaining ratios is zero. Put uN=∑k≤Ncksin⁡(kx). The coefficient bound in [F2] gives ∣ck∣≤Cαm−1∥f∥C0,αk−2−α and k∣ck∣≤Cαm−1∥f∥C0,αk−1−α. Thus only the series for uN and uN′ are asserted to converge absolutely and uniformly; [F4] gives a limit u∈C1([0,π]) with zero endpoint values. For tc<1 one has m≥1−tc, giving the stated coercive-range bound. To see u∈C0,α, write d=∣x−y∣. For 0<d<1, split ∑k∣ck∣min⁡(2,kd) at k≤d−1: the low-frequency part is at most Cm−1∥f∥d∑k≤d−1k−1−α≤Cm−1∥f∥d, and the high-frequency part is at most Cm−1∥f∥∑k>d−1k−2−α≤Cm−1∥f∥d1+α. For 1≤d≤π, the supremum bound gives the same Cm−1∥f∥dα control. Hence [u]0,α≤Cm−1∥f∥C0,α.

2.1step 1.3F2F7F8F9givenalgebra

Identify the equation and upgrade regularity. Put fN=∑k≤Nfksin⁡(kx). At a resonance the omitted coefficient is zero by hypothesis, so for every sufficiently large N the partial-sum identity is still uN′′=−fN−tcuN. By [F2], fN→f in L2(0,π), while uN→u uniformly; hence uN′′→g:=−f−tcu in L2. Since also uN→u in L2, continuity of distributional differentiation and the regular-function embedding in [F7--F8] show u′′=g distributionally on (0,π). The function g is continuous. Set G(x)=∫0xg(s) ds; then the distributional derivative of the continuous function u′−G is zero. By [F9], u′−G is a constant distribution, hence equals that constant pointwise; therefore u∈C2([0,π]) (with one-sided endpoint derivatives) and u′′=g. Since u∈C0,α by step 1.3 and f∈C0,α, g=−f−tcu∈C0,α, so u∈X and Ltu=f.

3.1step 1.2step 1.3step 2.1givenalgebra

The range at a spectral parameter. If tc=k02, integration by parts as in step 1.2 gives ∫0π(Ltu)ek0=0 for every u∈X, so the range lies in the proper closed hyperplane {f∈Y:fk0=0}. Conversely, for any f in that hyperplane, steps 1.3 and 2.1 construct u∈X with Ltu=f; thus this hyperplane is exactly the range. Moreover, the inverse norm of Lt on its bijective parameters blows up near t0:=k02/c: for t≠t0, testing on ek0 gives ∥Ltek0∥C0,α=∣k02−tc∣ ∥ek0∥C0,α and hence ∥Lt−1∥≥∥ek0∥X/(∣k02−tc∣ ∥ek0∥Y)→∞ as t→t0.

3.2step 1.2step 1.3step 2.1F1givenalgebra

Estimate in the coercive range. For tc<1, m≥1−tc in step 1.3, so the sup and Hölder bounds there control ∥u∥C0,α and ∥u′∥∞ by C(1−tc)−1∥f∥C0,α. From step 2.1, u′′=−f−tcu, hence ∥u′′∥C0,α≤C(1−tc)−1∥f∥C0,α. Thus ∥u∥C2,α≤C(1−tc)−1∥f∥C0,α. Uniqueness follows from step 1.2; in particular Lt is bijective for every non-spectral parameter, while this is the stated quantitative estimate on the coercive range.

4.1step 1.2step 2.1step 3.1F5givenalgebra

The two continuity properties of the bijectivity set. By steps 1.2 and 2.1, I=[0,1]∖{k2/c:k2≤c} is exactly the bijectivity set. Its complement is finite, so I is open in [0,1]. Every subinterval J⊆[0,1] on which all Lt are injective contains no spectral parameter by step 1.2, hence I∩J=J is relatively closed in J. These are the two properties inspected in the abstract method of continuity [F5]. At a spectral parameter the inverse norms on neighboring bijective parameters blow up as in step 3.1, so no a priori estimate uniform across that parameter can hold.

5.1step 1.2step 2.1step 3.1step 3.2step 4.1F5F6∎

Conclusion. The model family Ltu=−u′′−tcu on (0,π) is bounded X→Y for every t, has the bijective base point L0=−d2/dx2, and has bijectivity set I={t:tc∉{k2:k≥1}}. For tc<1 the eigenfunction expansion gives the inverse bound C(1−tc)−1; at tc=k02 the kernel is span⁡{sin⁡(k0x)} and the range is the closed hyperplane orthogonal to it. Openness and the relative-closedness property hold by direct inspection of the finite exceptional set. This one-dimensional example illustrates the abstract method of continuity [F5] and its PDE-level application [F6].

Remarks

  • The example isolates the two ingredients of the method of continuity: a uniform inverse bound holds on compact parameter sets a positive distance from the spectrum; an open interval can avoid resonance while approaching it, in which case the inverse norm still diverges, and the base point t=0 is bijective. The exceptional parameters are the zeros of k2−tc, where the inverse norm blows up like 1/∣k2−tc∣.
  • The coefficient decay ∣fk∣≤C∥f∥C0,αk−α is the only analytic input; it is exactly what makes ∑k−1−α and the splitting estimate for the H"older seminorm of u converge, and this absolute-summability argument does not apply at α=0. For continuous forcing off resonance, direct integration of the ODE is an alternative route.

Depends on

Used by

Nothing in the library uses this result yet.

Dependency tree · two levels

83 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