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.
- constantValue : ENNReal
The positive finite factor bounding each gradient coordinate in normalized
L^rby the sum of the parent cube coordinateL²norms. - memLp (Q : TriadicCube d) (u : H1Function (openCubeSet Q)) : (WeakPoissonEquationOn (openCubeSet Q) u fun (x : Vec d) => 0) → ∀ (i : Fin d), MeasureTheory.MemLp (fun (x : Vec d) => u.grad x i) r.exponent (normalizedCubeMeasure (centralDescendant Q depth))
- bound (Q : TriadicCube d) (u : H1Function (openCubeSet Q)) : (WeakPoissonEquationOn (openCubeSet Q) u fun (x : Vec d) => 0) → ∀ (i : Fin d), MeasureTheory.eLpNorm (fun (x : Vec d) => u.grad x i) r.exponent (normalizedCubeMeasure (centralDescendant Q depth)) ≤ self.constantValue * ∑ j : Fin d, MeasureTheory.eLpNorm (fun (x : Vec d) => u.grad x j) 2 (normalizedCubeMeasure Q)
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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.
- constantValue : ENNReal
The finite factor bounding the Euclidean gradient in normalized
L^rby the sum of the parent cube coordinateL²norms. - memLp (Q : TriadicCube d) (u : H1Function (openCubeSet Q)) : (WeakPoissonEquationOn (openCubeSet Q) u fun (x : Vec d) => 0) → MeasureTheory.MemLp (fun (x : Vec d) => HilbertVec.ofVec (u.grad x)) r.exponent (normalizedCubeMeasure (centralDescendant Q depth))
- bound (Q : TriadicCube d) (u : H1Function (openCubeSet Q)) : (WeakPoissonEquationOn (openCubeSet Q) u fun (x : Vec d) => 0) → MeasureTheory.eLpNorm (fun (x : Vec d) => HilbertVec.ofVec (u.grad x)) r.exponent (normalizedCubeMeasure (centralDescendant Q depth)) ≤ self.constantValue * ∑ j : Fin d, MeasureTheory.eLpNorm (fun (x : Vec d) => u.grad x j) 2 (normalizedCubeMeasure Q)
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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.
Equations
- HCPolySupport.CubeCalderonZygmund.INTERNAL.HarmonicEuclideanGradientGain.fromScalar G = { constantValue := ‖↑d‖ₑ * ↑d * G.constantValue, constant_ne_top := ⋯, memLp := ⋯, bound := ⋯ }
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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.
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.
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.
Equations
- G.downgrade hsr = { constantValue := G.constantValue, constant_pos := ⋯, constant_ne_top := ⋯, memLp := ⋯, bound := ⋯ }
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The explicit finite Sobolev ladder used above the L² base. The side
condition is precisely the positivity of its denominator.
Equations
- HCPolySupport.CubeCalderonZygmund.INTERNAL.sobolevLadderExponent d hd n hn = { exponent := ENNReal.ofReal (2 * ↑d / (↑d - 2 * ↑n)), one_lt := ⋯, lt_top := ⋯ }
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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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- HCPolySupport.CubeCalderonZygmund.INTERNAL.harmonicGradientGainLadder d hd 0 hn = ⋯.mpr (HCPolySupport.CubeCalderonZygmund.INTERNAL.harmonicGradientGainL2DepthZero 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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- One or more equations did not get rendered due to their size.
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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.