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LeanPool.HighContrastHomogenization.Support.Sobolev.Foundations.CubeCalderonZygmund.HarmonicGradientGainIteration

Coarse-graining support: #

Support.Sobolev.Foundations.CubeCalderonZygmund.HarmonicGradientGainIteration

Imported from the Apache-2.0 CoarseGraining development at commit c7ddd76c08ade64fed1b8d2ca51be14dfee8deb4.

Internal exponent-raising carrier for harmonic gradients #

The declarations in INTERNAL are an induction carrier, not a source-facing Calderón--Zygmund assumption. Its membership field is kept alongside the normalized extended-norm estimate because the next Sobolev step must construct a genuine W^{1,p} witness; finiteness must never be silently reintroduced as a caller hypothesis.

The proved induction carrier for a harmonic-gradient integrability gain. It is deliberately an explicit structure rather than an opaque predicate: its only analytic data are the stated membership and bound, both quantified over all harmonic cube solutions.

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    Euclidean-facing form of the internal carrier. This is the API consumed by vector-valued good-λ arguments; no caller supplies coordinate measurability data.

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      The unraised base of the induction carrier: normalized L² control at depth zero costs exactly one.

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        Convert coordinate gradient gains into a Euclidean gain at the same exponent and depth, multiplying the scalar bound constant by two dimension factors.

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          Lift an inequality between real realizations of finite extended norms back to ℝ≥0∞. All finiteness is explicit, so the induction carrier never turns an extended-norm comparison into an implicit integrability hypothesis.

          theorem HCPolySupport.CubeCalderonZygmund.INTERNAL.sum_fin_le_natCast_mul {d : ℕ} (f : Fin d → ENNReal) (A : ENNReal) (h : ∀ (i : Fin d), f i ≤ A) :
          ∑ i : Fin d, f i ≤ ↑d * A
          theorem HCPolySupport.CubeCalderonZygmund.INTERNAL.row_sum_le_double_sum {d : ℕ} (f : Fin d → Fin d → ENNReal) (i : Fin d) :
          ∑ j : Fin d, f i j ≤ ∑ k : Fin d, ∑ j : Fin d, f k j
          noncomputable def HCPolySupport.CubeCalderonZygmund.INTERNAL.hessianGradCoordToW1p {d : ℕ} {U : Set (Vec d)} {u : H1Function U} (H : HasWeakHessianOn U u) (i : Fin d) (p : FiniteLpExponent) (hvalue : MeasureTheory.MemLp (fun (x : Vec d) => u.grad x i) p.exponent (MeasureTheory.volume.restrict U)) (hgrad : ∀ (j : Fin d), MeasureTheory.MemLp (fun (x : Vec d) => H.hess i j x) p.exponent (MeasureTheory.volume.restrict U)) :

          Package gradient coordinate i as a W^{1,p} function with weak gradient given by Hessian row i, using the supplied L^p membership proofs.

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            The exact depth identity used in the derivative branch of the gain upgrade.

            theorem HCPolySupport.CubeCalderonZygmund.INTERNAL.scaled_row_sum_le_dimension_mul_energy {d : ℕ} (values : Fin d → ENNReal) (energy : Fin d → Fin d → ENNReal) (i : Fin d) {childScale parentScale coefficient A R : ENNReal} (hvalues : ∀ (j : Fin d), values j ≤ coefficient * ∑ k : Fin d, energy i k) (hscale : childScale ≤ parentScale) (henergy : parentScale * ∑ a : Fin d, ∑ b : Fin d, energy a b ≤ A * R) :
            childScale * ∑ j : Fin d, values j ≤ ↑d * coefficient * A * R
            noncomputable def HCPolySupport.CubeCalderonZygmund.INTERNAL.HarmonicGradientGain.upgrade {d : ℕ} (hd : 0 < d) {r q : FiniteLpExponent} (hqr : q.exponent.toReal⁻¹ = r.exponent.toReal⁻¹ - (↑d)⁻¹) (hrlt : r.exponent.toReal < ↑d) {depth : ℕ} (G : HarmonicGradientGain d r depth) :
            HarmonicGradientGain d q (depth + 1)

            One source-faithful Sobolev step in the internal harmonic-gradient iteration. The derivative harmonicity and Hessian witness are both produced inside the proof; callers supply only the preceding gain carrier.

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              Lowering the exponent on a probability-normalized cube preserves an internal gain carrier without changing its analytic constant.

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              • G.downgrade hsr = { constantValue := G.constantValue, constant_pos := ⋯, constant_ne_top := ⋯, memLp := ⋯, bound := ⋯ }
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                noncomputable def HCPolySupport.CubeCalderonZygmund.INTERNAL.sobolevLadderExponent (d : ℕ) (hd : 2 ≤ d) (n : ℕ) (hn : 2 * n < d) :

                The explicit finite Sobolev ladder used above the L² base. The side condition is precisely the positivity of its denominator.

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                  Iterate the harmonic gradient Sobolev gain from L² to exponent 2 * d / (d - 2 * n) at depth n, for d ≥ 3 and 2 * n < d.

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                    The finite source exponent d * q / (d + q) whose Sobolev conjugate is the target q, for dimension at least two and target exponent greater than two.

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                      In dimension two, one final finite Sobolev step from the downgraded L² base reaches every target above two.

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                        Construct the Euclidean harmonic gradient gain at depth one in dimension two for any finite target exponent greater than two.

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                          The final Sobolev step from the terminal ladder exponent.

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                            Every finite target exponent is reached in dimension at least three.

                            Vector-facing arbitrary finite target gain in dimensions at least three. Its membership and bound are in the HilbertVec.ofVec representation used by the stopping-time layer; all coordinate measurability is discharged inside fromScalar.

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                              Vector-facing normalized L^q gain for every target at or below L².

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                                Dimension-at-least-two public availability statement for the Euclidean gain API. It is deliberately Nonempty Σ because the depth is analytic data of the construction, not a hypothesis that callers must provide.

                                One-dimensional finite-target carrier, obtained from the source theorem's real bound only after the accompanying source-level MemLp witness has made both ENNReal sides finite.

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                                  Construct the Euclidean harmonic gradient gain at depth one in dimension one for any finite target exponent.

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                                    All positive dimensions now expose the Euclidean finite-target carrier. The depth is returned as construction data, not a caller hypothesis.