Local slow-order recursion from actual lower profiles #
The source algebra consists of genuine smooth, even radial functions with holomorphic parameter dependence. No preconstructed all-order jet family is assumed.
Actual positive-order axis solutions #
This module connects the sparse six-component Volterra construction to the explicit positive-order system, and to smooth profiles in the squared radius. All existence assertions are obtained from the actual convergent series.
Cache the standard NormedAddCommGroup (Matrix (Fin 6) (Fin 6) ℂ) instance to shorten
typeclass synthesis.
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Cache the standard NormedSpace ℝ (Matrix (Fin 6) (Fin 6) ℂ) instance to shorten typeclass
synthesis.
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Cache the standard NormedSpace ℂ (Matrix (Fin 6) (Fin 6) ℂ) instance to shorten typeclass
synthesis.
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The right side of the actual integral equation is radially continuous; the parameter derivative is supplied by the proved disk-space bootstrap.
The actual symmetric solution has the regular, nonsingular derivative formula at every interior radius, including the axis.
The singular first-order equation holds with genuine derivatives at every nonzero interior radius.
The standard matrix representation, as an actual bounded operator on the six-component space.
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Packaging the actual radial matrix coefficient in the compact path space.
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- NavierStokes.PositiveAxisExistence.matrixPath R A = NavierStokes.CompactSmoothFamily.family (Set.Icc (-R) R) fun (p : ℂ × ℝ) => NavierStokes.PositiveAxisExistence.matrixOperator (A p.2 p.1)
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Packaging the actual forcing in the compact path space.
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- NavierStokes.PositiveAxisExistence.forcingPath R f = NavierStokes.CompactSmoothFamily.family (Set.Icc (-R) R) fun (p : ℂ × ℝ) => f p.2 p.1
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Smoothness and parameter holomorphy of the given coefficients. These are hypotheses only on input functions.
- smooth : VolterraRegularity.SmoothCoefficientData T U A₀ A₁ f
- zeroth_holomorphic (r : ℝ) : r ∈ VolterraRegularity.radialDomain T → DifferentiableOn ℂ (A₀ r) U
- first_holomorphic (r : ℝ) : r ∈ VolterraRegularity.radialDomain T → DifferentiableOn ℂ (A₁ r) U
- forcing_holomorphic (r : ℝ) : r ∈ VolterraRegularity.radialDomain T → DifferentiableOn ℂ (f r) U
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The actual canonical solution for raw matrix coefficients.
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The disk-valued radial bootstrap and the Cauchy integral combine to give joint real smoothness, rather than merely separate smoothness.
Transparent regularity assumptions on the eleven finite lower-order
input functions. Smoothness is required of the signed square pullback, so
there is no artificial requirement on a negative-X extension.
- denominator (z : ℂ) : z ∈ U → PositiveAxisSystem.ell h z ≠ 0
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The concrete series solution for the explicit positive-order matrices.
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Real radial component, given by (W p.2 (p.1 : ℂ) i).re.
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- NavierStokes.PositiveAxisExistence.realRadialComponent W i p = (W p.2 (↑p.1) i).re
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Actual profiles, with the physical coordinate order (X,eta).
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Real base, given by ⟨⟨G 0 p, G 1 p, 0, G 2 p⟩, ⟨G 3 p, G 4 p, 0, G 5 p⟩, G 6 p⟩.
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Real source, given by ⟨G 7 p, G 8 p, G 9 p, G 10 p⟩.
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- NavierStokes.PositiveAxisExistence.realSource G p = { angular := G 7 p, axial := G 8 p, pressureProduct := G 9 p, omegaQuotient := G 10 p }
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The complex inputs restrict to the given real finite input jets on the
positive physical domain. Their smooth radial extension supplies the axis
limits, without referring to ordinary derivatives of a negative-X continuation.
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The genuine real first-order system, with all six ordinary derivatives.
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The first two rows recover the radial derivative coordinates without using the input jets.
The last two Volterra components are the actual radial derivatives of the first two descended profiles; they are not independent jet variables.
The recovered profiles solve the true differentiated system.
The eleven real inputs are computed from the given lower-order history.
The unknown order is not used in the finite source, as proved separately by
actualLowerSource_update.
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New beta, defined pointwise by betaValue h (slowPower h n) w.2 (actualJet u w) (actualJet k w).
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The original positive-order convolution equations evaluated on the history after inserting the newly constructed profiles.
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A competing solution is given by actual holomorphic continuous paths on the positive and reflected negative radial intervals.
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Candidate lift, constructed using glue.
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Actual uniqueness in the holomorphic continuous-path class. It is deduced from the decaying Volterra-word majorant, with no norm smallness.
The actual positive-order output: a smooth symmetric six-component field, its physical squared-radius profiles, and their exact equations and axis jets. Uniqueness is stated separately below.
- integral : VolterraParity.IsSymmetricIntegralSolution R U (PositiveAxisSystem.coefficient0 (↑h) (↑(PositiveAxisSystem.slowPower h n)) (↑C) F) (PositiveAxisSystem.coefficient1 (↑h) F) (PositiveAxisSystem.sourceField (↑h) (↑C) F) W
- smooth : ContDiffOn ℝ (↑⊤) (fun (p : ℝ × ℂ) => W p.1 p.2) (VolterraRegularity.radialDomain R ×ˢ U)
- equation (r : ℝ) : r ∈ VolterraRegularity.radialDomain R → r ≠ 0 → ∀ z ∈ U, ∀ (i : Fin 6), deriv (fun (s : ℝ) => W s z i) r + (↑(VolterraAnalyticBounds.exponent i) / r) • W r z i = NilpotentVolterra.equationRHS (PositiveAxisSystem.coefficient0 (↑h) (↑(PositiveAxisSystem.slowPower h n)) (↑C) F) (PositiveAxisSystem.coefficient1 (↑h) F) (PositiveAxisSystem.sourceField (↑h) (↑C) F) W r z i
- profiles_smooth (i : Fin 6) : ↑i < 4 → ContDiffOn ℝ (↑⊤) (xProfile W i) (Set.Ico 0 (R ^ 2) ×ˢ realParameterDomain U)
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Concrete positive-order existence from smooth radial, holomorphic parameter input jets of the lower history. No solution, convergence, positive-order equation, or output smoothness is an input assumption.
Uniqueness for the same explicit lower-data problem, for any competing pair of actual holomorphic continuous-path integral solutions.
Radial divisibility and regular slow-order sources #
This module removes the apparent 1/X singularities in the radial source
of equation (22), using the actual differential operators from SimilarityProfile.
Axis factor, given by w.1 * v w.
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- NavierStokes.AxisSourceRegularity.axisFactor v w = w.1 * v w
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Factoring out X shifts the similarity exponent by one.
Z2, given by Z h (b - D h) (Z h b v).
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Slow order, given by 2 * (k : ℝ) * h.
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- NavierStokes.AxisSourceRegularity.slowOrder h k = 2 * ↑k * h
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Shifted axial as an element of ℕ → InnerProfile | 0 => fun _ => 0 | k + 1 => Z2 h (slowOrder h k) (V k).
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Shifted axial factor as an element of ℕ → InnerProfile | 0 => fun _ => 0 | k + 1 => Z2 h (slowOrder h k - 1) (v k).
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The displayed Ω_k source before canceling its radial factor.
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An explicit expression for Ω_k/X with no division by X.
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Every term in the actual finite Ω_k source has the factor X.
The quotient formula is smooth at the axis, using only the finite input profiles occurring at this order. No division by the radial coordinate remains.
Joint analytic input germs give an analytic quotient germ, including at X=0.
Explicit finite jets and parameter-analytic source formulas #
Jet2 data, collecting value, dx, de, dxx, dxe, dex and their compatibility
conditions.
- value : K
Value of
Jet2, of typeK. - dx : K
Dx of
Jet2, of typeK. - de : K
De of
Jet2, of typeK. - dxx : K
Dxx of
Jet2, of typeK. - dxe : K
Dxe of
Jet2, of typeK. - dex : K
Dex of
Jet2, of typeK. - dee : K
Dee of
Jet2, of typeK.
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Profile jet, bundling value, dx, de, dxx and the required compatibility proofs.
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Jet L, given by 1 - 2 * h * e ^ 2.
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Jet Z numerator E, given by `2 * b * j.value + 2 * e * b * j.de - 2 * e * j.de + (1 - e ^ 2)
- j.dee - 2 * X * j.dx - 2 * e * X * j.dxe`.
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Jet Z, given by jetZNumerator b X e j / jetL h e.
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Jet ZX, given by jetZNumeratorX b X e j / jetL h e.
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Jet ZE, given by (jetZNumeratorE b X e j * jetL h e + 4 * h * e * jetZNumerator b X e j) / jetL h e ^ 2.
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Jet Z2, given by (2 * e * (b - (1 / 2 - h)) * jetZ h b X e j + (1 - e ^ 2) * jetZE h b X e j - 2 * e * X * jetZX h b X e j) / jetL h e.
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Jet shifted as an element of ℕ → K | 0 => 0 | k + 1 => jetZ2 h (2 * (k : K) * h - 1) X e (v k).
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- NavierStokes.AxisSourceRegularity.jetShifted h X e v 0 = 0
- NavierStokes.AxisSourceRegularity.jetShifted h X e v k.succ = NavierStokes.AxisSourceRegularity.jetZ2 h (2 * ↑k * h - 1) X e (v k)
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The same regular source formula over any field, so complex parameter extensions use precisely the algebra verified for the real profile derivatives.
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Holomorphic extensions of the seven actual input jets. This is stronger than separate analyticity of v alone and is the precise parameter hypothesis used.
- value : AnalyticAt ℂ (fun (z : ℂ) => (J z).value) e
- dx : AnalyticAt ℂ (fun (z : ℂ) => (J z).dx) e
- de : AnalyticAt ℂ (fun (z : ℂ) => (J z).de) e
- dxx : AnalyticAt ℂ (fun (z : ℂ) => (J z).dxx) e
- dxe : AnalyticAt ℂ (fun (z : ℂ) => (J z).dxe) e
- dex : AnalyticAt ℂ (fun (z : ℂ) => (J z).dex) e
- dee : AnalyticAt ℂ (fun (z : ℂ) => (J z).dee) e
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The finite quotient source is holomorphic in the parameter whenever the finite input jets have holomorphic extensions and the sole denominator is nonzero.
The first-order jet time formula commutes with the real inclusion.
The first-order jet axial formula commutes with the real inclusion.
The second-order jet axial formula commutes with the real inclusion.
The holomorphic algebra uses the exact real source formula on real inputs.
Lower pairs, given by (Finset.antidiagonal n).filter (fun ij => 0 < ij.1 ∧ 0 < ij.2).
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- NavierStokes.AxisSourceRegularity.lowerPairs n = {ij ∈ Finset.antidiagonal n | 0 < ij.1 ∧ 0 < ij.2}
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Lower convolution, given by ∑ ij ∈ lowerPairs n, a ij.1 w * b ij.2 w.
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- NavierStokes.AxisSourceRegularity.lowerConvolution a b n w = ∑ ij ∈ NavierStokes.AxisSourceRegularity.lowerPairs n, a ij.1 w * b ij.2 w
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Previous omega div X as an element of ℕ → InnerProfile | 0 => fun _ => 0 | k + 1 => omegaDivX h U v k.
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The known lower-order pressure source after its radial cancellation.
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The regular lower-order source agrees with the displayed pressure source away from the axis.
Jet previous omega as an element of ℕ → K | 0 => 0 | k + 1 => jetOmegaDivX h X e U v k.
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- NavierStokes.AxisSourceRegularity.jetPreviousOmega h X e U v 0 = 0
- NavierStokes.AxisSourceRegularity.jetPreviousOmega h X e U v k.succ = NavierStokes.AxisSourceRegularity.jetOmegaDivX h X e U v k
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Parameter-analytic algebra for the same finite lower pressure source.
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Only previously constructed profiles, indexed strictly below n, are needed for holomorphy of the known source at order n.
The other finite lower-order transport sources #
Shifted profile axial as an element of ℕ → InnerProfile | 0 => fun _ => 0 | k + 1 => Z2 h (b + slowOrder h k) (f k).
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The finite known transport part of the angular row has σ=1, and that of the axial row has σ=0. The base exponents b are supplied separately.
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Jet shifted profile axial as an element of ℕ → K | 0 => 0 | k + 1 => jetZ2 h (b + 2 * (k : K) * h) X e (f k).
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- NavierStokes.AxisSourceRegularity.jetShiftedProfileAxial h b X e f 0 = 0
- NavierStokes.AxisSourceRegularity.jetShiftedProfileAxial h b X e f k.succ = NavierStokes.AxisSourceRegularity.jetZ2 h (b + 2 * ↑k * h) X e (f k)
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Raw: an abbreviation for ℝ × ℂ → ℂ.
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The induction class for actual scalar radial profiles.
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The class is an actual real algebra of functions.
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- NavierStokes.SlowRecursion.instCoeFunAxisFunctionRaw = { coe := fun (F : NavierStokes.SlowRecursion.AxisFunction R U) => ↑F }
Real constant, given by algebraMap ℝ (AxisFunction R U) c.
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Squared radius as an element of AxisFunction R U.
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Restrict as an element of AxisFunction S U.
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- NavierStokes.SlowRecursion.restrict hSR F = ⟨↑F, ⋯⟩
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Inverse as an element of AxisFunction R U.
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Radial derivative as an element of AxisFunction R U.
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- NavierStokes.SlowRecursion.radialDerivative hR hU F = ⟨fun (p : ℝ × ℂ) => NavierStokes.BoundaryAxisJets.radialJet (↑F) 1 p.1 p.2, ⋯⟩
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Parameter derivative as an element of AxisFunction R U.
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Reflection gives a holomorphic extension of the actual real trace.
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- NavierStokes.SlowRecursion.realSymmetrization F p = (F p + (starRingEnd ℂ) (F (p.1, (starRingEnd ℂ) p.2))) / 2
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Symmetrize as an element of AxisFunction R U.
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- NavierStokes.SlowRecursion.symmetrize hU hconj F hs hh he = ⟨NavierStokes.SlowRecursion.realSymmetrization F, ⋯⟩
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Fixed geometric data for one analytic parameter neighborhood.
- open_set : IsOpen U
- conjugate (z : ℂ) : z ∈ U → (starRingEnd ℂ) z ∈ U
- denominator (z : ℂ) : z ∈ U → PositiveAxisSystem.ell (↑h) z ≠ 0
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Denominator function, given by 1 - realConstant R U (2 * h) * parameter R U ^ 2.
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Inverse denominator, given by inverse (denominatorFunction R U h) (fun p hp => by rw [denominatorFunction_apply] exact c.denominator p.2 hp.2).
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Time operator as an element of AxisFunction R U.
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Axial operator as an element of AxisFunction R U.
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Prior diffusion, with branches according to n = 0.
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Shifted beta diffusion used in slow recursion.
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- NavierStokes.SlowRecursion.shiftedBetaDiffusion c F 0 = 0
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Radial source, constructed using timeOperator.
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Previous radial source as an element of ℕ → AxisFunction R U | 0 => 0 | k + 1 => radialSource c u beta k.
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- NavierStokes.SlowRecursion.previousRadialSource c u beta 0 = 0
- NavierStokes.SlowRecursion.previousRadialSource c u beta k.succ = NavierStokes.SlowRecursion.radialSource c u beta k
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Angular source as an element of AxisFunction R U.
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Axial source as an element of AxisFunction R U.
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Pressure product, given by ∑ i ∈ Finset.range (n - 1), phi (i + 1) * phi (n - (i + 1)).
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- NavierStokes.SlowRecursion.pressureProduct phi n = ∑ i ∈ Finset.range (n - 1), phi (i + 1) * phi (n - (i + 1))
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Each of the eleven inputs is an actual member of the smooth function algebra; their regularity follows by construction from the lower profiles.
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Source data, defined pointwise by complexProfile (sourceFunctions c phi u beta n i).
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- NavierStokes.SlowRecursion.sourceData c phi u beta n i = NavierStokes.SlowRecursion.complexProfile (NavierStokes.SlowRecursion.sourceFunctions c phi u beta n i)
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Beta operator as an element of AxisFunction R U.
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Coefficient: an abbreviation for Fin 5 → AxisFunction R U.
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Step raw, constructed using PositiveAxisExistence.positiveSolution.
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Step component as an element of AxisFunction S U.
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- NavierStokes.SlowRecursion.stepComponent c hS hSR C n F i hi = NavierStokes.SlowRecursion.symmetrize ⋯ ⋯ (fun (p : ℝ × ℂ) => NavierStokes.SlowRecursion.stepRaw c hS C n F p.1 p.2 i) ⋯ ⋯ ⋯
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One actual inductive step. The first four profiles come from the convergent Volterra solution; the fifth is the genuine divergence formula.
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Buffer radii approach a fixed positive core without ever reaching it.
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- NavierStokes.SlowRecursion.radius core buffer n = core + buffer / (↑n + 1)
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Only coefficients with index below n are accessed. The zero branch
is outside every finite source sum and is not an assumed future coefficient.
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- NavierStokes.SlowRecursion.lowerHistory hbuffer n previous j = if hj : j < n then fun (i : Fin 5) => NavierStokes.SlowRecursion.restrict ⋯ (previous j hj i) else 0
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Recursion step used in slow recursion.
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- NavierStokes.SlowRecursion.recursionStep c hcore hbuffer C base 0 x_2 = base
- NavierStokes.SlowRecursion.recursionStep c hcore hbuffer C base n.succ previous = NavierStokes.SlowRecursion.step ⋯ ⋯ ⋯ C (n + 1) (NavierStokes.SlowRecursion.lowerHistory hbuffer (n + 1) previous)
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The actual sequence is built by well-founded recursion from one base coefficient. Every recursive input has a strictly smaller slow index.
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- NavierStokes.SlowRecursion.hierarchy c hcore hbuffer C base n = ⋯.fix (NavierStokes.SlowRecursion.recursionStep c hcore hbuffer C base) n
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All orders on the same radial rectangle and the same complex parameter neighborhood. Restriction changes no pointwise function value.
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- NavierStokes.SlowRecursion.sequence c hcore hbuffer C base n i = NavierStokes.SlowRecursion.restrict ⋯ (NavierStokes.SlowRecursion.hierarchy c hcore hbuffer C base n i)
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Every positive slow coefficient solves the actual finite convolution equations, with the lower radial residual computed from the same hierarchy.
The supplied regular representative really is the original radial residual divided by X, for every previously constructed order.
The stored average defect is the literal integral average, including the axis. No free integration constant survives the regular zero trace.
A base made from four genuine profiles; its divergence coefficient is computed by the same canonical derivative operator used in the recursion.
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The concrete finite equations of an actual sequence of profile functions.
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A local slow hierarchy is the output, not a hypothesis on the data. Its underlying type supplies genuine compatible smooth coefficient functions.
- coefficients : ℕ → Coefficient R U
Coefficients of
LocalHierarchy, of typeℕ → Coefficient R U. - beta (n : ℕ) : 0 < n → ∀ X ∈ Set.Ioo 0 (R ^ 2), ∀ (eta : ℝ), ↑eta ∈ U → profile (self.coefficients n 4) (X, eta) = PositiveAxisExistence.newBeta h n (profile (self.coefficients n 1)) (profile (self.coefficients n 2)) (X, eta)
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Construct every positive slow order from a single finite base profile. The entire sequence uses one fixed radial core and one fixed parameter domain.
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Any fixed real parameter window contained in the input neighborhood is retained at every slow order; the recursion consumes no further strip width.