roseking's picture
Add lean source and binary files (part 63)
760f90e verified
Raw History Blame Contribute Delete
7.81 kB
import OAI.Computability.UniqueGames.Games.FactorizationLemmas
import OAI.Computability.UniqueGames.Games.Variation
namespace OAI
section
/-! Exact variation decomposition for the two choices of revealed endpoint.
The support of the actual reveal profiles makes both branch identities valid,
including zero-probability revealed endpoints. -/
namespace UniqueGamesTheorem.Foundations.Repetition
open scoped BigOperators
noncomputable section
variable {S X Y : Type*} [Fintype S] [Fintype X] [Fintype Y]
[DecidableEq X] [DecidableEq Y]
def maskedJoint (p : S × (X × Y) → ℝ) : (S × (X ⊕ Y)) × (X × Y) → ℝ := fun z =>
(if z.1.2 = Sum.inl z.2.1 then p (z.1.1, z.2) / 2 else 0) +
(if z.1.2 = Sum.inr z.2.2 then p (z.1.1, z.2) / 2 else 0)
def maskedModel (μ : Games.FiniteDistribution (X × Y)) (p : S × (X × Y) → ℝ) :
(S × (X ⊕ Y)) × (X × Y) → ℝ := fun z =>
Information.firstMarginal (maskedJoint p) z.1 * (revealProfile μ z.1.2).weight z.2
def leftRevealModel (μ : Games.FiniteDistribution (X × Y)) (p : S × (X × Y) → ℝ) :
S × (X × Y) → ℝ := fun z =>
(∑ y, p (z.1, (z.2.1, y))) * (revealProfile μ (Sum.inl z.2.1)).weight z.2
def rightRevealModel (μ : Games.FiniteDistribution (X × Y)) (p : S × (X × Y) → ℝ) :
S × (X × Y) → ℝ := fun z =>
(∑ x, p (z.1, (x, z.2.2))) * (revealProfile μ (Sum.inr z.2.2)).weight z.2
theorem sum_maskedJoint (p : S × (X × Y) → ℝ) :
(∑ z, maskedJoint p z) = ∑ z, p z := by
classical
have hrow (s : S) (q : X × Y) :
(∑ r : X ⊕ Y, maskedJoint p ((s,r),q)) = p (s,q) := by
simp [maskedJoint]
calc
_ = ∑ s : S, ∑ r : X ⊕ Y, ∑ q : X × Y, maskedJoint p ((s,r),q) := by
simp only [Fintype.sum_prod_type]
_ = ∑ s : S, ∑ q : X × Y, p (s,q) := by
apply Finset.sum_congr rfl
intro s _
rw [Finset.sum_comm]
simp_rw [hrow]
_ = _ := (Fintype.sum_prod_type _).symm
theorem maskedJoint_isProbability_iff (p : S × (X × Y) → ℝ) :
Information.IsProbability (maskedJoint p) ↔ Information.IsProbability p := by
classical
constructor
· intro h
constructor
· intro z
have hp := h.1 ((z.1,Sum.inl z.2.1),z.2)
simp [maskedJoint] at hp
linarith
· rw [← sum_maskedJoint]
exact h.2
· intro h
constructor
· intro z
have hp : 0 ≤ p (z.1.1,z.2) / 2 := div_nonneg (h.1 _) (by norm_num)
dsimp [maskedJoint]
split_ifs <;> linarith
· rw [sum_maskedJoint]
exact h.2
omit [Fintype S] in
theorem maskedJoint_firstMarginal_inl (p : S × (X × Y) → ℝ) (s : S) (x : X) :
Information.firstMarginal (maskedJoint p) (s, Sum.inl x) =
(∑ y, p (s, (x, y))) / 2 := by
simp [Information.firstMarginal, maskedJoint, Fintype.sum_prod_type,
div_eq_mul_inv, Finset.sum_mul]
rw [Finset.sum_comm]
simp
omit [Fintype S] in
theorem maskedJoint_firstMarginal_inr (p : S × (X × Y) → ℝ) (s : S) (y : Y) :
Information.firstMarginal (maskedJoint p) (s, Sum.inr y) =
(∑ x, p (s, (x, y))) / 2 := by
simp [Information.firstMarginal, maskedJoint, Fintype.sum_prod_type,
div_eq_mul_inv, Finset.sum_mul]
private theorem abs_half_sub_half_mul (a b c : ℝ) :
|a / 2 - b / 2 * c| = |a - b * c| / 2 := by
rw [show a / 2 - b / 2 * c = (a - b * c) / 2 by ring, abs_div]
norm_num
omit [Fintype S] in
theorem abs_masked_inl (μ : Games.FiniteDistribution (X × Y))
(p : S × (X × Y) → ℝ) (s : S) (u x : X) (y : Y) :
|maskedJoint p ((s, Sum.inl u), (x, y)) - maskedModel μ p ((s, Sum.inl u), (x, y))| =
if x = u then |p (s, (x, y)) - leftRevealModel μ p (s, (x, y))| / 2 else 0 := by
by_cases hx : x = u
· subst x
simp only [maskedModel, maskedJoint_firstMarginal_inl]
simpa [maskedJoint, leftRevealModel] using
abs_half_sub_half_mul (p (s, (u, y))) (∑ v, p (s, (u, v)))
((revealProfile μ (Sum.inl u)).weight (u, y))
· have hs := revealProfile_inl_support μ u (x, y) hx
simp [maskedJoint, maskedModel, hs, hx, Ne.symm hx]
omit [Fintype S] in
theorem abs_masked_inr (μ : Games.FiniteDistribution (X × Y))
(p : S × (X × Y) → ℝ) (s : S) (v : Y) (x : X) (y : Y) :
|maskedJoint p ((s, Sum.inr v), (x, y)) - maskedModel μ p ((s, Sum.inr v), (x, y))| =
if y = v then |p (s, (x, y)) - rightRevealModel μ p (s, (x, y))| / 2 else 0 := by
by_cases hy : y = v
· subst y
simp only [maskedModel, maskedJoint_firstMarginal_inr]
simpa [maskedJoint, rightRevealModel] using
abs_half_sub_half_mul (p (s, (x, v))) (∑ u, p (s, (u, v)))
((revealProfile μ (Sum.inr v)).weight (x, v))
· have hs := revealProfile_inr_support μ v (x, y) hy
simp [maskedJoint, maskedModel, hs, hy, Ne.symm hy]
theorem masked_totalVariation_identity (μ : Games.FiniteDistribution (X × Y))
(p : S × (X × Y) → ℝ) :
2 * Information.totalVariation (maskedJoint p) (maskedModel μ p) =
Information.totalVariation p (leftRevealModel μ p) +
Information.totalVariation p (rightRevealModel μ p) := by
have hleft (s : S) :
(∑ u : X, ∑ q : X × Y,
|maskedJoint p ((s, Sum.inl u), q) - maskedModel μ p ((s, Sum.inl u), q)|) =
(∑ q : X × Y, |p (s, q) - leftRevealModel μ p (s, q)|) / 2 := by
simp_rw [Fintype.sum_prod_type, abs_masked_inl]
simp [Finset.sum_ite_irrel, div_eq_mul_inv, Finset.sum_mul]
have hright (s : S) :
(∑ v : Y, ∑ q : X × Y,
|maskedJoint p ((s, Sum.inr v), q) - maskedModel μ p ((s, Sum.inr v), q)|) =
(∑ q : X × Y, |p (s, q) - rightRevealModel μ p (s, q)|) / 2 := by
have hcollapse :
(∑ v : Y, ∑ q : X × Y,
|maskedJoint p ((s, Sum.inr v), q) - maskedModel μ p ((s, Sum.inr v), q)|) =
∑ v : Y, ∑ x : X, |p (s, (x, v)) - rightRevealModel μ p (s, (x, v))| / 2 := by
simp [Fintype.sum_prod_type, abs_masked_inr]
rw [hcollapse, Finset.sum_comm]
simp [Fintype.sum_prod_type, div_eq_mul_inv, Finset.sum_mul]
have hmass :
(∑ z : (S × (X ⊕ Y)) × (X × Y), |maskedJoint p z - maskedModel μ p z|) =
((∑ z : S × (X × Y), |p z - leftRevealModel μ p z|) +
(∑ z : S × (X × Y), |p z - rightRevealModel μ p z|)) / 2 := by
calc
_ = ∑ s : S,
((∑ u : X, ∑ q : X × Y, |maskedJoint p ((s, Sum.inl u), q) - maskedModel μ p ((s, Sum.inl u), q)|) +
(∑ v : Y, ∑ q : X × Y, |maskedJoint p ((s, Sum.inr v), q) - maskedModel μ p ((s, Sum.inr v), q)|)) := by
simp only [Fintype.sum_prod_type, Fintype.sum_sum_type]
_ = ∑ s : S,
((∑ q : X × Y, |p (s, q) - leftRevealModel μ p (s, q)|) / 2 +
(∑ q : X × Y, |p (s, q) - rightRevealModel μ p (s, q)|) / 2) := by
simp_rw [hleft, hright]
_ = _ := by
simp [Fintype.sum_prod_type, div_eq_mul_inv, Finset.sum_add_distrib, Finset.sum_mul, add_mul]
unfold Information.totalVariation
rw [hmass]
ring
theorem leftRevealModel_totalVariation_le (μ : Games.FiniteDistribution (X × Y))
(p : S × (X × Y) → ℝ) :
Information.totalVariation p (leftRevealModel μ p) ≤
2 * Information.totalVariation (maskedJoint p) (maskedModel μ p) := by
rw [masked_totalVariation_identity]
linarith [Information.totalVariation_nonneg p (rightRevealModel μ p)]
theorem rightRevealModel_totalVariation_le (μ : Games.FiniteDistribution (X × Y))
(p : S × (X × Y) → ℝ) :
Information.totalVariation p (rightRevealModel μ p) ≤
2 * Information.totalVariation (maskedJoint p) (maskedModel μ p) := by
rw [masked_totalVariation_identity]
linarith [Information.totalVariation_nonneg p (leftRevealModel μ p)]
end
end UniqueGamesTheorem.Foundations.Repetition
end
end OAI