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Add lean source and binary files (part 61)
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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