OddReflectionMap #
Ported from scottnarmstrong/Superdiffusion at 7f20476385d4af418f110303085ad0740c9eba46. Module imports, support namespace and local option directives adapted for Lean Pool.
The partial odd reflection operator, and the odd affine class #
The fold and its sign #
Each met face contributes one coordinate reflection, and by
not_meetsLowerFace_of_meetsUpperFace a coordinate meets at most one face, so
the whole group action is realized by a single coordinatewise fold
foldCoord i t = min t (3^m - t) if the upper i-face is met,
= max t (-3^m - t) if the lower i-face is met,
= t otherwise,
with the matching odd sign foldSignCoord i t = ±1 (negative exactly on the
reflected side), and windowFoldSign y = ∏ᵢ foldSignCoord i (y i).
oddExtend f is y ↦ windowFoldSign y · f (windowFold y), and oddExtendGrad G
carries the extra per-coordinate sign that the chain rule produces.
The odd affine class 𝕃_odd(V) #
IsOddAffineData x m k c A says the affine function ℓ(y) = c + A·(y-x)
vanishes on every hyperplane containing a met face — the paper's
𝕃_odd(V). Two structural facts are proved:
- if the
i-face is met thenA j = 0for everyj ≠ i(slope_eq_zero_of_ne_of_meets), so at one met face the class is the single lineℝ·(y_i - a_i); - if two different coordinates meet a face then
ℓ ≡ 0(affineLift_eq_zero_of_two_met) — at an edge or corner of□_mthe class𝕃_odd(V)collapses to{0}.
oddExtend_affineLift is the paper's "if ℓ ∈ 𝕃_odd(V), then ℓ is odd under
each of these reflections": the odd extension of such an ℓ is ℓ itself, so
the extension of v₀ - ℓ is the odd extension of v₀ - ℓ.
What is not done here #
No H¹ statement, no weak harmonicity, no measure-theoretic change of
variables.
References #
- CoarseGraining
Homogenization.Sobolev.Foundations.CubeDirichletH2.OddReflection(the all-faces construction adapted here) andHomogenization.Sobolev.Foundations.CubeReflection.Reflections(coordFaceReflection, the one-face affine map).
1. The coordinatewise fold and its sign #
The fold of one coordinate into the window's side of the met face.
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The odd sign attached to one coordinate: -1 exactly on the reflected
side of a met face.
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2. The fold, the global sign, and the odd extension #
The coordinatewise fold of Vec d onto the window's side of every met
face: the composite of the reflections in the met faces, applied to whichever
of the 2^{#S} cells the point lies in.
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The global odd sign: (-1)^{#\{i : y \text{ is beyond the met } i\text{-face}\}}.
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- Algsuperdiff.Section4.Provider.ExcessDecay.windowFoldSign x m k y = ∏ i : Fin d, Algsuperdiff.Section4.Provider.ExcessDecay.foldSignCoord x m k i (y i)
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The partial odd reflection of a scalar.
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The partial odd reflection of a gradient field. The chain rule for the coordinate fold contributes the extra per-coordinate sign.
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4. The fold maps the reflected window onto the window #
The fold is onto the window, off the interfaces. Every point of the
partially reflected window that avoids the reflection hyperplanes is carried
into the window itself by windowFold. (The excluded set is a finite union of
hyperplanes, hence Lebesgue-null; the null set is what the downstream change of
variables discards.)
5. The odd affine class 𝕃_odd(V) #
The odd affine class of the paper's e.v0.hessian: the affine
functions ℓ(y) = c + A·(y-x) that vanish on every hyperplane containing a
face of ∂□_m meeting the closure of the window.
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In the interior regime — no face met — the odd class is all of 𝕃.
The tangential slopes vanish. If the i-face is met then every
coordinate j ≠ i of the slope of an odd affine function is zero, so at a
single met face 𝕃_odd(V) is the one-dimensional space ℝ·(y_i - a_i).
At an edge or corner the odd class collapses. If two different
coordinates each meet a face of ∂□_m, the only odd affine function is 0.
6. Odd affine functions are fixed by the odd extension #
The oddness step. An affine function in 𝕃_odd(V) is odd
under every met-face reflection, hence is its own partial odd extension.
Consequently the odd extension of v₀ - ℓ is the odd extension of v₀ minus
ℓ, which is what the free parameter ℓ of e.v0.hessian is for.