import OAI.Computability.UniqueGames.Decoding.SparseLawLemmas import OAI.Computability.UniqueGames.Reduction.ExplicitLemmas import OAI.Computability.UniqueGames.Soundness.ActualCanonicalPullbackLemmas namespace OAI section /-! Actual linear-map realization of the sparse padded-table experiment. The finite sample has one independent full pair or singleton coefficient at each occurrence position and one independent homogeneous intercept. Its map is formed by composing a genuine map on the raw projected target with the actual parity projection. The third position contributes its parity-dependent intercept; it is not treated as a homogeneous two-coordinate projection. -/ namespace UniqueGamesTheorem.Decoder.PaddedLaw open scoped BigOperators open UniqueGamesTheorem.Integration.BinaryLinear open UniqueGamesTheorem.Reduction open UniqueGamesTheorem.Soundness open ConditionalIncidences PartnerProjection RawPartnerTarget RawMapLaw open ActualCanonicalPullback open SparseLaw noncomputable section attribute [local instance] Classical.propDecidable section FinitePushforward variable {α B : Type*} [Fintype α] def pushforwardWeight (p : α → ℝ) (f : α → B) (y : B) : ℝ := ∑ x, if f x = y then p x else 0 theorem pushforwardWeight_pi (p : α → ℝ) (f : α → B) (k : ℕ) (ys : Fin k → B) : pushforwardWeight (independentWeights p k) (fun xs i => f (xs i)) ys = independentWeights (pushforwardWeight p f) k ys := by classical simp only [pushforwardWeight, independentWeights] rw [Fintype.prod_sum] apply Finset.sum_congr rfl intro xs _ simp only [Fintype.prod_ite_zero, funext_iff] split_ifs <;> rfl theorem pushforwardWeight_joint_uniform_intercept {W : Type*} [Fintype W] [AddGroup W] (p : α → ℝ) (f : α → B) (shift : α → W) (z : W) (b : B) : pushforwardWeight (fun az : α × W => p az.1 * uniformWeights W az.2) (fun az => (az.2 + shift az.1, f az.1)) (z, b) = uniformWeights W z * pushforwardWeight p f b := by classical simp only [pushforwardWeight, Fintype.sum_prod_type] calc (∑ a : α, ∑ t : W, if (t + shift a, f a) = (z, b) then p a * uniformWeights W t else 0) = ∑ a : α, if f a = b then p a * uniformWeights W z else 0 := by apply Finset.sum_congr rfl intro a _ by_cases h : f a = b · simp only [Prod.mk.injEq, h, and_true, ite_true] exact joint_intercept_pushforward p shift a z · simp [Prod.mk.injEq, h] _ = uniformWeights W z * (∑ a : α, if f a = b then p a else 0) := by rw [Finset.mul_sum] apply Finset.sum_congr rfl intro a _ by_cases h : f a = b <;> simp [h, mul_comm] end FinitePushforward variable {k : ℕ} {V : Type} [AddCommGroup V] [Module F2 V] abbrev BlockDraw (V : Type) := (V × V) ⊕ (Fin 3 × V) def decodeSlot (i : Fin 3) : Slot := if i = 0 then .first else if i = 1 then .second else .third theorem slotIndex_decodeSlot (i : Fin 3) : ConcreteExtraction.slotIndex (decodeSlot i) = i := by fin_cases i <;> rfl def blockAmbient : BlockDraw V → Fin 3 → V | .inl ab => ![ab.1, ab.2, 0] | .inr ia => Pi.single ia.1 ia.2 def blockSlopes (d : BlockDraw V) : V × V := (blockAmbient d 0 + blockAmbient d 2, blockAmbient d 1 + blockAmbient d 2) def blockThird (d : BlockDraw V) : V := blockAmbient d 2 omit [Module F2 V] in @[simp] theorem blockSlopes_full (ab : V × V) : blockSlopes (.inl ab) = ab := by simp [blockSlopes, blockAmbient] omit [Module F2 V] in @[simp] theorem blockSlopes_first (a : V) : blockSlopes (.inr ((0 : Fin 3), a)) = (a, 0) := by simp [blockSlopes, blockAmbient] omit [Module F2 V] in @[simp] theorem blockSlopes_second (a : V) : blockSlopes (.inr ((1 : Fin 3), a)) = (0, a) := by simp [blockSlopes, blockAmbient] omit [Module F2 V] in @[simp] theorem blockSlopes_third (a : V) : blockSlopes (.inr ((2 : Fin 3), a)) = (a, a) := by simp [blockSlopes, blockAmbient] def singletonPositions (d : Fin k → BlockDraw V) : Finset (Fin k) := Finset.univ.filter fun j => (d j).isRight def drawSlots (d : Fin k → BlockDraw V) (j : Fin k) : Slot := match d j with | .inl _ => .first | .inr ia => decodeSlot ia.1 def drawCoefficients (d : Fin k → BlockDraw V) (z : V) : RawCoefficients (singletonPositions d) V | none => z | some (.inl (j, i)) => match d j.val with | .inl ab => if i = 0 then ab.1 else ab.2 | .inr _ => 0 | some (.inr j) => match d j.val with | .inl _ => 0 | .inr ia => ia.2 def paddedMap (rhs : Fin k → Bool) (d : Fin k → BlockDraw V) (z : V) : ActualHomogeneous.E k →ₗ[F2] V := (rawMap (singletonPositions d) V (drawCoefficients d z)).comp (rawProjection rhs (singletonPositions d) (drawSlots d)) omit [Module F2 V] in theorem ambientCoefficients_draw (d : Fin k → BlockDraw V) (z : V) : ambientCoefficients (singletonPositions d) V (drawCoefficients d z) (drawSlots d) = fun j => blockAmbient (d j) := by funext j i cases hd : d j with | inl ab => fin_cases i <;> simp [ambientCoefficients, singletonPositions, drawCoefficients, blockAmbient, hd] | inr ia => simp [ambientCoefficients, singletonPositions, drawCoefficients, drawSlots, blockAmbient, hd, slotIndex_decodeSlot, Pi.single_apply] def interceptShift (rhs : Fin k → Bool) (d : Fin k → BlockDraw V) : V := ∑ j, ofBit (rhs j) • blockThird (d j) theorem paddedMap_toCoefficients (rhs : Fin k → Bool) (d : Fin k → BlockDraw V) (z : V) : ActualEnumeration.toCoefficients k V (paddedMap rhs d z) = (z + interceptShift rhs d, fun j => blockSlopes (d j)) := by have hrep := raw_represents rhs (singletonPositions d) V (drawCoefficients d z) (drawSlots d) rw [ambientCoefficients_draw] at hrep have hc := ActualCanonical.extension_coefficients _ _ _ _ hrep have hmap : paddedMap rhs d z = freePullback rhs (singletonPositions d) V (drawCoefficients d z) (drawSlots d) := by unfold paddedMap rw [rawMap_pullback, coefficients_rawMap] rw [hmap] apply Prod.ext · exact hc.1 · funext j exact Prod.ext (hc.2 j).1 (hc.2 j).2 /-- Uniform raw coefficients are exactly uniform genuine maps on the actual projected target, for each fixed mask and projection choice. -/ theorem uniform_rawMaps [Fintype V] (J : Finset (Fin k)) (H : (RawPoint J →ₗ[F2] V) → ℝ) : (𝔼 gamma : RawCoefficients J V, H (rawMap J V gamma)) = 𝔼 Y, H Y := by exact Fintype.expect_equiv (rawMapEquiv J V) _ H (fun _ => rfl) /-- The conditional coefficient sample, with full pairs and singleton values kept at their occurrence-local positions. -/ abbrev RawTuple (J : Finset (Fin k)) (V : Type) := V × ((PositionOutside J → V × V) × (PositionInside J → V)) def rawTupleEquiv (J : Finset (Fin k)) : RawTuple J V ≃ RawCoefficients J V where toFun a | none => a.1 | some (.inl (j, i)) => if i = 0 then (a.2.1 j).1 else (a.2.1 j).2 | some (.inr j) => a.2.2 j invFun gamma := ⟨gamma none, ⟨(fun j => (gamma (some (.inl (j, 0))), gamma (some (.inl (j, 1))))), (fun j => gamma (some (.inr j)))⟩⟩ left_inv a := by apply Prod.ext rfl apply Prod.ext · funext j rfl · rfl right_inv gamma := by funext s rcases s with _ | (⟨j, i⟩ | j) · rfl · fin_cases i <;> rfl · rfl def tupleDraw (J : Finset (Fin k)) (slot : Fin k → Slot) (a : RawTuple J V) (j : Fin k) : BlockDraw V := if hj : j ∈ J then .inr (ConcreteExtraction.slotIndex (slot j), a.2.2 ⟨j, hj⟩) else .inl (a.2.1 ⟨j, hj⟩) omit [Module F2 V] in theorem tupleDraw_ambient (J : Finset (Fin k)) (slot : Fin k → Slot) (a : RawTuple J V) : (fun j => blockAmbient (tupleDraw J slot a j)) = ambientCoefficients J V (rawTupleEquiv J a) slot := by funext j i by_cases hj : j ∈ J · simp [tupleDraw, hj, blockAmbient, ambientCoefficients, rawTupleEquiv, Pi.single_apply] · fin_cases i <;> simp [tupleDraw, hj, blockAmbient, ambientCoefficients, rawTupleEquiv] theorem paddedMap_tupleDraw (rhs : Fin k → Bool) (J : Finset (Fin k)) (slot : Fin k → Slot) (a : RawTuple J V) : paddedMap rhs (tupleDraw J slot a) a.1 = (rawMap J V (rawTupleEquiv J a)).comp (rawProjection rhs J slot) := by have hr := raw_represents rhs J V (rawTupleEquiv J a) slot rw [← tupleDraw_ambient] at hr have hc := ActualCanonical.extension_coefficients _ _ _ _ hr apply (ActualEnumeration.coefficientEquiv k V).symm.injective change ActualEnumeration.toCoefficients k V _ = ActualEnumeration.toCoefficients k V _ rw [paddedMap_toCoefficients, rawMap_pullback, coefficients_rawMap] apply Prod.ext · exact hc.1.symm · funext j exact Prod.ext (hc.2 j).1.symm (hc.2 j).2.symm /-- Conditional on every fixed mask and position choice, independently uniform full pairs/singletons and intercept give the uniform law on genuine projected-target maps followed by the actual projection. -/ theorem uniform_fixed_projection_tuple [Fintype V] (rhs : Fin k → Bool) (J : Finset (Fin k)) (slot : Fin k → Slot) (H : (ActualHomogeneous.E k →ₗ[F2] V) → ℝ) : (𝔼 a : RawTuple J V, H (paddedMap rhs (tupleDraw J slot a) a.1)) = 𝔼 Y : RawPoint J →ₗ[F2] V, H (Y.comp (rawProjection rhs J slot)) := by simp_rw [paddedMap_tupleDraw] exact Fintype.expect_equiv ((rawTupleEquiv J).trans (rawMapEquiv J V)) _ _ (fun _ => rfl) section Law variable [Fintype V] /-- Retain a full pair with probability `1-beta`, or choose one of three singleton positions with probability `beta/3` and its uniform slope. -/ def blockWeights (β : ℝ) : BlockDraw V → ℝ | .inl ab => (1 - β) * uniformWeights (V × V) ab | .inr ia => (β / 3) * uniformWeights V ia.2 omit [Module F2 V] in theorem blockWeights_isProbability (β : ℝ) (hβ : 0 ≤ β) (hβ' : β ≤ 1) : UniqueGamesTheorem.Foundations.Information.IsProbability (blockWeights (V := V) β) := by constructor · intro d cases d with | inl ab => exact mul_nonneg (sub_nonneg.mpr hβ') (uniformWeights_pos ab).le | inr ia => exact mul_nonneg (div_nonneg hβ (by norm_num)) (uniformWeights_pos ia.2).le · rw [Fintype.sum_sum_type] simp only [blockWeights, ← Finset.mul_sum, (uniformWeights_isProbability (α := V × V)).2, mul_one, Fintype.sum_prod_type, (uniformWeights_isProbability (α := V)).2] simp omit [Module F2 V] in theorem blockWeights_slopes (β : ℝ) (ab : V × V) : pushforwardWeight (blockWeights (V := V) β) blockSlopes ab = mixture β (singletonPairWeights V) ab := by have hfull : (∑ x : V × V, if blockSlopes (.inl x) = ab then blockWeights β (.inl x) else 0) = (1 - β) * uniformWeights (V × V) ab := by simp [blockWeights] have hsingle : (∑ ia : Fin 3 × V, if blockSlopes (.inr ia) = ab then blockWeights β (.inr ia) else 0) = β * singletonSamplerWeights V ab := by rw [Fintype.sum_prod_type, Fin.sum_univ_three] simp only [blockSlopes_first, blockSlopes_second, blockSlopes_third, blockWeights] have hfactor (f : V → V × V) : (∑ a : V, if f a = ab then β / 3 * uniformWeights V a else 0) = (β / 3) * ∑ a : V, if f a = ab then uniformWeights V a else 0 := by rw [Finset.mul_sum] apply Finset.sum_congr rfl intro a _ split <;> simp_all simp only [hfactor, singletonSamplerWeights] ring unfold pushforwardWeight rw [Fintype.sum_sum_type] calc _ = (∑ x : V × V, if blockSlopes (.inl x) = ab then blockWeights β (.inl x) else 0) + (∑ ia : Fin 3 × V, if blockSlopes (.inr ia) = ab then blockWeights β (.inr ia) else 0) := by congr 1 <;> apply Finset.sum_congr rfl <;> intro x _ <;> split_ifs <;> rfl _ = _ := by rw [hfull, hsingle, singletonSamplerWeights_eq]; rfl def drawWeights (β : ℝ) (k : ℕ) : ((Fin k → BlockDraw V) × V) → ℝ := fun dz => independentWeights (blockWeights β) k dz.1 * uniformWeights V dz.2 def paddedWeights (rhs : Fin k → Bool) (β : ℝ) : ActualEnumeration.Coefficients k V → ℝ := pushforwardWeight (drawWeights β k) (fun dz => ActualEnumeration.toCoefficients k V (paddedMap rhs dz.1 dz.2)) theorem paddedWeights_eq (rhs : Fin k → Bool) (β : ℝ) (a : ActualEnumeration.Coefficients k V) : paddedWeights rhs β a = uniformWeights V a.1 * independentWeights (mixture β (singletonPairWeights V)) k a.2 := by rcases a with ⟨z, slopes⟩ unfold paddedWeights simp_rw [paddedMap_toCoefficients] unfold drawWeights have hj := pushforwardWeight_joint_uniform_intercept (independentWeights (blockWeights (V := V) β) k) (fun d j => blockSlopes (d j)) (interceptShift rhs) z slopes calc _ = uniformWeights V z * pushforwardWeight (independentWeights (blockWeights (V := V) β) k) (fun d j => blockSlopes (d j)) slopes := by convert hj using 1 _ = _ := by rw [pushforwardWeight_pi] congr 1 apply Finset.prod_congr rfl intro j _ exact blockWeights_slopes β (slopes j) theorem uniformWeights_prod {A B : Type*} [Fintype A] [Fintype B] (ab : A × B) : uniformWeights (A × B) ab = uniformWeights A ab.1 * uniformWeights B ab.2 := by simp [uniformWeights, Fintype.card_prod, Nat.cast_mul, one_div, mul_comm] theorem totalVariation_uniform_front {A B : Type*} [Fintype A] [Nonempty A] [Fintype B] (p q : B → ℝ) : UniqueGamesTheorem.Foundations.Information.totalVariation (fun ab : A × B => uniformWeights A ab.1 * p ab.2) (fun ab : A × B => uniformWeights A ab.1 * q ab.2) = UniqueGamesTheorem.Foundations.Information.totalVariation p q := by unfold UniqueGamesTheorem.Foundations.Information.totalVariation rw [Fintype.sum_prod_type] simp only [← mul_sub, abs_mul, abs_of_nonneg (uniformWeights_pos _).le, ← Finset.mul_sum, ← Finset.sum_mul, (uniformWeights_isProbability (α := A)).2, one_mul] theorem paddedWeights_totalVariation_eq_slope (rhs : Fin k → Bool) (β : ℝ) : UniqueGamesTheorem.Foundations.Information.totalVariation (paddedWeights (V := V) rhs β) (uniformWeights (ActualEnumeration.Coefficients k V)) = UniqueGamesTheorem.Foundations.Information.totalVariation (independentWeights (mixture β (singletonPairWeights V)) k) (uniformWeights (Fin k → V × V)) := by have hp : paddedWeights (V := V) rhs β = fun a => uniformWeights V a.1 * independentWeights (mixture β (singletonPairWeights V)) k a.2 := by funext a exact paddedWeights_eq rhs β a have hu : uniformWeights (ActualEnumeration.Coefficients k V) = fun a => uniformWeights V a.1 * uniformWeights (Fin k → V × V) a.2 := by funext a exact uniformWeights_prod a rw [hp, hu, totalVariation_uniform_front] /-- Full-table bound on the coordinates of the genuine composed maps. It includes the affine intercept and averages all projection choices. -/ theorem paddedWeights_totalVariation (rhs : Fin k → Bool) (β : ℝ) (hβ : 0 ≤ β) (hβ' : β ≤ 1) : UniqueGamesTheorem.Foundations.Information.totalVariation (paddedWeights (V := V) rhs β) (uniformWeights (ActualEnumeration.Coefficients k V)) ≤ Real.sqrt ((1 + β ^ 2 * ((Fintype.card V : ℝ) - 1) / 3) ^ k - 1) / 2 := by rw [paddedWeights_totalVariation_eq_slope] exact paddedSlope_totalVariation V β hβ hβ' k abbrev ProjectionChoice := Option (Fin 3) def choiceWeight (β : ℝ) : ProjectionChoice → ℝ | none => 1 - β | some _ => β / 3 theorem choiceWeight_isProbability (β : ℝ) (hβ : 0 ≤ β) (hβ' : β ≤ 1) : UniqueGamesTheorem.Foundations.Information.IsProbability (choiceWeight β) := by constructor · intro c cases c with | none => exact sub_nonneg.mpr hβ' | some i => exact div_nonneg hβ (by norm_num) · rw [Fintype.sum_option] simp [choiceWeight] ring def blockKernel : ProjectionChoice → BlockDraw V → ℝ | none, .inl ab => uniformWeights (V × V) ab | some i, .inr ja => if i = ja.1 then uniformWeights V ja.2 else 0 | _, _ => 0 def choiceTupleWeight (β : ℝ) (c : Fin k → ProjectionChoice) : ℝ := ∏ j, choiceWeight β (c j) theorem choiceTupleWeight_isProbability (β : ℝ) (hβ : 0 ≤ β) (hβ' : β ≤ 1) : UniqueGamesTheorem.Foundations.Information.IsProbability (choiceTupleWeight (k := k) β) := by exact independentWeights_isProbability (choiceWeight β) (choiceWeight_isProbability β hβ hβ') k def kernelTupleWeight (c : Fin k → ProjectionChoice) (d : Fin k → BlockDraw V) : ℝ := ∏ j, blockKernel (c j) (d j) omit [AddCommGroup V] [Module F2 V] in theorem blockWeights_choice_mixture (β : ℝ) (d : BlockDraw V) : blockWeights β d = ∑ c : ProjectionChoice, choiceWeight β c * blockKernel c d := by cases d <;> simp [Fintype.sum_option, choiceWeight, blockKernel, blockWeights, mul_ite] omit [AddCommGroup V] [Module F2 V] in theorem independent_blockWeights_mixture (β : ℝ) (d : Fin k → BlockDraw V) : independentWeights (blockWeights β) k d = ∑ c : Fin k → ProjectionChoice, choiceTupleWeight β c * kernelTupleWeight c d := by unfold independentWeights choiceTupleWeight kernelTupleWeight simp_rw [blockWeights_choice_mixture] rw [Fintype.prod_sum] apply Finset.sum_congr rfl intro c _ exact Finset.prod_mul_distrib omit [AddCommGroup V] [Module F2 V] in theorem drawWeights_choice_mixture (β : ℝ) (dz : (Fin k → BlockDraw V) × V) : drawWeights β k dz = ∑ c : Fin k → ProjectionChoice, choiceTupleWeight β c * (kernelTupleWeight c dz.1 * uniformWeights V dz.2) := by rw [drawWeights, independent_blockWeights_mixture, Finset.sum_mul] apply Finset.sum_congr rfl intro c _ ring omit [AddCommGroup V] [Module F2 V] in /-- This is the unconditioned law identity before replacing the coefficient kernel by uniform projected-target maps. No division by a mask probability. -/ theorem draw_expectation_choice_mixture (β : ℝ) (H : ((Fin k → BlockDraw V) × V) → ℝ) : (∑ dz, drawWeights β k dz * H dz) = ∑ c : Fin k → ProjectionChoice, choiceTupleWeight β c * ∑ dz, (kernelTupleWeight c dz.1 * uniformWeights V dz.2) * H dz := by simp_rw [drawWeights_choice_mixture, Finset.sum_mul] rw [Finset.sum_comm] apply Finset.sum_congr rfl intro c _ rw [Finset.mul_sum] apply Finset.sum_congr rfl intro dz _ ring /-- The actual coefficient type after a choice has been fixed. -/ def ChoiceValue (V : Type) : ProjectionChoice → Type | none => V × V | some _ => V instance choiceValueFintype (c : ProjectionChoice) : Fintype (ChoiceValue V c) := by cases c <;> dsimp [ChoiceValue] <;> infer_instance def choiceEmbed : (c : ProjectionChoice) → ChoiceValue V c → BlockDraw V | none, ab => .inl ab | some i, a => .inr (i, a) omit [AddCommGroup V] [Module F2 V] in theorem blockKernel_uniform_pushforward (c : ProjectionChoice) (d : BlockDraw V) : blockKernel c d = pushforwardWeight (uniformWeights (ChoiceValue V c)) (choiceEmbed c) d := by cases c with | none => cases d <;> simp [blockKernel, pushforwardWeight, choiceEmbed, ChoiceValue] exact fun h => False.elim (h (Finset.mem_univ _)) | some i => cases d with | inl ab => simp [blockKernel, pushforwardWeight, choiceEmbed, ChoiceValue] | inr ja => rcases ja with ⟨j, a⟩ by_cases h : i = j <;> simp [blockKernel, pushforwardWeight, choiceEmbed, ChoiceValue, Prod.mk.injEq, h] exact fun h => False.elim (h (Finset.mem_univ _)) theorem pushforwardWeight_pi_dep {I B : Type*} [Fintype I] {A : I → Type*} [∀ i, Fintype (A i)] (p : (i : I) → A i → ℝ) (f : (i : I) → A i → B) (ys : I → B) : pushforwardWeight (fun xs : ∀ i, A i => ∏ i, p i (xs i)) (fun xs : ∀ i, A i => fun i => f i (xs i)) ys = ∏ i, pushforwardWeight (p i) (f i) (ys i) := by classical simp only [pushforwardWeight] rw [Fintype.prod_sum] apply Finset.sum_congr rfl intro xs _ simp only [Fintype.prod_ite_zero, funext_iff] theorem uniformWeights_pi {I : Type*} [Fintype I] {A : I → Type*} [∀ i, Fintype (A i)] (x : ∀ i, A i) : uniformWeights (∀ i, A i) x = ∏ i, uniformWeights (A i) (x i) := by simp [uniformWeights, Fintype.card_pi, Nat.cast_prod, one_div, Finset.prod_inv_distrib] omit [AddCommGroup V] [Module F2 V] in theorem kernelTuple_uniform_pushforward (c : Fin k → ProjectionChoice) (d : Fin k → BlockDraw V) : kernelTupleWeight c d = pushforwardWeight (uniformWeights (∀ j, ChoiceValue V (c j))) (fun f j => choiceEmbed (c j) (f j)) d := by unfold kernelTupleWeight simp_rw [blockKernel_uniform_pushforward] rw [← pushforwardWeight_pi_dep] have hp : (fun f : ∀ j, ChoiceValue V (c j) => ∏ j, uniformWeights (ChoiceValue V (c j)) (f j)) = uniformWeights (∀ j, ChoiceValue V (c j)) := by funext f simp [uniformWeights, Fintype.card_pi, Nat.cast_prod, one_div, Finset.prod_inv_distrib] rw [hp] congr 1 exact Subsingleton.elim _ _ theorem sum_pushforwardWeight_mul {A B : Type*} [Fintype A] [Fintype B] (p : A → ℝ) (f : A → B) (H : B → ℝ) : (∑ b, pushforwardWeight p f b * H b) = ∑ a, p a * H (f a) := by classical simp only [pushforwardWeight, Finset.sum_mul] rw [Finset.sum_comm] apply Finset.sum_congr rfl intro a _ simp [ite_mul] theorem sum_uniformWeights_mul {A : Type*} [Fintype A] (H : A → ℝ) : (∑ a, uniformWeights A a * H a) = 𝔼 a, H a := by rw [Fintype.expect_eq_sum_div_card] simp only [uniformWeights, ← Finset.mul_sum] ring def choiceMask (c : Fin k → ProjectionChoice) : Finset (Fin k) := Finset.univ.filter fun j => (c j).isSome def choiceSlot : ProjectionChoice → Slot | none => .first | some i => decodeSlot i def choiceSlots (c : Fin k → ProjectionChoice) (j : Fin k) : Slot := choiceSlot (c j) theorem not_mem_choiceMask (c : Fin k → ProjectionChoice) (j : Fin k) : j ∉ choiceMask c ↔ c j = none := by cases h : c j <;> simp [choiceMask, h] def fullChoiceValue : (c : ProjectionChoice) → ChoiceValue V c → V × V | none, x => x | some _, _ => (0, 0) def singleChoiceValue : (c : ProjectionChoice) → ChoiceValue V c → V | none, _ => 0 | some _, x => x def readChoiceValue (q : ProjectionChoice) (full : q = none → V × V) (single : q.isSome = true → V) : ChoiceValue V q := by cases q with | none => exact full rfl | some i => exact single rfl omit [Module F2 V] [Fintype V] in theorem readChoiceValue_roundtrip (q : ProjectionChoice) (v : ChoiceValue V q) : readChoiceValue q (fun _ => fullChoiceValue q v) (fun _ => singleChoiceValue q v) = v := by cases q <;> rfl omit [Module F2 V] [Fintype V] in theorem readChoiceValue_full (q : ProjectionChoice) (full : q = none → V × V) (single : q.isSome = true → V) (h : q = none) : fullChoiceValue q (readChoiceValue q full single) = full h := by subst q rfl omit [Module F2 V] [Fintype V] in theorem readChoiceValue_single (q : ProjectionChoice) (full : q = none → V × V) (single : q.isSome = true → V) (h : q.isSome = true) : singleChoiceValue q (readChoiceValue q full single) = single h := by cases q with | none => simp at h | some i => rfl def choiceValuesToRawTuple (c : Fin k → ProjectionChoice) (fz : (∀ j, ChoiceValue V (c j)) × V) : RawTuple (choiceMask c) V := (fz.2, (fun j => fullChoiceValue (c j.val) (fz.1 j.val)), fun j => singleChoiceValue (c j.val) (fz.1 j.val)) def rawTupleToChoiceValues (c : Fin k → ProjectionChoice) (a : RawTuple (choiceMask c) V) (j : Fin k) : ChoiceValue V (c j) := readChoiceValue (c j) (fun h => a.2.1 ⟨j, (not_mem_choiceMask c j).mpr h⟩) (fun h => a.2.2 ⟨j, by simpa [choiceMask] using h⟩) /-- Choice fibers and the RawTuple model contain exactly the same coefficients, with no unused coordinate and no multiplicity. -/ def choiceValuesRawTupleEquiv (c : Fin k → ProjectionChoice) : ((∀ j, ChoiceValue V (c j)) × V) ≃ RawTuple (choiceMask c) V where toFun := choiceValuesToRawTuple c invFun a := (rawTupleToChoiceValues c a, a.1) left_inv fz := by apply Prod.ext · funext j exact readChoiceValue_roundtrip (c j) (fz.1 j) · rfl right_inv a := by apply Prod.ext · rfl · apply Prod.ext · funext j have hc : c j.val = none := (not_mem_choiceMask c j.val).mp j.property exact readChoiceValue_full (c j.val) _ _ hc · funext j have hc : (c j.val).isSome = true := by simpa [choiceMask] using j.property exact readChoiceValue_single (c j.val) _ _ hc omit [Module F2 V] [Fintype V] in theorem restoreChoiceDraw (q : ProjectionChoice) (v : ChoiceValue V q) : (if q.isSome then Sum.inr (ConcreteExtraction.slotIndex (choiceSlot q), singleChoiceValue q v) else Sum.inl (fullChoiceValue q v)) = choiceEmbed q v := by cases q <;> simp [fullChoiceValue, singleChoiceValue, choiceEmbed, choiceSlot, slotIndex_decodeSlot] omit [Module F2 V] [Fintype V] in theorem tupleDraw_choiceValues (c : Fin k → ProjectionChoice) (fz : (∀ j, ChoiceValue V (c j)) × V) : tupleDraw (choiceMask c) (choiceSlots c) (choiceValuesRawTupleEquiv c fz) = fun j => choiceEmbed (c j) (fz.1 j) := by funext j change (if j ∈ choiceMask c then Sum.inr (ConcreteExtraction.slotIndex (choiceSlot (c j)), singleChoiceValue (c j) (fz.1 j)) else Sum.inl (fullChoiceValue (c j) (fz.1 j))) = choiceEmbed (c j) (fz.1 j) simpa only [choiceMask, Finset.mem_filter, Finset.mem_univ, true_and] using restoreChoiceDraw (c j) (fz.1 j) /-- The whole fixed-choice kernel is precisely the uniform actual-map law. This lemma closes the gap between an arbitrary fixed-mask sampling experiment and the conditioning kernel that actually occurs in drawWeights. -/ theorem fixed_choice_kernel_map_expectation (rhs : Fin k → Bool) (c : Fin k → ProjectionChoice) (H : (ActualHomogeneous.E k →ₗ[F2] V) → ℝ) : (∑ dz : (Fin k → BlockDraw V) × V, (kernelTupleWeight c dz.1 * uniformWeights V dz.2) * H (paddedMap rhs dz.1 dz.2)) = 𝔼 Y : RawPoint (choiceMask c) →ₗ[F2] V, H (Y.comp (rawProjection rhs (choiceMask c) (choiceSlots c))) := by calc _ = ∑ d : Fin k → BlockDraw V, kernelTupleWeight c d * ∑ z : V, uniformWeights V z * H (paddedMap rhs d z) := by rw [Fintype.sum_prod_type] apply Finset.sum_congr rfl intro d _ rw [Finset.mul_sum] apply Finset.sum_congr rfl intro z _ ring _ = ∑ f : ∀ j, ChoiceValue V (c j), uniformWeights _ f * ∑ z : V, uniformWeights V z * H (paddedMap rhs (fun j => choiceEmbed (c j) (f j)) z) := by simp_rw [kernelTuple_uniform_pushforward] exact sum_pushforwardWeight_mul _ _ _ _ = 𝔼 fz : (∀ j, ChoiceValue V (c j)) × V, H (paddedMap rhs (fun j => choiceEmbed (c j) (fz.1 j)) fz.2) := by rw [← sum_uniformWeights_mul, Fintype.sum_prod_type] apply Finset.sum_congr rfl intro f _ rw [Finset.mul_sum] apply Finset.sum_congr rfl intro z _ rw [uniformWeights_prod] ring _ = 𝔼 a : RawTuple (choiceMask c) V, H (paddedMap rhs (tupleDraw (choiceMask c) (choiceSlots c) a) a.1) := by apply Fintype.expect_equiv (choiceValuesRawTupleEquiv c) intro fz rw [tupleDraw_choiceValues] rfl _ = _ := uniform_fixed_projection_tuple rhs (choiceMask c) (choiceSlots c) H theorem actual_projection_mixture_expectation (rhs : Fin k → Bool) (β : ℝ) (H : (ActualHomogeneous.E k →ₗ[F2] V) → ℝ) : (∑ dz : (Fin k → BlockDraw V) × V, drawWeights β k dz * H (paddedMap rhs dz.1 dz.2)) = ∑ c : Fin k → ProjectionChoice, choiceTupleWeight β c * (𝔼 Y : RawPoint (choiceMask c) →ₗ[F2] V, H (Y.comp (rawProjection rhs (choiceMask c) (choiceSlots c)))) := by rw [draw_expectation_choice_mixture] apply Finset.sum_congr rfl intro c _ rw [fixed_choice_kernel_map_expectation] /-- Combining independently uniform `M` and `T` into a map with product codomain is exactly uniform; the preceding law may take `V = K × W`. -/ theorem uniform_rawMap_pair {K W : Type} [AddCommGroup K] [Module F2 K] [Fintype K] [AddCommGroup W] [Module F2 W] [Fintype W] (J : Finset (Fin k)) (H : (RawPoint J →ₗ[F2] K × W) → ℝ) : (𝔼 MT : (RawPoint J →ₗ[F2] K) × (RawPoint J →ₗ[F2] W), H (MT.1.prod MT.2)) = 𝔼 Y : RawPoint J →ₗ[F2] K × W, H Y := by exact Fintype.expect_equiv (LinearMap.prodEquiv F2).toEquiv _ H (fun _ => rfl) section MapSpace variable [Fintype (ActualHomogeneous.E k →ₗ[F2] V)] def paddedMapWeights (rhs : Fin k → Bool) (β : ℝ) : (ActualHomogeneous.E k →ₗ[F2] V) → ℝ := pushforwardWeight (drawWeights β k) (fun dz => paddedMap rhs dz.1 dz.2) omit [Fintype (ActualHomogeneous.E k →ₗ[F2] V)] in theorem paddedMapWeights_eq (rhs : Fin k → Bool) (β : ℝ) (X : ActualHomogeneous.E k →ₗ[F2] V) : paddedMapWeights rhs β X = paddedWeights rhs β (ActualEnumeration.toCoefficients k V X) := by unfold paddedMapWeights paddedWeights pushforwardWeight apply Finset.sum_congr rfl intro dz _ have he : paddedMap rhs dz.1 dz.2 = X ↔ ActualEnumeration.toCoefficients k V (paddedMap rhs dz.1 dz.2) = ActualEnumeration.toCoefficients k V X := (ActualEnumeration.coefficientEquiv k V).symm.injective.eq_iff.symm simp only [he] split_ifs <;> rfl theorem uniform_sourceMap_coordinates (a : ActualEnumeration.Coefficients k V) : uniformWeights (ActualHomogeneous.E k →ₗ[F2] V) (ActualEnumeration.coefficientEquiv k V a) = uniformWeights (ActualEnumeration.Coefficients k V) a := by simp only [uniformWeights] rw [Fintype.card_congr (ActualEnumeration.coefficientEquiv k V)] theorem paddedMapWeights_totalVariation_eq_slope (rhs : Fin k → Bool) (β : ℝ) : UniqueGamesTheorem.Foundations.Information.totalVariation (paddedMapWeights (V := V) rhs β) (uniformWeights (ActualHomogeneous.E k →ₗ[F2] V)) = UniqueGamesTheorem.Foundations.Information.totalVariation (independentWeights (mixture β (singletonPairWeights V)) k) (uniformWeights (Fin k → V × V)) := by have heq : UniqueGamesTheorem.Foundations.Information.totalVariation (paddedMapWeights (V := V) rhs β) (uniformWeights (ActualHomogeneous.E k →ₗ[F2] V)) = UniqueGamesTheorem.Foundations.Information.totalVariation (paddedWeights (V := V) rhs β) (uniformWeights (ActualEnumeration.Coefficients k V)) := by unfold UniqueGamesTheorem.Foundations.Information.totalVariation rw [← (ActualEnumeration.coefficientEquiv k V).sum_comp] simp only [paddedMapWeights_eq, ActualEnumeration.coefficientEquiv, Equiv.coe_fn_mk, ActualEnumeration.to_fromCoefficients] congr 1 apply Finset.sum_congr rfl intro a _ rw [show uniformWeights (ActualHomogeneous.E k →ₗ[F2] V) (ActualEnumeration.fromCoefficients k V a) = uniformWeights (ActualEnumeration.Coefficients k V) a from uniform_sourceMap_coordinates a] rw [heq] exact paddedWeights_totalVariation_eq_slope rhs β theorem paddedMapWeights_totalVariation (rhs : Fin k → Bool) (β : ℝ) (hβ : 0 ≤ β) (hβ' : β ≤ 1) : UniqueGamesTheorem.Foundations.Information.totalVariation (paddedMapWeights (V := V) rhs β) (uniformWeights (ActualHomogeneous.E k →ₗ[F2] V)) ≤ Real.sqrt ((1 + β ^ 2 * ((Fintype.card V : ℝ) - 1) / 3) ^ k - 1) / 2 := by rw [paddedMapWeights_totalVariation_eq_slope] exact paddedSlope_totalVariation V β hβ hβ' k end MapSpace end Law end end UniqueGamesTheorem.Decoder.PaddedLaw end end OAI