import Mathlib import OAI.Computability.DirectedFeedback.Games.RowErasureSliceUniform namespace OAI noncomputable section namespace DFVSGames.Decoder.SelectedPolicies open DFVSGames.Integration.BinaryLinear DFVSGames.Reduction open DFVSGames.Inverse open ActualSource VisiblePolicies MatrixCoordinates open scoped BigOperators Classical attribute [local instance] Classical.propDecidable variable {k s d r : ℕ} def matrixTable (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (occ : ActualGame.Question S k) (T : ActualHomogeneous.E k →ₗ[F2] Vector d) (M : Shortcode.Mat s (1 + 2 * k)) : Alphabet s := TableKeysGame.unfolded S k s d labeling (occ, ((mapEquiv k s).symm M).prod T) def fullTable (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (q : LeftInput S k s d (Vector r)) : Shortcode.Mat s (1 + 2 * k) → Alphabet s := matrixTable S labeling q.occurrences q.complement theorem matrixTable_fold (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (occ : ActualGame.Question S k) (T : ActualHomogeneous.E k →ₗ[F2] Vector d) (h : Alphabet s) (M : Shortcode.Mat s (1 + 2 * k)) : matrixTable S labeling occ T (M + Shortcode.rankOne h (Shortcode.functionalRow (coordinateTau k))) = matrixTable S labeling occ T M + h := by unfold matrixTable rw [mapEquiv_symm_firstBit_shift] have hprod : (((mapEquiv k s).symm M + ActualHomogeneous.tau.smulRight h).prod T) = ((mapEquiv k s).symm M).prod T + ActualHomogeneous.tau.smulRight (h, (0 : Vector d)) := by apply LinearMap.ext intro x apply Prod.ext · rfl · simp rw [hprod] exact TableKeysGame.unfolded_equivariant S k s d labeling (occ, ((mapEquiv k s).symm M).prod T) h def GoodAdvice (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (q : LeftInput S k s d (Vector r)) : Prop := (RowErasureMatrix.family s (1 + 2 * k) r).GoodAdvice (fullTable S labeling q) α (LinearMap.toMatrix' q.rowMap) (mapEquiv k r q.rows) def normalizedDescription (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (hgood : GoodAdvice S labeling α q) : RowErasureDescriptions.Description s (1 + 2 * k) r := RowErasureMatrix.normalizedChosenDescription (fullTable S labeling q) α (LinearMap.toMatrix' q.rowMap) (mapEquiv k r q.rows) hgood (coordinateTau k) (matrixTable_fold S labeling q.occurrences q.complement) hα hsmall theorem normalizedDescription_spec (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (hgood : GoodAdvice S labeling α q) : let F := RowErasureMatrix.family s (1 + 2 * k) r let D := normalizedDescription S labeling α hα hsmall q hgood let D₀ := F.chosenDescription (fullTable S labeling q) α (LinearMap.toMatrix' q.rowMap) (mapEquiv k r q.rows) hgood F.rowMap D = LinearMap.toMatrix' q.rowMap ∧ F.rowValue D = mapEquiv k r q.rows ∧ (F.points D).Nonempty ∧ α / 2 ≤ F.agreement (fullTable S labeling q) D ∧ coordinateTau k D.coefficient = 1 ∧ D.toSlice = D₀.toSlice ∧ F.agreement (fullTable S labeling q) D = F.agreement (fullTable S labeling q) D₀ ∧ ∀ M, M ∈ F.points D₀ → F.target D M = F.target D₀ M := RowErasureMatrix.normalizedChosenDescription_spec (fullTable S labeling q) α (LinearMap.toMatrix' q.rowMap) (mapEquiv k r q.rows) hgood (coordinateTau k) (matrixTable_fold S labeling q.occurrences q.complement) hα hsmall def normalizedResponse (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (hgood : GoodAdvice S labeling α q) : ResponseWitness k where columns := (normalizedDescription S labeling α hα hsmall q hgood).toSlice.columnSpan.map (domainCoordinates k).symm.toLinearMap coefficient := (domainCoordinates k).symm (normalizedDescription S labeling α hα hsmall q hgood).coefficient firstBit := (normalizedDescription_spec S labeling α hα hsmall q hgood).2.2.2.2.1 theorem normalizedResponse_dimension (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (hgood : GoodAdvice S labeling α q) : Module.finrank F2 (normalizedResponse S labeling α hα hsmall q hgood).columns ≤ r := by exact (Submodule.finrank_map_le (domainCoordinates k).symm.toLinearMap (normalizedDescription S labeling α hα hsmall q hgood).toSlice.columnSpan).trans (normalizedDescription S labeling α hα hsmall q hgood).toSlice.columnSpan_finrank_le def goodPredicate (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (w : ResponseWitness k) : Prop := ∃ hgood : GoodAdvice S labeling α q, w = normalizedResponse S labeling α hα hsmall q hgood theorem chosenWitness_eq_normalizedResponse (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (hgood : GoodAdvice S labeling α q) : chosenWitness (goodPredicate S labeling α hα hsmall) q = normalizedResponse S labeling α hα hsmall q hgood := by obtain ⟨hgood', hw⟩ := chosenWitness_spec (goodPredicate S labeling α hα hsmall) q ⟨normalizedResponse S labeling α hα hsmall q hgood, hgood, rfl⟩ exact hw theorem leftPolicy_eq_candidateLaw (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (hgood : GoodAdvice S labeling α q) : leftPolicy (goodPredicate S labeling α hα hsmall) q = let w := normalizedResponse S labeling α hα hsmall q hgood PrivateStrategy.candidateLaw w.columns w.coefficient ActualHomogeneous.tau w.firstBit := by unfold leftPolicy rw [chosenWitness_eq_normalizedResponse S labeling α hα hsmall q hgood] theorem normalized_point_row (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (hgood : GoodAdvice S labeling α q) (M : Shortcode.Mat s (1 + 2 * k)) (hM : M ∈ (RowErasureMatrix.family s (1 + 2 * k) r).points (normalizedDescription S labeling α hα hsmall q hgood)) : q.rowMap.comp ((mapEquiv k s).symm M) = q.rows := by have hs := normalizedDescription_spec S labeling α hα hsmall q hgood have hm := (RowErasureMatrix.family s (1 + 2 * k) r).points_row (normalizedDescription S labeling α hα hsmall q hgood) M hM rw [hs.1, hs.2.1] at hm apply (mapEquiv k r).injective rw [mapEquiv_rowAdvice, LinearEquiv.apply_symm_apply] exact hm theorem normalized_target (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (hgood : GoodAdvice S labeling α q) (M : Shortcode.Mat s (1 + 2 * k)) : (RowErasureMatrix.family s (1 + 2 * k) r).target (normalizedDescription S labeling α hα hsmall q hgood) M = (mapEquiv k s).symm M (normalizedResponse S labeling α hα hsmall q hgood).coefficient + (normalizedDescription S labeling α hα hsmall q hgood).intercept := affine_evaluation k s M _ _ end DFVSGames.Decoder.SelectedPolicies end namespace DFVSGames.Decoder.ActualSeedEvents open Integration.BinaryLinear Reduction ActualSource Foundations.Games open scoped BigOperators Classical noncomputable section attribute [local instance] Fintype.ofFinite local instance homFintype {D F : Type*} [AddCommGroup D] [Module F2 D] [AddCommGroup F] [Module F2 F] [Fintype D] [Fintype F] : Fintype (D →ₗ[F2] F) := Fintype.ofInjective (fun M : D →ₗ[F2] F => (M : D → F)) DFunLike.coe_injective abbrev Seed (S : Source) (k s d r : ℕ) := AdviceLaw.FullSeed k (Fin S.occurrences) (Alphabet s) (Vector d) (Vector r) abbrev Datum (S : Source) (k s d r : ℕ) := AdviceLaw.CompleteData k (Fin S.occurrences) (Alphabet s) (Vector d) (Vector r) def law (S : Source) (k s d r : ℕ) (β : ℝ) (hβ : 0 ≤ β) (hβ' : β ≤ 1) : FiniteDistribution (Seed S k s d r) := AdviceLaw.fullSeedLaw (V := Ambient s d) (FiniteDistribution.uniform (ActualGame.Question S k)) (FiniteDistribution.uniform (Alphabet s →ₗ[F2] Vector r)) β hβ hβ' def draw {S : Source} {k s d r : ℕ} (x : Seed S k s d r) := AdviceLaw.seedToActualDraw x.1.1 x.1.2 x.2 def pad (S : Source) (k s d r : ℕ) (x : Seed S k s d r) : ActualEvents.Sample S k s d r := ActualEvents.fullTableEquiv S k s d r (AdviceLaw.fullSeedPad (fun i => toBit (ActualGame.rhs S i)) x) def slice (S : Source) (k s d r : ℕ) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) : Seed S k s d r → Bool := fun x => ActualEvents.sliceEvent S k s d r labeling α (pad S k s d r x) def targetHit (S : Source) (k s d r : ℕ) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) : Seed S k s d r → Bool := fun x => ActualEvents.targetHit S k s d r labeling α (pad S k s d r x) theorem pad_eq (S : Source) (k s d r : ℕ) (x : Seed S k s d r) : pad S k s d r x = (((draw x).occurrences, AdviceExperiment.paddedComplement (ActualGame.rhs S) (draw x)), (LinearMap.toMatrix' (draw x).rowMap, MatrixCoordinates.mapEquiv k s (AdviceExperiment.paddedMatrix (ActualGame.rhs S) (draw x)))) := rfl theorem slice_eq_selectedEvent (S : Source) (k s d r : ℕ) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (x : Seed S k s d r) : slice S k s d r labeling α x = decide ((Inverse.RowErasureMatrix.family s (1 + 2 * k) r).selectedEvent (SelectedPolicies.fullTable S labeling (AdviceExperiment.leftObservation (ActualGame.rhs S) (draw x))) α (LinearMap.toMatrix' (draw x).rowMap) (MatrixCoordinates.mapEquiv k s (AdviceExperiment.paddedMatrix (ActualGame.rhs S) (draw x)))) := rfl theorem targetHit_eq_selectedMatch (S : Source) (k s d r : ℕ) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (x : Seed S k s d r) : targetHit S k s d r labeling α x = decide ((Inverse.RowErasureMatrix.family s (1 + 2 * k) r).selectedMatch (SelectedPolicies.fullTable S labeling (AdviceExperiment.leftObservation (ActualGame.rhs S) (draw x))) α (LinearMap.toMatrix' (draw x).rowMap) (MatrixCoordinates.mapEquiv k s (AdviceExperiment.paddedMatrix (ActualGame.rhs S) (draw x)))) := rfl theorem slice_good (S : Source) (k s d r : ℕ) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (x : Seed S k s d r) (hx : slice S k s d r labeling α x = true) : SelectedPolicies.GoodAdvice S labeling α (AdviceExperiment.leftObservation (ActualGame.rhs S) (draw x)) := by rw [slice_eq_selectedEvent] at hx have h := (Inverse.RowErasureMatrix.family s (1 + 2 * k) r).selectedEvent_good (SelectedPolicies.fullTable S labeling (AdviceExperiment.leftObservation (ActualGame.rhs S) (draw x))) α (LinearMap.toMatrix' (draw x).rowMap) (MatrixCoordinates.mapEquiv k s (AdviceExperiment.paddedMatrix (ActualGame.rhs S) (draw x))) (of_decide_eq_true hx) change (Inverse.RowErasureMatrix.family s (1 + 2 * k) r).GoodAdvice (SelectedPolicies.fullTable S labeling (AdviceExperiment.leftObservation (ActualGame.rhs S) (draw x))) α (LinearMap.toMatrix' (draw x).rowMap) (MatrixCoordinates.mapEquiv k r ((draw x).rowMap.comp (AdviceExperiment.paddedMatrix (ActualGame.rhs S) (draw x)))) rw [MatrixCoordinates.mapEquiv_rowAdvice] exact h end end DFVSGames.Decoder.ActualSeedEvents namespace DFVSGames.Decoder.ActualSeedVariation open Integration.BinaryLinear Reduction ActualSource Foundations.Games open scoped BigOperators Classical noncomputable section attribute [local instance] Fintype.ofFinite local instance homFintype {D F : Type*} [AddCommGroup D] [Module F2 D] [AddCommGroup F] [Module F2 F] [Fintype D] [Fintype F] : Fintype (D →ₗ[F2] F) := Fintype.ofInjective (fun M : D →ₗ[F2] F => (M : D → F)) DFunLike.coe_injective theorem uniform_pushforward_equiv {X Y : Type*} [Fintype X] [Fintype Y] [Nonempty X] [Nonempty Y] (e : X ≃ Y) : (FiniteDistribution.uniform X).pushforward e = FiniteDistribution.uniform Y := by rw [FiniteDistribution.pushforward_equiv] apply FiniteDistribution.eq_of_weight_eq intro y simp only [FiniteDistribution.transport, FiniteDistribution.uniform, Fintype.card_congr e] theorem totalVariation_pushforward_equiv {X Y : Type*} [Fintype X] [Fintype Y] (μ ν : FiniteDistribution X) (e : X ≃ Y) : (μ.pushforward e).totalVariation (ν.pushforward e) = μ.totalVariation ν := by rw [FiniteDistribution.pushforward_equiv, FiniteDistribution.pushforward_equiv] unfold FiniteDistribution.totalVariation FiniteDistribution.transport congr 1 exact e.symm.sum_comp (fun x => |μ.weight x - ν.weight x|) theorem ideal_full_uniform (S : Source) (k s d r : ℕ) : AdviceLaw.withKernel ((FiniteDistribution.uniform (ActualGame.Question S k)).product (FiniteDistribution.uniform (Alphabet s →ₗ[F2] Vector r))) (fun _ => FiniteDistribution.uniform (ActualGame.Map k s d)) = FiniteDistribution.uniform (ActualEvents.FullTableSample S k s d r) := by apply FiniteDistribution.eq_of_weight_eq intro p simp only [AdviceLaw.withKernel, FiniteDistribution.product, FiniteDistribution.uniform, Fintype.card_prod, Nat.cast_mul] ring theorem ideal_pad_coordinates (S : Source) (k s d r : ℕ) : (AdviceLaw.withKernel ((FiniteDistribution.uniform (ActualGame.Question S k)).product (FiniteDistribution.uniform (Alphabet s →ₗ[F2] Vector r))) (fun _ => FiniteDistribution.uniform (ActualGame.Map k s d))).pushforward (ActualEvents.fullTableEquiv S k s d r) = ActualEvents.unrestricted S k s d r := by rw [ideal_full_uniform] exact uniform_pushforward_equiv _ theorem actual_totalVariation_le_slope (S : Source) (k s d r : ℕ) (β : ℝ) (hβ : 0 ≤ β) (hβ' : β ≤ 1) : (ActualEvents.unrestricted S k s d r).totalVariation ((ActualSeedEvents.law S k s d r β hβ hβ').pushforward (ActualSeedEvents.pad S k s d r)) ≤ Foundations.Information.totalVariation (SparseLaw.independentWeights (SparseLaw.mixture β (SparseLaw.singletonPairWeights (Ambient s d))) k) (SparseLaw.uniformWeights (Fin k → Ambient s d × Ambient s d)) := by rw [FiniteDistribution.totalVariation_comm] have h := AdviceLaw.fullSeed_totalVariation_le_slope (V := Ambient s d) (FiniteDistribution.uniform (ActualGame.Question S k)) (FiniteDistribution.uniform (Alphabet s →ₗ[F2] Vector r)) (fun i => toBit (ActualGame.rhs S i)) β hβ hβ' rw [← ideal_pad_coordinates S k s d r] change ((ActualSeedEvents.law S k s d r β hβ hβ').pushforward (fun x => ActualEvents.fullTableEquiv S k s d r (AdviceLaw.fullSeedPad (fun i => toBit (ActualGame.rhs S i)) x))).totalVariation _ ≤ _ rw [← FiniteDistribution.pushforward_comp, totalVariation_pushforward_equiv] convert h using 1 <;> congr 4 ; exact Subsingleton.elim _ _ end end DFVSGames.Decoder.ActualSeedVariation noncomputable section namespace DFVSGames.Decoder.SelectedDecoding open DFVSGames.Integration.BinaryLinear DFVSGames.Reduction DFVSGames.Soundness open DFVSGames.Inverse open ActualSource VisiblePolicies SelectedPolicies MatrixCoordinates open scoped BigOperators Classical attribute [local instance] Classical.propDecidable attribute [local instance] Fintype.ofFinite local instance homFintype {D F : Type*} [AddCommGroup D] [Module F2 D] [AddCommGroup F] [Module F2 F] [Fintype D] [Fintype F] : Fintype (D →ₗ[F2] F) := Fintype.ofInjective (fun M : D →ₗ[F2] F => (M : D → F)) DFunLike.coe_injective instance affineSliceFintype {E K L : Type*} [AddCommGroup E] [Module F2 E] [AddCommGroup K] [Module F2 K] [AddCommGroup L] [Module F2 L] [Fintype (E →ₗ[F2] K)] (A : K →ₗ[F2] L) (Q : Submodule F2 E) (Mstar : E →ₗ[F2] K) : Fintype (RowErasureSliceQuotient.AffineSlice A Q Mstar) := by unfold RowErasureSliceQuotient.AffineSlice infer_instance variable {k s d r : ℕ} theorem selectedEvent_iff_normalized (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (hgood : GoodAdvice S labeling α q) (M : Shortcode.Mat s (1 + 2 * k)) (hrow : RowErasureMatrix.rowAdvice (LinearMap.toMatrix' q.rowMap) M = mapEquiv k r q.rows) : (RowErasureMatrix.family s (1 + 2 * k) r).selectedEvent (fullTable S labeling q) α (LinearMap.toMatrix' q.rowMap) M ↔ M ∈ (RowErasureMatrix.family s (1 + 2 * k) r).points (normalizedDescription S labeling α hα hsmall q hgood) := by have he := (RowErasureMatrix.family s (1 + 2 * k) r).selectedEvent_iff_of_advice (fullTable S labeling q) α (LinearMap.toMatrix' q.rowMap) (mapEquiv k r q.rows) hgood M hrow obtain ⟨_, _, _, _, _, hslice, _, _⟩ := normalizedDescription_spec S labeling α hα hsmall q hgood rw [show (RowErasureMatrix.family s (1 + 2 * k) r).points (normalizedDescription S labeling α hα hsmall q hgood) = (RowErasureMatrix.family s (1 + 2 * k) r).points ((RowErasureMatrix.family s (1 + 2 * k) r).chosenDescription (fullTable S labeling q) α (LinearMap.toMatrix' q.rowMap) (mapEquiv k r q.rows) hgood) from congrArg Shortcode.Slice.points hslice] exact he theorem selectedMatch_iff_normalized (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (q : LeftInput S k s d (Vector r)) (hgood : GoodAdvice S labeling α q) (M : Shortcode.Mat s (1 + 2 * k)) (hrow : RowErasureMatrix.rowAdvice (LinearMap.toMatrix' q.rowMap) M = mapEquiv k r q.rows) : (RowErasureMatrix.family s (1 + 2 * k) r).selectedMatch (fullTable S labeling q) α (LinearMap.toMatrix' q.rowMap) M ↔ M ∈ (RowErasureMatrix.family s (1 + 2 * k) r).points (normalizedDescription S labeling α hα hsmall q hgood) ∧ fullTable S labeling q M = (mapEquiv k s).symm M (normalizedResponse S labeling α hα hsmall q hgood).coefficient + (normalizedDescription S labeling α hα hsmall q hgood).intercept := by let F := RowErasureMatrix.family s (1 + 2 * k) r let D := normalizedDescription S labeling α hα hsmall q hgood let D₀ := F.chosenDescription (fullTable S labeling q) α (LinearMap.toMatrix' q.rowMap) (mapEquiv k r q.rows) hgood have he := F.selectedMatch_iff_of_advice (fullTable S labeling q) α (LinearMap.toMatrix' q.rowMap) (mapEquiv k r q.rows) hgood M hrow obtain ⟨_, _, _, _, _, hslice, _, htarget⟩ := normalizedDescription_spec S labeling α hα hsmall q hgood have hp : F.points D = F.points D₀ := congrArg Shortcode.Slice.points hslice rw [← normalized_target S labeling α hα hsmall q hgood M] constructor · intro h obtain ⟨hm, hf⟩ := he.mp h refine ⟨hp.symm ▸ hm, ?_⟩ rw [htarget M hm] exact hf · rintro ⟨hm, hf⟩ have hm₀ : M ∈ F.points D₀ := hp ▸ hm apply he.mpr refine ⟨hm₀, ?_⟩ rw [← htarget M hm₀] exact hf theorem rowKernel_reciprocal_le (A : Alphabet s →ₗ[F2] Vector r) : 1 / (Fintype.card A.ker : ℝ) ≤ 1 / (2 : ℝ) ^ (s - r) := by have hk : 2 ^ (s - r) ≤ Fintype.card A.ker := by simpa only [Nat.card_eq_fintype_card] using binary_kernel_card_lower A have hk' : (2 : ℝ) ^ (s - r) ≤ (Fintype.card A.ker : ℝ) := by exact_mod_cast hk exact one_div_le_one_div_of_le (by positivity) hk' def transferredAgreement (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (draw : AdviceExperiment.Draw k (Fin S.occurrences) (Alphabet s) (Vector d) (Vector r)) (w : ResponseWitness k) (u : Alphabet s) (Mstar : RawPartnerTarget.RawPoint draw.singletons →ₗ[F2] Alphabet s) : ℝ := 𝔼 M : RowErasureSliceQuotient.AffineSlice draw.rowMap (w.columns.map (AdviceExperiment.projection (ActualGame.rhs S) draw)) Mstar, if TableKeysRestoration.projectedAnswer S k s d labeling draw.singletons (RawPrivateTable.supported draw.singletons (ActualGame.names S) draw.occurrences draw.positions) (M.val.prod draw.complement) = M.val (AdviceExperiment.projection (ActualGame.rhs S) draw w.coefficient) + u then (1 : ℝ) else 0 theorem observedAgreement_lower (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (draw : AdviceExperiment.Draw k (Fin S.occurrences) (Alphabet s) (Vector d) (Vector r)) (hgood : GoodAdvice S labeling α (AdviceExperiment.leftObservation (ActualGame.rhs S) draw)) (Mstar : RawPartnerTarget.RawPoint draw.singletons →ₗ[F2] Alphabet s) (hstar : draw.rowMap.comp Mstar = draw.rowMap.comp draw.hiddenMatrix) (hagreement : α / 4 ≤ transferredAgreement S labeling draw (normalizedResponse S labeling α hα hsmall (AdviceExperiment.leftObservation (ActualGame.rhs S) draw) hgood) (normalizedDescription S labeling α hα hsmall (AdviceExperiment.leftObservation (ActualGame.rhs S) draw) hgood).intercept Mstar) : (α / 8) ^ 2 / (2 : ℝ) ^ (s * r) / (2 : ℝ) ^ r ≤ observedAgreement S labeling (goodPredicate S labeling α hα hsmall) draw := by let q := AdviceExperiment.leftObservation (ActualGame.rhs S) draw let w := normalizedResponse S labeling α hα hsmall q hgood let u := (normalizedDescription S labeling α hα hsmall q hgood).intercept have hH : Module.finrank F2 draw.rowMap.ker ≤ s := by simpa only [Module.finrank_fin_fun] using draw.rowMap.ker.finrank_le have hs : 1 / (Fintype.card draw.rowMap.ker : ℝ) ≤ α / 8 := (rowKernel_reciprocal_le draw.rowMap).trans hsmall.le have h := TransferredDecoding.actual_transferred_decoding S labeling draw.singletons draw.occurrences draw.positions draw.rowMap (AdviceFibers.observe draw.rowMap draw.hiddenMatrix) draw.complement Mstar hstar w.columns w.coefficient w.firstBit u α hα.le s r hH (normalizedResponse_dimension S labeling α hα hsmall q hgood) hs hagreement rw [observedAgreement_eq_private, chosenWitness_eq_normalizedResponse S labeling α hα hsmall _ hgood] exact h end DFVSGames.Decoder.SelectedDecoding end noncomputable section namespace DFVSGames.Decoder.ProjectedColumnSlice open DFVSGames.Integration.BinaryLinear DFVSGames.Reduction DFVSGames.Soundness open DFVSGames.Inverse open ActualSource VisiblePolicies SelectedPolicies MatrixCoordinates open scoped BigOperators Classical attribute [local instance] Classical.propDecidable variable {k s d r : ℕ} section Algebra variable {V : Type*} [AddCommGroup V] [Module F2 V] theorem column_agreement_iff (Q : Submodule F2 (Vector (1 + 2 * k))) (π : ActualHomogeneous.E k →ₗ[F2] V) (M Mstar : V →ₗ[F2] Alphabet s) : (∀ x ∈ Q, M (π ((domainCoordinates k).symm x)) = Mstar (π ((domainCoordinates k).symm x))) ↔ ∀ v ∈ (Q.map (domainCoordinates k).symm.toLinearMap).map π, M v = Mstar v := by constructor · intro h v hv obtain ⟨z, hz, rfl⟩ := Submodule.mem_map.mp hv obtain ⟨x, hx, rfl⟩ := Submodule.mem_map.mp hz exact h x hx · intro h x hx apply h exact Submodule.mem_map.mpr ⟨(domainCoordinates k).symm x, Submodule.mem_map.mpr ⟨x, hx, rfl⟩, rfl⟩ theorem contains_padded_iff (D : RowErasureDescriptions.Description s (1 + 2 * k) r) (A : Alphabet s →ₗ[F2] Vector r) (hDrow : (RowErasureMatrix.family s (1 + 2 * k) r).rowMap D = LinearMap.toMatrix' A) (π : ActualHomogeneous.E k →ₗ[F2] V) (Mstar : V →ₗ[F2] Alphabet s) (hstar : mapEquiv k s (Mstar.comp π) ∈ D.toSlice.points) (M : V →ₗ[F2] Alphabet s) (hrow : A.comp M = A.comp Mstar) : mapEquiv k s (M.comp π) ∈ D.toSlice.points ↔ ∀ v ∈ (D.toSlice.columnSpan.map (domainCoordinates k).symm.toLinearMap).map π, M v = Mstar v := by have hr : D.toSlice.rowMap = A := by change Matrix.toLin' D.1 = A change D.1 = LinearMap.toMatrix' A at hDrow rw [hDrow, Matrix.toLin'_toMatrix'] have hc (N : V →ₗ[F2] Alphabet s) : Matrix.toLin' (mapEquiv k s (N.comp π)) = (N.comp π).comp (domainCoordinates k).symm.toLinearMap := by rw [mapEquiv_apply, Matrix.toLin'_toMatrix'] have hs : D.toSlice.Contains (mapEquiv k s (Mstar.comp π)) := (Finset.mem_filter.mp hstar).2 have he := D.toSlice.contains_iff_inSlice (mapEquiv k s (Mstar.comp π)) hs (mapEquiv k s (M.comp π)) rw [AffineWitness.InSlice, hr, hc, hc] at he have hrows : A.comp ((M.comp π).comp (domainCoordinates k).symm.toLinearMap) = A.comp ((Mstar.comp π).comp (domainCoordinates k).symm.toLinearMap) := by apply LinearMap.ext intro x exact LinearMap.congr_fun hrow (π ((domainCoordinates k).symm x)) constructor · intro h have hh := he.mp (Finset.mem_filter.mp h).2 exact (column_agreement_iff D.toSlice.columnSpan π M Mstar).mp hh.2 · intro h apply Finset.mem_filter.mpr exact ⟨Finset.mem_univ _, he.mpr ⟨hrows, (column_agreement_iff D.toSlice.columnSpan π M Mstar).mpr h⟩⟩ def paddedSliceEquiv (D : RowErasureDescriptions.Description s (1 + 2 * k) r) (A : Alphabet s →ₗ[F2] Vector r) (hDrow : (RowErasureMatrix.family s (1 + 2 * k) r).rowMap D = LinearMap.toMatrix' A) (π : ActualHomogeneous.E k →ₗ[F2] V) (Mstar : V →ₗ[F2] Alphabet s) (hstar : mapEquiv k s (Mstar.comp π) ∈ D.toSlice.points) : {M : V →ₗ[F2] Alphabet s // A.comp M = A.comp Mstar ∧ mapEquiv k s (M.comp π) ∈ D.toSlice.points} ≃ RowErasureSliceQuotient.AffineSlice A ((D.toSlice.columnSpan.map (domainCoordinates k).symm.toLinearMap).map π) Mstar where toFun M := ⟨M.val, M.property.1, (contains_padded_iff D A hDrow π Mstar hstar M.val M.property.1).mp M.property.2⟩ invFun M := ⟨M.val, M.property.1, (contains_padded_iff D A hDrow π Mstar hstar M.val M.property.1).mpr M.property.2⟩ left_inv _ := rfl right_inv _ := rfl theorem paddedSlice_expect (D : RowErasureDescriptions.Description s (1 + 2 * k) r) (A : Alphabet s →ₗ[F2] Vector r) (hDrow : (RowErasureMatrix.family s (1 + 2 * k) r).rowMap D = LinearMap.toMatrix' A) (π : ActualHomogeneous.E k →ₗ[F2] V) (Mstar : V →ₗ[F2] Alphabet s) (hstar : mapEquiv k s (Mstar.comp π) ∈ D.toSlice.points) [Fintype {M : V →ₗ[F2] Alphabet s // A.comp M = A.comp Mstar ∧ mapEquiv k s (M.comp π) ∈ D.toSlice.points}] [Fintype (RowErasureSliceQuotient.AffineSlice A ((D.toSlice.columnSpan.map (domainCoordinates k).symm.toLinearMap).map π) Mstar)] (f : (V →ₗ[F2] Alphabet s) → ℝ) : (𝔼 M : {M : V →ₗ[F2] Alphabet s // A.comp M = A.comp Mstar ∧ mapEquiv k s (M.comp π) ∈ D.toSlice.points}, f M.val) = 𝔼 M : RowErasureSliceQuotient.AffineSlice A ((D.toSlice.columnSpan.map (domainCoordinates k).symm.toLinearMap).map π) Mstar, f M.val := by exact Fintype.expect_equiv (paddedSliceEquiv D A hDrow π Mstar hstar) _ _ (fun _ => rfl) end Algebra theorem fullTable_padded (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (draw : AdviceExperiment.Draw k (Fin S.occurrences) (Alphabet s) (Vector d) (Vector r)) (M : RawPartnerTarget.RawPoint draw.singletons →ₗ[F2] Alphabet s) : fullTable S labeling (AdviceExperiment.leftObservation (ActualGame.rhs S) draw) (mapEquiv k s (M.comp (AdviceExperiment.projection (ActualGame.rhs S) draw))) = TableKeysRestoration.projectedAnswer S k s d labeling draw.singletons (RawPrivateTable.supported draw.singletons (ActualGame.names S) draw.occurrences draw.positions) (M.prod draw.complement) := by unfold fullTable matrixTable rw [LinearEquiv.symm_apply_apply, TableKeysRestoration.projectedAnswer_pullback] ; rfl theorem normalized_contains_iff (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (draw : AdviceExperiment.Draw k (Fin S.occurrences) (Alphabet s) (Vector d) (Vector r)) (hgood : GoodAdvice S labeling α (AdviceExperiment.leftObservation (ActualGame.rhs S) draw)) (Mstar : RawPartnerTarget.RawPoint draw.singletons →ₗ[F2] Alphabet s) (hstar : mapEquiv k s (Mstar.comp (AdviceExperiment.projection (ActualGame.rhs S) draw)) ∈ (normalizedDescription S labeling α hα hsmall (AdviceExperiment.leftObservation (ActualGame.rhs S) draw) hgood).toSlice.points) (M : RawPartnerTarget.RawPoint draw.singletons →ₗ[F2] Alphabet s) (hrow : draw.rowMap.comp M = draw.rowMap.comp Mstar) : mapEquiv k s (M.comp (AdviceExperiment.projection (ActualGame.rhs S) draw)) ∈ (normalizedDescription S labeling α hα hsmall (AdviceExperiment.leftObservation (ActualGame.rhs S) draw) hgood).toSlice.points ↔ ∀ v ∈ (normalizedResponse S labeling α hα hsmall (AdviceExperiment.leftObservation (ActualGame.rhs S) draw) hgood).columns.map (AdviceExperiment.projection (ActualGame.rhs S) draw), M v = Mstar v := by exact contains_padded_iff _ draw.rowMap (normalizedDescription_spec S labeling α hα hsmall _ hgood).1 (AdviceExperiment.projection (ActualGame.rhs S) draw) Mstar hstar M hrow theorem normalized_target_padded (S : Source) (labeling : Fin (TableKeysGame.vertexCount S k s d) → Fin (2 ^ s)) (α : ℝ) (hα : 0 < α) (hsmall : 1 / (2 : ℝ) ^ (s - r) < α / 8) (draw : AdviceExperiment.Draw k (Fin S.occurrences) (Alphabet s) (Vector d) (Vector r)) (hgood : GoodAdvice S labeling α (AdviceExperiment.leftObservation (ActualGame.rhs S) draw)) (M : RawPartnerTarget.RawPoint draw.singletons →ₗ[F2] Alphabet s) : (RowErasureMatrix.family s (1 + 2 * k) r).target (normalizedDescription S labeling α hα hsmall (AdviceExperiment.leftObservation (ActualGame.rhs S) draw) hgood) (mapEquiv k s (M.comp (AdviceExperiment.projection (ActualGame.rhs S) draw))) = M (AdviceExperiment.projection (ActualGame.rhs S) draw (normalizedResponse S labeling α hα hsmall (AdviceExperiment.leftObservation (ActualGame.rhs S) draw) hgood).coefficient) + (normalizedDescription S labeling α hα hsmall (AdviceExperiment.leftObservation (ActualGame.rhs S) draw) hgood).intercept := by rw [normalized_target, LinearEquiv.symm_apply_apply] ; rfl end DFVSGames.Decoder.ProjectedColumnSlice end namespace DFVSGames.Decoder.UniformConditioning open Foundations.Games open scoped BigOperators Classical noncomputable section variable {Ω : Type*} [Fintype Ω] theorem sum_over_event (given : Ω → Bool) (f : Ω → ℝ) : (∑ x, if given x then f x else 0) = ∑ x : {x : Ω // given x = true}, f x.val := by rw [← Finset.sum_filter] exact Finset.sum_subtype _ (fun x => by simp) f theorem probability_as_subtype_sum (μ : FiniteDistribution Ω) (given : Ω → Bool) : μ.probability given = ∑ x : {x : Ω // given x = true}, μ.weight x.val := sum_over_event given μ.weight theorem probability_and_as_subtype_sum (μ : FiniteDistribution Ω) (given event : Ω → Bool) : μ.probability (fun x => given x && event x) = ∑ x : {x : Ω // given x = true}, if event x.val then μ.weight x.val else 0 := by calc _ = ∑ x, if given x then (if event x then μ.weight x else 0) else 0 := by apply Finset.sum_congr rfl intro x _ change (if given x && event x then μ.weight x else 0) = _ cases given x <;> cases event x <;> rfl _ = _ := sum_over_event given _ theorem probability_of_constant_weight (μ : FiniteDistribution Ω) (given : Ω → Bool) (c : ℝ) (hconstant : ∀ x, given x = true → μ.weight x = c) : μ.probability given = (Fintype.card {x : Ω // given x = true} : ℝ) * c := by rw [probability_as_subtype_sum] calc _ = ∑ _x : {x : Ω // given x = true}, c := by apply Finset.sum_congr rfl intro x _ exact hconstant x.val x.property _ = _ := by simp [nsmul_eq_mul] theorem condition_probability_uniform (μ : FiniteDistribution Ω) (given event : Ω → Bool) (positive : 0 < μ.probability given) (c : ℝ) (hconstant : ∀ x, given x = true → μ.weight x = c) : (μ.condition given positive).probability event = 𝔼 x : {x : Ω // given x = true}, if event x.val then (1 : ℝ) else 0 := by have hp := probability_of_constant_weight μ given c hconstant have hc : c ≠ 0 := by intro hz rw [hp, hz, mul_zero] at positive exact (lt_irrefl 0) positive have hn : (Fintype.card {x : Ω // given x = true} : ℝ) ≠ 0 := by intro hz rw [hp, hz, zero_mul] at positive exact (lt_irrefl 0) positive rw [FiniteDistribution.probability_condition, probability_and_as_subtype_sum, hp, Fintype.expect_eq_sum_div_card] have hnum : (∑ x : {x : Ω // given x = true}, if event x.val then μ.weight x.val else 0) = c * ∑ x : {x : Ω // given x = true}, if event x.val then (1 : ℝ) else 0 := by rw [Finset.mul_sum] apply Finset.sum_congr rfl intro x _ rw [hconstant x.val x.property] cases event x.val <;> simp rw [hnum] field_simp [hc, hn] theorem condition_probability_equiv {Y : Type*} [Fintype Y] (μ : FiniteDistribution Ω) (given event : Ω → Bool) (positive : 0 < μ.probability given) (c : ℝ) (hconstant : ∀ x, given x = true → μ.weight x = c) (e : {x : Ω // given x = true} ≃ Y) (target : Y → Bool) (hevent : ∀ x, event x.val = target (e x)) : (μ.condition given positive).probability event = 𝔼 y : Y, if target y then (1 : ℝ) else 0 := by rw [condition_probability_uniform μ given event positive c hconstant] apply Fintype.expect_equiv e intro x rw [hevent x] end end DFVSGames.Decoder.UniformConditioning end OAI