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LeanPool.HighContrastHomogenization.Provider.Response.PreYoungBoundaryNormalization

High-contrast homogenization: Provider.Response.PreYoungBoundaryNormalization #

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

Boundary-row normalization #

The child--parent energy uses the half-energy normalization. Consequently, each of the two coordinate rows carries sqrt (4 * tau). Their half-sum is still controlled by the standard sqrt 2 * sqrt tau Schur-load coefficient.

theorem HCPolySupport.HighContrast.Response.abs_boundaryMean_le_of_four_mul_responseDefect {d : ℕ} {tau gain meanGrad meanFlux : ℝ} {row : ENNReal} {H : BlockMat d} {Pcen Qcen : Vec d} (hgradRow : ENNReal.ofReal |meanGrad| ≤ ENNReal.ofReal (√(4 * tau) * profileSchurLoadFlux H Qcen) + ENNReal.ofReal gain * row ^ (1 / 2)) (hfluxRow : ENNReal.ofReal |meanFlux| ≤ ENNReal.ofReal (√(4 * tau) * profileSchurLoadGradient H Pcen) + ENNReal.ofReal gain * row ^ (1 / 2)) :
ENNReal.ofReal (1 / 2 * |meanGrad + meanFlux|) ≤ ENNReal.ofReal (√2 * √tau * √(profileSchurLoad H Pcen Qcen)) + ENNReal.ofReal gain * row ^ (1 / 2)

Two coordinate-row estimates with the half-energy normalization combine into the standard boundary-mean estimate.