openAI-math-dataset / lean /OAI /Probability /CriticalZ3 /ShellProbability.lean
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import OAI.Probability.CriticalZ3.TrialCounts
namespace OAI
open MeasureTheory ProbabilityTheory Classical Filter
open scoped ENNReal BigOperators Matrix
namespace CriticalZ3.LatticeGraph
open MeasureTheory ProbabilityTheory Classical InfiniteConditioning
variable (G : LatticeGraph) (m : Model)
theorem shell_blocking_lower (p : m.Bit → Set.Icc (0 : ℝ) 1)
(C : Box) (o : G.Node) (q : Set.Icc (0 : ℝ) 1) {p₀ : ℝ}
(hq : (q : ℝ) ≤ p₀) (hp₀ : p₀ < 1) (L : ℕ)
(hp : ∀ y, C.Exterior y → p (C.entryBit m y) = q) :
(1-p₀)^L * (ProductCylinder.law p).real
{ω | 0 < (G.entrants m C ω o).card ∧ (G.entrants m C ω o).card < L} ≤
(ProductCylinder.law p).real
{ω | 0 < (G.entrants m C ω o).card ∧ (G.entrants m C ω o).card < L ∧
G.Blocked m C ω o} := by
let J := G.outsideBits m C
let ξ (a : J → Bool) := ProductCylinder.extend J a
let P (a : J → Bool) := 0 < (G.entrants m C (ξ a) o).card ∧
(G.entrants m C (ξ a) o).card < L
let A (a : J → Bool) := allValue (G.entryBits m C (ξ a) o) false
have h := select_probability_lower p J P A (fun a => measurableSet_allValue _ _) (b := (1-p₀)^L) ?_
· have hY (ω : m.Config) : G.entrants m C ω o = G.entrants m C (ξ (J.restrict ω)) o :=
ProductCylinder.determinedBy_eq_extend (G.entrants_determined m C o) ω
have hK (ω : m.Config) : G.entryBits m C ω o = G.entryBits m C (ξ (J.restrict ω)) o :=
ProductCylinder.determinedBy_eq_extend (G.entryBits_determined m C o) ω
have heP : {ω | P (J.restrict ω)} =
{ω | 0 < (G.entrants m C ω o).card ∧ (G.entrants m C ω o).card < L} := by
ext ω; simp only [P,Set.mem_ofPred_eq]; rw [←hY ω]
have heA : {ω | P (J.restrict ω) ∧ ω ∈ A (J.restrict ω)} =
{ω | 0 < (G.entrants m C ω o).card ∧ (G.entrants m C ω o).card < L ∧
G.Blocked m C ω o} := by
ext ω
simp only [P,A,allValue,Blocked,Set.mem_ofPred_eq]
rw [←hY ω,←hK ω]
exact and_assoc
rwa [heP,heA] at h
· intro a ha
rw [fixed_determined_probability p J (G.entryBits m C (ξ a) o)
(G.entryBits_disjoint_outside m C (ξ a) o).symm _ _ (allValue_determined _ _)]
rw [allValue_probability_constant p _ q ?_ false]
· change (1-p₀)^L ≤ (1-(q : ℝ))^(G.entryBits m C (ξ a) o).card
have h0 : 0 ≤ 1-p₀ := by linarith
have h1 : 1-(q : ℝ) ≤ 1 := by linarith [q.property.1]
calc
_ ≤ (1-(q : ℝ))^L := pow_le_pow_left₀ h0 (by linarith) L
_ ≤ _ := pow_le_pow_of_le_one (by linarith [q.property.2]) h1
((G.entryBits_card m C (ξ a) o).trans (Nat.le_of_lt ha.2))
· intro e he
obtain ⟨y,hy,rfl⟩ := Finset.mem_image.mp he
have hyG : y ∈ G.vertices := (Finset.mem_filter.mp hy).1
exact hp y ((G.mem_entrants m C (ξ a) o ⟨y,hyG⟩).mp hy).1
theorem measurableSet_shell_blocked (C : Box) (o : G.Node) (L : ℕ) :
MeasurableSet {ω | 0 < (G.entrants m C ω o).card ∧
(G.entrants m C ω o).card < L ∧ G.Blocked m C ω o} := by
let J := G.outsideBits m C
let ξ (a : J → Bool) := ProductCylinder.extend J a
let A (a : J → Bool) : Set m.Config := if 0 < (G.entrants m C (ξ a) o).card ∧
(G.entrants m C (ξ a) o).card < L then allValue (G.entryBits m C (ξ a) o) false else ∅
have h := measurableSet_select J A (fun a => by
dsimp only [A]; split_ifs
· exact measurableSet_allValue _ _
· exact MeasurableSet.empty)
have he : {ω | ω ∈ A (J.restrict ω)} = {ω | 0 < (G.entrants m C ω o).card ∧
(G.entrants m C ω o).card < L ∧ G.Blocked m C ω o} := by
ext ω
have hY := ProductCylinder.determinedBy_eq_extend (G.entrants_determined m C o) ω
have hK := ProductCylinder.determinedBy_eq_extend (G.entryBits_determined m C o) ω
change G.entrants m C ω o = G.entrants m C (ξ (J.restrict ω)) o at hY
change G.entryBits m C ω o = G.entryBits m C (ξ (J.restrict ω)) o at hK
simp only [A,←hY,←hK,Set.mem_ofPred_eq,Blocked,allValue]
split_ifs with hh
· tauto
· simp only [Set.mem_empty_iff_false]; tauto
rwa [he] at h
/-- Deterministic shell selection for the finite graph in bond and site percolation. -/
theorem exists_shell (p : m.Bit → Set.Icc (0 : ℝ) 1)
(B : Box) (o : G.Node) (q : Set.Icc (0 : ℝ) 1) {p₀ : ℝ}
(hq : (q : ℝ) ≤ p₀) (hp₀ : p₀ < 1) (L a R : ℕ) (haR : a < R)
(ho : ¬(B.expand R).Contains o.1)
(hp : ∀ j ∈ Finset.Ico a R, ∀ y, (B.expand j).Exterior y →
p ((B.expand j).entryBit m y) = q) :
∃ j ∈ Finset.Ico a R, (ProductCylinder.law p).real
{ω | G.Meets m ω o {x | B.Contains x} ∧ (G.entrants m (B.expand j) ω o).card < L} ≤
1/((1-p₀)^L*(R-a : ℕ)) := by
let I := ↥(Finset.Ico a R)
have : Nonempty I := ⟨⟨a,Finset.mem_Ico.mpr ⟨le_rfl,haR⟩⟩⟩
let Q (i : I) : Set m.Config :=
{ω | G.Meets m ω o {x | B.Contains x} ∧ (G.entrants m (B.expand i.1) ω o).card < L}
let A (i : I) : Set m.Config :=
{ω | 0 < (G.entrants m (B.expand i.1) ω o).card ∧
(G.entrants m (B.expand i.1) ω o).card < L ∧ G.Blocked m (B.expand i.1) ω o}
have hoi (i : I) : ¬(B.expand i.1).Contains o.1 := fun h =>
ho (B.expand_mono (Nat.le_of_lt (Finset.mem_Ico.mp i.2).2) h)
have hAd : Pairwise (fun i j : I => Disjoint (A i) (A j)) := by
intro i j hij
have hi : i.1 ≠ j.1 := fun h => hij (Subtype.ext h)
apply Set.disjoint_left.mpr
intro ω hωi hωj
rcases lt_or_gt_of_ne hi with hlt | hlt
· have he := G.blocked_earlier_entrants m hlt (hoi j) hωj.2.2
have hpos := hωi.1
rw [he,Finset.card_empty] at hpos
exact Nat.not_lt_zero _ hpos
· have he := G.blocked_earlier_entrants m hlt (hoi i) hωi.2.2
have hpos := hωj.1
rw [he,Finset.card_empty] at hpos
exact Nat.not_lt_zero _ hpos
have hblock (i : I) : (1-p₀)^L * (ProductCylinder.law p).real (Q i) ≤
(ProductCylinder.law p).real (A i) := by
have hsub : Q i ⊆ {ω | 0 < (G.entrants m (B.expand i.1) ω o).card ∧
(G.entrants m (B.expand i.1) ω o).card < L} := by
intro ω hω
refine ⟨Finset.card_pos.mpr (G.meets_entrants_nonempty m (hoi i) ?_),hω.2⟩
obtain ⟨z,hz,hconn⟩ := hω.1
exact ⟨z,B.contains_expand i.1 hz,hconn⟩
exact (mul_le_mul_of_nonneg_left (measureReal_mono hsub) (pow_nonneg (by linarith) _)).trans
(G.shell_blocking_lower m p (B.expand i.1) o q hq hp₀ L (hp i.1 i.2))
obtain ⟨i,hi⟩ := ShellEstimates.exists_layer (ProductCylinder.law p) Q A
(fun i => G.measurableSet_shell_blocked m (B.expand i.1) o L) hAd
(pow_pos (by linarith) L) hblock
refine ⟨i.1,i.2,?_⟩
simpa only [I,Fintype.card_coe,Nat.card_Ico] using hi
end CriticalZ3.LatticeGraph
namespace FiniteAssociation
open Classical
variable {E : Type}
theorem indicator_monotone {P : (E → Bool) → Prop} (hP : Monotone P) :
Monotone (fun ω => if P ω then (1 : ℝ) else 0) := by
intro ω ω' h
by_cases h' : P ω
· simp [h',hP h h']
· simp only [h',ite_false]
split_ifs <;> norm_num
theorem prob_and_increasing [Fintype E] (p : E → Set.Icc (0 : ℝ) 1)
{P Q : (E → Bool) → Prop} (hP : Monotone P) (hQ : Monotone Q) :
prob p P * prob p Q ≤ prob p (fun ω => P ω ∧ Q ω) := by
have h := increasing p _ _ (indicator_monotone hP) (indicator_monotone hQ)
change mean p _ * mean p _ ≤ mean p _
convert h using 1
congr 1
funext ω
by_cases h₁ : P ω <;> by_cases h₂ : Q ω <;> simp [h₁,h₂]
end FiniteAssociation
namespace ProductCylinder
open MeasureTheory ProbabilityTheory Classical
variable {E : Type}
theorem probability_congr_parameters (J : Finset E)
(p q : E → Set.Icc (0 : ℝ) 1) (hpq : ∀ e ∈ J, p e = q e)
(A : Set (E → Bool)) (hA : DeterminedBy (F := Prop) J (fun ω => ω ∈ A)) :
(law p).real A = (law q).real A := by
simp only [Measure.real_def,probability_determined J _ A (fun ω ω' h => eq_iff_iff.mp (hA ω ω' h))]
congr 2
unfold finiteLaw
congr 1
funext e
rw [hpq e e.2]
theorem determinedBy_mono {J K : Finset E} (hJK : J ⊆ K) {F : Type}
{f : (E → Bool) → F} (hf : DeterminedBy J f) : DeterminedBy K f :=
fun ω ω' h => hf ω ω' (fun e he => h e (hJK he))
theorem increasing_and (J : Finset E) (p : E → Set.Icc (0 : ℝ) 1)
(A B : Set (E → Bool))
(hA : DeterminedBy (F := Prop) J (fun ω => ω ∈ A))
(hB : DeterminedBy (F := Prop) J (fun ω => ω ∈ B))
(hmA : Monotone (fun ω => ω ∈ A)) (hmB : Monotone (fun ω => ω ∈ B)) :
(law p).real A*(law p).real B ≤ (law p).real (A ∩ B) := by
have he (C : Set (E → Bool)) (hC : DeterminedBy (F := Prop) J (fun ω => ω ∈ C)) :
(law p).real C = FiniteAssociation.prob (fun e : J => p e) (fun ξ => extend J ξ ∈ C) := by
rw [FiniteAssociation.prob_eq_real,Measure.real_def,Measure.real_def,
probability_determined J p C (fun ω ω' h => eq_iff_iff.mp (hC ω ω' h))]
rfl
have hAB : DeterminedBy (F := Prop) J (fun ω => ω ∈ A ∩ B) := by
intro ω ω' h
simp only [Set.mem_inter_iff,hA ω ω' h,hB ω ω' h]
rw [he A hA,he B hB,he (A ∩ B) hAB]
exact FiniteAssociation.prob_and_increasing _ (hmA.comp (extend_mono J)) (hmB.comp (extend_mono J))
/-- The open-seed Harris estimate, with a separate increasing connecting event. -/
theorem seed_failure_bound (J : Finset E) (p : E → Set.Icc (0 : ℝ) 1)
(O A C : Set (E → Bool))
(hO : DeterminedBy (F := Prop) J (fun ω => ω ∈ O))
(hA : DeterminedBy (F := Prop) J (fun ω => ω ∈ A))
(hmO : Monotone (fun ω => ω ∈ O)) (hmA : Monotone (fun ω => ω ∈ A))
(hsub : O ∩ A ⊆ C) {γ : ℝ} (hprob : 1-γ ≤ (law p).real A) :
(law p).real (O ∩ Cᶜ) ≤ (law p).real O*γ := by
have hm := measurableSet_determined J A (fun ω ω' h => eq_iff_iff.mp (hA ω ω' h))
have ha := increasing_and J p O A hO hA hmO hmA
have hadd := measureReal_inter_add_sdiff (μ := law p) (s := O) hm
have hsub' : O ∩ Cᶜ ⊆ O \ A := by
intro ω hω
exact ⟨hω.1,fun h => hω.2 (hsub ⟨hω.1,h⟩)⟩
have hle := measureReal_mono (μ := law p) hsub'
have h0 : 0 ≤ (law p).real O := measureReal_nonneg
nlinarith
end ProductCylinder
namespace InfiniteConditioning
open MeasureTheory ProbabilityTheory Classical
variable {E : Type}
theorem allValue_true_monotone (J : Finset E) : Monotone (fun ω => ω ∈ allValue J true) := by
intro ω ω' h hh e he
have hi := h e
rw [hh e he] at hi
exact le_antisymm le_top hi
theorem measurableSet_conditional_test (p : E → Set.Icc (0 : ℝ) 1) (J : Finset E)
(C : Set (E → Bool)) (a : ℝ) :
MeasurableSet {ω | conditionalProbability p J C ω ≤ a} := by
refine ProductCylinder.measurableSet_determined J _ ?_
intro ω ω' h
simp only [Set.mem_ofPred_eq,conditionalProbability_determined p J C ω ω' h]
end InfiniteConditioning
namespace CriticalZ3.LatticeGraph
open MeasureTheory ProbabilityTheory Classical InfiniteConditioning
variable (G : LatticeGraph) (m : Model)
theorem conn_mono {ω ω' : m.Config} (h : ω ≤ ω') {x y : G.Node}
(hc : G.Conn m ω x y) : G.Conn m ω' x y := by
have hopen {e : m.Bit} (he : ω e = true) : ω' e = true := by
have hi := h e
rw [he] at hi
exact le_antisymm le_top hi
obtain ⟨hx,hc⟩ := (G.conn_iff m ω x y).mp hc
refine (G.conn_iff m ω' x y).mpr ⟨?_,?_⟩
· cases m
· trivial
· exact hopen hx
· apply Relation.ReflTransGen.mono (r := G.Adj m ω) (p := G.Adj m ω') ?_ x y hc
intro a b hab
cases m
· obtain ⟨e,he,hi,ho⟩ := hab
exact ⟨e,he,hi,hopen ho⟩
· exact ⟨hab.1,hopen hab.2.1,hopen hab.2.2⟩
theorem meets_mono (o : G.Node) (T : Set Vertex) : Monotone (fun ω => G.Meets m ω o T) := by
intro ω ω' h ⟨y,hy,hc⟩
exact ⟨y,hy,G.conn_mono m h hc⟩
noncomputable def goodRelays (p : m.Bit → Set.Icc (0 : ℝ) 1) (J : Finset m.Bit)
(T : Set Vertex) (τ : ℝ) (ω : m.Config) : Set Vertex :=
{v | ∃ a : G.Node, a.1 = v ∧ 1-τ < conditionalProbability p J {ω | G.Meets m ω a T} ω}
theorem goodRelays_determined (p : m.Bit → Set.Icc (0 : ℝ) 1) (J : Finset m.Bit)
(T : Set Vertex) (τ : ℝ) : ProductCylinder.DeterminedBy J (G.goodRelays m p J T τ) := by
intro ω ω' h
ext v
simp only [goodRelays,Set.mem_ofPred_eq,conditionalProbability_determined p J _ ω ω' h]
theorem random_relay_failure (p : m.Bit → Set.Icc (0 : ℝ) 1) (J : Finset m.Bit)
(o : G.Node) (T : Set Vertex) {τ : ℝ} (hτ : 0 ≤ τ) :
(ProductCylinder.law p).real
{ω | G.Meets m ω o (G.goodRelays m p J T τ ω) ∧ ¬G.Meets m ω o T} ≤ τ := by
let A (a : J → Bool) : Set m.Config :=
{ω | G.Meets m ω o (G.goodRelays m p J T τ (ProductCylinder.extend J a)) ∧ ¬G.Meets m ω o T}
have he : {ω | G.Meets m ω o (G.goodRelays m p J T τ ω) ∧ ¬G.Meets m ω o T} =
{ω | ω ∈ A (J.restrict ω)} := by
ext ω
simp only [A,Set.mem_ofPred_eq,
ProductCylinder.determinedBy_eq_extend (G.goodRelays_determined m p J T τ) ω]
rw [he]
apply select_probability_le p J A
· intro a
exact (G.measurableSet_meets m _ _).inter (G.measurableSet_meets m _ _).compl
· intro a
apply G.failure_comparison m _ o _ T hτ
intro v ⟨u,hu,hh⟩
have heu : u = v := Subtype.ext hu
subst u
exact hh.le
end CriticalZ3.LatticeGraph
end OAI