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Complexitylib.BooleanAnalysis.MirrorSets.Internal.Completion

Completion density in Korten's improved mirror-set argument #

Apply the entropy lemma and improved light-patterns lemma inside the sampled union fiber. The exact conditional sampling law yields the 31/32 estimate for the fraction of first-stage modifications with low completion density.

Source: Oliver Korten, Top-Down Lower Bounds for All Depths, ECCC TR26-221 (2026), https://eccc.weizmann.ac.il/report/2026/221/, Sections 3--4. The explicit constants here are q = 32768*k*p and completion deficit 194*k.

theorem Complexity.BooleanAnalysis.projectionAverage_const_mul_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (a : ℝ) (f : (ι → Bool) → ℝ) (s x : ι → Bool) :
projectionAverage (fun (y : ι → Bool) => a * f y) s x = a * projectionAverage f s x
theorem Complexity.BooleanAnalysis.projectionAverage_fiber_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (f : (ι → Bool) → ℝ) (s x : ι → Bool) (R u : { i : ι // s i = true } → Bool) :
projectionAverage (fun (z : { i : ι // s i = true } → Bool) => f (completePattern s x z)) R u = projectionAverage f (fun (i : ι) => if h : s i = true then R ⟨i, h⟩ else true) (completePattern s x u)
theorem Complexity.BooleanAnalysis.coordinateDensity_eq_projection_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (X : Finset (ι → Bool)) (s x : ι → Bool) :
coordinateDensity X s x = projectionAverage (fun (y : ι → Bool) => if y ∈ X then 1 else 0) (fun (i : ι) => !s i) x
theorem Complexity.BooleanAnalysis.projectionAverage_uniformDensity_fiber_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (X : Finset (ι → Bool)) (s x : ι → Bool) (hX : (coordinateFiber X s x).Nonempty) (R u : { i : ι // s i = true } → Bool) :
projectionAverage (uniformDensity (coordinateFiber X s x)) R u = 2 ^ uniformDeficit (coordinateFiber X s x) * coordinateDensity X (fun (i : ι) => if h : s i = true then !R ⟨i, h⟩ else false) (completePattern s x u)
theorem Complexity.BooleanAnalysis.expect_coordinateMarginal_comp_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (f : (ι → Bool) → ℝ) (s : ι → Bool) (g : ℝ → ℝ) :
(Finset.univ.expect fun (x : ι → Bool) => g (projectionAverage f s x)) = Finset.univ.expect fun (z : { i : ι // s i = true } → Bool) => g (coordinateMarginal f s z)
theorem Complexity.BooleanAnalysis.coordinateFiber_light_patterns_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (X : Finset (ι → Bool)) (hX : X.Nonempty) (s : ι → Bool) {k r : ℝ} (hk : 1 ≤ k) (hdef : uniformDeficit X ≤ k) (hr : 0 ≤ r) (hr' : r ≤ 1 / (32768 * k)) :
31 / 32 ≤ X.expect fun (x : ι → Bool) => bernoulliAverage r fun (R : { i : ι // s i = true } → Bool) => if uniformDeficit (coordinateFiber X s x) ≤ 64 * k ∧ (Finset.univ.expect fun (z : { i : { i : ι // s i = true } // R i = true } → Bool) => if coordinateMarginal (uniformDensity (coordinateFiber X s x)) R z ≤ 2 ^ (-128 * k - 2) then 1 else 0) ≤ 2 ^ (-64 * k) then 1 else 0
theorem Complexity.BooleanAnalysis.fiber_completion_density_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (X : Finset (ι → Bool)) (s x : ι → Bool) (hX : (coordinateFiber X s x).Nonempty) (R : { i : ι // s i = true } → Bool) {k : ℝ} (hk : 1 ≤ k) (hd : uniformDeficit (coordinateFiber X s x) ≤ 64 * k) (hl : (Finset.univ.expect fun (z : { i : { i : ι // s i = true } // R i = true } → Bool) => if coordinateMarginal (uniformDensity (coordinateFiber X s x)) R z ≤ 2 ^ (-128 * k - 2) then 1 else 0) ≤ 2 ^ (-64 * k)) :
(Finset.univ.expect fun (u : { i : ι // s i = true } → Bool) => if coordinateDensity X (fun (i : ι) => if h : s i = true then !R ⟨i, h⟩ else false) (completePattern s x u) < 2 ^ (-194 * k) then 1 else 0) ≤ 2 ^ (-k - 6)
theorem Complexity.BooleanAnalysis.coordinateDensity_resample_union_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (X : Finset (ι → Bool)) (P Q x y : ι → Bool) :
coordinateDensity X Q (resample P x y) = coordinateDensity X Q (resample (fun (i : ι) => P i || Q i) x y)
theorem Complexity.BooleanAnalysis.fiber_completion_density_union_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (X : Finset (ι → Bool)) (P Q x : ι → Bool) (hx : x ∈ X) {k : ℝ} (hk : 1 ≤ k) (hd : uniformDeficit (coordinateFiber X (fun (i : ι) => P i || Q i) x) ≤ 64 * k) (hl : (Finset.univ.expect fun (z : { i : { i : ι // (P i || Q i) = true } // (P ↑i && !Q ↑i) = true } → Bool) => if coordinateMarginal (uniformDensity (coordinateFiber X (fun (i : ι) => P i || Q i) x)) (fun (i : { i : ι // (P i || Q i) = true }) => P ↑i && !Q ↑i) z ≤ 2 ^ (-128 * k - 2) then 1 else 0) ≤ 2 ^ (-64 * k)) :
(Finset.univ.expect fun (y : ι → Bool) => if coordinateDensity X Q (resample P x y) < 2 ^ (-194 * k) then 1 else 0) ≤ 2 ^ (-k - 6)
theorem Complexity.BooleanAnalysis.bad_modifications_probability_aux_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (X : Finset (ι → Bool)) (hX : X.Nonempty) {k p q r : ℝ} (hk : 1 ≤ k) (hdef : uniformDeficit X ≤ k) (hp : 0 ≤ p) (hp' : p ≤ 1) (hq : 0 ≤ q) (hq' : q ≤ 1) (hr : 0 ≤ r) (hr' : r ≤ 1 / (32768 * k)) (hjoint : (p + q - p * q) * r = p * (1 - q)) :
31 / 32 ≤ bernoulliAverage p fun (P : ι → Bool) => bernoulliAverage q fun (Q : ι → Bool) => X.expect fun (x : ι → Bool) => if (Finset.univ.expect fun (y : ι → Bool) => if coordinateDensity X Q (resample P x y) < 2 ^ (-194 * k) then 1 else 0) ≤ 2 ^ (-k - 6) then 1 else 0
theorem Complexity.BooleanAnalysis.mirror_bad_modifications_probability_internal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (X : Finset (ι → Bool)) (hX : X.Nonempty) {k p q : ℝ} (hk : 1 ≤ k) (hdef : uniformDeficit X ≤ k) (hp : 0 < p) (hq : q = 32768 * k * p) (hq' : q ≤ 1 / 2) :
31 / 32 ≤ bernoulliAverage p fun (P : ι → Bool) => bernoulliAverage q fun (Q : ι → Bool) => X.expect fun (x : ι → Bool) => if (Finset.univ.expect fun (y : ι → Bool) => if coordinateDensity X Q (resample P x y) < 2 ^ (-194 * k) then 1 else 0) ≤ 2 ^ (-k - 6) then 1 else 0