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LeanPool.Superdiffusion.Algsuperdiff.Section4.Provider.ExcessDecay.BoundaryLaneMaxPrinciple

BoundaryLaneMaxPrinciple #

Ported from scottnarmstrong/Superdiffusion at 7f20476385d4af418f110303085ad0740c9eba46. Module imports, support namespace and local option directives adapted for Lean Pool.

The weak maximum principle for the Laplacian on the truncated window #

The boundary lane's residual corrector w (draft item 2(ii)) is controlled by

  ‖w‖_{L^∞(V)} ≤ ‖h - ℓ_h‖_{L^∞(∂V ∩ ∂□_m)} ,

which the draft justifies as "the maximum principle for the Laplacian". This module proves that step in the weak (H¹) formulation:

  v weakly harmonic on V,  (v - M)₊ ∈ H¹₀(V)   ⟹   v ≤ M  a.e. on V ,

together with its two-sided form. The proof is the standard energy argument: test the harmonicity against the truncation (v-M)₊, use the Stampacchia chain rule ∇(v-M)₊ = 1_{v>M} ∇v to see that the tested integral is the full Dirichlet energy of the truncation, conclude that the truncation has vanishing gradient, and close with the zero-trace Poincaré inequality.

Why this is the right rendering (and what it costs) #

(v - M)₊ ∈ H¹(V) with the Stampacchia gradient is free: CoarseGraining proves it for every H¹ function and every level (exists_h1_max_sub_const, Homogenization/Sobolev/Truncation/Basic.lean). The whole content of the hypothesis HasBoundaryUpperBoundOn is therefore the zero trace of the truncation, which is exactly the weak reading of "v ≤ M on ∂V" — the standard hypothesis of the weak maximum principle, not a proof step in disguise. No pointwise trace operator is used anywhere in this repository, and none is introduced here.

What is not done here #

The lane still owes: the construction of the corrector w with the draft's boundary data on ∂V ∩ ∂□_m and ∂V ∩ □_m, and (b) the verification of HasBoundaryUpperBoundOn for that w from the pointwise bound on h - ℓ_h (AffineSplitLift.abs_sub_affineLift_volumeAverage_le).

References #

1. The weak boundary bound #

u ≤ M on ∂V, weakly. The positive part (u - M)₊ lies in H¹₀(V), carrying CoarseGraining's Stampacchia gradient 1_{u>M} ∇u.

The H¹ membership and the gradient formula are unconditional (Homogenization.exists_h1_max_sub_const); the content of this predicate is the zero trace. (Given the first component, the second is forced almost everywhere by uniqueness of weak gradients on an open window; it is bundled so that no consumer has to rerun that argument, not to strengthen the hypothesis.)

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    2. The maximum principle #

    The weak maximum principle for the Laplacian.

    A weakly harmonic H¹ function on an open bounded convex window which is ≤ M on the boundary (in the zero-trace sense of HasBoundaryUpperBoundOn) is ≤ M almost everywhere in the window.

    3. The two-sided form #

    The two-sided weak maximum principle. This is the display ‖w‖_{L^∞(V)} ≤ M of the draft's item 2(ii), with M the sup-bound of the boundary data.