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LeanPool.HighContrastHomogenization.Entry.Response.Cutoff.CutoffPairingCubeAverageIdentity

High-contrast homogenization: Entry.Response.Cutoff.CutoffPairingCubeAverageIdentity #

Imported from the Apache-2.0 HighContrastHomogenization development at commit 7a13dbcd8d6609264a713373f5c69ceeac870472.

The cutoff pairing as a centred cube average, and its duality-bound hypotheses #

For a cutoff φ in the response cutoff class IsResponseCutoff, this file derives from the class's defining bounds that the pulled-back weight field ξ = scalarCutoffGradientField (φ ∘ qq) is smooth, uniformly bounded to second order, measurable, and hence essentially bounded for the normalized cube measure - the hypotheses the negative-Besov duality bound of e.response.cutoff.estimate (AK.HC Lemma A.1, (A.4)) needs. Testing the weak solenoidal condition HCPolySupport.IsSolenoidalOn moves a cutoff off the gradient of an H¹ test function at the cost of a sign and makes a solenoidal field pair to zero against a compactly supported cutoff's gradient. Combining this integration-by-parts step with the centering identity for a normalized cube average and the pathwise estimate's integrability side conditions identifies the cutoff-weighted pairing on a cell with minus the pairing of the centred potential against the flux defect contracted with the cutoff's gradient, and, after the adapted cell's change of variables, the same identity on the reference cube.

The weight-field hypotheses of the duality bound, from the cutoff class #

For a cutoff φ in the response cutoff class IsResponseCutoff and a matrix qq, put ξ = scalarCutoffGradientField (fun z => φ (matVecMul qq z)). The negative-Besov duality bound (e.response.cutoff.estimate) needs three facts about this weight field: it is smooth coordinatewise, each coordinate field has derivative bounded by the second-order scale 3^{-2t}, and ξ itself is bounded by the first-order scale 3^{-t}, both bounds carrying only the dimensional prefactors recorded in the cutoff class. The declarations below discharge those three hypotheses directly from membership in IsResponseCutoff.

theorem HCPolySupport.HighContrast.Multiscale.contDiff_xi_of_isResponseCutoff {d : ℕ} {qq : Mat d} {t : ℤ} {φ : Vec d → ℝ} (h : IsResponseCutoff qq t φ) (i : Fin d) :
ContDiff ℝ ↑⊤ fun (y : Vec d) => scalarCutoffGradientField (fun (z : Vec d) => φ (matVecMul qq z)) y i

A cutoff in the response class has a coordinatewise smooth gradient field (e.response.cutoff.estimate).

theorem HCPolySupport.HighContrast.Multiscale.norm_fderiv_xi_le_of_isResponseCutoff {d : ℕ} {qq : Mat d} {t : ℤ} {φ : Vec d → ℝ} (h : IsResponseCutoff qq t φ) (i : Fin d) (z : Vec d) :
‖fderiv ℝ (fun (y : Vec d) => scalarCutoffGradientField (fun (w : Vec d) => φ (matVecMul qq w)) y i) z‖ ≤ 1024 * ↑d ^ 4 * responseCutoffProfileConst ^ 2 * 3 ^ (-2 * t)

For a cutoff in the response class, the derivative of each coordinate of the gradient field of the pulled-back cutoff is bounded by the second-order scale recorded in the class (e.response.cutoff.estimate).

theorem HCPolySupport.HighContrast.Multiscale.norm_xi_le_of_isResponseCutoff {d : ℕ} {qq : Mat d} {t : ℤ} {φ : Vec d → ℝ} (h : IsResponseCutoff qq t φ) (y : Vec d) :
‖scalarCutoffGradientField (fun (z : Vec d) => φ (matVecMul qq z)) y‖ ≤ 32 * ↑d ^ 2 * responseCutoffProfileConst * 3 ^ (-t)

For a cutoff in the response class, the gradient field of the pulled-back cutoff is bounded by the first-order scale recorded in the class (e.response.cutoff.estimate).

Integration by parts against a divergence-free field #

Testing the weak solenoidal condition HCPolySupport.IsSolenoidalOn on the product of a smooth cutoff φ with an H¹(U) function w moves the cutoff off the gradient of w and onto w itself, at the cost of a sign. This is the integration-by-parts step in the derivation of the cutoff estimate e.response.cutoff.estimate (AK.HC Lemma A.1, (A.4)); it turns the cutoff-weighted pairing of the response estimate into a pairing of a centred potential against a flux.

theorem HCPolySupport.HighContrast.Multiscale.integral_cutoff_vecDot_grad_eq_neg_integral_vecDot_gradCutoff {d : ℕ} {U : Set (Vec d)} (hU : IsOpenBoundedConvexDomain U) {g : Vec d → Vec d} (hsol : IsSolenoidalOn U g) (w : H1Function U) {φ : Vec d → ℝ} (hφ : ContDiff ℝ (↑⊤) φ) (hφ_compact : HasCompactSupport φ) (hφ_sub : tsupport φ ⊆ U) (hint1 : MeasureTheory.IntegrableOn (fun (x : Vec d) => φ x * vecDot (g x) (w.grad x)) U MeasureTheory.volume) (hint2 : MeasureTheory.IntegrableOn (fun (x : Vec d) => w.toFun x * vecDot (g x) fun (j : Fin d) => (fderiv ℝ φ x) (basisVec j)) U MeasureTheory.volume) :
∫ (x : Vec d) in U, φ x * vecDot (g x) (w.grad x) = -∫ (x : Vec d) in U, w.toFun x * vecDot (g x) fun (j : Fin d) => (fderiv ℝ φ x) (basisVec j)

Integration by parts against a weakly solenoidal field g on an open bounded convex domain U: for an H¹(U) function w and a smooth compactly supported cutoff φ whose support lies in U, the cutoff-weighted pairing ∫_U φ (g · ∇w) equals the negative of the pairing ∫_U w (g · ∇φ) in which the cutoff has been differentiated. Both pairings are assumed integrable on U. This is the integration-by-parts step in the derivation of the cutoff estimate e.response.cutoff.estimate (AK.HC Lemma A.1, (A.4)).

Vanishing of a solenoidal field against a cutoff gradient #

Testing the weak solenoidal condition HCPolySupport.IsSolenoidalOn on a smooth compactly supported function φ whose support lies in the open bounded convex domain U shows that the pairing of the field with the gradient of φ integrates to zero. A smooth compactly supported function supported in U is an H¹₀(U) test function, so the weak divergence-free condition applies to it directly, and its gradient is the Fréchet derivative.

Consequently the normalized volume average of the same pairing vanishes as well. This is the observation that lets the cutoff argument behind e.response.cutoff.estimate replace a potential by its centred version at no cost: the difference produced by centring is a constant multiple of this average.

theorem HCPolySupport.HighContrast.Multiscale.integral_vecDot_solenoidal_gradCutoff_eq_zero {d : ℕ} {U : Set (Vec d)} (hU : IsOpenBoundedConvexDomain U) {g : Vec d → Vec d} (hsol : IsSolenoidalOn U g) {φ : Vec d → ℝ} (hφ : ContDiff ℝ (↑⊤) φ) (hφ_compact : HasCompactSupport φ) (hφ_sub : tsupport φ ⊆ U) :
(∫ (x : Vec d) in U, vecDot (g x) fun (j : Fin d) => (fderiv ℝ φ x) (basisVec j)) = 0

A weakly divergence-free field pairs to zero against the gradient of a smooth compactly supported cutoff whose support lies in the domain. For an open bounded convex domain U, a field g satisfying IsSolenoidalOn U g, and a smooth φ with compact support contained in U, the integral over U of the pairing of g with the gradient fun j => (fderiv ℝ φ x) (basisVec j) is zero. This is the vanishing used in the cutoff argument e.response.cutoff.estimate.

theorem HCPolySupport.HighContrast.Multiscale.volumeAverage_vecDot_solenoidal_gradCutoff_eq_zero {d : ℕ} {U : Set (Vec d)} (hU : IsOpenBoundedConvexDomain U) {g : Vec d → Vec d} (hsol : IsSolenoidalOn U g) {φ : Vec d → ℝ} (hφ : ContDiff ℝ (↑⊤) φ) (hφ_compact : HasCompactSupport φ) (hφ_sub : tsupport φ ⊆ U) :
(volumeAverage U fun (x : Vec d) => vecDot (g x) fun (j : Fin d) => (fderiv ℝ φ x) (basisVec j)) = 0

The normalized volume average of a weakly divergence-free field against the gradient of a smooth compactly supported cutoff vanishes. For an open bounded convex domain U, a field g satisfying IsSolenoidalOn U g, and a smooth φ with compact support contained in U, the volume average over U of the pairing of g with fun j => (fderiv ℝ φ x) (basisVec j) is zero. This is the vanishing used in the cutoff argument e.response.cutoff.estimate.

The integrability hypotheses of the pathwise cutoff estimate #

The pathwise cutoff pairing bound of e.response.cutoff.estimate (AK.HC Lemma A.1, (A.4)) is assembled in abs_volumeAverage_cutoff_pairing_le_of_inputs with several analytic inputs exposed as hypotheses: the integrability of the cutoff-weighted pairing and of the centred-potential pairing on the adapted cell, the integrability on the reference cube of the pulled-back flux defect against the pulled-back cutoff gradient and of that pairing multiplied by the centred potential, and the vanishing of the cube average of the flux defect against the cutoff gradient.

The hypotheses only assert what the caller already has: IsResponseCutoff (respGrid jStar F) t φ, positive definiteness of the canonical metric with the grid-depth inequality 2 * d ≤ 3 ^ jStar, and an almost-everywhere uniformly elliptic representative of the coefficient on the cell. This file discharges each hypothesis from that data. The fields occurring in the pairings are square integrable on the cell (e.response.cutoff.estimate): the optimizer flux by ellipticity, its gradient because the optimizer is H¹, the pulled-back flux on the cube by the change of variables, and the cutoff and its gradient are bounded there.

Paper: e.response.cutoff.estimate and the negative-Besov duality bound (AK.HC Lemma A.1, (A.4)).

theorem HCPolySupport.HighContrast.Multiscale.cutoffPairingIntegrability_of_inputs {d jStar : ℕ} {F : BlockMat d} {t : ℤ} {φ : Vec d → ℝ} {b : CoeffField d} (hjStar : 2 * d ≤ 3 ^ jStar) (hm : Matrix.PosDef (explicitCanonicalMetric F)) (hφ : IsResponseCutoff (respGrid jStar F) t φ) (hb : ∃ (lam : ℝ) (Lam : ℝ) (f : CoeffField d), 0 < lam ∧ lam ≤ Lam ∧ IsEllipticFieldOn lam Lam (respCell jStar F t) f ∧ b =ᵐ[volumeMeasureOn (respCell jStar F t)] f) (u : AHarmonicFunction b (respCell jStar F t)) (Y : BlockVec d) :
MeasureTheory.IntegrableOn (fun (x : Vec d) => φ x * vecDot (matVecMul (b x) (u.toH1.grad x) - Y.2) (u.toH1.grad x - Y.1)) (respCell jStar F t) MeasureTheory.volume

The cut-off-weighted pairing is integrable on the adapted cell. If the coefficient b agrees almost everywhere on respCell jStar F t with a field uniformly elliptic there and u is b-harmonic on the cell, then the cutoff φ of the response class times the Euclidean pairing of the flux defect b ∇u − Y.2 with the centred gradient ∇u − Y.1 is integrable on the cell. This is the hint1 input of the pathwise cutoff estimate e.response.cutoff.estimate: the flux defect and the gradient defect are both coordinatewise square integrable on the cell, and the cutoff is bounded and measurable.

Bounded weight fields are L^∞ for the normalized cube measure #

The negative-Besov duality bound (AK.HC Lemma A.1, (A.4)) pairs the cutoff weight field ξ against a centred potential in the normalized pairing on a cube. Its hypothesis on ξ is uniform boundedness, ‖ξ y‖ ≤ K for every y. The two declarations below show that such a field is L^∞ for normalizedCubeMeasure Q, with L^∞ norm at most K, so that the duality bound can consume the weight field directly.

A vector field bounded uniformly by K is essentially bounded, hence L^∞, for the normalized cube measure (AK.HC Lemma A.1, (A.4)).

theorem HCPolySupport.HighContrast.Multiscale.cubeLpNorm_top_le_of_norm_le {d : ℕ} (Q : TriadicCube d) {ξ : Vec d → Vec d} {K : ℝ} (hK0 : 0 ≤ K) (hK : ∀ (y : Vec d), ‖ξ y‖ ≤ K) :

The normalized L^∞ norm of a vector field bounded uniformly by K is at most K (AK.HC Lemma A.1, (A.4)).

The bundled weight-field and Hessian hypotheses of the cutoff pairing bound #

For a cutoff φ in the response cutoff class IsResponseCutoff and a matrix qq, the negative-Besov duality bound behind e.response.cutoff.estimate consumes the weight field ξ = scalarCutoffGradientField (fun y => φ (qq y)) through its measurability, its uniform first-order bound, and its resulting L^∞ membership for the normalized reference-cube measure; the same estimate consumes the nonnegativity of the second-order Hessian coefficient carried by the cutoff class. The declarations below discharge those four requirements directly from membership in IsResponseCutoff, so that the hypotheses hB, hξLp, hξ, hderiv and hflux of the pathwise cutoff pairing bound can be fed from the class instead of being carried separately.

The gradient field of the pulled-back cutoff of the response class is a.e. strongly measurable for every measure on Vec d (e.response.cutoff.estimate).

The gradient field of a cutoff of the response class is essentially bounded, hence L^∞, for the normalized measure of the reference cube (e.response.cutoff.estimate).

Centring one factor in a normalized cube average #

cubeAverage Q f is the average of f over the cube Q, normalized by the volume of Q. Subtracting a constant from one factor of a product changes the average of the product by that constant times the average of the other factor. Consequently, if the other factor has zero average, the centred and uncentred products have the same average.

This is the algebraic step used in the cutoff argument e.response.cutoff.estimate, where the negative-Besov duality bound is stated for a centred potential while the integration by parts produces the uncentred one; the difference is a constant multiple of the average of the pairing, which vanishes because the field paired against is divergence free.

theorem HCPolySupport.HighContrast.Multiscale.cubeAverage_sub_const_mul {d : ℕ} (Q : TriadicCube d) (c : ℝ) {f g : Vec d → ℝ} (hf : MeasureTheory.IntegrableOn (fun (y : Vec d) => f y * g y) (cubeSet Q) MeasureTheory.volume) (hg : MeasureTheory.IntegrableOn g (cubeSet Q) MeasureTheory.volume) :
(cubeAverage Q fun (y : Vec d) => (f y - c) * g y) = (cubeAverage Q fun (y : Vec d) => f y * g y) - c * cubeAverage Q g

Centring one factor of a normalized cube average. For a cube Q and a constant c, the average of (f - c) * g over Q equals the average of f * g minus c times the average of g, whenever f * g and g are integrable on cubeSet Q.

theorem HCPolySupport.HighContrast.Multiscale.cubeAverage_centered_mul_of_average_eq_zero {d : ℕ} (Q : TriadicCube d) {f g : Vec d → ℝ} (hf : MeasureTheory.IntegrableOn (fun (y : Vec d) => f y * g y) (cubeSet Q) MeasureTheory.volume) (hg : MeasureTheory.IntegrableOn g (cubeSet Q) MeasureTheory.volume) (hzero : cubeAverage Q g = 0) :
(cubeAverage Q fun (y : Vec d) => (f y - cubeAverage Q f) * g y) = cubeAverage Q fun (y : Vec d) => f y * g y

The centred and uncentred pairings agree when the paired field has zero average. If cubeAverage Q g = 0, then the average over Q of (f - cubeAverage Q f) * g equals the average of f * g, whenever f * g and g are integrable on cubeSet Q.

The cutoff pairing on a cell, after integration by parts #

On a cell U, the cutoff-weighted pairing of the gradient defect of an A-harmonic function against its flux defect equals minus the pairing of the centred potential against the flux defect contracted with the gradient of the cutoff. This is the normalization by the cell volume of the integration-by-parts identity integral_cutoff_vecDot_grad_eq_neg_integral_vecDot_gradCutoff applied to the flux defect and to the affine defect of the potential; it is the step that opens the cutoff argument of the response estimate e.response.cutoff.estimate (AK.HC Lemma A.1, (A.4)) by moving one derivative off the optimizer and onto the cutoff.

The centring constant c is arbitrary; it is chosen later to centre the potential.

theorem HCPolySupport.HighContrast.Multiscale.volumeAverage_cutoff_pairing_eq_neg {d : ℕ} {U : Set (Vec d)} (hU : IsOpenBoundedConvexDomain U) [MeasureTheory.IsFiniteMeasure (volumeMeasureOn U)] {b : CoeffField d} (u : AHarmonicFunction b U) (hflux : MemVectorL2 U fun (x : Vec d) => matVecMul (b x) (u.toH1.grad x)) (Y : BlockVec d) (c : ℝ) {φ : Vec d → ℝ} (hφ : ContDiff ℝ (↑⊤) φ) (hφ_compact : HasCompactSupport φ) (hφ_sub : tsupport φ ⊆ U) (hint1 : MeasureTheory.IntegrableOn (fun (x : Vec d) => φ x * vecDot (matVecMul (b x) (u.toH1.grad x) - Y.2) (u.toH1.grad x - Y.1)) U MeasureTheory.volume) (hint2 : MeasureTheory.IntegrableOn (fun (x : Vec d) => (u.toH1.toFun x - vecDot Y.1 x - c) * vecDot (matVecMul (b x) (u.toH1.grad x) - Y.2) fun (j : Fin d) => (fderiv ℝ φ x) (basisVec j)) U MeasureTheory.volume) :
(volumeAverage U fun (x : Vec d) => φ x * vecDot ((optimizerField b u x).1 - Y.1) ((optimizerField b u x).2 - Y.2)) = -volumeAverage U fun (x : Vec d) => (u.toH1.toFun x - vecDot Y.1 x - c) * vecDot (matVecMul (b x) (u.toH1.grad x) - Y.2) fun (j : Fin d) => (fderiv ℝ φ x) (basisVec j)

On a cell U, the volume average of the cutoff-weighted pairing of the gradient defect ∇v - Y.1 against the flux defect b ∇v - Y.2 of an A-harmonic function v equals the negative of the volume average of the pairing of the centred potential v - Y.1 · x - c against the flux defect contracted with the gradient of the cutoff. Both pairings are assumed integrable on U. This is the normalized form of the integration-by-parts step in the derivation of the cutoff estimate e.response.cutoff.estimate (AK.HC Lemma A.1, (A.4)).

The cutoff pairing after integration by parts, written on the reference cube #

On the adapted cell HighContrast.adaptedCell q t, the integration-by-parts form of the cutoff pairing is the negative of the volume average of the centred potential against the flux defect contracted with the gradient of the cutoff. Composing that identity with the change of variables x = q y that identifies the normalized average on the adapted cell with the normalized average on the reference cube originCube d t gives the form of the cutoff argument in which the negative-Besov duality of the response estimate e.response.cutoff.estimate (AK.HC Lemma A.1, (A.4)) applies.

theorem HCPolySupport.HighContrast.Multiscale.cubeAverage_cutoff_pairing_eq_neg {d : ℕ} {q : Mat d} (hq : IsUnit q) (t : ℤ) (hU : IsOpenBoundedConvexDomain (adaptedCell q t)) [MeasureTheory.IsFiniteMeasure (volumeMeasureOn (adaptedCell q t))] {b : CoeffField d} (u : AHarmonicFunction b (adaptedCell q t)) (hflux : MemVectorL2 (adaptedCell q t) fun (x : Vec d) => matVecMul (b x) (u.toH1.grad x)) (Y : BlockVec d) (c : ℝ) {φ : Vec d → ℝ} (hφ : ContDiff ℝ (↑⊤) φ) (hφ_compact : HasCompactSupport φ) (hφ_sub : tsupport φ ⊆ adaptedCell q t) (hint1 : MeasureTheory.IntegrableOn (fun (x : Vec d) => φ x * vecDot (matVecMul (b x) (u.toH1.grad x) - Y.2) (u.toH1.grad x - Y.1)) (adaptedCell q t) MeasureTheory.volume) (hint2 : MeasureTheory.IntegrableOn (fun (x : Vec d) => (u.toH1.toFun x - vecDot Y.1 x - c) * vecDot (matVecMul (b x) (u.toH1.grad x) - Y.2) fun (j : Fin d) => (fderiv ℝ φ x) (basisVec j)) (adaptedCell q t) MeasureTheory.volume) :
(volumeAverage (adaptedCell q t) fun (x : Vec d) => φ x * vecDot ((optimizerField b u x).1 - Y.1) ((optimizerField b u x).2 - Y.2)) = -cubeAverage (originCube d t) fun (y : Vec d) => (u.toH1.toFun (matVecMul q y) - vecDot Y.1 (matVecMul q y) - c) * vecDot (matVecMul (b (matVecMul q y)) (u.toH1.grad (matVecMul q y)) - Y.2) fun (j : Fin d) => (fderiv ℝ φ (matVecMul q y)) (basisVec j)

The integration-by-parts identity for the cutoff pairing on the adapted cell HighContrast.adaptedCell q t, transported to the reference cube. The volume average on the adapted cell of the cutoff-weighted pairing of the gradient defect ∇v - Y.1 against the flux defect b ∇v - Y.2 equals the negative of the cube average on originCube d t of the centred potential v (q y) - Y.1 · (q y) - c against the flux defect evaluated at q y, contracted with the gradient of the cutoff at q y. Both pairings are assumed integrable on the adapted cell. This is the form of the cutoff estimate e.response.cutoff.estimate (AK.HC Lemma A.1, (A.4)) in which the negative-Besov duality is applied.