import OAI.Probability.RandomSAT.CenterBounds namespace OAI /-! Auxiliary ordered clauses allow repeated variables. Commuting finite averaging operators give the fixed-count partition interpolation corresponding to the marked-Poisson comparison. -/ namespace FixedClauseThreshold open Finset noncomputable section attribute [local instance] Classical.propDecidable abbrev AuxiliaryClause (n k : ℕ) := Fin k → (Fin n × Bool) def auxiliarySatisfies {n k : ℕ} (σ : Assignment n) (C : AuxiliaryClause n k) : Prop := ∃ j, σ (C j).1 = (C j).2 def finiteClauseAverage {n : ℕ} {C : Type*} [Fintype C] (sat : C → Assignment n → Prop) (f : Finset (Assignment n) → ℝ) (S : Finset (Assignment n)) : ℝ := uniformMean (fun c => f (S.filter (sat c))) theorem finiteClauseAverage_mono {n : ℕ} {C : Type*} [Fintype C] (sat : C → Assignment n → Prop) {f g : Finset (Assignment n) → ℝ} (hfg : ∀ S, f S ≤ g S) : ∀ S, finiteClauseAverage sat f S ≤ finiteClauseAverage sat g S := by intro S exact uniformMean_mono (fun c => hfg _) theorem finiteClauseAverage_add {n : ℕ} {C : Type*} [Fintype C] (sat : C → Assignment n → Prop) (f g : Finset (Assignment n) → ℝ) : finiteClauseAverage sat (fun S => f S + g S) = (fun S => finiteClauseAverage sat f S + finiteClauseAverage sat g S) := by funext S exact uniformMean_add _ _ theorem finiteClauseAverage_const_mul {n : ℕ} {C : Type*} [Fintype C] (sat : C → Assignment n → Prop) (f : Finset (Assignment n) → ℝ) (c : ℝ) : finiteClauseAverage sat (fun S => c * f S) = (fun S => c * finiteClauseAverage sat f S) := by funext S exact uniformMean_const_mul _ _ theorem finiteClauseAverage_mul_const {n : ℕ} {C : Type*} [Fintype C] (sat : C → Assignment n → Prop) (f : Finset (Assignment n) → ℝ) (c : ℝ) : finiteClauseAverage sat (fun S => f S * c) = (fun S => finiteClauseAverage sat f S * c) := by funext S exact uniformMean_mul_const _ _ theorem finiteClauseAverage_commute {n : ℕ} {C D : Type*} [Fintype C] [Fintype D] (satC : C → Assignment n → Prop) (satD : D → Assignment n → Prop) : Function.Commute (finiteClauseAverage satC) (finiteClauseAverage satD) := by intro f funext S unfold finiteClauseAverage rw [uniformMean_comm] apply uniformMean_congr intro d apply uniformMean_congr intro c congr 1 ext σ simp only [Finset.mem_filter] tauto theorem finiteClauseAverage_binomialMean {n : ℕ} {C : Type*} [Fintype C] (sat : C → Assignment n → Prop) (p : ℝ) (m : ℕ) (f : ℕ → Finset (Assignment n) → ℝ) : finiteClauseAverage sat (fun S => binomialMean p m (fun j => f j S)) = (fun S => binomialMean p m (fun j => finiteClauseAverage sat (f j) S)) := by funext S exact uniformMean_binomialMean _ _ _ theorem iterate_compare_of_commute {X : Type*} (A B : (X → ℝ) → (X → ℝ)) (hA : Monotone A) (hB : Monotone B) (hcomm : Function.Commute A B) {f : X → ℝ} (hf : B f ≤ A f) (m : ℕ) : B^[m] f ≤ A^[m] f := by induction m with | zero => exact le_rfl | succ m ih => rw [Function.iterate_succ_apply', Function.iterate_succ_apply'] calc B (B^[m] f) ≤ B (A^[m] f) := hB ih _ = A^[m] (B f) := (hcomm.symm.iterate_right m f) _ ≤ A^[m] (A f) := hA.iterate m hf _ = A (A^[m] f) := (Function.iterate_succ_apply A m f).symm.trans (Function.iterate_succ_apply' A m f) def mixedAverage {X : Type*} (p : ℝ) (A B : (X → ℝ) → (X → ℝ)) (f : X → ℝ) : X → ℝ := fun S => (1 - p) * B f S + p * A f S theorem mixedAverage_mono {X : Type*} {p : ℝ} (hp0 : 0 ≤ p) (hp1 : p ≤ 1) {A B : (X → ℝ) → (X → ℝ)} (hA : Monotone A) (hB : Monotone B) : Monotone (mixedAverage p A B) := by intro f g hfg S exact add_le_add (mul_le_mul_of_nonneg_left (hB hfg S) (sub_nonneg.mpr hp1)) (mul_le_mul_of_nonneg_left (hA hfg S) hp0) theorem finiteClauseAverage_commute_mix {n : ℕ} {C D E : Type*} [Fintype C] [Fintype D] [Fintype E] (satC : C → Assignment n → Prop) (satD : D → Assignment n → Prop) (satE : E → Assignment n → Prop) (p : ℝ) : Function.Commute (finiteClauseAverage satC) (mixedAverage p (finiteClauseAverage satD) (finiteClauseAverage satE)) := by intro f unfold mixedAverage rw [finiteClauseAverage_add, finiteClauseAverage_const_mul, finiteClauseAverage_const_mul, finiteClauseAverage_commute satC satD f, finiteClauseAverage_commute satC satE f] def embedAuxiliaryClause {n v k : ℕ} (e : Fin v → Fin n) (C : AuxiliaryClause v k) : AuxiliaryClause n k := fun j => (e (C j).1, (C j).2) def embeddedAverage {n v : ℕ} (e : Fin v → Fin n) (k : ℕ) : (Finset (Assignment n) → ℝ) → (Finset (Assignment n) → ℝ) := finiteClauseAverage (fun C : AuxiliaryClause v k => fun σ => auxiliarySatisfies σ (embedAuxiliaryClause e C)) def auxiliaryAverage {n : ℕ} (k : ℕ) : (Finset (Assignment n) → ℝ) → (Finset (Assignment n) → ℝ) := embeddedAverage (id : Fin n → Fin n) k def auxiliarySurvival {n : ℕ} (k m : ℕ) (S : Finset (Assignment n)) : ℝ := ((auxiliaryAverage k)^[m] alive) S def auxiliaryProbability (n k m : ℕ) : ℝ := auxiliarySurvival k m (Finset.univ : Finset (Assignment n)) def embeddedForced {n v : ℕ} (S : Finset (Assignment n)) (e : Fin v → Fin n) : Finset (Fin v) := Finset.univ.filter (fun i => e i ∈ forcedVariables S) @[simp] theorem mem_embeddedForced {n v : ℕ} (S : Finset (Assignment n)) (e : Fin v → Fin n) (i : Fin v) : i ∈ embeddedForced S e ↔ e i ∈ forcedVariables S := by simp [embeddedForced] @[simp] theorem embeddedForced_id {n : ℕ} (S : Finset (Assignment n)) : embeddedForced S (id : Fin n → Fin n) = forcedVariables S := by ext i; simp theorem opposing_literal_iff {n v : ℕ} (S : Finset (Assignment n)) (e : Fin v → Fin n) (σ₀ : Assignment n) (hσ₀ : σ₀ ∈ S) (l : Fin v × Bool) : (∀ σ ∈ S, σ (e l.1) ≠ l.2) ↔ l.1 ∈ embeddedForced S e ∧ l.2 = !(σ₀ (e l.1)) := by rw [mem_embeddedForced, forcedVariables_eq_frozen hσ₀] simp only [frozenCoordinates, Finset.mem_filter, Finset.mem_univ, true_and] constructor · intro h have h0 := h σ₀ hσ₀ constructor · intro σ hσ have hs := h σ hσ cases h1 : σ (e l.1) <;> cases h2 : σ₀ (e l.1) <;> cases h3 : l.2 <;> simp_all · cases h2 : σ₀ (e l.1) <;> cases h3 : l.2 <;> simp_all · rintro ⟨h, hb⟩ σ hσ rw [h σ hσ, hb] cases σ₀ (e l.1) <;> decide theorem opposing_literal_probability {n v : ℕ} (S : Finset (Assignment n)) (e : Fin v → Fin n) (hS : S.Nonempty) : uniformProbability (fun l : Fin v × Bool => ∀ σ ∈ S, σ (e l.1) ≠ l.2) = ((embeddedForced S e).card : ℝ) / (2 * v) := by obtain ⟨σ₀, hσ₀⟩ := hS let eqv : {l : Fin v × Bool // ∀ σ ∈ S, σ (e l.1) ≠ l.2} ≃ ↥(embeddedForced S e) := { toFun := fun l => ⟨l.val.1, ((opposing_literal_iff S e σ₀ hσ₀ l.val).mp l.property).1⟩ invFun := fun i => ⟨(i.val, !(σ₀ (e i.val))), (opposing_literal_iff S e σ₀ hσ₀ _).mpr ⟨i.property, rfl⟩⟩ left_inv := fun l => by apply Subtype.ext change (l.val.1, !(σ₀ (e l.val.1))) = l.val apply Prod.ext · rfl · exact ((opposing_literal_iff S e σ₀ hσ₀ l.val).mp l.property).2.symm right_inv := fun _ => rfl } unfold uniformProbability simp only [← Nat.card_eq_fintype_card] rw [Nat.card_congr eqv] simp only [Nat.card_eq_fintype_card, Fintype.card_coe, Fintype.card_prod, Fintype.card_fin, Fintype.card_bool, Nat.cast_mul, Nat.cast_ofNat] rw [mul_comm (v : ℝ) 2] theorem embedded_kill_probability {n v k : ℕ} (S : Finset (Assignment n)) (e : Fin v → Fin n) (hS : S.Nonempty) : uniformProbability (fun C : AuxiliaryClause v k => ¬ (S.filter fun σ => auxiliarySatisfies σ (embedAuxiliaryClause e C)).Nonempty) = (((embeddedForced S e).card : ℝ) / (2 * v))^k := by calc _ = uniformProbability (fun C : AuxiliaryClause v k => ∀ j, ∀ σ ∈ S, σ (e (C j).1) ≠ (C j).2) := by apply uniformProbability_congr intro C constructor · intro h j σ hσ heq apply h exact ⟨σ, Finset.mem_filter.mpr ⟨hσ, ⟨j, heq⟩⟩⟩ · intro h ⟨σ, hσ⟩ obtain ⟨hσ, j, hj⟩ := Finset.mem_filter.mp hσ exact h j σ hσ hj _ = _ := by change (uniformProbability (fun C : Fin k → Fin v × Bool => ∀ j, (fun l : Fin v × Bool => ∀ σ ∈ S, σ (e l.1) ≠ l.2) (C j))) = _ have hf := uniformProbability_forall_fintype (α := Fin v × Bool) (β := Fin k) (fun l => ∀ σ ∈ S, σ (e l.1) ≠ l.2) simpa only [Fintype.card_fin, opposing_literal_probability S e hS] using hf theorem embeddedAverage_alive {n v k : ℕ} (hv : 0 < v) (e : Fin v → Fin n) (S : Finset (Assignment n)) : embeddedAverage e k alive S = alive S * (1 - (((embeddedForced S e).card : ℝ) / (2 * v))^k) := by let : NeZero v := ⟨Nat.ne_of_gt hv⟩ by_cases hS : S.Nonempty · have ha : alive S = 1 := by simp [alive, hS] rw [ha, one_mul] have h := uniformProbability_not (fun C : AuxiliaryClause v k => (S.filter fun σ => auxiliarySatisfies σ (embedAuxiliaryClause e C)).Nonempty) rw [embedded_kill_probability S e hS] at h have he : embeddedAverage e k alive S = uniformProbability (fun C : AuxiliaryClause v k => (S.filter fun σ => auxiliarySatisfies σ (embedAuxiliaryClause e C)).Nonempty) := by rw [uniformProbability_eq_mean] unfold embeddedAverage finiteClauseAverage apply uniformMean_congr intro C by_cases hC : (S.filter fun σ => auxiliarySatisfies σ (embedAuxiliaryClause e C)).Nonempty · simp only [alive, ite_eq_left hC] · simp only [alive, ite_eq_right hC] rw [he] linarith · have he : S = ∅ := Finset.not_nonempty_iff_eq_empty.mp hS subst S simp [embeddedAverage, finiteClauseAverage, alive_empty, uniformMean_zero] theorem auxiliaryAverage_alive {n k : ℕ} (hn : 0 < n) (S : Finset (Assignment n)) : auxiliaryAverage k alive S = alive S * (1 - (forcedFraction S / 2)^k) := by rw [auxiliaryAverage, embeddedAverage_alive hn, embeddedForced_id] congr 2 unfold forcedFraction ring theorem forced_card_partition {r s : ℕ} (S : Finset (Assignment (r + s))) : (forcedVariables S).card = (embeddedForced S (Fin.castAdd s)).card + (embeddedForced S (Fin.natAdd r)).card := by have h := Fin.sum_univ_add (fun i : Fin (r + s) => if i ∈ forcedVariables S then (1 : ℕ) else 0) simpa only [← Finset.sum_filter, Finset.sum_const, smul_eq_mul, mul_one, Finset.filter_mem_eq_inter, Finset.univ_inter, embeddedForced] using h theorem partition_kill_convex {r s k : ℕ} (hr : 0 < r) (hs : 0 < s) (S : Finset (Assignment (r + s))) : (forcedFraction S / 2)^k ≤ ((r : ℝ) / (r + s)) * (((embeddedForced S (Fin.castAdd s)).card : ℝ) / (2 * r))^k + ((s : ℝ) / (r + s)) * (((embeddedForced S (Fin.natAdd r)).card : ℝ) / (2 * s))^k := by have hr' : (0 : ℝ) < r := by exact_mod_cast hr have hs' : (0 : ℝ) < s := by exact_mod_cast hs have hsum : (r : ℝ) / (r + s) + (s : ℝ) / (r + s) = 1 := by field_simp have h := (convexOn_pow (𝕜 := ℝ) k).2 (show ((embeddedForced S (Fin.castAdd s)).card : ℝ) / (2 * r) ∈ Set.Ici (0 : ℝ) by simp only [Set.mem_Ici]; positivity) (show ((embeddedForced S (Fin.natAdd r)).card : ℝ) / (2 * s) ∈ Set.Ici (0 : ℝ) by simp only [Set.mem_Ici]; positivity) (show 0 ≤ (r : ℝ) / (r + s) by positivity) (show 0 ≤ (s : ℝ) / (r + s) by positivity) hsum simp only [smul_eq_mul] at h convert h using 1 congr 1 unfold forcedFraction rw [forced_card_partition, Nat.cast_add, Nat.cast_add] field_simp theorem globalAverage_ge_local {r s k : ℕ} (hr : 0 < r) (hs : 0 < s) : mixedAverage ((r : ℝ) / (r + s)) (embeddedAverage (Fin.castAdd s) k) (embeddedAverage (Fin.natAdd r) k) alive ≤ auxiliaryAverage k alive := by intro S have hr' : (0 : ℝ) < r := by exact_mod_cast hr have hs' : (0 : ℝ) < s := by exact_mod_cast hs have hw : 1 - (r : ℝ) / (r + s) = (s : ℝ) / (r + s) := by field_simp; ring unfold mixedAverage rw [embeddedAverage_alive hr, embeddedAverage_alive hs, auxiliaryAverage_alive (by omega), hw] have h := mul_le_mul_of_nonneg_left (partition_kill_convex (k := k) hr hs S) (alive_nonneg S) have hsum : (r : ℝ) / (r + s) + (s : ℝ) / (r + s) = 1 := by field_simp have hsum_mul := congrArg (fun x : ℝ => alive S * x) hsum nlinarith theorem mixed_finiteAverage_iterate {n : ℕ} {C D : Type*} [Fintype C] [Fintype D] (satC : C → Assignment n → Prop) (satD : D → Assignment n → Prop) (p : ℝ) (m : ℕ) (f : Finset (Assignment n) → ℝ) : (mixedAverage p (finiteClauseAverage satC) (finiteClauseAverage satD))^[m] f = (fun S => binomialMean p m (fun j => ((finiteClauseAverage satC)^[j] ((finiteClauseAverage satD)^[m - j] f)) S)) := by induction m with | zero => simp [binomialMean] | succ m ih => rw [Function.iterate_succ_apply', ih] unfold mixedAverage rw [finiteClauseAverage_binomialMean, finiteClauseAverage_binomialMean] funext S rw [binomialMean] congr 1 · congr 1 apply binomialMean_congr intro j hj rw [(finiteClauseAverage_commute satD satC).iterate_right j, ← Function.iterate_succ_apply' (finiteClauseAverage satD) (m - j) f] rw [show (m - j).succ = m.succ - j by omega] · congr 1 apply binomialMean_congr intro j hj rw [← Function.iterate_succ_apply' (finiteClauseAverage satC) j] simp only [Nat.add_sub_add_right] def blockSet {r s : ℕ} (S : Finset (Assignment r)) (T : Finset (Assignment s)) : Finset (Assignment (r + s)) := Finset.univ.filter (fun σ => (fun i => σ (Fin.castAdd s i)) ∈ S ∧ (fun i => σ (Fin.natAdd r i)) ∈ T) @[simp] theorem mem_blockSet {r s : ℕ} (S : Finset (Assignment r)) (T : Finset (Assignment s)) (σ : Assignment (r + s)) : σ ∈ blockSet S T ↔ (fun i => σ (Fin.castAdd s i)) ∈ S ∧ (fun i => σ (Fin.natAdd r i)) ∈ T := by simp [blockSet] @[simp] theorem blockSet_univ (r s : ℕ) : blockSet (Finset.univ : Finset (Assignment r)) (Finset.univ : Finset (Assignment s)) = Finset.univ := by ext σ; simp theorem blockSet_nonempty {r s : ℕ} (S : Finset (Assignment r)) (T : Finset (Assignment s)) : (blockSet S T).Nonempty ↔ S.Nonempty ∧ T.Nonempty := by constructor · rintro ⟨σ, hσ⟩ have h := (mem_blockSet S T σ).mp hσ exact ⟨⟨_, h.1⟩, ⟨_, h.2⟩⟩ · rintro ⟨⟨σ, hσ⟩, ⟨τ, hτ⟩⟩ refine ⟨Fin.addCases σ τ, ?_⟩ simpa only [mem_blockSet, Fin.addCases_left, Fin.addCases_right] using And.intro hσ hτ theorem alive_blockSet {r s : ℕ} (S : Finset (Assignment r)) (T : Finset (Assignment s)) : alive (blockSet S T) = alive S * alive T := by simp only [alive, blockSet_nonempty] split_ifs <;> simp_all theorem filter_blockSet_left {r s k : ℕ} (S : Finset (Assignment r)) (T : Finset (Assignment s)) (C : AuxiliaryClause r k) : (blockSet S T).filter (fun σ => auxiliarySatisfies σ (embedAuxiliaryClause (Fin.castAdd s) C)) = blockSet (S.filter (fun σ => auxiliarySatisfies σ C)) T := by ext σ constructor · intro h obtain ⟨hσ, hC⟩ := Finset.mem_filter.mp h obtain ⟨hS, hT⟩ := (mem_blockSet S T σ).mp hσ exact (mem_blockSet _ _ σ).mpr ⟨Finset.mem_filter.mpr ⟨hS, hC⟩, hT⟩ · intro h obtain ⟨hS, hT⟩ := (mem_blockSet _ _ σ).mp h obtain ⟨hS, hC⟩ := Finset.mem_filter.mp hS exact Finset.mem_filter.mpr ⟨(mem_blockSet S T σ).mpr ⟨hS, hT⟩, hC⟩ theorem filter_blockSet_right {r s k : ℕ} (S : Finset (Assignment r)) (T : Finset (Assignment s)) (C : AuxiliaryClause s k) : (blockSet S T).filter (fun σ => auxiliarySatisfies σ (embedAuxiliaryClause (Fin.natAdd r) C)) = blockSet S (T.filter (fun σ => auxiliarySatisfies σ C)) := by ext σ constructor · intro h obtain ⟨hσ, hC⟩ := Finset.mem_filter.mp h obtain ⟨hS, hT⟩ := (mem_blockSet S T σ).mp hσ exact (mem_blockSet _ _ σ).mpr ⟨hS, Finset.mem_filter.mpr ⟨hT, hC⟩⟩ · intro h obtain ⟨hS, hT⟩ := (mem_blockSet _ _ σ).mp h obtain ⟨hT, hC⟩ := Finset.mem_filter.mp hT exact Finset.mem_filter.mpr ⟨(mem_blockSet S T σ).mpr ⟨hS, hT⟩, hC⟩ theorem auxiliarySurvival_succ {n k m : ℕ} (S : Finset (Assignment n)) : auxiliarySurvival k (m + 1) S = uniformMean (fun C : AuxiliaryClause n k => auxiliarySurvival k m (S.filter (fun σ => auxiliarySatisfies σ C))) := by unfold auxiliarySurvival rw [Function.iterate_succ_apply'] rfl theorem local_iterates_block {r s k : ℕ} (j l : ℕ) (S : Finset (Assignment r)) (T : Finset (Assignment s)) : ((embeddedAverage (Fin.castAdd s) k)^[j] ((embeddedAverage (Fin.natAdd r) k)^[l] alive)) (blockSet S T) = auxiliarySurvival k j S * auxiliarySurvival k l T := by induction j generalizing S T with | zero => simp only [Function.iterate_zero, id_eq] change _ = alive S * auxiliarySurvival k l T induction l generalizing T with | zero => exact alive_blockSet S T | succ l ih => rw [Function.iterate_succ_apply', auxiliarySurvival_succ, ← uniformMean_const_mul] unfold embeddedAverage finiteClauseAverage apply uniformMean_congr intro C rw [filter_blockSet_right] exact ih _ | succ j ih => rw [Function.iterate_succ_apply', auxiliarySurvival_succ, ← uniformMean_mul_const] unfold embeddedAverage finiteClauseAverage apply uniformMean_congr intro C rw [filter_blockSet_left] exact ih _ _ theorem auxiliary_interpolation {r s k : ℕ} (hr : 0 < r) (hs : 0 < s) (m : ℕ) : binomialMean ((r : ℝ) / (r + s)) m (fun j => auxiliaryProbability r k j * auxiliaryProbability s k (m - j)) ≤ auxiliaryProbability (r + s) k m := by have hp0 : 0 ≤ (r : ℝ) / (r + s) := by positivity have hp1 : (r : ℝ) / (r + s) ≤ 1 := by apply (div_le_one (by positivity : (0 : ℝ) < r + s)).mpr exact le_add_of_nonneg_right (Nat.cast_nonneg s) have h := iterate_compare_of_commute (auxiliaryAverage (n := r + s) k) (mixedAverage ((r : ℝ) / (r + s)) (embeddedAverage (Fin.castAdd s) k) (embeddedAverage (Fin.natAdd r) k)) (fun _ _ h => finiteClauseAverage_mono _ h) (mixedAverage_mono hp0 hp1 (fun _ _ h => finiteClauseAverage_mono _ h) (fun _ _ h => finiteClauseAverage_mono _ h)) (finiteClauseAverage_commute_mix _ _ _ _) (globalAverage_ge_local hr hs) m Finset.univ change _ ≤ auxiliaryProbability (r + s) k m at h convert h using 1 unfold embeddedAverage rw [mixed_finiteAverage_iterate] apply binomialMean_congr intro j hj change _ = ((embeddedAverage (Fin.castAdd s) k)^[j] ((embeddedAverage (Fin.natAdd r) k)^[m - j] alive)) Finset.univ rw [← blockSet_univ r s, local_iterates_block] rfl end end FixedClauseThreshold end OAI