openAI-math-dataset / lean /OAI /Computability /UniqueGames /Repetition /RoundingPaddingLemmas.lean
roseking's picture
Add lean source and binary files (part 64)
92416a2 verified
Raw History Blame Contribute Delete
20 kB
import Mathlib.Analysis.Real.Sqrt
import Mathlib.Data.Fintype.Sum
import OAI.Computability.UniqueGames.Foundations.FiniteTrialsLemmas
import OAI.Computability.UniqueGames.Repetition.AnalyticCheegerLemmas
import OAI.Computability.UniqueGames.Repetition.CollisionLemmas
namespace OAI
section
/-! Finite vertex-specific padding of nonnegative vectors to unit squared row
mass. The new coordinates can only increase any nonnegative relation energy. -/
namespace UniqueGamesTheorem.Repetition
open scoped BigOperators
open Foundations.Games
noncomputable section
variable {V A Ω E : Type*} [Fintype V] [Fintype Ω] [Fintype E]
def rowSquareMass (f : V → Ω → ℝ) (v : V) : ℝ := ∑ ω, (f v ω) ^ 2
def paddedAmplitude [DecidableEq V] (f : V → Ω → ℝ) (v : V) : Ω ⊕ V → ℝ
| Sum.inl ω => f v ω
| Sum.inr w => if v = w then Real.sqrt (1 - rowSquareMass f v) else 0
def paddedLabel (a : V → Ω → A) (fallback : A) (v : V) : Ω ⊕ V → A
| Sum.inl ω => a v ω
| Sum.inr _ => fallback
omit [Fintype V] in
theorem paddedAmplitude_nonnegative [DecidableEq V] (f : V → Ω → ℝ)
(hf : ∀ v ω, 0 ≤ f v ω) (v : V) (ω : Ω ⊕ V) :
0 ≤ paddedAmplitude f v ω := by
cases ω with
| inl ω => exact hf v ω
| inr w =>
simp only [paddedAmplitude]
split
· exact Real.sqrt_nonneg _
· exact le_rfl
theorem paddedAmplitude_row [DecidableEq V] (f : V → Ω → ℝ)
(hrow : ∀ v, rowSquareMass f v ≤ 1) (v : V) :
rowSquareMass (paddedAmplitude f) v = 1 := by
have hs : Real.sqrt (1 - rowSquareMass f v) ^ 2 = 1 - rowSquareMass f v :=
Real.sq_sqrt (sub_nonneg.mpr (hrow v))
simp only [rowSquareMass] at hs
simp only [rowSquareMass, Fintype.sum_sum_type, paddedAmplitude]
simp only [ite_pow, zero_pow (by decide : 2 ≠ 0)]
rw [Finset.sum_ite_eq, ite_eq_left (Finset.mem_univ v), hs]
ring
def pairEnergy (ν : FiniteDistribution E) (left right : E → V)
(R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) : ℝ :=
ν.expectation fun e => ∑ ω,
if R e (a (left e) ω) (a (right e) ω)
then f (left e) ω * f (right e) ω else 0
def pairOverlap (ν : FiniteDistribution E) (left right : E → V)
(R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) : ℝ :=
ν.expectation fun e => ∑ ω,
if R e (a (left e) ω) (a (right e) ω)
then min ((f (left e) ω) ^ 2) ((f (right e) ω) ^ 2) else 0
omit [Fintype V] in
theorem pairEnergy_nonnegative (ν : FiniteDistribution E) (left right : E → V)
(R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ)
(hf : ∀ v ω, 0 ≤ f v ω) : 0 ≤ pairEnergy ν left right R a f := by
apply Finset.sum_nonneg
intro e _
apply mul_nonneg (ν.nonnegative e)
apply Finset.sum_nonneg
intro ω _
split
· exact mul_nonneg (hf (left e) ω) (hf (right e) ω)
· exact le_rfl
theorem pairEnergy_le_padded [DecidableEq V] (ν : FiniteDistribution E)
(left right : E → V) (R : E → A → A → Bool)
(a : V → Ω → A) (f : V → Ω → ℝ)
(hf : ∀ v ω, 0 ≤ f v ω) (fallback : A) :
pairEnergy ν left right R a f ≤
pairEnergy ν left right R (paddedLabel a fallback) (paddedAmplitude f) := by
unfold pairEnergy FiniteDistribution.expectation
apply Finset.sum_le_sum
intro e _
apply mul_le_mul_of_nonneg_left _ (ν.nonnegative e)
dsimp only
rw [Fintype.sum_sum_type]
simp only [paddedLabel, paddedAmplitude]
have hnonneg : 0 ≤ ∑ w : V,
if R e fallback fallback then
(if left e = w then Real.sqrt (1 - rowSquareMass f (left e)) else 0) *
(if right e = w then Real.sqrt (1 - rowSquareMass f (right e)) else 0)
else 0 := by
apply Finset.sum_nonneg
intro w _
split
· exact mul_nonneg (paddedAmplitude_nonnegative f hf (left e) (Sum.inr w))
(paddedAmplitude_nonnegative f hf (right e) (Sum.inr w))
· exact le_rfl
exact le_add_of_nonneg_right hnonneg
end
end UniqueGamesTheorem.Repetition
end
section
/-! Flatten the genuine finite occurrence law together with the auxiliary
coordinate into the Cheeger inequality. The occurrence may retain hidden
information; both endpoint label tables still depend only on their vertex. -/
namespace UniqueGamesTheorem.Repetition
open scoped BigOperators
open Foundations.Games
noncomputable section
variable {V A Ω E : Type*} [Fintype V] [Fintype Ω] [Fintype E]
omit [Fintype V] in
theorem pairQuadraticMass_eq_one (ν : FiniteDistribution E) (left right : E → V)
(f : V → Ω → ℝ) (hrow : ∀ v, rowSquareMass f v = 1) :
Analytic.quadraticMass (fun p : E × Ω => ν.weight p.1)
(fun p => f (left p.1) p.2) (fun p => f (right p.1) p.2) = 1 := by
unfold Analytic.quadraticMass
rw [Fintype.sum_prod_type]
have he (e : E) :
(∑ ω, ν.weight e * ((f (left e) ω) ^ 2 + (f (right e) ω) ^ 2) / 2) =
ν.weight e := by
calc
_ = ν.weight e *
((∑ ω, (f (left e) ω) ^ 2) + (∑ ω, (f (right e) ω) ^ 2)) / 2 := by
simp only [div_eq_mul_inv, mul_add, add_mul, Finset.sum_add_distrib,
Finset.mul_sum, Finset.sum_mul]
_ = ν.weight e := by
change ν.weight e * (rowSquareMass f (left e) + rowSquareMass f (right e)) / 2 = _
rw [hrow, hrow]
ring
simp_rw [he]
exact ν.normalized
omit [Fintype V] in
theorem pairGatedCorrelation_eq_energy (ν : FiniteDistribution E) (left right : E → V)
(R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) :
Analytic.gatedCorrelation (fun p : E × Ω => ν.weight p.1)
(fun p => f (left p.1) p.2) (fun p => f (right p.1) p.2)
(fun p => R p.1 (a (left p.1) p.2) (a (right p.1) p.2)) =
pairEnergy ν left right R a f := by
simp only [Analytic.gatedCorrelation, pairEnergy, FiniteDistribution.expectation,
Fintype.sum_prod_type, Finset.mul_sum, mul_ite, mul_zero, mul_assoc]
omit [Fintype V] in
theorem pairGatedMinimum_eq_overlap (ν : FiniteDistribution E) (left right : E → V)
(R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) :
Analytic.gatedMinimum (fun p : E × Ω => ν.weight p.1)
(fun p => f (left p.1) p.2) (fun p => f (right p.1) p.2)
(fun p => R p.1 (a (left p.1) p.2) (a (right p.1) p.2)) =
pairOverlap ν left right R a f := by
simp only [Analytic.gatedMinimum, pairOverlap, FiniteDistribution.expectation,
Fintype.sum_prod_type, Finset.mul_sum, mul_ite, mul_zero]
omit [Fintype V] in
theorem pairEnergy_le_one_of_unit_rows (ν : FiniteDistribution E) (left right : E → V)
(R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ)
(hrow : ∀ v, rowSquareMass f v = 1) : pairEnergy ν left right R a f ≤ 1 := by
have h := Analytic.gatedCorrelation_le_mass (fun p : E × Ω => ν.weight p.1)
(fun p => f (left p.1) p.2) (fun p => f (right p.1) p.2)
(fun p => R p.1 (a (left p.1) p.2) (a (right p.1) p.2))
(fun p => ν.nonnegative p.1)
rw [pairGatedCorrelation_eq_energy, pairQuadraticMass_eq_one ν left right f hrow] at h
exact h
omit [Fintype V] in
/-- The overlap used by finite threshold sampling is large whenever the
actual weighted occurrence energy is large. -/
theorem pairOverlap_ge_energy (ν : FiniteDistribution E) (left right : E → V)
(R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ)
(hf : ∀ v ω, 0 ≤ f v ω) (hrow : ∀ v, rowSquareMass f v = 1) :
1 - Real.sqrt (2 * (1 - pairEnergy ν left right R a f)) ≤
pairOverlap ν left right R a f := by
have h := Analytic.gatedMinimum_unit_mass (fun p : E × Ω => ν.weight p.1)
(fun p => f (left p.1) p.2) (fun p => f (right p.1) p.2)
(fun p => R p.1 (a (left p.1) p.2) (a (right p.1) p.2))
(fun p => ν.nonnegative p.1) (fun p => hf (left p.1) p.2)
(fun p => hf (right p.1) p.2) (pairQuadraticMass_eq_one ν left right f hrow)
rw [pairGatedCorrelation_eq_energy, pairGatedMinimum_eq_overlap] at h
exact h
end
end UniqueGamesTheorem.Repetition
end
section
/-!
The collision norm as an actual finite distribution on symmetrized edges.
An edge retains the hidden common right question, while each label remains a
function of its own left question. Projection uniqueness turns the sum over
common right answers into a Boolean compatibility predicate exactly.
-/
namespace UniqueGamesTheorem.Repetition.ProjectionKernel
open Foundations.Games
open scoped BigOperators
noncomputable section
attribute [local instance] Classical.propDecidable
variable {Q₁ Q₂ A₁ A₂ Ω : Type*}
[Fintype Q₁] [Fintype Q₂] [Fintype A₁] [Fintype A₂] [Fintype Ω]
abbrev SymmetricEdge (Q₁ Q₂ : Type*) := Q₂ × Q₁ × Q₁
def symmetricLeft (e : SymmetricEdge Q₁ Q₂) : Q₁ := e.2.1
def symmetricRight (e : SymmetricEdge Q₁ Q₂) : Q₁ := e.2.2
def symmetricDistribution (K : ProjectionKernel Q₁ Q₂ A₁ A₂) :
FiniteDistribution (SymmetricEdge Q₁ Q₂) where
weight e := K.outer.weight e.1 * (K.inner e.1).weight e.2.1 *
(K.inner e.1).weight e.2.2
nonnegative e := mul_nonneg
(mul_nonneg (K.outer.nonnegative _) ((K.inner _).nonnegative _))
((K.inner _).nonnegative _)
normalized := by
rw [Fintype.sum_prod_type]
calc
_ = ∑ y, K.outer.weight y := by
apply Finset.sum_congr rfl
intro y _
rw [Fintype.sum_prod_type]
calc
_ = ∑ x, K.outer.weight y * (K.inner y).weight x := by
apply Finset.sum_congr rfl
intro x _
dsimp only
rw [← Finset.mul_sum, (K.inner y).normalized, mul_one]
_ = K.outer.weight y := by
rw [← Finset.mul_sum, (K.inner y).normalized, mul_one]
_ = 1 := K.outer.normalized
def symmetricAccept (K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(e : SymmetricEdge Q₁ Q₂) (a a' : A₁) : Bool := by
classical
exact decide (∃ b, K.accepts e.2.1 e.1 a b = true ∧
K.accepts e.2.2 e.1 a' b = true)
/-- A coordinate has one possible nonzero label at each question. -/
def singleLabelVector (a : Q₁ → Ω → A₁) (f : Q₁ → Ω → ℝ)
(ω : Ω) (x : Q₁) (b : A₁) : ℝ := by
classical
exact if a x ω = b then f x ω else 0
theorem sum_projection_gates (K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(y : Q₂) (x x' : Q₁) (a a' : A₁) (r s : ℝ) :
(∑ b, (if K.accepts x y a b then r else 0) *
(if K.accepts x' y a' b then s else 0)) =
if K.symmetricAccept (y, x, x') a a' then r * s else 0 := by
classical
by_cases hex : ∃ b, K.accepts x y a b = true ∧ K.accepts x' y a' b = true
· obtain ⟨b₀, hb₀, hb₀'⟩ := hex
have hex' : ∃ b, K.accepts x y a b = true ∧ K.accepts x' y a' b = true :=
⟨b₀, hb₀, hb₀'⟩
simp only [symmetricAccept, hex', decide_true, ite_true]
calc
_ = (if K.accepts x y a b₀ then r else 0) *
(if K.accepts x' y a' b₀ then s else 0) := by
apply Finset.sum_eq_single b₀
· intro b _ hne
have hb : K.accepts x y a b ≠ true := by
intro hb
exact hne (K.projection x y a b b₀ hb hb₀)
simp [hb]
· simp
_ = r * s := by simp [hb₀, hb₀']
· simp only [symmetricAccept, hex, decide_false, Bool.false_eq_true, ite_false]
apply Finset.sum_eq_zero
intro b _
by_cases hb : K.accepts x y a b = true
· have hb' : K.accepts x' y a' b ≠ true := fun hb' => hex ⟨b, hb, hb'⟩
simp [hb']
· simp [hb]
theorem apply_single_label (K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(labels : Q₁ → A₁) (f : Q₁ → ℝ) (y : Q₂) (b : A₂) :
K.apply (fun x a => if labels x = a then f x else 0) y b =
∑ x, (K.inner y).weight x * (if K.accepts x y (labels x) b then f x else 0) := by
classical
unfold apply
apply Finset.sum_congr rfl
intro x _
congr 1
calc
_ = ∑ a, if labels x = a then
(if K.accepts x y (labels x) b then f x else 0) else 0 := by
apply Finset.sum_congr rfl
intro a _
by_cases ha : labels x = a
· subst a
simp
· simp [ha]
_ = _ := by simp
theorem energy_single_label (K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(labels : Q₁ → A₁) (f : Q₁ → ℝ) :
K.energy (fun x a => if labels x = a then f x else 0) =
K.symmetricDistribution.expectation (fun e =>
if K.symmetricAccept e (labels (symmetricLeft e)) (labels (symmetricRight e))
then f (symmetricLeft e) * f (symmetricRight e) else 0) := by
classical
have hexpand (y : Q₂) :
(∑ b, (∑ x, (K.inner y).weight x *
(if K.accepts x y (labels x) b then f x else 0)) ^ 2) =
∑ x, ∑ x', (K.inner y).weight x * (K.inner y).weight x' *
(if K.symmetricAccept (y, x, x') (labels x) (labels x')
then f x * f x' else 0) := by
simp only [pow_two, Finset.sum_mul, Finset.mul_sum]
rw [Finset.sum_comm]
apply Finset.sum_congr rfl
intro x _
rw [Finset.sum_comm]
apply Finset.sum_congr rfl
intro x' _
calc
_ = (K.inner y).weight x * (K.inner y).weight x' *
∑ b, (if K.accepts x y (labels x) b then f x else 0) *
(if K.accepts x' y (labels x') b then f x' else 0) := by
rw [Finset.mul_sum]
apply Finset.sum_congr rfl
intro b _
ring
_ = _ := by rw [K.sum_projection_gates]
unfold energy
simp_rw [K.apply_single_label, hexpand]
simp only [FiniteDistribution.expectation, symmetricDistribution,
Fintype.sum_prod_type, symmetricLeft, symmetricRight, Finset.mul_sum]
apply Finset.sum_congr rfl
intro y _
apply Finset.sum_congr rfl
intro x _
apply Finset.sum_congr rfl
intro x' _
simp only [mul_assoc]
rfl
/-- Coordinate expansion and the symmetrized edge law agree exactly. -/
theorem vectorEnergy_singleLabelVector (K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(a : Q₁ → Ω → A₁) (f : Q₁ → Ω → ℝ) :
K.vectorEnergy (singleLabelVector a f) =
pairEnergy K.symmetricDistribution symmetricLeft symmetricRight K.symmetricAccept a f := by
classical
unfold vectorEnergy singleLabelVector
simp_rw [K.energy_single_label]
unfold pairEnergy FiniteDistribution.expectation
rw [Finset.sum_comm]
apply Finset.sum_congr rfl
intro e _
rw [Finset.mul_sum]
/-- Ordinary deterministic labelings give the collision assignment energy. -/
theorem symmetric_probability_eq_assignmentEnergy (K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(labels : Q₁ → A₁) :
K.symmetricDistribution.probability (fun e =>
K.symmetricAccept e (labels (symmetricLeft e)) (labels (symmetricRight e))) =
K.assignmentEnergy labels := by
classical
change _ = K.energy (fun x a => if labels x = a then (1 : ℝ) else 0)
rw [K.energy_single_label]
simp only [FiniteDistribution.probability, FiniteDistribution.expectation,
mul_ite, mul_one, mul_zero]
end
end UniqueGamesTheorem.Repetition.ProjectionKernel
end
section
/-!
Apply finite positive-vector determinization to the actual projection kernel.
The target coordinates retain both the right question and the right answer.
The selected label may depend on the auxiliary coordinate, but only on its own
left question. Every question's squared vector mass is preserved exactly.
-/
namespace UniqueGamesTheorem.Repetition.ProjectionKernel
open scoped BigOperators
noncomputable section
attribute [local instance] Classical.propDecidable
variable {Q₁ Q₂ A₁ A₂ Ω : Type*}
[Fintype Q₁] [Fintype Q₂] [Fintype A₁] [Fintype A₂] [Fintype Ω]
/-- Explicit matrix coefficients of the projection operator. -/
def linearCoefficient (K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(t : Q₂ × A₂) (x : Q₁) (a : A₁) : ℝ :=
(K.inner t.1).weight x * (if K.accepts x t.1 a t.2 then 1 else 0)
theorem apply_eq_linearCoefficient_sum (K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(h : Q₁ → A₁ → ℝ) (y : Q₂) (b : A₂) :
K.apply h y b = ∑ x, ∑ a, K.linearCoefficient (y, b) x a * h x a := by
unfold apply
simp_rw [Finset.mul_sum]
apply Finset.sum_congr rfl
intro x _
apply Finset.sum_congr rfl
intro a _
by_cases ha : K.accepts x y a b = true <;> simp [linearCoefficient, ha]
theorem energy_eq_linearCoefficient_sum (K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(h : Q₁ → A₁ → ℝ) :
K.energy h = ∑ t : Q₂ × A₂, K.outer.weight t.1 *
(∑ x, ∑ a, K.linearCoefficient t x a * h x a) ^ 2 := by
rw [Fintype.sum_prod_type]
simp_rw [← K.apply_eq_linearCoefficient_sum, ← Finset.mul_sum]
rfl
/-- Scalar kernel determinization preserves the whole mass at every question. -/
theorem exists_energy_le_deterministicVector [Nonempty A₁]
(K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(h : Q₁ → A₁ → ℝ) (hh : ∀ x a, 0 ≤ h x a) :
∃ labels : Q₁ → A₁,
K.energy h ≤ K.energy (deterministicVector h labels) := by
classical
obtain ⟨labels, _, _, hlabels⟩ := exists_deterministic_vector h hh
(fun t : Q₂ × A₂ => K.outer.weight t.1)
(fun t => K.outer.nonnegative t.1) K.linearCoefficient
refine ⟨labels, ?_⟩
rw [K.energy_eq_linearCoefficient_sum, K.energy_eq_linearCoefficient_sum]
exact hlabels
/-- The amplitude at a question is the sum of its original label entries. -/
def vectorAmplitude (h : Ω → Q₁ → A₁ → ℝ) (x : Q₁) (ω : Ω) : ℝ :=
rowMass (h ω) x
omit [Fintype Q₁] [Fintype Ω] in
theorem vectorAmplitude_nonnegative (h : Ω → Q₁ → A₁ → ℝ)
(hh : ∀ ω x a, 0 ≤ h ω x a) (x : Q₁) (ω : Ω) :
0 ≤ vectorAmplitude h x ω :=
rowMass_nonnegative (h ω) (hh ω) x
omit [Fintype Q₁] in
@[simp] theorem rowSquareMass_vectorAmplitude (h : Ω → Q₁ → A₁ → ℝ) (x : Q₁) :
rowSquareMass (vectorAmplitude h) x = vectorMass h x := rfl
/-- Auxiliary coordinates are determinized separately; they need not be
independent, normalized, or nonempty. -/
theorem exists_vectorEnergy_le_singleLabelVector [Nonempty A₁]
(K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(h : Ω → Q₁ → A₁ → ℝ) (hh : ∀ ω x a, 0 ≤ h ω x a) :
∃ labels : Q₁ → Ω → A₁,
K.vectorEnergy h ≤ K.vectorEnergy (singleLabelVector labels (vectorAmplitude h)) := by
classical
have hex (ω : Ω) := K.exists_energy_le_deterministicVector (h ω) (hh ω)
let labels (ω : Ω) : Q₁ → A₁ := Classical.choose (hex ω)
have hlabels (ω : Ω) : K.energy (h ω) ≤
K.energy (deterministicVector (h ω) (labels ω)) := Classical.choose_spec (hex ω)
refine ⟨fun x ω => labels ω x, ?_⟩
apply Finset.sum_le_sum
intro ω _
have heq : deterministicVector (h ω) (labels ω) =
singleLabelVector (fun x ω => labels ω x) (vectorAmplitude h) ω := by
funext x a
by_cases ha : a = labels ω x
· simp [deterministicVector, singleLabelVector, vectorAmplitude, ha]
· simp [deterministicVector, singleLabelVector, ha, Ne.symm ha]
exact heq ▸ hlabels ω
/-- Package the deterministic labels, amplitudes, exact mass preservation, and
energy inequality for use by the finite threshold-rounding construction. -/
theorem exists_mass_preserving_singleLabelVector [Nonempty A₁]
(K : ProjectionKernel Q₁ Q₂ A₁ A₂)
(h : Ω → Q₁ → A₁ → ℝ) (hh : ∀ ω x a, 0 ≤ h ω x a) :
∃ (labels : Q₁ → Ω → A₁) (f : Q₁ → Ω → ℝ),
(∀ x ω, 0 ≤ f x ω) ∧
(∀ x, rowSquareMass f x = vectorMass h x) ∧
K.vectorEnergy h ≤ K.vectorEnergy (singleLabelVector labels f) := by
obtain ⟨labels, hlabels⟩ := K.exists_vectorEnergy_le_singleLabelVector h hh
exact ⟨labels, vectorAmplitude h, vectorAmplitude_nonnegative h hh,
rowSquareMass_vectorAmplitude h, hlabels⟩
end
end UniqueGamesTheorem.Repetition.ProjectionKernel
end
end OAI